essay on self regulation

What is Self-Regulation? (+95 Skills and Strategies)

This is a question that you might hear from kids, and it perfectly encapsulates what baffles them about adults.

As adults, we pretty much have free rein to do whatever we want, whenever we want. The vast majority of us won’t get arrested for not showing up to work, and no one will haul us off to prison for eating cake for breakfast.

So, why do we show up for work? Why don’t we eat cake for breakfast?

Perhaps the better question is, how do we keep ourselves from shirking work when we don’t want to go? How do we refrain from eating cake for breakfast and eating healthy, less-delicious food instead?

The answer is self-regulation. It’s a vital skill, but it’s also something we generally do without much thought.

If you want to learn more about what self-regulation is, how we make the decisions we make, and why we are more susceptible to temptation at certain moments, read on. We also provide plenty of resources for teaching self-regulation skills to both children and adults.

Before you continue, we thought you might like to download our three Self-Compassion Exercises for free . These detailed, science-based exercises will not only help you increase the compassion and kindness you show yourself but will also give you the tools to help your clients, students, or employees show more compassion to themselves.

This Article Contains:

What is self-regulation.

• What Is Self-Regulation Theory?

The Psychology of Self-Regulation

The self-regulatory model, why self-regulation is important for wellbeing, self-regulation test and assessment, early childhood and child development, self-regulation in adults, activities and worksheets for training self-regulation (pdfs), further resources, interventions, and tools, a take-home message.

Andrea Bell from GoodTherapy.org has a straightforward definition of self-regulation: It’s “control [of oneself] by oneself” (2016).

Self-control can be used by a wide range of organisms and organizations, but for our purposes, we’ll focus on the psychological concept of self-regulation.

As Bell also notes:

“Someone who has good emotional self-regulation has the ability to keep their emotions in check. They can resist impulsive behaviors that might worsen their situation, and they can cheer themselves up when they’re feeling down. They have a flexible range of emotional and behavioral responses that are well matched to the demands of their environment”

The goal of most types of therapy is to improve an individual’s ability to self-regulate and to gain (or regain) a sense of control over one’s behavior and life. Psychologists might be referring to one of two things when they use the term “self-regulation”: behavioral self-regulation or  emotional self-regulation . We’ll explore the difference between the two below.

What Is Behavioral Self-Regulation?

Behavioral self-regulation is “the ability to act in your long-term best interest, consistent with your deepest values” (Stosny, 2011). It is what allows us to feel one way but act another.

If you’ve ever dreaded getting up and going to work in the morning but convinced yourself to do it anyway after remembering your goals (e.g., a raise, a promotion) or your basic needs (e.g., food, shelter), you displayed effective behavioral self-regulation.

What Is Emotional Self-Regulation?

On the other hand, emotional self-regulation involves control of—or, at least, influence over—your emotions.

If you had ever talked yourself out of a bad mood or calmed yourself down when you were angry, you were displaying effective emotional self-regulation.

What is Self-Regulation Theory?

Self-regulation theory (SRT) simply outlines the process and components involved when we decide what to think, feel, say, and do. It is particularly salient in the context of making a healthy choice when we have a strong desire to do the opposite (e.g., refraining from eating an entire pizza just because it tastes good).

According to modern SRT expert Roy Baumeister, there are four components involved (2007):

• Standards  of desirable behavior;
• Motivation  to meet standards;
• Monitoring  of situations and thoughts that precede breaking standards;
• Willpower   allowing one’s internal strength to control urges.

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According to Albert Bandura , an expert on self-efficacy and a leading researcher of SRT, self-regulation is a continuously active process in which we:

• Monitor our own behavior, the influences on our behavior, and the consequences of our behavior;
• Judge our behavior in relation to our own personal standards and broader, more contextual standards;
• React to our own behavior (i.e., what we think and how we feel about our behavior)  (1991).

Bandura also notes that self-efficacy plays a significant role in this process, exerting its influence on our thoughts, feelings, motivations, and actions.

A quick thought experiment can show the significance of self-efficacy:

Imagine two people who are highly motivated to lose weight. They are both actively monitoring their food intake and their exercise, and they have specific, measurable goals that they have set for themselves.

One of them has high self-efficacy and believes he can lose weight if he puts in the effort to do so. The other has low self-efficacy and feels that there’s no way he can hold to his prescribed weight loss plan.

Who do you think will be better able to say no to second helpings and decadent desserts? Which of them do you think will be more successful in getting up early to exercise each morning?

We can say with reasonable certainty that the man with higher self-efficacy is likely to be more effective, even if both men start with the exact same standards, motivation, monitoring, and willpower.

Barry Zimmerman, another big name in SRT research, put forth his own theory founded on self-regulation: self-regulated learning theory.

We explore this further in The Science of Self-Acceptance Masterclass© .

What is Self-Regulated Learning?

Self-regulated learning  (SRL) refers to the process a student engages in when she takes responsibility for her own learning and applies herself to academic success (Zimmerman, 2002).

This process happens in three steps:

• Planning: The student plans her task, sets goals, outlines strategies to tackle the task, and/or creates a schedule for the task;
• Monitoring: In this stage, the student puts her plans into action and closely monitors her performance and her experience with the methods she chose;
• Reflection: Finally, after the task is complete and the results are in, the student reflects on how well she did and why she performed the way she did (Zimmerman, 2002).

When students take initiative and regulate their own learning, they gain deeper insights into how they learn, what works best for them, and, ultimately, they perform at a higher level. This improvement springs from the many opportunities to learn during each phase:

• In the planning phase, students have an opportunity to work on their self-assessment and learn how to pick the best strategies for success;
• In the monitoring phase, students get experience implementing the strategies they chose and making real-time adjustments to their plans as needed;
• In the reflection phase, students synthesize everything they learned and reflect on their experience, learning what works for them and what should be altered or replaced with a new strategy.

While the model is specific to health- and illness-related (rather than emotional) self-regulation, it is still a good representation of the complex processes at work during self-regulation of any kind.

The figure to the right shows how the model works:

• Stimuli are presented (i.e., something happens that provokes a reaction, whether it’s a thought, something another person said, receiving significant news, etc.);
• The individual makes sense of the stimuli, both cognitively (understanding it) and emotionally (feeling it);
• The sense-making leads the individual to choose  coping responses (i.e., what the person does to influence her feelings about the stimuli or the actions she takes to address the stimuli);
• The sense-making and coping responses determine the outcomes (i.e., the individual’s overall response and how she chooses to behave);
• The individual evaluates her coping responses in light of these outcomes and determines whether to continue using the same coping responses or to alter her formula.

An Example of the Model in Action

If words like “stimuli” and “emotional representations” throw you off, perhaps an example of the model in action will help.

Let’s use Bob as our example.

Bob was just diagnosed with diabetes and is facing his new reality: having to check his blood sugar regularly, changing his diet, and getting comfortable with needles. The diagnosis is Bob’s stimulus .

Bob attempts to make sense of his diagnosis. He talks to his doctor, recalls a friend’s experience with diabetes, thinks about a character’s struggle with diabetes on his favorite TV show, and tries to remember what he learned about diabetes in his college health classes. All of this information feeds into his cognitive representation of his diagnosis.

It’s not all objective thoughts, though. Bob also feels a little shocked about getting this diagnosis since he hadn’t even considered that he might have diabetes. He is worried about how long he’ll be around for his kids and is anxious about how much his life will change. He’s also scared about what will happen if he doesn’t change his life. These feelings make up his emotional representation of his diagnosis.

Once Bob has a semi-firm grasp of his thoughts and feelings about the diagnosis, he makes some decisions about what comes next. Through discussions with his doctor, he decides to start a new, healthier diet and commits to taking frequent walks. However, he also finds that it’s easy to put his diagnosis out of his mind when he’s not having an episode or being directly affected by it.

These decisions and actions are his coping responses .

Bob implements these responses for a few days, then reflects on how he’s been doing. He realizes that, although he is eating marginally healthier and he’s taken a short walk each day, he has mostly refrained from thinking about his diagnosis at all.

Bob reminds himself that if he keeps ignoring his diabetes, he will eventually get sick and may even suffer significant, long-term consequences. This is his evaluation of his representations and coping methods .

Bob commits to facing his diabetes head-on instead of denying it and resolves to work on remembering the potential consequences of not staying healthy. He also resolves to embrace fully the diet he and his doctor planned out and to start going to the gym three times a week.

Bob is using his evaluation of his representations, coping responses, and outcomes to assess how well his actions align with his desired future: a happy and healthy Bob who is around to see his kids grow up. This is the feedback loop .

This example is a good representation of what self-regulation looks like. Essentially, it’s the process of monitoring your own thoughts, feelings, and behaviors; comparing the outcomes against your goals; then deciding whether to maintain your current attitudes and behaviors or to adjust them in order to meet your goals more effectively.

What is Self-Regulation Therapy?

As noted earlier, you could argue that all forms of therapy are centered on self-regulation—they all aim to help clients reach levels of equilibrium in which they are able to effectively regulate their own emotions and behaviors (and, sometimes, thought patterns, in the case of therapies like cognitive behavioral therapy and mindfulness-based cognitive therapy ).

However, there is also a form of therapy that is specifically designed with self-regulation theory and its principles in mind. Self-regulation therapy draws from research findings in neuroscience and biology to help clients reduce “excess activation in the nervous system” (Canadian Foundation for Trauma Research & Education, n.d.).

This excess activation (i.e., an off-balance or inappropriate fight-or-flight response) can be triggered by a traumatic incident or any life event that is significant or overwhelming.

Self-regulation therapy aims to help the client correct this problem, building new pathways in the brain that allow for more flexibility and more appropriate emotional and behavioral responses. The ultimate goal is to turn emotional and/or behavioral dysregulation into effective self-regulation.

Self-Regulation Versus Self-Control

If you’re thinking that self-regulation and self-control have an awful lot in common, you’re correct. They are similar concepts and they deal with some of the same processes. However, they are two distinct constructs.

As psychologist Stuart Shanker (2016) put it:

“Self-control is about inhibiting strong impulses; self-regulation [is about] reducing the frequency and intensity of strong impulses by managing stress-load and recovery. In fact, self-regulation is what makes self-control possible, or, in many cases, unnecessary.”

Viewed in this light, we can think about self-regulation as a more automatic and subconscious process (unless the individual determines to purposefully monitor or alter his or her self-regulation), while self-control is a set of active and purposeful decisions and behaviors.

Understanding Ego Depletion

An important SRT concept is that of self-regulatory depletion, also called ego depletion.

This is a state in which an individual’s willpower and control over self-regulation processes have been used up, and the energy earmarked for inhibiting impulses has been expended. It often results in poor decision-making and performance (Baumeister, 2014).

When a person has been faced with many temptations (especially strong temptations), he or she must exert an equally powerful amount of energy when it comes to controlling impulses. SRT argues that people have a limited amount of energy for this purpose, and once it’s gone, two things happen:

• Inhibitions and behavioral restraints are weaker, meaning that the individual has less motivation and willpower to refrain from the temptations;
• The temptations, desires, or urges are felt much more strongly than when willpower is at a normal, non-depleted level (Baumeister, 2014).

This is a key idea in SRT. It explains why we struggle to avoid engaging in “bad behavior” when we are tempted by it over a long period of time. For example, it explains why many dieters can keep to their strict diet all day but once dinner’s over they will give in when tempted by dessert.

It also explains why a married or otherwise committed person can rebuff an advance from someone who is not their partner for days or weeks but might eventually give in and have an affair.

Recent neuroscience research supports this idea of self-regulatory depletion. A study from 2013 by Wagner and colleagues used functional neuroimaging to show that people who had depleted their self-regulatory energy experienced less connectivity between the regions of the brain involved in self-control and rewards.

In other words, their brains were less accommodating in helping them resist temptation after sustained self-regulatory activity.

5 Examples of Self-Regulatory Behavior

Although self-regulatory depletion is a difficult hurdle, SRT does not imply that it is impossible to remain in control of your urges and behavior when your energy is depleted. It merely states that it becomes harder and harder as your energy level decreases.

However, there are many examples of successful self-regulatory behavior, even when the individual is fatigued from constant self-regulation.

Examples include:

• A cashier who stays polite and calm when an angry customer is berating him for something he has no control over;
• A child who refrains from throwing a tantrum when she is told she cannot have the toy she desperately wants;
• A couple who’s in a heated argument about something that is important to both of them deciding to take some time to cool off before continuing their discussion, instead of devolving into yelling and name-calling;
• A student who is tempted to join her friends for a fun night out but instead decides to stay in to study for tomorrow’s exam;
• A man trying to lose weight meets a friend at a restaurant and sticks with the “healthy options” menu instead of ordering one of his favorite high-calorie dishes.

As you can see, self-regulation covers a wide range of behaviors from the minute-to-minute choices to the larger, more significant decisions that can have a significant impact on whether we meet our goals.

Let’s take a closer look at how self-regulation helps us in enhancing and maintaining a healthy sense of wellbeing.

Overall, there’s tons of evidence suggesting that those who successfully display self-regulation in their everyday behavior enjoy greater wellbeing. Researchers Skowron, Holmes, and Sabatelli (2003) found that greater self-regulation was positively correlated with wellbeing for both men and women.

The findings are similar in studies of young people. A study from 2016 showed that adolescents who regularly engage in self-regulatory behavior report greater wellbeing than their peers, including enhanced life satisfaction, perceived social support, and positive affect (i.e., good feelings) (Verzeletti, Zammuner, Galli, Agnoli, & Duregger).

On the other hand, those who suppressed their feelings instead of addressing them head-on experienced lower wellbeing, including greater loneliness, more negative affect (i.e., bad feelings), and worse psychological health overall (Verzeletti, Zammuner, Galli, Agnoli, & Duregger, 2016).

Emotional Intelligence and Wellbeing

To get more specific, one of the ways in which self-regulation contributes to wellbeing is through emotional intelligence.

Emotional intelligence can be described as:

“The ability to perceive emotions, to access and generate emotions so as to assist thought, to understand emotions and emotional knowledge, and to reflectively regulate emotions so as to promote emotional and intellectual growth”

(Mayer & Salovey, 1997).

According to emotional intelligence expert Daniel Goleman, there are five components of emotional intelligence:

• Self-awareness ;
• Self-regulation;
• Internal motivation;
• Social skills.

Self-regulation, or the extent of an individual’s ability to influence or control his or her own emotions and impulses, is a vital piece of emotional intelligence, and it’s easy to see why: Can you imagine someone with high levels of self-awareness, intrinsic motivation, empathy, and social skills who inexplicably has little to no control over his or her own impulses and is driven by uninhibited emotion?

There’s something off about that picture because of self-regulation’s important role in  emotional intelligence . And, as researchers Di Fabio and Kenny found, emotional intelligence is strongly related to wellbeing  (2016).

The better we are at understanding and addressing our emotions and the emotions of others, the better we are at making sense of our environments, adjusting to them, and pursuing our goals.

Self-Regulation and the Motivation to Succeed

Speaking of pursuing our goals, self-regulation is also entwined with motivation. As stated earlier in this article, motivation is one of the core components of self-regulation; it is one factor that determines how well we are able to regulate our emotions and behaviors.

An individual’s level of motivation to succeed in his endeavors is directly related to his performance. Even if he has the best of intentions, well-laid plans, and extraordinary willpower, he will likely fail if he is not motivated to regulate his behavior and avoid the temptation to slack off or set his goals aside for another day.

The more motivated we are to achieve our goals, the more capable we are to strive toward them. This impacts our wellbeing by filling us with a sense of purpose, competence, and self-esteem , especially when we are able to meet our goals.

Self-Regulation in ADHD and Autism

As you might have guessed, self-regulation is also an important topic for those struggling with attention-deficit hyperactivity disorder (ADHD) or autism spectrum disorders (ASD).

One of the hallmarks of ADHD is a limited ability to focus and regulate one’s attention. For example, ADDitude’s Penny Williams (n.d.) describes her 11-year-old son Ricochet’s struggles with ADHD in terms of the struggle to self-regulate:

“At times, he has struggled with identifying his feelings. He is overwhelmed with emotion sometimes, and he has trouble labeling his feelings. You can’t deal with what you can’t define, so this often creates a troublesome situation for him and me. Now that Ricochet is old enough to start regulating his reactions, one of our current behavior goals is identifying, communicating, and regulating feelings and actions.”

Similarly, difficulty with emotional self-regulation is part and parcel of ASD. Those on the autism spectrum often have trouble identifying their emotions. Even if they are able to identify their emotions, they generally have trouble modulating or regulating their emotions.

Difficulty with self-regulation is well-understood as a common symptom of ASD, but effective methods for improving self-regulation in ASD is unfortunately not as well-known or regularly implemented as one might wish.

The nonprofit advocacy group Autism Speaks suggests several strategies for helping children with autism to learn how to self-regulate. Many of these strategies can also be applied to children with ADHD, including:

• Celebrate and build your child’s strengths and successes;
• Respect and listen to your child;
• Validate your child’s concerns and emotions;
• Provide clear expectations of behavior (using visual aids if necessary);
• Set your child up for success (e.g., accepting a one-word answer, providing accommodations, using Velcro instead of shoelaces);
• Ignore the challenging behavior, like screaming or biting;
• Alternate tasks; do something fun, then something challenging;
• Teach and interact at your child’s current level rather than at what level you want him or her to be;
• Give your child choices within strict parameters (e.g., allowing the child to choose what activity to do first);
• Provide access to breaks when needed—this will give him or her an opportunity to avoid bad behavior;
• Promote the use of a safe calm-down place as a positive place, not a place of punishment;
• Set up reinforcement systems to reward your child for desired behavior;
• Allow times and places for your child to do what he or she wants (when not an inconvenience or intrusion for anyone else);
• Reward flexibility and self-control, verbally and with tangible rewards;
• Use positive/proactive language to encourage good behavior rather than pointing out bad behavior (2012).

Helping your child learn to self-regulate more effectively will ultimately benefit you, your child, and everyone he or she interacts with and will improve his or her overall wellbeing.

The Art of Mindfulness

Mindfulness can be defined as the conscious effort to maintain a moment-to-moment awareness of what’s going on, both inside your head and around you. Mindfulness and self-regulation are a powerful combination for contributing to wellbeing.

As we learned earlier, self-regulation requires self-awareness and monitoring of one’s own emotional state and responses to stimuli. Being conscious of your own thoughts, feelings, and behavior is the foundation of self-regulation: Without it, there is no ability to reflect or choose a different path.

Teaching mindfulness is a great way to improve one’s ability to self-regulate and to enhance overall well-being. Mindfulness encourages active awareness of one’s own thoughts and feelings and promotes conscious decisions about how to behave over simply going along with whatever your feelings tell you.

There is good evidence that mindfulness is an effective tool for teaching self-regulation. Researchers Razza, Bergen-Cico, and Raymond recently published a study on the effects of  mindfulness-based yoga intervention in preschool children (2015).

The researchers found that those in the mindfulness group exhibited greater attention, better ability to delay gratification and more effective inhibitory control than those in the control group.

Findings also suggested that those with the most trouble self-regulating benefited the most from the mindfulness intervention, indicating that those at the lower end of the self-regulation continuum are not a “lost cause.”

Self-Regulation and Executive Function

These skills are known as executive function skills, and they involve three key types of brain functions:

• Working memory: our cache of short-term memories, or information we recently took in;
• Mental flexibility: our ability to shift our focus from one stimulus to another and apply context-appropriate rules for attention and behavior;[be]
• Self-control: our ability to set priorities, regulate our emotions, and to resist our impulses (Center on the Developing Child, n.d.).

These skills are not inherent but are learned and built over time. They are vital skills for navigating the world and they contribute to good decisionmaking.

When we are able to successfully navigate the world and make good choices, we set ourselves up to meet our goals and enjoy greater wellbeing.

Do you ever find your emotions frustrating, overwhelming, or even rather unbearable? Are you able to cultivate an awareness of these emotions but aren’t really sure what to do next?

After noticing and understanding your emotions, it is important to think about how to deal with or regulate these emotions. There are many ways to do this, but a good place to start is to consider asking yourself the questions in the images below.

The more you challenge yourself to answer these important questions and try out other emotional regulation strategies, the more resources you’ll have to process your emotions effectively. This idea has been termed “learned resourcefulness”.

Research shows people who have learned to be resourceful in this way, have a more diverse range of emotional-regulation strategies in their toolkit to deal with difficult emotions and have learned to consider the demands of a difficult situation before selecting an appropriate strategy.

Importantly, these strategies are equally relevant when attempting to regulate positive emotions like happiness, excitement, and optimism. One may engage in techniques to prolong positive emotions in an attempt to feel better for longer or even inspire motivation and other adaptive behaviors.

If you’re interested in measuring your level of self-regulation (or using it in research), there are two solid options in terms of a self-monitoring scale and self-regulation questionnaire:

• The Self-Regulation Questionnaire (SRQ) for adults (Brown, Miller, & Lawendowski, 1999);
• The Preschool Self-Regulation Assessment (PSRA) for children (Smith-Donald, Raver, Hayes, & Richardson, 2007).

The SRQ is a 63-item assessment measured on a scale from 1 (strongly disagree) to 5 (strongly agree). The items correspond to one of seven components:

• Receiving relevant information;
• Evaluating the information and comparing it to norms;
• Triggering change;
• Searching for options;
• Formulating a plan;
• Implementing the plan;
• Assessing the plan’s effectiveness.

If you’re interested in learning more about this scale or using it in your own work, visit this website .

If you’re more interested in working with young children on self-regulatory strategies, the PRSA will probably work best for you. It’s described as a portable direct assessment of self-regulation in young children based on a set of structured tasks, including activities like:

• Balance Beam;
• Pencil Tap;
• Tower Task;
• Tower Cleanup.

To learn more about this assessment or to inquire about using it for your research, click here .

What is self-regulation? – Empowered to Connect

As noted earlier, the development of self-regulation begins very early on. As soon as children are able to access working memory, exhibit mental flexibility, and control their behavior, you can get started with helping them develop self-regulation.

How to Teach and Develop Self-Regulation in Toddlers

So, you’re probably convinced that self-regulation in children is a good thing, but you might be wondering, Where do I begin?

If that captures your thought process, don’t worry. We have some tips and suggestions to get you started.

Here’s a good list of suggestions from Day2Day Parenting for supporting the self-regulation of very young children (e.g., toddlers and preschoolers):

• Provide a structured and predictable daily routine and schedule;
• Change the environment by eliminating distractions: turn off the tv, dim lights, or provide a soothing object (like a teddy bear or a photo of the child’s parent[s]) when you sense a child is becoming upset;
• Roleplay with the child to practice how to act or what to say in certain situations;
• Teach and talk about feelings and review home/classroom rules regularly;
• Allow children to let off steam by creating a quiet corner with a small tent or pile of pillows;
• Encourage pretend play scenarios among preschoolers;
• Stay calm and firm in your voice and actions even when a child is “out of control”;
• Anticipate transitions and provide ample warning to the child or use picture schedules or a timer to warn of transitions;
• Redirect inappropriate words or actions when needed;
• In the classroom or at playgroups, pair children with limited self-regulatory skills with those who have good self-regulatory skills as a peer model;
• Take a break yourself when needed, as children with limited self-regulatory skills can test an adult’s patience (Thrive Place, 2013).

15 Activities and Games for Kindergarten and Preschool Children

Check out the resources listed below for some fun and creative ideas for kindergarten and preschool children.

Classic Games

We titled these the “classic games” because they are popular, well-known games that you are probably already familiar with. Luckily, they can also be used to help your child develop self-regulation.

If you haven’t already, give these a try:

• Duck, Duck, Goose
• Hide and Seek
• Musical Chairs
• Mirror, Mirror

Some further suggestions come from the Your Therapy Source website (2017):

• Red Light, Green Light : Kids move after “green light” is called and freeze when “red light” is called. If a kid is caught moving during a red light, they’re out;
• Mother May I : One child is the leader. The rest of the children ask: “Mother may I take [a certain number of steps, hops, jumps, or leaps to get to the leader] ? The leader approves or disapproves of the action. The first child to touch the leader wins;
• Freeze Dance : Turn on music. When the music stops, the children have to freeze;
• Follow My Clap : The leader creates a clapping pattern. Children have to listen and repeat the pattern;
• Loud or Quiet : Children have to perform an action that is either loud or quiet. First, pick an action, i.e., stomping feet. The leader says “loud,” and the children stomp their feet loudly.
• Simon Says : Children perform an action as instructed by the leader, but only if the leader starts with, “Simon says . . .” For example, if the leader says, “Simon says touch your toes,” then all the children should touch their toes. If the leader only says, “Touch your toes,” no one should touch their toes because Simon didn’t say so;
• Body Part Mix-Up : The leader will call out body parts for the children to touch. For example, the leader might call out “knees,” and the children touch their knees. Create one rule to start; for example, each time the leader says “head” the kids will touch their toes instead of their heads. This requires the children to stop and think about their actions and not just to react. The leader calls out “knees, head, elbow.” The children should touch their knees, toes , and elbow. Continue practicing and adding other rules that change body parts;
• Follow the Leader : The leader performs different actions and the children have to follow those actions exactly;
• Ready, Set, Wiggle : If the leader calls out, “Ready . . . Set . . . Wiggle,” everyone should wiggle their bodies. If the leader calls out, “Ready . . . Set . . . Watermelon,” no one should move. If the leader calls out, “Ready . . . Set . . . Wigs,” no one should move. The game continues like this. You can change the commands to whatever wording you want. The purpose is to have the children waiting to move until a certain word is said out loud;
• Color Moves : Explain to the children that they will walk around the room. They’ll move based on the color of the paper you are holding up. Green paper means walk fast, yellow paper means regular pace, and blue paper means slow-motion walking. Whenever you hold up a red paper, they stop. Try different locomotor skills like running in place, marching, or jumping.

Another list from The Inspired Treehouse includes good suggestions for other games you can play to calm an emotional or overwhelmed child when you’re on an outing. You can find that list here .

Self-Regulation in Adolescence

As your child grows, you will probably find it harder to encourage continuing self-regulation skills. However, adolescence is a vital time for further development of these skills, particularly for:

• Persisting on complex, long-term projects (e.g., applying to college);
• Problem-solving to achieve goals (e.g., managing work and staying in school);
• Delaying gratification to achieve goals (e.g., saving money to buy a car);
• Self-monitoring and self- rewarding progress on goals;
• Guiding behavior based on future goals and concern for others;
• Making decisions with a broad perspective and compassion for oneself and others;
• Managing frustration and distress effectively;
• Seeking help when stress is unmanageable or the situation is dangerous (Murray & Rosenbalm, 2017).

To ensure that you are supporting adolescents in developing these vital skills, there are three important steps you can take:

• Teaching self-regulation skills through modeling them yourself, providing opportunities to practice these skills, monitoring and reinforcing their progress, and coaching them on how, why, and when to use their skills;
• Providing a warm, safe, and responsive relationship in which adolescents are comfortable with making mistakes;
• Structuring the environment to make adolescents’ self-regulation easier and more manageable. Limit opportunities for risk-taking behavior, provide positive discipline, highlight natural consequences of poor decision-making, and reduce the emotional intensity of conflict situations (Murray & Rosenbalm, 2017).

The Role of Self-Regulation in Education

This leads to an important point: Children reach another significant stage of self-regulation development when they begin attending school—and self-regulation is tested as school gets more challenging.

This is where Zimmerman’s self-regulated learning theory comes into play again. Recall that there are three times when self-regulation can aid the learning process:

• Before the learning task is begun, when the student can consider the task, set goals, and develop a plan to tackle the task;
• During the task, when the student must monitor his own performance and see how well his strategies work;
• After the task, when the student can reflect back on their performance and determine what worked well, what didn’t, and what needs to change.

Zimmerman encourages teachers to do the following three things to help students continue to develop self-regulation:

• Give students a choice in tasks, methods, or study partners as often as you can;
• Give students the opportunity to assess their own work and learn from their mistakes;
• Pay attention to the student’s beliefs about his or her own learning abilities and respond with encouragement and support when necessary (2002).

Strategies, Exercises, and Lesson Plans for Students in the Classroom

If you’re a teacher who is interested in implementing more techniques and strategies for encouraging self-regulation in your classroom, consider the resources and methods outlined below.

McGill Self-Regulation Lesson Plans

This resource from McGill University in Canada includes several helpful lesson plans for building self-regulatory skills in students, including lessons on:

• Cognitive emotion regulation;
• Acceptance ;
• Self-blame;
• Positive refocusing;
• Rumination;
• Refocus of planning;
• Catastrophizing;
• Positive reappraisal;
• Blaming others;
• Putting things into perspective.

College & Career Competency Framework and Lessons

The self-regulation lesson plans from the College & Career Competency Framework detail nine separate lessons you can use to help your students continue to develop their skills. The lessons range in length from about 20 to 40 minutes and can be modified or adapted as needed.

The lessons include:

• Define Self-Regulation;
• Understand Your Ability to Self-Regulate by Taking the Questionnaire;
• Make a Plan;
• Practice Making a Plan;
• Monitor Your Plan;
• Make Changes;
• Find Missing Components;
• Practice Self-Regulation.

Click here to access and purchase the workbook containing the lessons. It includes the information you need to build effective strategies into your curriculum.

Finally, for a treasure trove of lesson plans, activities, and readings you can implement in your classroom, click here .

This resource comes from Scott Carchedi at the School Social Work Network, and includes a student manual and four lesson plans:

• Lesson on emotional regulation: “How Hot or Cold Does Your Emotional ‘Engine’ Run?”;
• Lesson on self-calming methods: “Downshift to a Lower Gear, with Help From Your Body”;
• Lesson on reframing feelings before acting on them: “Slow Down and Look Around You”;
• Lesson on conflict resolution: “Find the Best Route to Your Destination” (2013).

For each lesson, you can access a lesson plan and student activity (or activities) via a Word document and a student reading via a PDF. Use these lessons to help your students boost their self-regulation skill development and adapt or modify them as needed.

Although much attention is paid to self-regulation in children and adolescents because that’s when those skills are developing, it’s also important to keep self-regulation in mind for adults.

Self-Regulation and Navigating the Workplace

For example, self-regulation is extremely important in the workplace. It’s what keeps you from yelling at your boss when he’s getting on your nerves, slapping a coworker who threw you under the bus, or from engaging in more benign but still socially unacceptable behaviors like falling asleep at your desk or stealing someone’s lunch from the office fridge.

Those with high self-regulation skills are better able to navigate the workplace, which means they are better equipped to obtain and keep jobs and generally outperform their less-regulated peers.

To help you effectively manage your emotions at work (and build them up outside of work as well), try these tips:

• Do breathing exercises (like mindful breathing);
• Eat healthy, drink lots of water, and limit alcohol consumption;
• Use self-hypnosis to reduce your stress level and remain calm;
• Exercise regularly;
• Sleep seven to eight hours a night;
• Make time for fun outside of work;
• Laugh more often;
• Spend time alone;
• Manage your work-life balance (Connelly, 2012).

These tips likely come off as very general, but it’s true that living a generally healthy life is key to reducing your stress and reserving your energy for self-regulation.

For more specific tips on building your self-regulation skills, read on.

33 Skills and Techniques to Improve Self-Regulation

There are many tips you can use to enhance your self-regulation skills. If you want to give it a shot, read through these techniques and pick one that resonates with you—then try it out.

Mindfulness

Cultivating the skill of mindfulness will improve your ability to maintain your moment-to-moment awareness, which in turn helps you delay gratification and manage your emotions.

Research has shown that mindfulness is very effective at boosting one’s conscious control over attention, helping people regulate negative emotions, and improving executive functioning (Cundic, 2018).

Cognitive Reappraisal

This strategy can be described as a conscious effort to change your thought patterns. This is one of the main goals of cognitive-based therapies (e.g., co gnitive- behavioral therapy  or mindfulness-based cognitive behavioral therapy).

To build your cognitive reappraisal skills, you will need to work on changing and reframing your thoughts when you encounter a difficult situation. Adopting a more adaptive perspective to your situation will help you find a silver lining and help you manage emotion regulation and keep negative emotions at bay (Cundic, 2018).

Cognitive self-regulation has also been found to be positively correlated with social functioning. It involves the cognitive abilities we use to integrate different learning processes, which also help us support our personal goals.

8 Ways to Improve Self-Regulation

This list comes from the Mind Tools website but can also be found in this PDF from Course Hero. It outlines eight methods and strategies for building self-regulation:

• Leading and living with integrity: being a good role model, practicing what you preach, creating trusting environments, and living in alignment with your values ;
• Being open to change: challenging yourself to deal with change in a straightforward and positive manner and working to improve your ability to adapt to different situations while staying positive;
• Identifying your triggers: cultivating a sense of self-awareness that will help you learn what your strengths and weaknesses are and what can trigger you into a difficult state of mind;
• Practicing self-discipline: committing to taking initiative and staying persistent in working toward your goals, even when it’s the last thing you feel like doing;
• Reframing negative thoughts: working on your ability to take a step back from your own thoughts and feelings, analyze them, and come up with positive alternative thoughts;
• Keeping calm under pressure: keeping your cool by removing yourself from the situation for the short-term—whether mentally or physically—and using relaxation techniques like deep breathing;
• Considering the consequences: stopping and thinking about the consequences of giving in to “bad” behavior (e.g., what happened in the past, what is likely to happen now, what this behavior could trigger in terms of longer-term consequences);
• Believing in yourself: boosting your self-efficacy by working on your self-confidence , focusing on the experiences in your life when you succeeded and keeping your mistakes in perspective. Choose to believe in your own abilities and surround yourself with positive, supportive people.

Self-Regulation Strategies: Methods for Managing Myself

This table from Jan Johnson at Learning in Action Technologies lists 23 strategies we can use to self-regulate, both as an individual and as someone in a relationship.

The strategies are categorized into two groups: “Positive or Neutral” and “Negative or Neutral.” Check out some examples in each column and think about where your most frequently used self-regulating learning strategies fall on the chart.

For example, in the upper-left quadrant (“Alone Focus, Positive or Neutral”), strategies include:

• Consciously attend to breathing, relaxing;
• Awareness of body sensations;
• Attending to care for my body, nutrition;
• Meditation and prayer;
• Self-expression: art , music , dance, writing , etc.;
• Caring, nurturing self-talk;
• Laughing, telling jokes;
• Positive self-talk (“I can,” “I’m sufficient” messages);
• Go inside with intentional nurturing of self.

Under the “Relationship—Focus on Other, Positive or Neutral” category, strategies include:

• Seeking dialogue and learning;
• Playing with others;
• Sharing humor;
• Moving toward the relationship to learn (mutual inquiry);
• Desire and/or movement toward collaboration;
• Intentionally honoring or celebrating the other/calling attention to the other.

Finally, the strategies under the “Relationship – Focus on Self, Positive or Neutral” category include:

• Acknowledging what I said or did and any truth in it;
• Moving toward the relationship to learn;
• Desiring collaboration;
• Inquiring about impact;
• Intentionally honoring or celebrating me (throw myself a party).

To see the rest of these strategies, click here (Clicking the link will trigger a download of the PDF).

Self-Regulation in the Classroom

This worksheet is a handy tool that teachers can implement in the classroom. It can be used to help students assess their levels of self-regulation and find areas for improvement.

It lists 23 traits and tendencies that the students can say they do “Always,” “Sometimes,” or “Not So Much.” For the full list, you can see the worksheet here , but below are some examples:

• Participate in small and large group activities;
• Complete work on time;
• Remain on task;
• Follow the classroom rules and routines;
• Ask for help at appropriate times;
• Wait for your turn;
• Refrain from speaking out of turn.

Emotion Regulation Skills

This handout can be useful for both adults and older children and teens. It describes some of the main strategies and skills you can implement to keep emotions under control.

The handout covers four main strategies:

• Opposite action: doing the opposite of what you feel like doing;
• Check the facts: looking back over your experiences to learn the facts of what happened, like the event that triggered a reaction, any interpretations or assumptions made, and whether the response matched the intensity of the situation;
• P.L.E.A.S.E.: This acronym stands for “treat physical illness (PL), eat healthy (E), avoid mood-altering drugs (A), sleep well (S), and exercise (E).” All of these behaviors will help you maintain control of your emotions;
• Paying attention to positive events: keeping your focus on the positive aspects of an experience instead of the negative, trying to engage in a positive activity, and keeping yourself open to the good things.

You can download this handout here .

Handouts: Emotional Regulation, Social Sills, and Problem-Solving

This resource includes several worksheets and handouts you can use as a teacher, parent, or therapist with the children in your care.

It includes worksheets and handouts like Wally’s Problem-Solving Steps, which helps children learn how to problem-solve, and Tiny’s Anger Management Steps, which helps kids figure out how to deal with their anger.

It also includes helpful worksheets that teachers can use to enhance their ability to help students develop better self-regulation skills.

Click here to find out more.

17 Exercises To Foster Self-Acceptance and Compassion

Help your clients develop a kinder, more accepting relationship with themselves using these 17 Self-Compassion Exercises [PDF] that promote self-care and self-compassion.

Created by Experts. 100% Science-based.

If you’re still hungry for more information on self-regulation, there are tons of resources available on the subject. Check out the sources listed below.

Self-Regulation Chart

Aside from the worksheets and handouts noted earlier, there are another handy tool to use with kids: the self-regulation chart.

This self-regulation chart is for parents and/or teachers to complete, but it is focused on the child. It lists 30 skills related to emotional regulation and instructs the adult to rate the child’s performance in each area on a four-point scale that ranges from “Almost Always” to “Almost Never.”

All of these skills are important to keep in mind, but the skills specific to self-regulation include:

• Allows others to comfort him/her if upset or agitated;
• Self-regulates when tense or upset;
• Self-regulates when the energy level is high;
• Deals with being teased in acceptable ways;
• Deals with being left out of a group;
• Accepts not being first at a game or activity;
• Accepts losing at a game without becoming upset/angry;
• Says “no” in an acceptable way to things he/she does not want to do;
• Accepts being told “no” without becoming upset/angry;
• Able to say “I don’t know”;
• Able to end conversations appropriately.

You can find the self-regulation chart and checklist at this link .

The Zones of Self-Regulation

If you spend some time poking exploring self-regulation literature or talking to others about the topic, you’re bound to run into mentions of The Zones of Regulation .

According to developer Leah Kuypers, The Zones of Regulation is a “systematic, cognitive-behavioral approach used to teach self-regulation by categorizing all the different ways we feel and states of alertness we experience into four concrete colored zones” (Kuypers, n.d.).

This book describes the Zones of Regulation curriculum, including lessons and activities you can use in the classroom, in your therapy office, or at home.

In this book, you will learn about the four zones:

• Red Zone: extremely heightened states of alertness and intense emotions (e.g., rage, anger, devastation, terror);
• Yellow Zone: heightened states of alertness and elevated emotions (e.g., silliness, stress, frustration, “the wiggles”), but with more control than the Red Zone;
• Green Zone: calm states of alertness and regulated emotions (e.g., happy, focused, content, ready to learn);
• Blue Zone: states of low alertness and down feelings (e.g., sad, sick, tired, bored).

In addition, reading the book will teach you how to apply the Zones model to help your children, students, or clients build their emotional regulation skills.

You can learn more about this book here .

Handbook of Self-Regulation: Research, Theory, and Applications

For a more academic look at self-regulation, you might want to give this handbook a try.

This volume from researchers Kathleen D. Vohs and Roy F. Baumeister offers a comprehensive look at the theory of self-regulation, the research behind it, and the ways it can be applied to improve quality of life. It also explains how self-regulation is developed and shaped by experiences, and how it both influences and is influenced by social relationships.

Chapters on self-dysregulation (e.g., addiction, overeating, compulsive spending, ADHD) explore what happens when self-regulation skills are not developed to an adequate level.

If you’re a student, researcher, academic, a helping professional, or an aspiring helping professional, you won’t regret investing your time and energy into reading this book and familiarizing yourself with this important topic.

Click here to see the book on Amazon.

The skills involved in self-regulation are necessary for achieving success in life and reaching our most important goals. These skills can also have a major impact on overall wellbeing.

Self-regulation is truly an important topic for everyone to consider. However, it might be even more important for parents and educators to learn about it, since it is an important skill for children to develop.

What do you think of self-regulation theory? What are your strategies for boosting your own self-regulation? What about your strategies for building it in children?

Let us know in the comments section below. If you want to learn more about a similar topic, try reading this piece on posi tive mindsets .

We hope you enjoyed reading this article. Don’t forget to download our three Self Compassion Exercises for free .

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How to Develop and Practice Self-Regulation

Arlin Cuncic, MA, is the author of The Anxiety Workbook and founder of the website About Social Anxiety. She has a Master's degree in clinical psychology.

Rachel Goldman, PhD FTOS, is a licensed psychologist, clinical assistant professor, speaker, wellness expert specializing in eating behaviors, stress management, and health behavior change.

Tony Anderson / Getty Images

How Self-Regulation Develops

Common self-regulation problems.

• Effective Strategies
• How to Practice

Frequently Asked Questions

Self-regulation is the ability to control one's behavior, emotions, and thoughts in the pursuit of long-term goals. More specifically, emotional self-regulation refers to the ability to manage disruptive emotions and impulses—in other words, to think before acting.

Self-regulation also involves the ability to rebound from disappointment and to act in a way consistent with your values. It is one of the five key components of emotional intelligence .

This article discusses how self-regulation develops and the important impact it can have. It also covers some common problems you may face and what you can do to self-regulate more effectively.

Your ability to self-regulate as an adult has roots in your childhood. Learning how to self-regulate is an important skill that children learn both for emotional maturity and, later, for social connections.

In an ideal situation, a toddler who throws tantrums grows into a child who learns how to tolerate uncomfortable feelings without throwing a fit, and later into an adult who is able to control impulses to act based on uncomfortable feelings.

In essence, maturity reflects the ability to face emotional, social, and cognitive threats in the environment with patience and thoughtfulness. If this description reminds you of mindfulness, that's no accident— mindfulness does indeed relate to the ability to self-regulate.

Why Self-Regulation Is Important

Self-regulation involves taking a pause between a feeling and an action—taking the time to think things through, make a plan, wait patiently. Children often struggle with these behaviors, and adults may as well.

It's easy to see how a lack of self-regulation will cause problems in life. A child who yells or hits other children out of frustration will not be popular among peers and may face discipline at school.

An adult with poor self-regulation skills may lack self-confidence and self-esteem and have trouble handling stress and frustration. Often, this might result in anger or anxiety. In more severe cases, it can even lead to being diagnosed with a mental health condition.

Qualities of Self-Regulators

In general, people who are adept at self-regulating tend to be able to:

• Act in accordance with their values
• Calm themselves when upset
• Cheer themselves when feeling down
• Maintain open communication
• Persist through difficult times
• Put forth their best effort
• Remain flexible and adapting to situations
• See the good in others
• Stay clear about their intentions
• Take control of situations when necessary
• View challenges as opportunities

Self-regulation allows you to act in accordance with your deeply held values or social conscience and to express yourself appropriately. If you value academic achievement, it will allow you to study instead of slack off before a test. If you value helping others, it will allow you to help a coworker with a project, even if you are on a tight deadline yourself.

In its most basic form, self-regulation allows us to be more resilient and bounce back from failure while also staying calm under pressure. Researchers have found that self-regulation skills are tied to a range of positive health outcomes. This includes better resilience to stress, increased happiness, and better overall well-being.

Self-regulation can play an important role in relationships, well-being, and overall success in life. People who can manage their emotions and control their behavior are better able to manage stress, deal with conflict, and achieve their goals.

How do problems with self-regulation develop? It could start early, such as an infant being neglected. A child who does not feel safe and secure, or who is unsure whether their needs will be met, may have trouble self-soothing and self-regulating.

Later, a child, teen, or adult may struggle with self-regulation, either because this ability was not developed during childhood, or because of a lack of strategies for managing difficult feelings. When left unchecked, over time this could lead to more serious issues such as mental health disorders and risky behaviors such as substance use .

Effective Skills for Self-Regulation

If self-regulation is so important, why were most of us never taught strategies for using this skill? Most often, parents, teachers, and other adults expect that children will "grow out of" the tantrum phase. While this is true for the most part, all children and adults can benefit from learning concrete strategies for self-regulation.

Mindfulness

According to Jon Kabat-Zinn, PhD, founder of Mindfulness-Based Stress Reduction (MBSR), mindfulness is "the awareness that arises from paying attention, on purpose, in the present moment and non-judgmentally."

By engaging in skills such as focused breathing and gratitude, mindfulness enables us to put some space between ourselves and our reactions, leading to better focus and feelings of calmness and relaxation.

In a 2019 review of 27 research studies, mindfulness was shown to improve attention, which in turn helped with regulating negative emotions and improving executive function .

Cognitive Reappraisal

Cognitive reappraisal, or cognitive reframing , is another strategy that can be used to improve self-regulation abilities. This strategy involves changing thought patterns. Specifically, cognitive reappraisal involves reinterpreting a situation in order to change the emotional response to it.

For example, imagine a friend did not return your calls or texts for several days. Rather than thinking that this reflected something about yourself, such as "my friend hates me," you might instead think, "my friend must be really busy." Research has shown that using cognitive reappraisal in everyday life is related to experiencing more positive and fewer negative emotions.

In a 2016 study examining the link between self-regulation strategies (i.e., mindfulness, cognitive reappraisal, and emotion suppression) and emotional well-being, researchers found cognitive reappraisal to be associated with daily positive emotions, including feelings of enthusiasm, happiness, satisfaction, and excitement.

Some other useful strategies for self-regulation include acceptance and problem-solving. In contrast, unhelpful strategies that people sometimes use include avoidance, distraction, suppression, and worrying.

You can improve your self-regulation skills by practicing mindfulness and changing how you think about the situation.

How Do You Practice Self-Regulation?

If you or your child needs help with self-regulation, there are strategies you can use to improve skills in this area.

Helping Kids With Self-Regulation

In children, parents can help develop self-regulation through routines (e.g., regular mealtimes and consistent bedtime routines). Routines help children learn what to expect, which makes it easier for them to feel comfortable.

When children act in ways that don't demonstrate self-regulation, ignore their requests. For example, if they interrupt a conversation, don't stop your discussion to attend to their needs. Tell that that they will need to wait.

Self-Regulation Tips for Adults

The first step to practicing self-regulation is to recognize that everyone has a choice in how to react to situations. While you may feel like life has dealt you a bad hand, it's not the hand you are dealt, but how you react to it that matters most.

• Recognize that in every situation you have three options : approach, avoidance , and attack. While it may feel as though your choice of behavior is out of your control, it's not. Your feelings may sway you more toward one path, but you are more than those feelings.
• Become aware of your emotions . Do you feel like running away from a difficult situation? Do you feel like lashing out in anger at someone who has hurt you?
• Monitor your body to get clues about how you are feeling if it is not immediately obvious to you. For example, a rapidly increasing heart rate may be a sign that you are entering a state of rage or even experiencing a panic attack.

Start to restore balance by focusing on your deeply held values, rather than those transient emotions. Look beyond momentary discomfort to the larger picture.

Recognizing your options can help you put your self-regulation skills into practice. Focus on identifying what you are feeling, but remember that feelings are not facts. Giving yourself time to stay calm and deliberate your options can help you make better choices.

A Word From Verywell

Once you've learned this delicate balancing act, you will begin to self-regulate more often, and it will become a way of life for you. Developing self-regulation skills will improve your resilience and ability to face difficult circumstances in life.

However, if you find you are unable to teach yourself to self-regulate, consider consulting a  mental health professional . A trained therapist can help you learn and implement strategies and skills specific to your situation. Therapy can also be a great place to practice those skills for use in your everyday life.

You can practice self-regulation staying calm and thinking carefully before you react. Engaging in relaxation tactics like deep breathing or mindfulness can help you keep your cool while deliberately considering the consequences of your actions can help you focus on the potential outcomes.

Emotional intelligence refers to a person's ability to recognize, interpret, and regulate emotions. This ability plays an important part in self-regulation and also contributes to the development and maintenance of healthy relationships.

You can help teach your child self-control by managing your own stress, remaining calm, and modeling effective self-regulation skills. You can also strengthen this ability by helping children recognize their emotions, teaching problem-solving skills, setting limits, and enforcing rules with natural consequences.

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Hampson SE, Edmonds GW, Barckley M, Goldberg LR, Dubanoski JP, Hillier TA. A Big Five approach to self-regulation: personality traits and health trajectories in the Hawaii longitudinal study of personality and health .  Psychol Health Med . 2016;21(2):152-162. doi:10.1080/13548506.2015.1061676

Hofmann W, Luhmann M, Fisher RR, Vohs KD, Vaumeister RF.  Yes, but are they happy? Effects of trait self-control on affective well-being and life satisfaction .  J Person . 2014;82(4):265-277. doi:10.1111/jopy.12050

Spratt EG, Friedenberg SL, Swenson CC, et al. The effects of early neglect on cognitive, language, and behavioral functioning in childhood . Psychology . 2012;3(2):175-182. doi:10.4236/psych.2012.32026

Leyland A, Rowse G, Emerson L-M. Experimental effects of mindfulness inductions on self-regulation: Systematic review and meta-analysis . Emotion . 2019;19(1):108-122. doi:10.1037/emo0000425

Brockman R, Ciarrochi J, Parker P, Kashdan T. Emotion regulation strategies in daily life: mindfulness, cognitive reappraisal and emotion suppression . Cogn Behav Ther . 2017;46(2):91-113. doi:10.1080/16506073.2016.1218926

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By Arlin Cuncic, MA Arlin Cuncic, MA, is the author of The Anxiety Workbook and founder of the website About Social Anxiety. She has a Master's degree in clinical psychology.

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Self-regulation is the process by which students monitor and control their cognition, motivation, and behaviour in order to achieve certain goals. There are several interweaving theories of self-regulation, but most common models conceptualise self-regulation in terms of a series of steps involving forethought or planning, performance, and reflection [i] [ii] . These steps can be explicitly taught and, while self-regulation increases to some extent with age, the research is clear that self-regulation can be improved and that the role of the teacher is crucial in supporting and promoting self-regulated learning. What is more, students’ emotions and their beliefs about their own ability play a key role in the development and exercise of self-regulation, and teachers can further support self-regulation by teaching students about growth mindset and the role of the emotions in learning .

The first step in self-regulated learning is to plan and set goals . Goals are guideposts that students use to check their own progress. Setting goals involves activating prior knowledge about the difficulty of the task and about one’s own ability in that content area. Students may weigh in their mind how long an activity may take and set a time management plan in place. They may also think about particular learning strategies (such as asking themselves questions as they read) that they will use in reaching their goal/s.

Students self-regulate by focusing their energy and attention on the task at hand. This next step involves exercising control. Control can be exercised by implementing any of the learning strategies (such as rehearsal, elaboration, summarising or asking themselves questions) chosen in the first step. Help-seeking can also be a form of control, but only when the learner uses it to develop their own skill or understanding: help-seeking is not considered self-regulatory behaviour when it is used as a crutch to arrive at the answer without the hard work. Control can also take the form of using attention-focusing strategies such as turning off all music, sitting alone, or going to the library, and it involves postponing enjoyable activities in order to make progress towards one’s goals. Simply put, control is general persistence to stick with the strategies that work.

Next, self-regulated learners monitor progress towards their goal. Individuals can monitor their own understanding, motivation, feelings, or behaviour towards a goal. For example, by using the metacognitive strategy they decided to use in the goal-setting stage (asking themselves questions), students can clarify for themselves what they do and do not yet know. Other ways of self-monitoring include keeping track of how much studying truly gets done with a study group, or noticing which contexts and environments allow them to focus on their work.

Finally, students use the information gathered through the previous self-evaluation to metacognitively reflect and respond . A student’s confidence in their own abilities will shape how they reflect on their progress or lack thereof. For example, a student with a stable, high belief that they are capable will attribute a low grade on a math test to their lack of sleep the night before or their minimal study time as opposed to a lack of intelligence. Responding to a self-evaluation functions like a thermostat, either turning up the dial on effort to increase progress towards one’s goals or easing back to focus on other tasks. This adjustment can manifest as help-seeking behaviour, persistence, or shifting learning strategies.

Why is self-regulation important?

It is increasingly important that students are able to proactively evaluate and improve upon their own learning. In a rapidly changing world, successful individuals must be life-long learners who are metacognitive about and able to effectively evaluate their learning. Within the education system, students without the ability to focus their attention and maintain perseverance will be constantly pulled left and right by their immediate impulses. Furthermore, students who fail to learn self-evaluation strategies will not be able to effectively direct their attention towards the areas that need it the most. While some students may find poor study conditions, confusing lessons or difficult texts to be insurmountable obstacles, self-regulation allows learners to navigate these conditions by discovering solutions that work.

In addition to developing personal responsibility about learning, self-regulation also solidifies the content of learning. Self-regulation practices improve the encoding of knowledge and skills in memory, especially in reading comprehension and writing. [iii] Research has also identified that self-regulation strategies are associated with increased student effort and motivation, improved scores on standardised tests and general preparedness for class.

How do we cultivate self-regulation?

As discussed above, the self-regulation process is composed of a series of steps. These steps are not rigid in their order. In actuality, self-regulated learners engage in many of these processes simultaneously or shift the steps as they become adept self-regulators. To teach and develop student self-regulation as a whole, teachers can support each of the underlying stages. It is also important to support students’ self-efficacy, encourage them to adopt a growth mindset and prioritise learning over grades and marks.

Match the form of learning with appropriate strategies

In this first stage, students identify particular learning strategies that fit with their goals. Basic learning tasks such as encoding information for memory recall are best learned through rehearsal, organisation or categorisation, mnemonic devices, or paraphrasing the information. However, more elaborate strategies are used when students are asked to make information meaningful. In building connections between new concepts and a learner’s existing knowledge, students may choose to list underlying causes or themes, outline the structure of the process or paper, or diagram spatial relationships to create a network of ideas. This is not a comprehensive catalogue of learning strategies but serves to illustrate the value in carefully choosing a learning strategy to align with goals. It is important for teachers to explicitly teach a range of learning strategies, and to enable and support students to determine which form of learning strategy is most appropriate for the type of work.

Always include positive feedback

Maintaining attention throughout a task takes practice. However, teachers can support students’ focus through positive feedback. Students often adopt their teacher’s evaluations of their work as their own, which means that teachers can highly influence a student’s persistence in engaging with a task or giving up. In addition, developing a culture around celebrating mistakes as opportunities to learn is crucial. Authentically discussing areas of improvement allows room for growth, and an inclusion of positive feedback should not be interpreted as giving exclusively positive feedback. Teachers can also use their expertise to differentiate their level of positive and negative feedback according to student self-efficacy in a particular task.

Maintain an environment conducive to focus

Teachers can ensure that the study environment is conducive to focus, as a relatively quiet space for individual work is invaluable. Beyond this, students learn how to regulate their own attention and impulses best through sustained and regular practice, increasing in duration each session. While collaboration and discussion are an important part of learning, self-regulation becomes much more challenging in a noisy environment. In secondary education this is particularly important, as the higher critical thinking skills required by adolescents are severely inhibited by distractions. Teachers can further support the development of self-regulation by providing complex, open-ended tasks that give students the opportunity to practise managing distractions and maintaining focus while tackling increasingly challenging academic work.

Guide students to track their progress

At the heart of monitoring understanding lies the question: ‘what do I know, and how can I improve?’ Students can push themselves to become aware of the limits of their own knowledge through recall, practice and extension, depending on the nature of the goal. One monitoring strategy might be summarising the main points of a lesson following direct instruction. A student trying to increase her reading comprehension may pause to ask herself questions about the text (at varying levels of complexity).

Some students may wish to improve their time management skills. These students would benefit from keeping a record of how they spend their time and then comparing it with their task goals. For example, I may believe that two hours of studying with a study group each week is a strong plan in preparing for a test at the end of the term. However, I may in fact find that one of the two hours is generally spent socialising. This new information can then be used to shift my behaviour moving forward.

Practise evaluating ‘like a detective’

In the reflection and response stage, students utilise feedback from the monitoring stage to inform their shift in learning strategies or effort moving forward. This requires a high level of resilience in order to bounce back from the inevitable highs and lows in learning. Similarly, it also necessitates metacognition to dig into why certain strategies may not work, and why others might be more effective moving forward. These metacognitive strategies can be taught explicitly through talking with students about how to be a detective in reflecting on their areas of strength or growth. In addition, resilience can be fostered through conversations surrounding growth mindset, and context- rather than person-specific attribution of failure. Encouraging students to attribute poor performance on a test to lack of preparation rather than unintelligence, and supporting students to respond to feedback with an understanding that achievement is variable based on effort rather than stable personality traits, are highly predictive of the development of positive self-regulation in students.

For example, a student who has failed a maths test may feel like giving up completely in maths. However, she demonstrates emotional resilience and decides to reflect on which particular problems gave her trouble in order to shift her learning strategies. On reflection, she realises that during the previous term she never went to the library by herself, summarised the material to herself following a lesson, or asked the teacher for help. She considers the merit of these changes, how she will implement them, and makes a plan to manage her time accordingly.

Measuring self-regulation

Periodically evaluating students’ social-emotional learning serves the dual purpose of informing the teacher of their students’ progress and wellbeing, and prompting students to practise self-awareness. While formal school-wide social-emotional assessments are valuable for collecting comprehensive data, these measures are time-consuming and cannot practically be implemented more than once or twice each year. For these formal assessments, one reliable measure with strong evidence of validity is the Panorama Social-Emotional Learning Survey. However, on a fortnightly or monthly basis, teachers can informally gauge student self-regulation by asking the following questions:

• When you get stuck while learning something new, how likely are you to try a different strategy? (Not at all likely/Quite likely/Likely/Highly likely)
• Before you start on a challenging project, how often do you think about the best way to approach the project? (Almost never/Sometimes/Fairly often/Almost always)
• Overall, how well do your learning strategies help you learn and focus more effectively? (Not at all well/Quite well/Well/Very well)
• How often do you stay focused on the same goal for several months at a time? (Almost never/Sometimes/Fairly often/Almost always)
• When you are working on a project that matters a lot to you, how focused can you stay when there are lots of distractions? (Not at all focused/Quite focused/Focused/Very focused)
• If you have a problem while working towards an important goal, how well can you keep working? (Not at all well/Quite well/Well/Very well)
• How consistently do you pay attention and resist distractions? (Not at all consistently/Quite consistently/Consistently/Very consistently)
• When you work independently, how often do you stay focused? (Almost never/Sometimes/Fairly often/Almost always)
• How often do you follow through in completing the goals you set for yourself? (Almost never/Sometimes/Fairly often/Almost always)
• How do you keep yourself motivated when a concept or lesson is not inherently interesting to you? _
• When you feel yourself becoming distracted, do you try to counteract this effect? How? ________
• The last time you experienced a setback in school, how did you respond? _______

Boekaerts, M. (1999). Self-regulated learning: Where we are today. International Journal of Educational Research , 31 (6), 445-457.

Murray, D. W., & Rosanbalm, K. (2017). Promoting self-regulation in adolescents and young adults: A practice brief. OPRE Report #2015-82. Washington, DC: Office of Planning, Research, and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services.

Panadero, E. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology , 8 , 422.

Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In M. Boekarts, P.R. Pintrich & M. Zeidner (Eds.), Handbook of Self-Regulation (pp. 451-502). San Diego & London: Academic Press.

Weinstein, C. E., Husman, J., & Dierking, D. R. (2000). Self-regulation interventions with a focus on learning strategies. In M. Boekarts, P.R. Pintrich & M. Zeidner (Eds.), Handbook of Self-Regulation (pp. 727-747). San Diego & London: Academic Press.

Winne, P. H., & Hadwin, A. F. (1998). Studying as self-regulated learning. In D. J. Hacker, J. Dunlosky, & A. Graesser (Eds.), Metacognition in educational theory and practice (pp. 277-304). Hillsdale, NJ: Lawrence Erlbaum.

Zimmerman, B. J. (1990). Self-regulated learning and academic achievement: An overview. Educational Psychologist , 25 (1), 3-17.

Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into Practice , 41 (2), 64-70.

[i] Pintrich (2000).

[ii] Zimmerman (2002).

[iii] Zimmerman (2002).

PREPARED FOR THE EDUCATION HUB BY

Claire Chuter

Claire is a Ph.D. student at Johns Hopkins University – School of Education. Her primary interest lies in improving students’ empathy through virtual reality perspective-taking activities. Previously, Claire conducted research as a consultant for the non-profit organization Opportunity Education, as well as teaching in K-12 settings for four years. She holds a B.A. in Italian Studies, a B.S. in Human Development, and an M.A. in Education from the University of California, Davis. Claire enjoys developing guides with The Education Hub for teachers as they support students in their personal and academic lives.

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The Self-Regulation-View in Writing-to-Learn: Using Journal Writing to Optimize Cognitive Load in Self-Regulated Learning

• Review Article
• Open access
• Published: 25 July 2020
• Volume 32 , pages 1089–1126, ( 2020 )

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• Matthias Nückles   ORCID: orcid.org/0000-0001-9924-5806 1 ,
• Julian Roelle 2 ,
• Inga Glogger-Frey 3 ,
• Julia Waldeyer 2 &
• Alexander Renkl 3  

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We propose the self-regulation view in writing-to-learn as a promising theoretical perspective that draws on models of self-regulated learning theory and cognitive load theory. According to this theoretical perspective, writing has the potential to scaffold self-regulated learning due to the cognitive offloading written text generally offers as an external representation and memory aid, and due to the offloading, that specifically results from the genre-free principle in journal writing. However, to enable learners to optimally exploit this learning opportunity, the journal writing needs to be instructionally supported. Accordingly, we have set up a research program—the Freiburg Self-Regulated-Journal-Writing Approach—in which we developed and tested different instructional support methods to foster learning outcomes by optimizing cognitive load during self-regulated learning by journal writing. We will highlight the main insights of our research program which are synthesized from 16 experimental and 4 correlative studies published in 16 original papers. Accordingly, we present results on (1) the effects of prompting germane processing in journal writing, (2) the effects of providing worked examples and metacognitive information to support students in effectively exploiting prompted journal writing for self-regulated learning, (3) the effects of adapting and fading guidance in line with learners’ expertise in self-regulated learning, and (4) the effects of journal writing on learning motivation and motivation to write. The article closes with a discussion of several avenues of how the Freiburg Self-Regulated-Journal-Writing Approach can be developed further to advance research that integrates self-regulated learning with cognitive load theory.

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Writing, just as reading, is basic to academic learning both in school and at the university (Phillips and Norris 2009 ). In academic writing tasks such as learning journals or essays, learners are supposed to develop their ideas about subject matter in a self-determined way and thereby to construct sustainable knowledge. With the advent of a scientific writing pedagogy in the early seventies of the last century, the idea was born that writing is a natural tool for thinking and learning. This idea of writing as a learning tool (see also Tynjälä et al. 2012 ) was first suggested by the educational reform movement “writing across the curriculum” in the UK and soon spread over to many high schools and universities in the USA (Britton et al. 1975 ; Emig 1977 ). In this article, we present the main tenets of our research program on writing-to-learn which focuses on journal writing (called the Freiburg Self-Regulated-Journal-Writing Approach in the following). In our definition of writing-to-learn, we take up the old idea of writing as a tool for thinking and learning, meaning that with appropriate instructional support, writing activities such as journal writing in particular may serve students as a beneficial medium to enact knowledge construction processes that result in deep comprehension of subject matter, increased learning motivation, and long-term retention.

In the following, we will first discuss diverging classic theoretical views on writing-to-learn. Based on a critique of these approaches, we will then derive and characterize in detail a new theoretical perspective, called the self-regulation view in writing-to-learn. Following this theoretical discussion, we will present and discuss major results of the empirical studies of our research program, in which we systematically tested different support methods to optimize cognitive load and learning outcomes in writing learning journals.

Theoretical Perspectives on Writing-to-Learn

In research on writing-to-learn, two contesting theoretical views can be distinguished (Nückles et al. 2009 ). Following the so-called romantic view (Galbraith 1992 ), the idea of writing as a tool for thinking and learning is rooted in the work of Vygotsky, who regarded the human language as fundamental for the development of reasoning and thought. Building on Vygotsky’s work, James Britton ( 1980 ), the founder of the British writing-across-the-curriculum movement, argued that a great deal of our knowledge stored in long-term memory is tacit and therefore not directly accessible to us. According to Britton’s shaping-at-the-point-of utterance-hypothesis (Klein 1999 ), it is only by articulating our thoughts in the course of writing, that this tacit knowledge becomes explicit and our thoughts take shape. Thus, the very act of writing itself should induce germane cognitive load, Footnote 1 that is, evoke knowledge construction processes that inevitably result in learning (Sweller et al. 1998 ). Galbraith ( 1992 ) termed this view the “romantic” stance in writing-to-learn to highlight the idea that learning would emerge from spontaneous, expressive writing without consideration of rhetorical forms.

From another prominent perspective on writing, the so-called classic view (Galbraith 1992 ), in contrast, writing does not at all appear as a natural learning medium, in particular when regarded through the lens of cognitive load theory. Early writing theorists such as Flower and Hayes ( 1980 ) or Bereiter and Scardamalia ( 1987 ) characterized the nature of writing as complex problem solving that is likely to produce cognitive overload especially in novice writers. Based on empirical analyses of think-aloud protocols, Hayes and Flower ( 1986 ) emphasized the goal-directed nature of such problem solving: A writing plan based on a hierarchy of writing goals is generated, this plan is translated into written text, and the produced text is revised. Hayes and Flower conceived of these steps as interactive and recursive complex cognitive processes.

Building on Hayes and Flower ( 1986 ), Bereiter and Scardamalia ( 1987 ) proposed a theory of how writing may contribute to learning which is diametrically opposed to the romantic view sketched above. Following Bereiter and Scardamalia ( 1987 ), the complex task of writing requires the writer to integrate knowledge from two different problem spaces: (1) a content space that represents a writer’s knowledge and beliefs about subject matter (i.e., “what do I want so say?”) and (2) a rhetorical space that comprises the writer’s knowledge about rhetorical goals and schemata (i.e., “how do I say what I mean?”). Bereiter and Scardamalia proposed that the writer’s dialectical movement between these two problem spaces in seeking to satisfy both content and rhetorical requirements may produce learning. According to this assumption, germane cognitive load is induced when during planning, a writer selects specific knowledge elements from the content problem space and attempts to translate them into written text by drawing on rhetorical schemata such as metaphor (Ortony 1993 ) or Toulmin’s schema of argument (consisting of claim, data, and warrant, see Toulmin 1958 ). Bereiter and Scardamalia ( 1987 ) assumed that through this working-out of content elements by instantiating rhetorical schemata, the writer’s knowledge becomes reorganized or transformed: For example, a writer works out an envisaged line of argument and realizes in the course of writing how the information in the semantic problem space selected from long-term memory has to be presented as data and warrant in the draft in order to convincingly support an intended claim. Following Bereiter and Scardamalia, it is through such knowledge transforming (i.e., the reorganization and elaboration of a writer’s content knowledge through the instantiation of rhetorical schemata) that learning is produced. As rhetorical schemata play a constitutive role in this conception of writing-to-learn, Galbraith ( 1992 ) has termed the writing-as-problem-solving perspective as the “classic” view in research on writing-to-learn.

The two perspectives on writing-to-learn mentioned above make quite distinct assumptions about the specific cognitive activities involved in writing on which learners should focus their mental effort in order to expand their knowledge and comprehension of subject matter. Following the romantic view, the mere activity of articulating one’s ideas about subject matter in written text should entail learning. Hence, with regard to the design of writing tasks, forms of spontaneous and expressive writing, which allow the writer to freely develop their ideas about subject matter, should yield the greatest learning gains. Following the classic view, on the other hand, learners should explicitly be encouraged to invest mental effort in rhetorical writing, that is, to focus on the rhetorical aspects of writing and trying to instantiate a particular genre, for example, writing an argumentative essay or a research report in line with APA guidelines, as perfect as possible.

However, a closer inspection reveals that the assumptions of both the romantic view and the classic view regarding how to best achieve learning by writing can be called into question. On the one hand, it is obvious that writing to instantiate a particular genre (e.g., a research report in psychology) imposes high cognitive load on the writer and is likely to overtax novice writers. Every professor who ever supervised a bachelor, master, or PhD thesis knows how demanding it is—even for graduate students—to produce a coherent and rhetorically well worked-out empirical journal article. Accordingly, Scardamalia and Bereiter ( 1991 ) regularly found in their expert-novice studies that expert writers were much better than novices at controlling their text production in line with rhetorical goals. However, their empirical studies eventually left open the question whether novice writers with a low level of rhetorical genre knowledge (see Winter-Hölzl et al. 2016 ) can indeed deepen and expand their knowledge by trying to conform to a particular rhetorical genre.

On the other hand, with regard to the romantic view, it is questionable whether unguided expressive writing would indeed lead to substantial learning gains. For example, Nückles et al. ( 2004 ) had university students write learning journal entries as follow-up course work to the weekly seminar sessions. For writing the learning journal, the students received only a brief and informal introduction. Nückles and colleagues found that, on average, the students showed a rather low level of cognitive knowledge construction activities in the journal entries; at the same time, the amount of actually realized knowledge construction strongly correlated with learning outcomes as measured by a test at the end of the term.

In line with this result, the available empirical evidence generally suggests that the effects of writing-to-learn tasks typically are rather small, though positive. In their meta-analysis on school-based writing-to-learn task assignments, which included different types of “informational” writing such as writing summaries, reports, or descriptions of scientific processes, Bangert-Drowns et al. ( 2004 ) obtained an average effect size of 0.26 standard deviations, which can be regarded as a small to medium effect (Cohen 1988 ). This finding has to be considered as rather weak evidence both for the romantic and the classic view of writing-to-learn. On the other hand, the meta-analysis by Bangert-Drowns et al. ( 2004 ) also showed that writing tasks that included metacognitive prompts encouraging students to reflect on their knowledge, comprehension difficulties, and learning processes had a significantly larger effect on learning success (Cohen’s d  = 0.44) compared with writing tasks without such prompts. Hence, the learning effect of writing might specifically be dependent on the scaffolding that it provides for metacognitive and self-regulatory processes. Accordingly, Bangert-Drowns et al. ( 2004 ) concluded that the stimulation of metacognitive reflection in writing to learn should be promising especially if metacognitive reflection is combined with a thorough application of cognitive knowledge construction activities.

The Self-Regulation View in Writing-to-Learn: Focusing Mental Effort on the Content Space Rather Than on the Rhetorical Space

In our approach to writing-to-learn, we sought to incorporate the main conclusions of the discussion of the theoretical perspectives and empirical results sketched above. To this end, we adopted journal writing as our writing task. In a learning journal, learners typically write down their reflections on previously presented learning contents. In addition, they should ask themselves what they do not understand and what can be done to close this gap in understanding. In this way, learners can apply beneficial cognitive strategies such as organization and elaboration strategies as well as metacognitive strategies such as monitoring and regulation. We consider learning journals as a promising way of conducting follow-up coursework and as a method to foster self-regulated learning by writing.

In the learning journal entry in Fig.  1 , the first sentence represents a type of organization strategy as the student identified the main points of the last lesson. In the next paragraph, the student applies an elaboration strategy by providing an example for non-specific immune defense. Then, another organization strategy follows by distinguishing different types of cells executing specific immune defense. Afterwards, the student shows an episode of negative monitoring as she articulates difficulties in understanding the functioning of the helper cells. Last, the student regulates her comprehension by developing ideas of how to overcome her comprehension difficulty (see Fig. 1 ).

Excerpt of a learning journal entry as follow-up coursework of a 7th grade secondary student about a lesson on immunology. Note: The text was translated from German and slightly amended for presentation purposes

In line with the romantic view, the writing of such a learning journal is a self-determined way of writing that allows learners to freely develop their ideas about subject matter and to personally select which aspects of a learning episode require deeper reflection. Contrary to the classic view, learners do not need to follow a certain rhetorical structure during this reflection because—unlike genres such as argumentative essays or scientific reports—learning journals specifically do not have a conventionalized rhetorical structure. However, the results of Nückles et al. ( 2004 ) suggest that learners spontaneously tend to keep their invested mental effort at a minimum during journal writing (see also Feldon et al. 2019 ; Shenhav et al. 2017 ) and thus do not sufficiently engage in germane processes of self-regulated learning such as elaboration, organization, monitoring, and regulating knowledge gaps. Consequently, in our journal writing approach, learners are instructionally supported to invest sufficient mental effort in germane processing. In other words, this support consists of prompts eliciting cognitive learning strategies (elaboration and organization) as well as metacognitive learning strategies (monitoring and regulating, see Table 1 for example prompts). Inspired by the meta-analytic results of Bangert-Drowns et al. ( 2004 ), we termed this idea of combining free and expressive writing with a systematic prompting of self-regulatory processes the self-regulation view of writing-to-learn.

Our notion to instructionally support students in investing sufficient effort in germane processes of self-regulated learning without imposing genre-driven cognitive load aligns well with research question 3 of the Effort Monitoring and Regulation (EMR) framework, which has been proposed by de Bruin et al. ( in press ). The framework builds on the model of Nelson and Narens ( 1994 ) that distinguishes between an object level and a meta-level of cognitive processing. At the meta-level, judgments of learning and regulation decisions (referred to as control) take place. Via the process of monitoring, the meta-level receives input from the object level, at which learners engage with the content that is to be learned (see Fig.  2 ). Cognitive load is assumed to have direct links with both levels. The execution of both object-level and meta-level processes imposes cognitive load. On the other hand, cognitive load can influence both learners’ monitoring and regulation processes. For instance, monitoring can be influenced because learners monitor cognitive load and use it as a cue for judging their level of comprehension; regulation can be affected because learners might decide on the basis of their perceived cognitive load whether investing further mental effort is useful and possible (see de Bruin et al. in press ).

The Effort Monitoring and Regulation (EMR) Framework. Note: Reprinted with permission from “Synthesizing cognitive load and self-regulation theory: A theoretical framework and research agenda” by A. B. H. de Bruin, J. Roelle, and M. Baars, this issue

In the EMR framework, the question of how cognitive load on self-regulated learning tasks can be optimized is one of three main research questions (see Fig. 2 ; for detailed information on the other two research questions, see de Bruin et al. in press ). With our approach to journal writing, we seek to provide answers to this research question in particular.

Cognitive Offloading in Journal Writing

From the perspective of cognitive load theory, journal writing appears to be especially promising to facilitate self-regulated learning because of two reasons: First, writing naturally affords writers to externalize their thoughts on paper or on a computer screen. Externalizing one’s thoughts in a written text preserves them, allowing the writer to reread them, and to develop them further (Klein 1999 ). Hence, through externalization, information processing load on working memory is greatly reduced so that cognitive capacity is freed for metacognitive reflection (i.e., monitoring and regulation). At the same time, the externalized thoughts may act as feedback for the writer that triggers associative processes through spreading activation and both facilitates and guides idea generation. Galbraith ( 1992 , 2009 ) has described this dynamic interaction between the writer and the emerging text using connectionist modeling (see Rogers and McClelland 2004 ) and termed it as the implicit knowledge-constituting process in writing. Thus, the potential of writing as a scaffold for self-regulated learning can theoretically be underpinned by the advantages written text offers as an external representation and memory aid (Klein 1999 ).

Second, cognitive offloading is further achieved by the fact that—as argued above—learners do not have to meet prescribed rhetorical standards in journal writing. We call this particularity of journal writing the “genre-free principle.” Accordingly, a high-quality learning journal entry is per definition not expected to be a rhetorically well-shaped text. Thus, in terms of classic linguistic criteria such as text cohesion (Lachner et al. 2017 ), audience design (Traxler and Gernsbacher 2011 ), or readability (e.g., Kincaid et al. 1975 ), a learning journal entry may appear as rather imperfect and idiosyncratic from a reader’s perspective, but may nevertheless prove to be highly beneficial to the writer herself concerning her learning progress achieved by writing this entry. We assume the genre-free principle to facilitate self-regulated learning by journal writing precisely because the writer is offloaded from the burden to invest substantial mental effort in instantiating rhetorical schemata which may be regarded as extrinsic to the goal of comprehending subject matter especially for novice writers. Consequently, because learners are offloaded from focusing much on rhetorical aspects of writing, the available cognitive capacity can fully be invested in germane processing of subject matter.

We suggest that the genre-free principle in journal writing can be considered, at least on a more general level, as a particular variant of the goal-free effect in cognitive load theory (e.g., Paas and Kirschner 2012 ; Sweller et al. 2019 ). In cognitive load theory, it is assumed that trying to reach a specific goal (e.g., finding the solution of a particular mathematics problem, as it is usually required) leads to strategies that do not contribute to learning (e.g., means-ends analysis), imposes extraneous (i.e., unproductive) cognitive load on working memory, and reduces learning outcomes. It is more effective to provide unspecific goals such as “calculate the value of as many variables as you can” so that leaners can focus on learning-relevant (germane) aspects (here: to-be-learned solution steps). Similarly, setting a specific rhetorical format as writing goal would induce writing strategies to stick to this format (genre). These strategies are extraneous to applying cognitive and metacognitive strategies to the learning contents (i.e., germane processes). Hence, taking away the goal to stick to a rhetorical format (i.e., genre-free principle) allows the learners to devote more of their cognitive capacities to germane processing.

What Types of Germane Processing Should Be Instructionally Supported According to the Self-Regulation View?

Based on learning strategy research (e.g., Mayer 2002 ; Weinstein and Mayer 1986 ) and models of self-regulated learning (e.g., Winne and Hadwin 1998 ; Zimmerman 2008 ), several core cognitive and metacognitive learning strategies can be distinguished whose application in journal writing should result in germane processing. We termed these processes “strategies” to highlight that learners would be expected to enact them intentionally when writing a learning journal. On the object level, core cognitive strategies are organization and elaboration (Mayer 2002 ). Through organization strategies, a writer may, for example, identify main ideas of the learning contents, establish links between concepts, and structure the learning contents in a meaningful way. Via elaboration strategies, the writer fleshes out her ideas, particularly by generating examples to illustrate abstract concepts, by using analogies to relate new concepts to familiar ones, and through the critical discussion of contents. Following Mayer ( 2002 , 2009 ) organization and elaboration are at the heart of meaningful learning because they enable the learner to organize the learning contents into a coherent whole and to integrate new information with prior knowledge, thereby enabling deep understanding and long-term retention. As organization and elaboration are assumed to inevitably produce learning, we consider them as germane processes.

On the meta-level, journal writing might in particular facilitate metacognitive strategies such as the monitoring and regulation of comprehension. Comprehension monitoring by writing a learning journal entry particularly enables the identification of knowledge gaps and comprehension difficulties, for example, when a learner fails to find an appropriate example to elucidate the meaning of an abstract concept, or if the learner has difficulty in resolving a contradiction that became apparent by working-out a line of thought. If such impasses are detected during the writing process, the learner could plan to enact remedial activities in order to overcome the identified difficulties and augment their understanding. In the context of this regulation, the learner would return to remedial organization and elaboration strategies. To the extent that learners successfully detect and overcome impasses in their comprehension of subject matter by executing monitoring and regulation strategies, we consider monitoring and regulation also as important germane processes.

Models of self-regulated learning such as the model by Zimmerman ( 2008 ) describe the interplay between cognitive and metacognitive strategies as a cyclical and interactive process (see Fig.  3 ), in which the execution of a particular cognitive or metacognitive strategy recursively initiates an adjacent cognitive or metacognitive process. Thus, completing one learning cycle may naturally segue into further learning cycles until a level of comprehension is achieved that is personally regarded as satisfactory.

Cyclical model of the cognitive and metacognitive processes involved in self-regulated learning by journal writing

Prompting learners to engage in the outlined cognitive and metacognitive strategies of self-regulated learning during journal writing has been proven highly beneficial. To foreshadow the effects of prompted journal writing on learning outcomes, a mini meta-analysis following Goh et al. ( 2016 ) showed a medium-to-large effect size in favor of instructionally supported journal writing by prompts versus unsupported journal writing, Hedges’s g of 0.78, SE  = 0.14, p  < .0001. Footnote 2 This effect is almost double as large as the average effect size Bangert-Drowns et al. ( 2004 ) obtained in their meta-analysis of writing interventions using prompts for metacognitive reflection. Hence, the self-regulation view of writing-to-learn, which is reflected in the outlined journal writing approach, is highly promising. Likely, the substantial benefits of journal writing are due not only to the fact that we designed the journal writing as a self-regulated learning task, but also to the fact that the learners were provided with prompts to optimize cognitive load in performing this task (see Table 1 for example prompts).

How to Optimize Cognitive Load in Self-Regulated Learning by Journal Writing

In view of research question 3 of the EMR framework (i.e., How do we optimize cognitive load on self-regulated learning tasks?), we will summarize and reflect on the main insights of our research program on diverse instructional support procedures that aim to optimize learning outcomes by optimizing cognitive load during self-regulated learning by journal writing. These insights are synthesized from 16 experimental and four correlative studies published in 16 original papers on the Freiburg Self-Regulated-Journal-Writing Approach (all 16 papers are highlighted with an asterisk in the reference list; see also Table 2 for an overview).

Historically, we developed our approach to journal writing primarily for university students to improve self-regulated learning in follow-up coursework at the university and then extended our intervention studies to younger students. When school students participated, we took care that the students could be assumed to have sufficient mastery of transcription skills which can roughly be assumed to be achieved with the entry into secondary school (Wilson and Braaten 2019 ). Transcription is a writer’s ability to transform the words she or he wants to say into written symbols on a page. Transcription comprises the subskills of spelling and handwriting or typing (Graham and Harris 2000 ). We regarded sufficient mastery of transcription skills as an important precondition for successful journal writing, because the execution of these skills can bind considerable working memory resources, especially if the writer cannot carry them out fluently and efficiently. Thus, regarding the goal of the journal writing, that is, deepening one’s comprehension about subject matter by applying cognitive and metacognitive strategies, paying too much attention on how to get the words on the paper would create undesirable extraneous cognitive load. For this reason, we focused on students who could be assumed to have already some mastery of the mechanics of writing (see Graham and Harris 2000 ).

Part of our studies were realized in the laboratory and part of them in the field. In the laboratory studies, students typically received different combinations of prompts for writing a single learning journal entry about a videotaped lecture they had previously viewed. Prompts were typically delivered via a prepared word document in which learners typed their learning journal. In some studies, students received further instructional support in addition to the prompts (e.g., a worked-out example journal entry or meta-strategic information in relation to the prompted strategies, i.e., information about how, when, and why to use the prompted strategies, see Paris et al. 1983 ; Zohar and Peled 2008 ). After they had finished their journal entry, the students took a comprehension test. In some experiments, they took the same test again one or several weeks later to measure the students’ retention of the learning contents. In the field experiments, students usually wrote several learning journal entries, usually once a week after a class or seminar session, over a period of about 3 to 6 weeks, or in some studies, over a whole term (12 weeks). In these field studies, students typically received an extended introduction to journal writing which included a presentation of the cyclical model of cognitive and metacognitive processes involved in self-regulated learning by journal writing (see Fig. 3 ) and a modeling of how the strategies should be applied in writing. We then either varied experimentally different combinations of prompts or we compared a prompted journal writing condition with a no writing control condition. Prompts were delivered via a printed worksheet or a card.

Generally, we measured the quantity of cognitive and metacognitive strategies in learning journals by a coding scheme, differentiating between rehearsal, elaboration, organization, monitoring, and remedial (regulation) strategies (Chi 1997 ). In addition, in some studies, we rated the quality of the strategies (e.g., Glogger et al. 2012 ; Roelle et al. 2017 ). We usually used 6-point rating scales ranging from 1 (very low quality) to 6 (very high quality). At least two independent raters coded and rated the learning journals after having achieved good inter-rater reliabilities (usually ICC > .85, Cohen’s Kappa > .80). Appendix Table 3 shows examples of learning journal excerpts, as well as the coding of the according learning strategy category. The findings from the research program on the Freiburg Self-Regulated-Journal-Writing Approach will be described in more detail in the following subsections of this paper.

Prompting Germane Processing in Journal Writing

Given the aforementioned germane processes involved in self-regulated learning, the question arises, how germane cognitive load can be increased effectively (see research question 3 by de Bruin et al. in press ). That is, how can the cognitive strategies of elaboration and organization, and the metacognitive strategies of monitoring and regulation be activated in an optimal way? As mentioned, unsupported learners tend to use journal writing in sub-optimal ways. Nückles et al. ( 2004 ) found that journal writing without instructional support resulted in almost absent metacognitive strategies and clear deficits in the use of cognitive strategies. Prompts can be used to address such deficits. Prompts are hints or questions that induce productive learning processes (Bannert and Reimann 2012 ; Zheng 2016 ). We conceive of prompts as strategy activators following Reigeluth and Stein ( 1983 ). That is, we assume that learners are, in principle, capable of using learning strategies, but do not spontaneously use them, at least not to a satisfactory degree (e.g., Bannert 2009 ; Nückles et al. 2004 ). In our research program, we developed sets of cognitive and metacognitive prompts in order to increase germane processing in journal writing (see Table 1 ). We investigated whether and how they encourage learners to enact powerful learning strategies and improve learning outcomes.

Experiments that varied the provision of prompts clearly showed that strategy prompts strongly increased learners’ use of the prompted strategies in the learning journals (e.g., an elaboration prompt increases elaboration; Berthold et al. 2007 ; Glogger et al. 2009 ; Nückles et al. 2009 ; Schwonke et al. 2006 ). In addition, the increased use of strategies was accompanied by enhanced learning outcomes (see the mini meta-analysis reported above). Several studies further found that the effect on comprehension (and sometimes retention) was mediated by the strategy use. That is, the prompting is effective through the learning strategies they activate. In Berthold et al. ( 2007 ), the use of cognitive strategies mediated learning outcomes. Roelle et al. ( 2017 ) found the quality of organization strategies to mediate learning outcomes in a conceptual knowledge test in two experiments. These findings underline the germane nature of the learning strategies and that the prompts are the activators of this germane processing.

The prompting germane processing principle in journal writing, however, does not only refer to the pure increase of strategy use. Much of our research program has concentrated on finding the optimal combination (e.g., combination of cognitive and metacognitive prompts) and sequencing of different types of prompts in order to maximize germane cognitive load and to foster deep comprehension and acquisition of sustainable knowledge.

How to Combine Prompts to Optimize Germane Processing

Do learners need both cognitive prompts and metacognitive prompts (i.e., for monitoring and regulation) to optimize germane processing in journal writing? Berthold et al. ( 2007 ) found that undergraduate students who received cognitive, or a combination of cognitive and metacognitive prompts learned more than students without prompts. Students provided only with metacognitive prompts, however, did not learn more than those without prompts. They applied a high amount of metacognitive strategies but very few cognitive strategies. The two successful groups, however, used a balanced amount of cognitive and metacognitive strategies in their learning journals. The use of cognitive learning strategies mediated the effect on learning outcomes.

Is the unbalanced use of metacognitive strategies a problem? Are the prompted metacognitive strategies rather detrimental to learning (i.e., inducing not only germane load)? Nückles et al. ( 2009 ) replicated the experiment of Berthold et al., but this time gave all learners time and access to the learning material during a later writing phase to better allow for metacognitive regulation of detected comprehension problems and application of remedial strategies. Accordingly, during this writing phase, students were given the opportunity to revise their learning journal. Nückles et al. also included a further experimental condition, as compared to Berthold et al. ( 2007 ), in which prompts for the planning of remedial strategies were added to the formerly used cognitive and metacognitive prompts. More specifically, the learners received either (a) no prompts, (b) cognitive prompts (elaboration and organization, see cognitive prompts with superscript “b” in Table 1 ), (c) all types of metacognitive prompts (superscript “b” in Table 1 : monitoring, planning of remedial strategies), (d) mixed prompts (cognitive and metacognitive prompts) without, or (e) with prompts for planning of remedial strategies (marked with superscript “a” in Table 1 ). The experiment successfully replicated the results in Berthold et al. ( 2007 ) with regard to the learning outcomes of cognitive prompts (i.e., condition b) and the combination of cognitive and metacognitive prompts (i.e., mixed prompts, see condition d above). In contrast to the results of Berthold et al. ( 2007 ), however, metacognitive prompts alone (i.e., condition c, see above) also improved learning outcomes. That is, prompting metacognitive strategies alone is not detrimental—if the planning of remedial strategies is prompted and learners have the opportunity to realize the remedial strategies. In real-world contexts, this opportunity is usually given.

The most successful set of prompts, however, was the combination of all types of prompts (i.e., condition e, see above). That is, prompting all essential sub-processes of self-regulated learning fostered students’ comprehension best. The two most successful groups in this study again used cognitive as well as metacognitive strategies and showed a balanced use of the different strategies.

In a correlative field study, Glogger et al. ( 2012 ) had ninth graders write learning journals in mathematics over the term of 6 weeks. The quality and quantity of cognitive strategies predicted learning outcomes, controlling for prior knowledge. Learners who applied both cognitive plus metacognitive strategies were particularly successful. Learners who mainly used one type of strategy performed similarly poorly as did learners who hardly used strategies. In a conceptual replication in biology classes, again the combination of cognitive and metacognitive strategies made students most successful.

All in all, using a combination of cognitive and metacognitive prompts is a powerful instructional strategy to optimize germane processing. At the same time, it is important to activate all sub-processes of self-regulated learning in learners, that is, to prompt organization and elaboration, monitoring of comprehension, and planning of remedial cognitive strategies (see Fig. 3 ).

How to Sequence Prompts to Optimize Germane Processing

A further, more recent question in our research program is, whether the sequence of different types of prompts is important in order to optimize germane cognitive load. In our previous research, we usually gave cognitive and metacognitive prompts at the same time, but cognitive prompts were printed above metacognitive ones (e.g., Berthold et al. 2007 ; Nückles et al. 2009 ). In the correlative field study with ninth graders (Glogger et al. 2012 ), we prompted the following sequence, depicted as a round-trip: (1) monitoring, (2) organization, (3) elaboration, (4) monitoring again and planning remedial strategies. However, in none of the mentioned studies, we investigated to what extent learners realized the metacognitive strategies prior to the cognitive strategies or vice versa and whether the sequence matters for learning. There is reason to expect that the sequence matters.

After engaging in metacognitive strategies, that is, identifying gaps in understanding and putting effort into closing them, learners should have a more solid knowledge base. Thus, they should be able to organize the main content in a more coherent manner and elaborate on the main content more deeply (cognitive processing) than before (e.g., Glogger-Frey et al. 2015 ; Mayer 2009 ; Roelle and Berthold 2016 ). On the other hand, cognitive processing of the learning contents should give cues as to how well learners have understood the contents and where exactly they have gaps in understanding (de Bruin et al. in press ; Nelson and Narens 1994 ). Thus, engaging in cognitive processing first might inform comprehension monitoring and planning of remedial strategies to close specific gaps. It might improve subsequent metacognitive processing.

Against this background, Roelle et al. ( 2017 ) manipulated the sequence in which tenth-graders responded to cognitive and metacognitive prompts (see superscript “c” in Table 1 ). More specifically, after attending a lecture in a first experiment, or regular school lessons in a second experiment, the students wrote learning journals as follow-up activity. During writing, the learners were prompted to either (a) engage in the cognitive processes of organization and elaboration prior to engaging in metacognitive processes (i.e., monitoring and planning of remedial strategies) and implementing their remediation plans (cognitive-first group), or (b) engage in the same metacognitive and remedial processes prior to organizing and elaborating on the learning content (metacognitive-first group).

In both experiments, the learners in the metacognitive-first group outperformed their counterparts regarding the quality of the executed organization and metacognitive processes as well as in a conceptual knowledge test. These results can be interpreted as follows: writing down gaps in understanding as well as planning and realizing remedial strategies built a more solid knowledge base, on which the students were better able to organize the learning contents. It is also possible that engaging in comprehension monitoring (and actually identifying gaps in understanding) first helped the learners to recognize the need for engaging in deep processing of the learning content. As a consequence, they invested more effort in subsequent organization (and elaboration) processes (see the preparation-to-learn effect of knowledge gap experiences, Glogger-Frey et al. 2015 ; Loibl et al. 2017 ). Investigating this effort in future studies would contribute to answering research question 1 (How do students monitor effort?) and research question 2 (How do students regulate effort?) of the EMR Framework (de Bruin et al. in press ). First evidence by Roelle et al. ( 2017 ) suggests that the sequence matters in prompting germane processing. Further possible sequences of prompts could be investigated in further research.

In summary, our research program on self-regulated learning journals suggests that learners are optimally supported in distributing germane load between the object level and the meta-level by prompting them to engage in all sub-processes involved in self-regulated learning: cognitive (elaboration, organization) and metacognitive strategies including monitoring as well as planning of remedial strategies (see Fig. 3 ). In addition to prompting all types of sub-processes, metacognitive strategies should be prompted first.

Effects of Worked Examples and Self-Explanations

The worked example effect is a classical cognitive load theory effect (e.g., Sweller and Cooper 1985 ; Sweller et al. 1998 ). It describes the advantage of studying worked examples as compared to learning by doing (e.g., problem solving, exploring) for the initial acquisition of cognitive skills (e.g., solving certain types of mathematical problems or engaging in effective learning strategies; e.g., Renkl 2014a , b ). Note that learning by worked examples is usually optimized if the learners not only (superficially) read through the examples but are nudged to self-explain the principles (e.g., mathematical theorems, strategy guidelines) applied in the examples (self-explanation effect; e.g., Chi et al. 1989 ; Renkl 2017 , Renkl and Eitel 2019 ). In recent publications, the self-explanation effect has been integrated into cognitive load theory (e.g., Sweller et al. 2019 ).

In our research program on the Freiburg Self-Regulated-Learning-Journals Approach, we tested whether the worked example effect can be exploited for fostering the quality of students’ learning journals. More specifically, we tested whether students react to provided strategy prompts (see our previous sections on prompting) more adequately if we show them and have them self-explain examples of good responses to such prompts before journal writing. Furthermore, we also tested whether the potentially improved responses to prompts also led to better learning outcomes.

Hübner et al. ( 2010 ) had their participating high school students read a general introduction into journal writing. In particular, they were informed about the main objectives of journal writing and possible fields of application. In addition, cognitive and metacognitive prompts for journal writing were introduced. Afterwards, half of the students got an example of a well-written learning journal entry about a fictitious physics lesson to illustrate how to react sensibly to the introduced cognitive and metacognitive prompts. Moreover, these students were requested to self-explain the examples by assigning single passages in the learning journal to the corresponding cognitive or metacognitive prompts; the students got feedback to their assignments. Following this, the high school students entered a training phase. They first watched a videotaped lecture on a topic from social psychology (topic: social pressure) and then engaged in journal writing. A comprehension-oriented posttest assessed how much the students had learned about social pressure. In a transfer session, 1 week later, the students watched again a social psychology lecture (topic: destructive obedience) and engaged in journal writing. In this transfer session, all students just received the prompts (without any further support such as examples). Finally, a comprehension-oriented posttest assessed how much the students had learned about destructive obedience. Hübner et al. ( 2010 ) obtained the following main findings: Self-explaining a learning journal example enhanced in particular elaborative learning strategies as expressed in the learning journals, both in the training and in the transfer session (strong effects). A similar effect was found for metacognitive strategies (strong effect in the training session); however, this effect slightly failed to reach the level of statistical significance in the transfer session. Most importantly, self-explaining a learning journal example had a strong effect on the learning outcomes on destructive obedience in the transfer session. Overall, Hübner et al. ( 2010 ) showed that the worked example effect and the self-explanation effect could be exploited to enhance transfer in the sense that the students wrote better learning journals (in particular, more elaboration) on a new topic and also achieved better learning outcomes on this topic.

Roelle et al. ( 2012 ) tested whether the examples should be provided right from the beginning, as in Hübner et al., or after some experience in journal writing. Although worked examples are usually introduced early (see Renkl 2011 , 2014b ), there might be advantages of a delayed provision of worked examples: Even in the case of missing examples, the learners receive an introduction to journal writing (see the previous description of the study by Hübner et al. 2010 ), which is usually a new and complex learning method, and they have to apply this method to some new learning contents (e.g., social psychology topics or mathematics). Having additionally to self-explain examples on an additional topic (i.e., physics in the case of Hübner et al. 2010 ) and to relate these examples to the new topic might be very demanding and potentially lead to cognitive overload in some students (see, e.g., Sweller 2006 ). To test the effect of immediate or delayed presentation of examples, Roelle et al. ( 2012 ) conducted a quasi-experimental field experiment in high school mathematics (5th grade). Journal writing was used as homework after each of four mathematics lessons. In one classroom, the examples were introduced before the first learning journal entry and withdrawn after having written the second learning journal entry; in another classroom, the examples were provided as additional support before writing the third and fourth learning journal entries. Basically, it was found that providing examples early led to qualitatively better learning journal entries in the beginning (first two lessons) and to the acquisition of more conceptual knowledge from the first two and the last two lessons (no effects on procedural knowledge). Overall, presenting examples for productive journal writing early is superior, which is in line with cognitive load theory and the theory of example-based learning by Renkl ( 2014b ).

Graichen et al. ( 2019 ) tried to conceptually replicate the effects of examples on the quality of learning journals and learning outcomes in the context of teacher education. More specifically, the authors had their participating student teachers (geography) write learning journal entries in which they should integrate information from three texts providing content knowledge (here: on geography), pedagogical content knowledge (here: on geography education), and pedagogical knowledge (see Shulman 1987 ). Footnote 3 For this purpose, the prompts used by Hübner et al. ( 2010 ) were modified so that they also encouraged the learners (except for those of the control group) to integrate the information from the different texts, that is, to use coherence-creating strategies. Overall, the authors found mixed results. Combining prompts with examples, as compared to providing just prompts, led to more high-quality coherence-creating strategies in learning journals. However, this example effect did not lead to more knowledge or better knowledge application, as compared to prompts alone. A tentative explanation might be that a case of a utilization deficiency was found (e.g., Miller 2000 ): The execution of the unfamiliar and demanding coherence-creating strategies imposed heavy cognitive load so that the learners were partly distracted form the learning contents. Only after more training on these strategies less cognitive load would be imposed when applying them, and they would then provide the expected benefit.

Note that examples of journal entries were also used in other studies on the Freiburg Self-Regulated-Journal-Writing Approach to prepare the learners for their writing task (e.g., Glogger et al. 2009 , Roelle et al. 2011 , Roelle et al. 2017 , see Table 2 ). However, there was no experimental variation in these studies in this respect. Nevertheless, using worked examples has proven to be a sensible part of the introduction to journal writing. Thereby, the students are enabled to engage in productive journal writing.

Overall, the available evidence suggests that self-explaining worked examples is a sensible instructional procedure to prepare the learners for journal writing, in particular, as transfer effects were repeatedly found, which is usually hard to achieve (e.g., Barnett and Ceci 2002 ). Self-explaining worked examples probably optimizes cognitive load during journal writing in terms of reducing extraneous activities during writing and fostering germane writing activities.

Self-management Effects in Journal Writing

A recent effect within cognitive load theory is the self-management effect (e.g., Eitel et al., in press , Mizza et al. 2020 ). This effect refers to enabling learners who are confronted with learning materials violating design principles from cognitive load theory to cope successfully with this sub-optimality; hence, their learning is not hampered. For example, the learners are taught (a) to detect that split attention is evident in learning materials (i.e., text and picture as separate information sources) and (b) to then apply strategies to map the two information sources onto each other. Up to now, this effect has been mainly established for the split attention sub-optimality (Mizza et al. 2020 ). Note that the students usually get very detailed instruction on how to proceed (i.e., little self-regulation) so that they can compensate for split-attention effects (e.g., Roodenrys et al. 2012 ).

Eitel et al. ( 2020 ) recently extended the self-management effect by emphasizing learners’ self-regulation. These authors “just” provided parsimonious information about the specifics of learning materials (e.g., what type of information is peripheral) and counted on learners’ self-regulation to avoid potential extraneous load from sub-optimal design (i.e., no provision of detailed instruction). More specifically, the learners were informed before entering the learning environment that the pictures (including a short accompanying text) about the consequences of lightening (i.e., seductive details) were not relevant for the present learning goal to understand the development of lightening. Actually, this information enabled the learners to self-manage their later learning in that they largely ignored the seductive details so that these details did not hamper learning outcomes; the learners without this information, in contrast, were hampered in their learning by the seductive details (Eitel et al. 2020 ).

The positive effects of two instructional support procedures that we have found in our research program on the Freiburg Self-Regulated-Learning-Journals Approach can be re-interpreted as self-management effects primarily in the sense of Eitel et al. ( 2020 ). First, the worked example effects that were discussed in the previous section can be regarded as a self-management effect. Such a claim may be puzzling at first glance as in classical cognitive load research, these two effects are not related: Worked examples help learning on the content or object level (e.g., mathematics); providing information for self-management helps on the meta-level to best exploit the present learning opportunity. Note, however, that in our journal writing approach, the worked examples do not teach knowledge on the object level (e.g., physics or social psychology; see Hübner et al. 2010 ) but on the meta-level, that is, knowledge about how to best exploit the learning opportunity of journal writing (for an extensive discussion of different levels in worked examples see Renkl et al. 2009 ). More specifically, we tried to teach the (potentially) transferable skill to self-manage journal writing by our worked examples. Actually, we found such transfer effects in Hübner et al. ( 2010 : enhanced learning outcomes with respect to obstructive obedience).

Second, Hübner et al. ( 2010 ) not only provided worked examples as support procedure for journal writing but also presented to half of their learners a type of informed training (Paris et al. 1983 ). More specifically, half of the learners received a short presentation (10 min) about the utility of the strategies to be elicited by our prompts; in particular, declarative knowledge about learning strategies and corresponding conditional knowledge (i.e., when and how to use these strategies) was taught. As expected, the metacognitive knowledge about the strategies (targeted by our prompts) that was provided by the informed training fostered learning on the object level in the training phase (topic: social pressure; strong effect) as well as in the transfer phase (topic: destructive obedience; medium effect). Again, these findings can be interpreted as a self-management effect: The informed training taught the learners on the meta-level how to effectively exploit prompted journal writing so that transfer effects to learning on the object level could be achieved.

Relating our findings to the EMR framework (research question 3), worked examples and informed training enabled the learners to effectively regulate their strategy use in journal writing on the meta-level: Tentatively, the supported learners minimized writing that was not connected to applying learning strategies, thereby reducing extraneous load. In addition, an increased focus on strategy-related writing fostered germane cognitive load.

Adapting and Fading Guidance in Line with Learners’ Expertise in Self-Regulated Learning Strategies

Inspired by the guidance-fading effect (e.g., Sweller et al. 2011b ) and the expertise reversal effect (e.g., Kalyuga et al. 2003 ), we also delved into the role of adapting the instructional support measures that are designed to foster cognitive and metacognitive strategies of self-regulated learning, to the learners’ expertise. Up to date, this research has yielded three main insights.

Fading Guidance Adaptively in Line with Learners’ Growing Strategic Expertise

The first main insight is that in prompting germane processing, learners’ learning strategy expertise needs to be considered. In a field experiment with university students, Nückles et al. ( 2010 ; Exp. 1) found that the benefits of prompting cognitive and metacognitive strategies concerning both the elicitation of the respective strategies and learning outcomes diminished when the prompts were provided over the course of 12 weeks. More specifically, similar to the abovementioned studies that involved only one or two journal entries (e.g., Berthold et al. 2007 ; Nückles et al. 2009 ), the authors found beneficial prompt effects in an initial phase of journal writing (i.e., in the first 6 weeks). By contrast, in a later phase of journal writing (i.e., the following 6 weeks), the provision of prompts led to a significant decrease in the use of cognitive and metacognitive learning strategies and the superiority of the prompted group over the not-prompted group in terms of learning outcomes completely diminished. One explanation for this pattern of results is that over time learners internalized the guidance provided by the prompts, which caused the prompts to change from essential guidance that helps learners to engage in germane processing to redundant guidance that requires reconciliation with internal guidance and thus mainly induced extraneous cognitive load. This explanation is supported by the second experiment of Nückles et al. ( 2010 ). In this experiment, the authors tested a procedure in which the prompts were faded once a learner had applied the respective prompted strategies in high quality in two previous journal entries. The results showed that this adaptive fading procedure fostered cognitive learning strategies and learning outcomes (but not metacognitive strategies) in comparison to permanent prompting in subsequent journal entries. Hence, prompts should be faded out past a certain point in a manner adapted to learners’ learning strategy expertise.

Adapting Guidance to Learners’ Level of Strategic Expertise

Further evidence that the extent to which prompts contribute to germane processing in journal writing can be optimized by adapting the prompts to learners’ learning strategy expertise stems from an experiment of Schwonke et al. ( 2006 ). In this experiment, learners first wrote a learning journal entry without prompt support and subsequently were instructed to revise their drafts. For revising, the learners received either prompts that were adapted to them on the basis of their responses to a learning strategy questionnaire or a meta-strategic knowledge test; two comparison groups received either a random set of (cognitive or metacognitive) prompts or no prompts at all. With respect to both elaboration and metacognitive strategies, the adaptive prompts (the two adaptation procedures yielded similar effects) proved to be more effective than the random prompts and no prompts, whereas the random prompts were partly even worse than no prompts. Similar effects were obtained with respect to learning outcomes. The adaptive prompting fostered understanding in comparison to both random and no prompts, whereas there was no significant benefit of random prompts over no prompts. In conjunction with the abovementioned findings concerning the benefits of the adaptive fading procedure, these results make a strong case for the notion that implementing the prompting germane processing principle needs to consider learners’ learning strategy expertise.

The studies by Nückles et al. ( 2010 ) and Schwonke et al. ( 2006 ) refer to the role of inter-individual differences in learning strategy expertise within a certain student population (i.e., within university students). There is also evidence that in prompting germane processing, differences between student populations that pertain to learners’ developmental level should be considered as well. In a quasi-experiment by Glogger et al. ( 2009 ), ninth-grade high school students received cognitive and metacognitive prompts (as well as worked examples) that were similar to the ones that had proven to be effective in university students. For these learners, the prompts scarcely elicited cognitive and metacognitive strategies. One explanation for this finding is that the guidance provided by the prompts was too low for ninth-grade high school students. This explanation is underpinned by a second finding of Glogger et al. ( 2009 ). When ninth-grade high school students received prompts that were enriched by specific suggestions concerning the implementation of cognitive and metacognitive strategies (e.g., the prompt “Try to build connections between what you have learned last week and what you already know” was enriched by the suggestion “For this purpose, write down how you could apply what you have learned this week at home in your spare time,” see also the prompts with superscript “d” in Table 1 ), the prompts were more effective concerning the elicitation of the cognitive learning strategies of organization and elaboration. Apparently, this level of guidance was better aligned with learners’ learning strategy expertise than the rather abstract prompts that are effective for university students. In terms of metacognitive strategies, however, no beneficial effects of the specific prompts were found. Possible explanations for the lack of effect concerning metacognitive strategies could be that metacognitive strategies are cognitively more demanding than cognitive ones (e.g., Bannert 2007 ) and/or that putting one’s understanding into question might be regarded as unpleasurable by many learners.

Learner Expertise and Feedback

The third main insight concerning the adaptation of instructional support to learners’ learning strategy expertise relates to the provision of feedback. In a field study, Roelle et al. ( 2011 ) provided learners writing learning journals over the course of 14 weeks with elaborated feedback on the quality of their cognitive and metacognitive strategies. The authors found that the feedback fostered the quality of cognitive learning strategies for learners who performed relatively poorly in their journal entries before the feedback. By contrast, for learners who had already shown high-quality cognitive strategies in their learning journals before the feedback, the feedback detrimentally affected the quality of cognitive strategies in subsequent journal entries (in terms of metacognitive strategies, the feedback did not entail any significant effects). This pattern of findings, which aligns with a full expertise reversal effect (e.g., Kalyuga et al. 2003 ), can be interpreted as follows. For the learners who merely executed low-quality cognitive learning strategies in their journal entries, the external guidance by the feedback compensated for the lack of learning strategy expertise and thus fostered cognitive learning strategy quality in subsequent entries. In contrast, for the learners who were already able to apply high-quality cognitive learning strategies, the external guidance was redundant and interfered with learners’ internal guidance thus contributing to extraneous rather than to germane cognitive load. Consequently, it detrimentally affected the quality of cognitive learning strategies in subsequent entries. Although to date there is no evidence concerning potential benefits of adaptively faded feedback, these findings suggest that in optimizing cognitive load in self-regulated learning through journal writing, instructors should consider learners’ learning strategy expertise when providing feedback.

Relatedness of Cognitive and Motivational Processes in Journal Writing

Our research program on self-regulated-learning-journals has also yielded insights into the relatedness of cognitive and motivational processes whereby both beneficial and detrimental effects have been found. A first main insight of the studies that dealt with this issue is that the prompting germane processing principle entails motivational costs. Specifically, in two experiments with university students, Nückles et al. ( 2010 ) found that both permanent prompting of cognitive and metacognitive strategies over the course of 12 weeks and faded prompting of cognitive and metacognitive strategies (see the adapting and fading guidance in line with learners’ expertise section above) yielded substantial decreases in students’ motivation to engage in journal writing over time.

One explanation for these motivational decreases could be that learners perceive the cognitive load that they have to invest in applying the prompted strategies during journal writing as motivational cost (see Feldon et al. 2019 ). The concept of cost (i.e., the effort needed to complete a task and the other activities that one must give up in order to complete the task) has been recently considered as a third important core component that determines learners’ motivation in expectancy-value theories, in addition to expectancy (i.e., the extent to which learners believe they can succeed in a task) and value (i.e., that the respective task is important; see, e.g., Barron and Hulleman 2015 ). The higher the costs, the lower learners’ motivation to engage in a task. Following this line of argumentation, regardless of whether learners receive instructional support that is well aligned with their expertise (i.e., faded prompting in Exp. 2 of Nückles et al.) or (at least in part) redundant (i.e., permanent prompting in Exp. 1 of Nückles et al.), it might be the case that learners perceive the effort they have to invest into the prompted germane cognitive and metacognitive strategies as relatively high and thus responding to the prompts as cost-intensive. As a consequence, their motivation to engage in journal writing decreases over time.

There is also evidence, however, that even when the prompting germane processing principle is not implemented, learners’ motivation to engage in journal writing slightly decreases over time (Exp. 1 of Nückles et al. 2010 ). Hence, the journal writing itself likely entails some motivational costs as well. In the mentioned experiments by Nückles and colleagues, the learners might over time have perceived that the time and effort invested in journal writing has detrimental consequences on either other academic tasks or non-academic activities that learners had to give up or in which they could merely invest insufficient effort due to the journal writing. Future studies should delve into these motivational effects of journal writing more deeply and aim to differentiate between the perceived costs of the journal writing and the benefits of the prompting germane processing principle.

Despite the outlined detrimental effects concerning the motivation to engage in journal writing, it cannot be concluded that prompting germane processing entails detrimental motivational effects only. The detrimental effects regarding learners’ journal writing motivation are contrasted by beneficial effects regarding learners’ motivation to engage with the learning content on which they reflect in their journal entries. Specifically, Wäschle et al. ( 2015 ; Exp. 1) found that prompted journal writing performed as homework fostered seventh-grade high school students’ interest in the learning content (i.e., immunology) in comparison to three different homework tasks (i.e., answering teacher provided questions, creating a concept map, writing a summary). This beneficial effect regarding content-related motivation, which occurred only after a delay of several weeks, was mediated via the benefits of prompted journal writing regarding comprehension. That is, because prompting germane processing fostered comprehension of the learning content, learners’ motivation to engage with the learning content in subsequent learning phases was fostered, too.

In an attempt to mitigate the detrimental effect of the prompting germane processing principle on journal writing motivation without decreasing the beneficial effect on content-related motivation, Schmidt et al. ( 2012 ) investigated the effects of prompting learners to reflect on the personal relevance of the learning content in addition to prompting the established cognitive and metacognitive learning strategies. The results of their experiment indicated that a personal utility prompt (“Why is the learning material personally relevant for you at present or future out of school?”) increased both students’ acceptance of journal writing as well as content-related motivation in comparison to prompting only cognitive and metacognitive strategies. Moreover, the beneficial motivational effects were accompanied by increased learning outcomes (i.e., comprehension). Jointly, these findings suggest that the motivational costs of the prompting germane processing principle can be mitigated via prompting learners to reflect on the personal relevance of the respective learning content in their learning journals. Further support for the benefits of the personal utility prompt stems from Wäschle et al. ( 2015 , Exp. 2). In a field study with tenth-grade high school students, the authors replicated the finding that the personal utility prompt increased content-related motivation as compared to the established cognitive and metacognitive prompts only. Although the increased motivation was not reflected in higher performance on a comprehension test in this study, it nevertheless fostered another facet of learning outcomes. Those learners who received the personal utility prompt outperformed their counterparts on an argumentation task that required them to critically reflect on the learning content.

A final insight of the studies that dealt with the role of motivation in journal writing is that not only the type of prompts, but also the goal structure in which the journal writing is embedded matters. In an experiment with ninth-grade high school students, Moning and Roelle ( 2020 ) varied whether the journal writing task was embedded in a mastery goal structure or in a performance goal structure. The mastery goal-structured journal writing task emphasized students’ individual effort and progress. Specifically, the students were told that, by writing the learning journal, they should try to improve their comprehension of a text they had read before. Furthermore, in order to induce a self-referential feedback expectation, they were told that they would receive feedback on the improvement of their comprehension afterwards. In contrast, the performance goal-structured journal writing task emphasized high normative performance (i.e., in comparison with the performance of the other classmates). Accordingly, the students in that condition were told to demonstrate a better comprehension than their classmates of the text they had read before. Furthermore, in order to induce a normative feedback expectation, they were told that they would receive feedback concerning their own comprehension compared to the comprehension of their classmates.

The authors found that a mastery goal structure better fostered the quality of metacognitive processes (i.e., the specificity of monitoring, self-diagnosis, and regulation), learning efficiency, and learning outcomes than a performance goal structure. One explanation for this finding is that the students in the mastery goal structure group might have considered detailed comprehension monitoring as highly useful because journal writing can be used particularly to improve comprehension of initially poorly understood content. In contrast, as overtly reflecting on comprehension difficulties would have conflicted with demonstrating high competence, the students in the performance goal structure group might have considered detailed comprehension monitoring at least in part as a waste of time and effort. The outlined differences in comprehension monitoring potentially brought about the differences in learning efficiency (learning outcomes in relation to invested mental effort) and learning outcomes. High-quality comprehension monitoring might have fostered the degree to which learners deeply engaged with content they had not yet understood well, which, in comparison to engaging with already well-understood content, fostered both learning efficiency and outcomes in the mastery goal structure group.

Summary and Directions for Future Research

In the present paper, we have introduced the self-regulation view in writing-to-learn as a promising theoretical perspective that draws on models of self-regulated learning (e.g., Zimmerman 2008 ) and cognitive load theory (e.g., Sweller et al. 2011a , 2011b , 2019 ). Accordingly, we argued that writing has the potential to act as a powerful scaffold for self-regulated learning due to the cognitive offloading written text generally offers as an external representation and memory aid, and due to the offloading, that specifically results from the genre-free principle in journal writing. However, to enable learners to optimally exploit this learning opportunity, the journal writing needs to be instructionally supported. Accordingly, we developed and tested in our research program instructional support methods for self-regulated journal writing. Irrespective of the offloading nature of the journal writing (especially because of the genre-free principle), our support methods were of course intended to increase cognitive load by inducing higher levels of germane cognitive load. However, if the support is not well aligned with the learners’ strategic expertise, it can also induce extraneous load (see expertise reversal effect).

The most important support procedure is prompting cognitive und metacognitive strategies. Learning was best when prompts activated all major sub-processes of self-regulated learning (i.e., organization, elaboration, monitoring of comprehension, and planning of remedial cognitive strategies) and when metacognitive prompts preceded cognitive prompts. Other effective support procedures were informed prompting, (self-explaining) worked examples, and feedback. Informed prompting and worked examples fostered also the skill to self-manage effective journal writing on new topics. Evidence for the relevance of the expertise reversal effect was shown in our research program for (the way of) prompting (Nückles et al. 2010 ) and for feedback (Roelle et al. 2011 ). Hence, these support procedures are best used in an adaptive way (e.g., fading support with growing learner expertise). Our findings also suggest that the effort that students have to invest for the journal writing to be effective has motivational costs. These motivational costs can be buffered with prompts for reflecting on the personal relevance of the learning contents. Finally, emphasizing mastery (vs. performance) goals has been shown to benefit learning.

Relating the Results of the Freiburg Research Program on Journal Writing to Other Research on Writing-to-Learn

Experimental research on journal writing outside the Freiburg Self-Regulated-Journal-Writing Approach is scarce and has mainly been published in the form of case studies presenting anecdotal evidence from applications of journal writing in higher education (e.g., Burke and Dunn 2006 ; Creme 2005 ) and as part of classroom instruction in secondary education (Carson and Longhini 2002 ; Swafford and Bryan 2000 ). In one of the few published quasi-experimental studies, Cantrell et al. ( 2000 ) contrasted prompted journal writing with summary writing to support reading comprehension. In the journal writing condition, students were prompted to ask themselves what they already knew about the learning content, what they would like to know about the topic, and what they had learned from their reading. Thus, Cantrell et al.’s ( 2000 ) prompts were similar to the elaboration and organization prompts of the Freiburg approach to journal writing inasmuch as they asked students to activate and relate their prior knowledge to the to be learned information (i.e., elaboration) and to determine for themselves the main points they had learned from the reading (i.e., organization). Cantrell et al. found accordingly that the prompted journal writing significantly benefitted more students’ learning than the summary writing. In a related experimental study, McCrindle and Christensen ( 1995 ) contrasted journal writing with writing a conventional scientific report in a first-year biology course at university. The researchers found that students in the journal writing condition articulated more cognitive and metacognitive learning strategies on a learning strategy assessment task, acquired more complex and integrated knowledge, and performed significantly better on the final exam as compared with the students in the scientific report condition. Together, the scarce available (quasi-) experimental evidence outside the Freiburg Self-Regulated-Journal-Writing Approach confirms the main insights from the Freiburg research program inasmuch as using the journal writing to encourage the application of cognitive and metacognitive strategies clearly improved students’ learning gains.

In a recent overview on different approaches to writing-to-learn, Klein et al. ( 2019 ) identified besides journal writing several other approaches, with writing summaries or discourse syntheses and writing argumentations as the most important ones. With regard to summary/synthesis writing and argumentative writing, the available empirical evidence is quite mixed (see Klein 1999 , and Klein et al. 2019 , for summaries) and difficult to compare to the Freiburg research program on journal writing. A major difference to the Freiburg approach to journal writing is that researchers investigating summary/synthesis or argumentative writing typically implemented and evaluated complex and time-intensive writing trainings including phases of modeling and writing exercises often lasting over several weeks (e.g., Gelati et al. 2014 ; Martínez et al. 2015 ). In these writing trainings, the goal typically was to teach students how to write a good summary or synthesis. Accordingly, text quality and the acquisition of the rhetorical genre in question (i.e., what makes a good summary or a good argumentation?) was the main focus in those studies and learning goals such as deep comprehension and long-term retention of subject matter were rather secondary (see, e.g., Klein et al. 2017 ; Nussbaum and Schraw 2007 ). In contrast to those approaches, acquisition of a particular text genre is not the goal of the Freiburg Self-Regulated-Journal-Writing Approach. Accordingly, by implementing instructional procedures such as strategy prompts and worked examples of journal entries, we sought to keep the rhetorical demands of journal writing as low as possible in order to optimize germane processing and learning outcomes in terms of deep comprehension and long-term retention of subject matter.

The Role of Learner Prerequisites for the Benefits of Journal Writing

Our extant research clearly shows that, on the whole, instructionally supported journal writing benefits a wide range of students including young secondary school students aged between 11 and 14 years as well as older university students aged between 20 and 25 years old (see Table 2 or an overview). Also, the tested support methods such as the provision of prompts or worked examples proved to be similarly effective both for younger secondary students (e.g., Roelle et al. 2012 ; Wäschle et al. 2015 ) and older secondary or university students (e.g., Hübner et al. 2010 ; Nückles et al. 2009 ).

On the other hand, our studies also showed that, in order to optimize cognitive load in journal writing, instructional support methods such as the provision of prompts or feedback should be adapted to the learners’ individual strategic expertise (see the previous subsection on adapting and fading guidance in line with learners’ expertise). At the same time, strategic expertise is also linked to age (Klein et al. 2019 ). Thus, the younger the students, the more it is likely that they are unfamiliar with certain learning strategies (Zimmerman and Martinez-Pons 1990 ). Therefore, in order to benefit from journal writing, younger students may need more instructional support, for instance, by worked examples (Roelle et al. 2012 ) and concrete suggestions of how to execute cognitive and metacognitive strategies (Glogger et al. 2009 ; Klein et al. 2019 ). Besides learning strategy expertise, however, there are also other potentially relevant learner prerequisites such as students’ writing skills or their prior knowledge about the learning content which we, hitherto, have not focused on.

With regard to writing skills, we included mainly students in our studies at an age level where they could be assumed to have sufficient mastery of transcription skills (spelling and handwriting ability) such that the execution of these skills does no longer consume substantial working memory resources. Nevertheless, there are case studies in primary school mathematics education suggesting that beginning writers may also benefit from trying to articulate their mathematical reasoning in writing a learning journal (Gallin and Ruf 1998 ). Furthermore, in a recent unpublished study (Nückles 2019 ), young secondary school students with exceptionally low writing skills improved their learning outcomes by prompted journal writing if they received formative teacher feedback on the quality of their enacted learning strategies in addition to cognitive and metacognitive prompts. Thus, it could be fruitful for future research to investigate more systematically, to what extent the benefits of journal writing are dependent on or rather independent of students’ mastery of the mechanics of writing.

Besides writing skills as a relevant learner prerequisite, delving into the role of prior knowledge on the learning content could further be fruitful for it is reasonable to assume that such prior knowledge matters for the benefits of self-regulated journal writing. For instance, recent findings by Roelle and Nückles ( 2019 ) suggest that learners who have not yet formed a coherent and well-integrated mental representation of the learning content in particular benefit from organization and elaboration activities. On this basis, it could be assumed that the benefits of journal writing and the support measures to enhance the object-level processes of organization and elaboration (e.g., the outlined prompting procedures) are high for learners with low topic-related prior knowledge in particular. However, there might also be some type of tipping point concerning prior knowledge in which it is no more possible for learners to meaningfully engage in organization and elaboration because their prior knowledge is too low.

Automated Coding of Learning Journals

When we analyzed the application of learning strategies during journal writing in our previous studies (e.g., Berthold et al. 2007 ; Glogger et al. 2012 ), we used a “manual” coding procedure (see Appendix Table 3 ). Although we obtained good inter-rater reliabilities and successfully predicted learning outcomes by our strategy measures, which indicates validity, this procedure takes a lot of time; it is not economical. In particular, if an adaptive fading of prompts (see Nückles et al. 2010 ) should be used in regular teaching practice, it is necessary to develop more parsimonious coding procedures to quickly have the necessary database for adaptive decisions. A promising approach might be to use natural language processing techniques. Techniques for coding complex student-generated texts (automated essay scoring) have already been developed (e.g., Seifried et al. 2012 ; Burstein et al. 2013 ). A promising avenue of further research is to adapt such techniques for the automated coding of learning journals.

Relating the Results of the Freiburg Research Program on Journal Writing to the Effort Monitoring and Regulation Framework

With regard to the EMR framework proposed in the Editorial of this special issue (see also Fig. 2 ), the research program on the Freiburg approach to journal writing addresses in particular research question 3 (How do we optimize cognitive load on self-regulated learning tasks?) and partly also research question 2 (How do students regulate mental effort?). Concerning the question of how to optimize germane cognitive load in self-regulated learning, we found that prompting all essential sub-processes involved in self-regulated journal writing (see Fig. 3 ) resulted in the largest learning gains both in terms of deep comprehension and retention of subject matter (Nückles et al. 2009 ). Concerning the question of how to best sequence these learning processes, we have evidence that engaging learners in metacognitive monitoring and regulation prior to organization and elaboration was more beneficial to learning than vice versa (Roelle et al. 2017 ).

The latter result suggests that prompting students to monitor their current understanding of subject matter by journal writing apparently makes them aware of the gaps in their current understanding of subject matter and thus effectively prepares them for the subsequent working-through of the learning content via organization and elaboration processes. This interpretation resembles, in some respect, recent assumptions about the mechanisms underlying productive failure (see Loibl et al. 2017 ). In sharp contrast to productive failure, however, in our approach to journal writing, students do not engage in problem solving (see the genre-free principle); rather, they are invited to use the journal writing as an opportunity to reflect on their ideas about subject matter in order to become aware of what they already know and what they do not know or find difficult to comprehend.

Journal Writing and Monitoring Accuracy

Relating the findings by Roelle et al. ( 2017 ) on sequencing to the research suggested on basis of the EMR framework (see de Bruin et al. in press ), it would be interesting to investigate whether learners’ metacognitive monitoring accuracy can be improved by prompting the metacognitive strategies in journal writing. To date, judgments of learning have scarcely been assessed in journal writing research. Exploring this possibility could be promising because several effective methods to enhance monitoring accuracy, such as asking learners to generate keywords (Thiede et al. 2003 ) or to complete a diagram (van de Pol et al. 2019 ), this issue; Prinz et al. 2020 ), similarly engage learners in writing down their responses to the respective prompts. However, other than in these paradigms, in journal writing, learners are not required to react to demands that are related to specific parts of the learning content such as in the studies by Thiede et al. and van de Pol et al. ( 2019 ) On the contrary, the generic prompts for cognitive and metacognitive strategies used in the Freiburg research program leave it up to the learner to decide on which aspects of the learning contents the learner wants to focus on in order to monitor their comprehension. Thus, it is a question for future research whether prompted journal writing, which gives the learner ample freedom to determine the focus of the comprehension monitoring, will prove to be similarly effective as the more directive methods applied in current research on monitoring accuracy (e.g., Thiede et al. 2003 ; van de Pol et al. 2019 ; see also Waldeyer and Roelle 2020 ). Possibly, the answer to this question differs for students with different prior knowledge levels. Furthermore, it could be fruitful to integrate the mentioned established means to enhance judgment accuracy (e.g., the keyword-method) in journal writing.

How to Encourage Effort into Monitoring and Regulation Sustainably

The available evidence suggests that the use of metacognitive learning strategies in journal writing can successfully be prompted and also contributes to germane cognitive load as indicated by enhanced learning outcomes (Glogger et al. 2012 ; Nückles et al. 2009 ). Nevertheless, prompting metacognition in the long run (i.e., over the course of a whole term) proved to be relatively ineffective regardless of whether the prompts were adapted to the learners’ individual strategic expertise or not (Nückles et al. 2010 ). It is possible that learners perceived the cognitive load that they had to invest in the prompted strategies as a substantial motivational cost (Feldon et al. 2019 ) given that learners are generally inclined to keep their invested mental effort as minimal as possible (Shenhav et al. 2017 ). This inclination might apply in particular for metacognitive strategies which require learners to put their current understanding into question. Accordingly, assuming a self-critical stance towards one’s current understanding over a longer period of time (over a whole term in the journal writing studies of Nückles et al. 2010 ) is likely regarded as unpleasurable by many learners. Hence, the question of how to stimulate metacognitive reflection sustainably probably touches upon a fundamental constraint of human cognition. This question might not be answerable from the perspective of the individual learner but rather from a perspective that views learning and metacognition as a collective endeavor. For example, most authors would probably refrain from thoroughly revising their “already well written” articles if they were not forced to do so by reviewers and editors. Taking a critical and reflective stance towards one’s submission is initially perceived by many authors as a considerable motivational cost. Hence, fostering metacognitive processes in journal writing sustainably might be rather achieved in a social, collaborative learning environment where the tasks of generating ideas by journal writing and taking a metacognitive critical stance towards those ideas may be socially distributed among learning partners.

The approach of allocating specific cognitive and metacognitive processes to different roles learners may adopt during the learning process has successfully been established, for example, in reciprocal teaching (e.g., Palincsar and Brown 1984 ). With regard to journal writing, Nückles et al. ( 2005 ) conducted a small-scale field study on reciprocal commenting on each other’s learning journals within dyadic learning partnerships in the context of a blended learning university course. The authors found that the feedback provided by one learning partner strongly influenced the degree of elaboration and organization of the other partner’s learning journal. Glogger-Frey et al. ( 2019 ) found that students who received higher-quality feedback from peers as compared with students who received lower-quality feedback, perceived their learning outcomes as higher and felt more confident to do well in journal writing. Thus, future research could investigate as to whether the willingness to sustainably apply metacognitive strategies in journal writing could also be improved by such dialogical elements in journal writing.

Introducing Journal Writing as Intentional Learning

The results of the Nückles et al. studies (Nückles et al. 2010 ) further suggest that the journal writing itself likely entailed some motivational costs irrespective of whether prompts for cognitive and metacognitive strategies were provided or not. These costs can be assumed because journal writing can be regarded as a learning task that creates desirable difficulties (Bjork and Bjork 2011 ) whose benefit typically becomes transparent for learners not immediately but only at a later time. Accordingly, when implementing journal writing as follow-up course work in our university courses, students often commented on the journal writing in their evaluation sheets at the end of the term with sentences such as “All this journal writing was hard work, but looking back now, I can see that I have learned a lot.” Hence, it is an important question for future research to investigate how students can be encouraged to maintain their invested level of mental effort into the journal writing over a longer period of time (see research question 2 of the Editorial: How do students regulate their mental effort, de Bruin et al. in press ). In our previous studies, the journal writing was typically imposed on the students as follow-up course work. Therefore, they might not have sufficiently recognized the benefit of the journal writing because they considered it as schoolwork which has to be done and with little personal value. In particular, because the writing took place as an obligatory after school assignment, it is an open question to what extent students were able, under these conditions, to conceive the journal writing as an opportunity to freely develop their ideas about the subject matter. Accordingly, a challenge for future research is how to introduce the journal writing to students such that they will be able to perceive the journal writing as a valuable opportunity for intentional learning (see Bereiter and Scardamalia 1989 ). One promising starting point for this future avenue in journal writing research could be the outlined effects of the personal utility prompts. Long-term effects of these prompts as well as potential differences between prompts that relate to the utility of the learning content and prompts that refer to the utility of the journal writing itself still need to be addressed. Nevertheless, the consistent beneficial effects on learners’ motivation already suggest that such prompts entail high potential for convincing learners of the usefulness of self-regulated journal writing.

Journal Writing as Preparation for Future Problem Solving

In this paper, we have argued that the potential of journal writing to foster self-regulated learning can especially be attributed to the genre-free principle according to which the learner is freed from the burden to invest mental effort in the instantiation of rhetorical schemata. Hence, learners are explicitly encouraged not to conceive of journal writing as problem solving but rather as an opportunity to freely develop ideas about subject matter and examine one’s current understanding for gaps and inconsistencies. Thus, the self-regulation view on journal writing parallels Sweller’s goal-free-effect in this respect (see Sweller et al. 2011a ). Due to its goal-free nature, journal writing might be particularly suited to prepare learners for future problem solving. We are currently investigating this possibility in a project on teacher education where history teacher students are writing learning journal entries to develop ideas for later lesson planning (see Nückles and Schuba 2019 ). Based on three texts providing content knowledge (here: on history), pedagogical content knowledge (here: on history education), and pedagogical knowledge (see also Graichen et al. 2019 ; Wäschle et al., 2015b)), they independently identify and develop didactic goals for teaching history. After the journal writing, the students work out a formal plan for a history lesson. The results of this study so far suggest that the journal writing helps the students to define appropriate didactic goals and to adopt these goals for their lesson planning (“For planning my lesson, it will be important to consider students’ prior knowledge about the second world war …”). Accordingly, the number of articulated and personally valued teaching goals in the journal writing mediated the quality of the formal lesson plans which the students produced afterwards as a transfer and application task (Nückles & Schuba 2019 ). Thus, using journal writing for preparing lesson planning can be regarded as another fruitful instantiation of the goal-free-principle (see Sweller et al. 2011a ). Defining goals for later problem solving basically is planning, and planning is viewed (besides monitoring and evaluation) as an essential component of people’s metacognitive competence to regulate cognition (Nückles et al. 2009 ; Schraw 1998 ). Given the preliminary character of the results of Nückles and Schuba ( 2019 ), future studies should examine more broadly how journal writing can be used as an opportunity to facilitate students’ self-regulation in solving core teaching problems such as lesson planning.

Journal Writing—a Circumscribed Intervention with Wide-Ranging Effects

A final direction for further research is derived from an observation made in our high school studies on journal writing. In the studies by Glogger et al. ( 2009 , 2012 ) and Wäschle et al. ( 2015a ), it turned out that both the 9th graders of the Glogger et al. studies and the 7th graders of Wäschle et al. wrote rather short weekly journal entries ranging roughly between 100 and 350 words. Despite their brevity, however, the journal entries nevertheless strongly contributed to learning outcomes as measured by learning outcome tests that covered all central aspects of the topic (e.g., immunology in the study by Wäschle et al. 2015a ) taught in the weeks before. This pattern of results suggests that the relatively local writing intervention (encouraging application of cognitive and metacognitive strategies in a weekly journal entry) impacted students’ learning behavior positively also on a more global level and improved students’ use of learning strategies in and outside the classroom beyond the learning journal. However, to date, we do not have any data that would provide direct evidence for this assumption. Accordingly, it would be interesting to conduct observational studies to investigate to what extent journal writing indeed generally influenced the students’ use of learning strategies in the wide-ranging way as can be speculated on basis of the studies of Glogger et al. ( 2009 , 2012 ) and Wäschle et al. ( 2015a ).

In summary, these are numerous promising directions of how to develop the Freiburg Self-Regulated-Journal-Writing Approach further. Furthermore, it is necessary to conduct replication studies in order to consolidate the results found, for example, for the positive motivational effects of journal writing (i.e., raised interest subject matter, see Wäschle et al. 2015a ) or for the positive effect of feedback on the quality of the enacted learning strategies in the learning journals (see Roelle et al. 2011 ) as well as on self-efficacy and perceived learning outcomes (Glogger-Frey et al. 2019 ). First steps towards such consolidation of the benefits of feedback are currently undertaken by Pieper et al. ( 2019 ) who investigated the effects of prompts, expert feedback, and worked examples in journal writing during the practical semester of teacher students. A recent quasi-experimental study by Nückles ( 2019 ) further replicated the positive effects of elaborated expert feedback on the quality of the cognitive learning strategies enacted by 7th grade low-ability writers in their learning journals. Additionally, the quality of the cognitive strategies mediated the effect of the feedback on students’ learning outcomes.

Although we have discussed numerous aspects of our journal writing approach from the perspective of cognitive load theory, we have yet in our extant studies not systematically included measures of cognitive load. Accordingly, it would be interesting to test whether the inclusion of specific types of prompts (e.g., including a metacognitive or personal utility prompt) leads to a raised perception of (germane) cognitive load in students.

To conclude, the Freiburg Self-Regulated-Journal-Writing Approach has yielded valuable insights into the question of how writing can be instructionally supported to effectively scaffold self-regulated learning and optimize cognitive load. Yet, these insights open up a considerable number of new avenues of how to further advance the self-regulation view in writing-to-learn and how to advance research that integrates self-regulated learning with cognitive load theory.

In the present paper, we refer to the concept of germane load as introduced by Sweller et al. ( 1998 ). Germane load refers to the effort contributing to knowledge construction (e.g., by elaboration) and adds to the intrinsic load (determined by the complexity of the learning contents in relation to the learners’ prior knowledge) as well as the extraneous (unproductive) load. Recently, another conception of germane load has been proposed (e.g., Sweller et al. 2019 ). However, we stick to the conception from 1998 for several reasons: (1) It guided large parts of the cognitive load research to which we refer in this article; (2) when considering cognitive load in our research program on journal writing, we had the 1998 conception in mind; (3) we find it helpful in our context to clearly differentiate the separate contributions to the overall load resulting from the complexity of the learning contents and from the learning strategies applied when studying these contents.

The mini meta-analysis is based on those experimental studies in which the combined application of cognitive and metacognitive strategies was prompted and contrasted with unsupported journal writing. These studies are published in Berthold et al. ( 2007 ); Nückles, Hübner, and Renkl et al. ( 2009 ); Nückles et al. ( 2010 ); and Schwonke et al. ( 2006 ). Accordingly, the calculation of Hedges’s g was based on the data of 238 participants.

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Acknowledgments

We thank Alex Ulyet for proofreading the manuscript. Special thanks go to Kirsten Berthold whose experimental study on prompting cognitive and metacognitive strategies marked a milestone in our research program on journal writing.

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Excerpts are close to the German originals. The part from Glogger et al., Learning strategies assessed by journal writing: Prediction of learning outcomes by quantity, quality, and combinations of learning strategies, Journal of Educational Psychology, 104, 452–468, 25.04.2020, APA, is adapted with permission.

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Nückles, M., Roelle, J., Glogger-Frey, I. et al. The Self-Regulation-View in Writing-to-Learn: Using Journal Writing to Optimize Cognitive Load in Self-Regulated Learning. Educ Psychol Rev 32 , 1089–1126 (2020). https://doi.org/10.1007/s10648-020-09541-1

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Self-Regulation Essay

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Introduction

The ability to manage and control one’s behaviors defines self-regulation. By self- regulating a person will be able to better pay attention to important information that they need to know. By managing behaviors this can help people to stay aligned to what is socially acceptable in today’s society. Self-regulation works to help a person to follow rules, pay attention even if distracted, be able to handle their anger, and to be patient enough to figure their way through challenging times. This is an ongoing life process that continues to change and develop. Not everyone handles the stresses of everyday life in the same manner (Lowry, 2016). Self-regulation may be easy for one person and more difficult for another person. The boom of technology in recent years has impacted how people may self-regulate their behavior.

Technology’s Influence on the Ability to Self-Regulate

Technology seems to go hand in hands with our daily activities. This is especially true for students of online learning. Knowing how to use the technology and navigate through the website for their online school is crucial for a student’s success. Research has shown that the social cognitive theory gives a framework for determining the trait of self-regulating behavior that is associated with the success of students who study online (Lynch &amp; Dembo, 2004). A positive online learning experience is the result of the student being self-efficient. A student’s ability to use technology easily to conduct research and attain course material to study, creates a feeling that the student is competent and comfortable of using technology to complete their courses and helps the student to becomes self-efficient in their learning (Young-Ju, Bong, &amp; Choi, 2000).

Technology can help to ease and calm emotions that may rise throughout one’s day. If a person is missing a friend who lives far away they can be cheered up by face timing that friend on their iPhone. This helps a person to emotionally self-regulate their feeling of sadness by taking action to reach out to their friend to cure the feeling of missing that person. When a person can calm themselves down or change the emotion they are feeling to a better more uplifting feeling they are emotionally self-regulating behavior.

Recent research has shown that people who keep checking their mobile electronics are less able to manage their impulses leading to the likelihood of not being able to delay gratification (Wilmer &amp; Chein, 2016). Devices such as IPhone, tablets and laptops have allowed technology to go mobile. Since technology is now at our finger tips at any time we can access whatever we want, whenever we want. This can affect self-regulating behavior in a negative way, impulse control can become harder to delay gratification (Wilmer &amp; Chein, 2016). Becoming bored can easily be taken care of with mindless searching on the internet, games or communicating with others using electronic devices. Dependency on electronic devices can take away from socially interacting with others (Bindley, 2011). The other downside to constantly being connect to a mobile electronic device, is being bombarded by commercials about products. There is no need to wait to purchase, you can click a button right from the advertisement and purchase. This can influence compulsive buying (Makolajczak-Dagrauwe &amp; Brengman, 2014). Impulse control has become harder to develop and manage with technology keeping us connect to anything we want at any time.

Conflict Between Impulse and Socially Beneficial Behavior

When a person uses self-regulation, they are watching and controlling their own feelings, thought and behaviors. While at the same time changing their feelings, thoughts and behaviors to properly respond to different situations and challenges (Cook &amp; Cook, 2014). Self-regulation helps to respond quickly which sometimes puts their own desires in the back ground to focus on the issue at hand (Bindley, 2011). Daily routine can sometimes become boring and monotonous, self-regulation helps individuals to push through everyday tasks even if they do not want to.

Beginning in the early years of child development the self-regulation process starts to form, this process continues throughout the rest of one’s lifetime (Bindley, 2011). Temptation and immediate gratification are kept under control and in check using self-control. Using self- control in these times is known as delayed gratification (Cook &amp; Cook, 2014). Being able to regulate one’s behavior is using self-control in the right way (Lowry, 2016). Self-control is important to help control impulses that one may have such as smoking cigarettes, taking illegal drugs or to not drink alcohol. One may want to go to a movie instead of doing homework, yet they know if they see the movie they will be too tired to do their homework after. The person may come to the conclusion it is more important to get the homework completed since they can always see the movie later.

Earlier research has implied that learning is accentuated more by a person’s personal experiences. Albert Bandura developed the social cognitive theory that suggests learning is altered based on behavioral, cognitive as well as environmental influences (Johri &amp; Misra, 2014). Bandura demonstrated that a good portion of learning happens from watching and observing the behaviors of other people. An attribute that comes from self-regulation is the behavior of personal motivation. This has been seen with students who are attending online colleges. Once a person feels they can handle the technology and studies that come along with attending an online college, they are personally motivated to achieve their goals through attaining the right skills to succeed.

Self-regulation is a constant continual evolution throughout one’s lifetime, starting in the early years of childhood development. Current information shows that self-regulation, when developed correctly can help individuals to get through most of life’s challenges (Korinek &amp; deFur, 2016). Self-regulation can help individuals react in a more positive way with stressors that may come up in their life time. Being able to rebound to a place where a person becomes calm after being agitated or angry is a positive trait that comes out of self-regulation. Throughout a person’s life they will be introduced by many different forms of challenges and situations they will need to get through, self-regulation will help a person in these times. Self-regulation can help a person achieve personal goals and achievements. When a person is reaching their goals, conditions become more positive for social interaction, learning and overall sense of well-being.

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ORIGINAL RESEARCH article

Self-regulation in preschool: examining its factor structure and associations with pre-academic skills and social-emotional competence.

• 1 Child Study Center, Yale University, New Haven, CT, United States
• 2 Department of Medical Social Sciences, Northwestern University, Evanston, IL, United States
• 3 Department of Human Development and Family Studies, Purdue University, West Lafayette, IN, United States
• 4 Extension Family and Community Health Program, Oregon State University, Corvallis, OR, United States

Self-regulation in early childhood is an important predictor of success across a variety of indicators in life, including health, well-being, and earnings. Although conceptually self-regulation has been defined as multifaceted, previous research has not investigated whether there is conceptual and empirical overlap between the factors that comprise self-regulation or if they are distinct. In this study, using a bifactor model, we tested the shared and unique variance among self-regulation constructs and prediction to pre-academic and social-emotional skills. The sample included 932 preschool children ( M age = 48 months, SD = 6.55; 49% female), their parents, and their teachers in the United States. Children’s self-regulation was assessed using measures of executive function, behavioral self-regulation, and emotion regulation. The bifactor model demonstrated a common overarching self-regulation factor, as well as distinct executive function and emotion regulation factors. The common overarching self-regulation factor and executive function predicted children’s pre-academic (i.e., mathematics and literacy) and social-emotional skills. The emotion regulation factor predicted children’s social-emotional skills. Identifying the shared and unique aspects of self-regulation may have important implications for supporting children’s regulatory skills as well as their success in school.

Introduction

Children’s ability to regulate themselves is a key developmental task during early childhood ( Allan et al., 2014 ; Robson et al., 2020 ). Self-regulation is generally defined as the ability to control thoughts, behaviors, and feelings to achieve goal-directed behaviors and has been conceptualized broadly to include neurological processes [executive function (EF)], EF in overt behavior (behavioral self-regulation), and emotion regulation ( McClelland et al., 2018 ). Despite theoretical perspectives suggesting self-regulation is comprised of EF, behavioral self-regulation, and emotion regulation, there has been little empirical work dedicated to testing how the components of self-regulation remain distinct yet simultaneously comprise an overarching self-regulation factor. Although some studies have examined correlations among some constructs of self-regulation (EF and behavioral self-regulation; McClelland et al., 2014 ; Finders et al., 2021 ; EF and emotion regulation; Lieberman, 2007 ), no studies to date have examined whether these indeed constitute one overarching self-regulation construct while remaining distinct subordinate constructs. Therefore, in this study, we use a bifactor model to explore (1) the extent to which different aspects of children’s self-regulation constitute one overarching self-regulation construct while remaining distinct subordinate constructs, and (2) the extent to which an overall self-regulation construct and/or the individual subordinate constructs predict children’s pre-academic and social-emotional competencies.

Self-Regulation in Early Childhood

Self-regulation broadly refers to the ability to regulate behavior, cognition, and emotion to pursue goal-directed behaviors ( Diamond and Lee, 2011 ; Hofmann et al., 2012 ). Self-regulation has received increased attention in various disciplines due to its important role in development across the life span ( Posner and Rothbart, 2000 ; Moffitt et al., 2011 ; McClelland et al., 2013 ). In early childhood, self-regulation has been associated with pre-academic skills, including literacy and numeracy, and social-emotional outcomes, including social competence and externalizing and internalizing behaviors ( Blair and Razza, 2007 ; McClelland et al., 2007 ). In addition, a recent meta-analysis on self-regulation analyzing 150 studies documented that self-regulation in early childhood, measured around age 4, predicted 25 outcomes, including achievement, mental health, and interpersonal behaviors in early and later school years as well as in adulthood ( Robson et al., 2020 ).

Theoretical perspectives suggest that self-regulation is multifaceted and consists of different constructs including EF, behavioral self-regulation, and emotion regulation ( Frye et al., 1998 ; Gottlieb, 2007 ; Blair et al., 2016 ; Zelazo et al., 2017 ). Neurological processes underlying EF involve inhibitory control, the ability to inhibit one behavior in favor of another, cognitive flexibility, the ability to flexibly pay attention, and working memory, the ability to hold and manipulate information in mind and have often been measured using performance-based direct assessments ( Zelazo et al., 2013 ). EF in overt behavior, often called behavioral self-regulation, has also been assessed through performance-based direct assessments ( McClelland et al., 2014 ) as well as teacher and parent-report questionnaires. Emotional self-regulation, defined as the ability to modulate strong emotional reactions with adaptive strategies, has typically been assessed through teacher and parent ratings ( Raver, 2004 ).

The broad definition of self-regulation, as well as the lack of a cohesive framework for defining and measuring self-regulation, has led to different conceptualizations of this construct and its components across various disciplines in developmental (e.g., behavioral self-regulation), cognitive and neuroscience (e.g., EF), and social and personality psychology (e.g., effortful control; see Nigg, 2017 for a review). Although previous research has linked these different components of self-regulation, and multiple calls have been made to integrate them under the broader umbrella term of self-regulation ( Zhou et al., 2012 ; Morrison and Grammer, 2016 ), no study has empirically tested the theoretical perspective that all comprise a larger self-regulation construct.

Self-Regulation and Academic Skills

A robust body of literature underscores the importance of self-regulation for children’s concurrent and subsequent school performance (see Robson et al., 2020 for review). The explanation for this association is that children must possess the ability to control their thoughts, feelings, and behaviors in order to navigate complex learning environments ( Morrison et al., 2010 ; Duckworth and Carlson, 2013 ). Research suggests that broad measures of self-regulation, as well as each of the self-regulation components that are of interest in this study, are related to academic outcomes ( Smithers et al., 2018 ). For instance, findings indicate that children who have stronger EF also tend to have higher academic achievement, particularly in mathematics ( Bull et al., 2008 ; Cragg and Gilmore, 2014 ; Ahmed et al., 2019 ). Similarly, results indicate that behavioral self-regulation skills are predictive of growth in mathematics, literacy, and vocabulary during kindergarten ( McClelland et al., 2007 , 2014 ; Schmitt et al., 2017 ; Pandey et al., 2018 ). Finally, studies have shown that children with increased emotion regulation were found to have higher levels of pre-academic skills and achievement in early childhood ( Graziano et al., 2007 ; Ursache et al., 2012 ; Kwon et al., 2017 ; Mattar et al., 2020 ). What is unclear in this line of work is whether an overarching self-regulation construct or its components are driving the associations between children’s self-regulatory skills and their pre-academic skills.

Self-Regulation and Social-Emotional Competence

Research has also highlighted relations among self-regulation and social-emotional skills ( Rademacher and Koglin, 2019 ). Children who can regulate attention, behavior, and emotion are thought to better navigate the complex social interactions that frequently necessitate recognizing one’s and others’ emotions and intentions, cooperating with one another, and building relationships ( Raver, 2002 ; McClelland et al., 2007 ). For instance, EF helps children resist impulsive emotional responses, observe and process the emotions of others, and have more positive social interactions with peers and teachers ( Teglasi et al., 2015 ; Mann et al., 2017 ; Rademacher and Koglin, 2019 ). Further, strong behavioral self-regulation supports peer competence and control of positive and negative emotions ( Trentacosta and Izard, 2007 ; Ponitz et al., 2009 ). Alternatively, poor behavioral self-regulation is linked to increased disruptive and/or aggressive behaviors which can lead to peer rejection and difficulties in forming peer friendships ( McClelland et al., 2007 ). Similarly, research shows that emotion regulation is associated with children’s social-emotional competence, particularly emotion knowledge, which is important for creating successful personal relationships and encourages prosocial responsiveness to peers ( Eisenberg et al., 2005 ; Di Maggio et al., 2016 ; Ornaghi et al., 2019 ). Taken together, previous research examining the associations between self-regulation and its components included in the present study demonstrates commonalities in their associations between pre-academic skills and social-emotional competence.

Prior Factor Analytic Approaches and the Utility of a Bifactor Modeling Approach

Despite the commonalities, extant studies have not assessed the overlap and unique aspects of self-regulation constructs (i.e., EF, behavioral self-regulation, and emotion regulation) and whether there is a unique contribution of each component to pre-academic and social-emotional skills when the shared/common variance is partialed out. Prior factor analytic studies mostly rely on common factor models (i.e., correlated-factor models) or second-order (i.e., hierarchical) factor models when examining multifaceted constructs, and bifactor models have not been utilized to explore self-regulation and its subordinate constructs. The majority of prior work focuses on common factor models, and when a general underlying factor is present, multidimensionally cannot be easily examined in these models. Second-order and bifactor models can account for multidimensionality while acknowledging the presence of a general factor ( Reise, 2012 ), but they differ with regard to how they model the data. In second-order factor models, observed variables are specified to measure first-order factors that represent the components of the general construct, and a higher-order factor accounts for the correlations among the first-order factors. Thus, in second-order factor models, it is assumed that first order factors have direct effects on their indicators, but the second-order factor only has indirect effects on its indicators through the first-order factors. It is also assumed that the second order factor accounts for all the associations between the specific factors. Thus, it is not possible to detect the existence of specific factors (i.e., unique variances of the factors that are not explained by the common higher-order factor) with traditional models ( Gustafsson and Balke, 1993 ).

In contrast to second-order models, bifactor models include general and specific factors, but indicators have two direct effects in these models, one from the general factor and one from the specific factor to which the indicator is assigned. Further, in bifactor models, the general factor and the specific factors are within the same measurement level, and the general factors and specific factors are orthogonal, which allows the model to disentangle the sources of reliable variance in composite and subdomain scores. Thus, bifactor models allow for the examination of the unique effects of the general factor as well as the specific factors, which helps to identify whether self-regulation is indeed an overarching construct for EF, behavioral self-regulation, and emotion regulation. Bifactor models also include prediction to external variables based on specific factors above and beyond the general factor using structural equation models (SEM), which would further our understanding about the associations between self-regulation, its constructs, and pre-academic and social-emotional skills. By employing a bifactor modeling approach, we extend prior work by addressing the need for a better understanding of the empirical structure of self-regulation in early childhood and its association with two important skills, pre-academic and social-emotional skills.

Present Study

In the current study, utilizing a bifactor model, we had two aims: (1) examine the extent to which different aspects of children’s self-regulation constitute one overarching self-regulation construct and the degree to which they are distinct, and (2) explore the extent to which an overarching self-regulation construct (if one emerges from research aim 1) and/or the individual constructs predict children’s pre-academic and social-emotional competencies. We expected that a general overarching self-regulation construct would emerge and predict pre-academic and social-emotional skills. Further, we expected that each construct of self-regulation would also have unique variance and load onto their respective constructs (see Figure 1 ), and thus, we hypothesized that each would uniquely predict pre-academic and social-emotional skills controlling for child’s age, sex, and family income-to-needs ratio.

Figure 1. Conceptual bifactor model self-regulation.

Materials and Methods

Participants.

Participants included 932 preschool-aged children ( M age = 48 months [ SD = 6.55]; 49% female), their parents, and their teachers from 62 preschools and 188 classrooms across a Northeastern region of the United States. The sample for this study came from an evaluation of a social-emotional program on children’s school readiness. The sample included racially and ethnically diverse children: 47% White or Caucasian, 28% Black or African American, 11% multiracial, 9% American Indian or Alaskan Native, 4% Asian, and 44% identified as Hispanic or Latinx, representing the broader area in the Northeast region of the United States. Children primarily spoke English (77%), with 14% speaking primarily Spanish, and 9% who were multilingual or spoke other languages.

Data were collected from children, teachers, and parents at one time point in the fall of the preschool year. Participants were recruited from publicly (84%) and privately (5%) funded community-based preschools, 16% of which were Head Start centers serving low-income children and families. Parents of all children at participating schools were sent home an invitation to participate in the study with a letter including a consent form, a description of the study, and a short demographic survey. Trained research assistants directly assessed participating children’s EF, behavioral self-regulation, pre-academic skills, and social-emotional competence after receiving verbal assent from children to participate in the activities. Assessments were conducted in preschools in quiet spaces across two sessions on separate days. Each session took approximately 20 min to complete. For children whose parents indicated that they speak a language other than English, a bilingual research assistant administered a language screening test. Children whose primary language was Spanish and could not pass the screening test in English were assessed in Spanish. Children who spoke a language other than Spanish and did not pass the screening task in English were not administered any of the assessments. Children’s emotion regulation and one aspect of behavioral self-regulation (i.e., Child Behavior Rating Scale) were assessed through teacher reports. After participation in the assessment battery, children received a sticker. Following study participation, teachers received a $30 gift card.

Executive Function

Children’s EF was measured by the Day-Night Stroop task ( Montgomery and Koeltzow, 2010 ). Research assistants presented cards depicting either a sun or a moon and asked the children to say the opposite of what they saw. For example, children were asked to say “night” when shown a picture of a sun. Children were first given trials to be sure they understood the task and then were given 14 test items. If the child answered correctly, they received a score of 2, similar responses (e.g., “sun” when the correct response is “day”) or a self-correct received a score of 1, and incorrect or no response received a score of 0. This measure has strong reliability and has been shown to be correlated with other EF measures in previous studies ( Carlson, 2005 ). The measure demonstrated high internal consistency in the current sample (Cronbach’s α = 0.93).

Behavioral Self-Regulation

Children’s behavioral self-regulation was measured using the Head-Toes-Knees-Shoulders task (HTKS; McClelland et al., 2014 ), a direct child assessment, the Child Behavior Rating Scale (CBRS; Bronson et al., 1995 ), a teacher report, and the Preschool Self-Regulation Assessment—Assessor Report (PSRA-AR; Smith-Donald et al., 2007 ), an assessor report completed by research assistants after administration of direct-child assessments.

Head-Toes-Knees-Shoulders

The HTKS measures behavioral self-regulation skills in preschool children, tapping into working memory, inhibitory control, and cognitive flexibility in overt behavior. This direct assessment consists of 30-items across three sections. During the first section of the HTKS, the research assistant asked the child to touch their head and then their toes. Children were then challenged to do the opposite of what the researcher says (e.g., “When I say touch your head, instead of touching your head, touch your toes”). The second section of the HTKS increases in difficulty adding in knees and shoulders (e.g., “When I say touch your knees, instead of touching your knees, you touch your shoulders”). The final section increases in difficulty again by changing the original rules (e.g., “When I say touch your head, instead of touching your head, touch your knees”). Children only continued to the subsequent section if they received four or more points. Correct responses on this task were scored as 2 points, self-correct responses were scored as 1 point, and incorrect responses were scored as 0 points. Scores were summed to create a total score. Previous research with the HTKS has produced strong reliability and validity statistics within diverse samples ( McClelland et al., 2014 ). The HTKS demonstrated high internal consistency in the current sample (Cronbach’s α = 0.93).

Child Behavior Rating Scale

The CBRS is a teacher report assessment evaluating a child’s task behavior and social behavior with peers and adults ( Bronson et al., 1995 ). The original measure is comprised of 32 questions, but for the purposes of this study, only the self-regulation subscale was used consisting of 10 questions (e.g., “observes rules and follows directions without reminders”). The classroom self-regulation subscale assesses children’s behavioral self-regulation during academic tasks (e.g., following directions, staying on task), as rated by teachers using a scale from Never (1) to Always (5). A sum score was used in the analyses. The measure has demonstrated high internal consistency in previous studies ( Ponitz et al., 2009 ; Schmitt et al., 2014 ) and in the current study (Cronbach’s α = 0.95).

Preschool Self-Regulation Assessment-Assessor Report

The PSRA-AR is an assessor report of the child’s performance on tasks related to attention/impulse control, compliance, activity level, feelings, and sociability ( Smith-Donald et al., 2007 ). The original assessment is composed of 28 items and adapted from the Leiter-R scale ( Roid and Miller, 1997 ) and Disruptive Behavior-Diagnostic Observation coding system ( Wakschlag et al., 2005 ). The short version of the scale includes 12 questions with two subscales, the attentive/impulse control scale and the positive emotion scale, and provides a global picture of children’s emotion, attention, and behavior throughout the assessor-child interaction during the assessments. Seven items representing the attentive/impulse control subscale were used for the purpose of the current study (e.g., “sustains concentration while doing task; distracted by sounds and sights throughout the assessment”). Assessors rated these items by using a scale from child was not able to concentrate (0) to child was able to concentrate and persist with task (3). A sum score was used in the analyses. The measure has been shown to be reliable and valid in previous studies ( Williford et al., 2013 ; Daneri et al., 2018 ). The measure demonstrated high internal consistency in the current sample (Cronbach’s α = 0.76).

Emotion Regulation

The Emotion Regulation Checklist (ERC; Shields and Cicchetti, 1997 ) is a teacher-report assessment and measures children’s emotional expression and regulation patterns and skills by items describing situationally appropriate affective displays, empathy, and emotional self-awareness. The emotion regulation subscale of the ERC was used (e.g., “can recover quickly from episodes of upset or distress, does not remain anxious or sad after emotionally distressing events”). It includes 14 items rated on a scale from Never (1) to Almost Always (4). The measure has been shown to be reliable and valid in previous studies ( Shields and Cicchetti, 1997 ; Graziano et al., 2007 ) and demonstrated high internal consistency in the current sample (Cronbach’s α = 0.74).

Pre-academic Skills

The Woodcock Johnson IV Tests of Achievement was used to test children’s literacy and mathematic abilities, specifically the Letter-Word Identification and Applied Problems subtests ( Schrank et al., 2014 ). The Woodcock Johnson Letter-Word Identification (WJLW) subtest assesses children’s developing word-coding skills, including the ability to recognize letters, name letters, and (for children who are advanced on the task) read words. The Woodcock Johnson Applied Problems (WJAP) subtest assesses children’s abilities related to counting objects, reading numbers, and performing basic addition and subtraction. Children are tested until they receive six consecutive questions incorrect for the Letter-Word Identification subtest and five consecutive questions incorrect for the Applied Problems subtest before the research assistant ends the assessment. Correct responses are scored as 1, and incorrect responses are scored as 0. Final scores are calculated by summing correct items for each subtest. The raw scores are then uploaded onto the Woodcock-Johnson Scoring website to obtain the W-scores. W scores are used in the analyses, which are the conversion of raw scores into centered W-scores. The assessment has strong psychometric properties as demonstrated in previous validation studies ( McGrew et al., 2014 ).

Social-Emotional Competence

The Affect Knowledge Test (AKT; Denham et al., 2003 , 2015 ; Bassett et al., 2012 ) was used to evaluate social-emotional competencies. The AKT measures expressive, receptive, and situation emotion knowledge using facial expressions, stereotypical and non-stereotypical vignettes, and a teacher-informed survey. Before children were assessed, teachers completed a short survey of 12 questions asking how the child would normally respond emotionally in various situations, which were then used to inform the presentation of the non-stereotypical vignettes. First, children were presented with felt faces of emotional expressions (i.e., happy, sad, angry, and afraid). Children were asked, “How does she/he feel?” for each emotion to evaluate children’s expressive emotion knowledge. Then, children were asked to “Point to the [emotion] face” for each emotion to assess children’s receptive emotion knowledge. Next, research assistants performed nine vignettes using puppets that depicted children expressing emotions in developmentally appropriate, emotionally charged situations. For the first three vignettes, the puppet depicted the same emotion most children would feel, as an index of children’s stereotypical emotion knowledge. For the remaining six vignettes, the puppet depicted different emotions from what the teacher reported that the child would normally feel (e.g., happy or sad to come to preschool), as an index of children’s non-stereotypical emotion knowledge. Correct responses were given 2 points, responses with the same emotional valence were given 1 point, and incorrect responses were given 0 points. Scores were created for each component (e.g., expressive, receptive, situation emotion knowledge), z-scored, and summed into a total score (Cronbach’s α = 0.87). The AKT has been shown to be reliable and valid in previous studies ( Denham et al., 2003 , 2015 ; Bassett et al., 2012 ).

Analytical Strategies

The confirmatory bifactor models and the SEM were estimated using the lavaan package ( Rosseel, 2012 ) in R (version = 3.6.2; R Core Team, 2019 ). Full information maximum likelihood estimation ( Rhemtulla et al., 2012 ) with cluster-robust standard errors and a Satorra-Bentler scaled test statistic were used. The cluster-robust SEs we report were adjusted accounting for the nested structure of the dataset (i.e., children nested within classrooms). We first examined an a priori measurement model: a bifactor model in which a single general factor accounts for the shared variance among the indicators of the EF, behavioral self-regulation, and emotion regulation, and three orthogonal specific factors representing EF, behavioral self-regulation, and emotion regulation that account for the remaining common variance among their respective indicators. Since EF and emotion regulation were measured using single measures, we generated three random parcels for each to make sure we had an equal number of indicators in each domain-specific factor. In this configuration, EF was measured with three random parcels of the Day-Night Stroop task, behavioral self-regulation was measured with CBRS, HTKS, and PSRA scores, and emotion regulation was measured with three random parcels of the ERC item scores. The latent scales (i.e., both the specific and general) of the bifactor model were defined by fixing the variance of the latent factors to one.

We used a range of goodness-of-fit indices for model evaluation. The χ 2 statistic compares the observed and the model-implied covariance matrices. A non-significant χ 2 -test indicates a close correspondence between the model and the sample data. However, as widely acknowledged, Type I error rates of the χ 2 -test inflate with increased sample sizes (>200; Steiger, 2007 ; Van de Schoot et al., 2012 ). The Comparative Fit Index (CFI; Bentler, 1990 ) assesses how much better the specified model fits the sample data compared to a baseline model in which the observed variables are uncorrelated. CFI values ≥ 0.90 and ideally ≥ 0.93 indicate adequate fit ( Byrne, 1994 ; Hu and Bentler, 1999 ). The root mean square error of approximation (RMSEA; Steiger and Lind, 1980 ) represents the discrepancy between the model and observed covariances per degree of freedom and can be considered a measure of effect size. We considered point estimates of the RMSEA values < 0.08 as an indication of acceptable fit. We also expected a good fitting model to produce an upper bound of the 90% confidence-interval of the RMSEA < 0.10 ( Browne and Cudeck, 1992 ). Mardia’s (1970) multivariate skewness (b-1 p . = 7.43, skewness = 771.90, p < 0.001) and kurtosis (b-2 p . = 99.79, kurtosis = 0.71, p = 0.43) tests indicated multivariate non-normality of the data; therefore, we reported the robust versions of these fit indices (univariate descriptive statistics are presented in Table 1 ). In addition to the goodness-of-fit indices, we evaluated the pattern of factor loadings to examine the relative strength of the relations between the observed variables and the general factor and their respective domain-specific factors.

Table 1. Descriptive statistics and correlations for study variables.

Next, we ran a series of SEMs to investigate the unique relations of the general and specific factors of the bifactor model of self-regulation with the scores from three outcome measures of pre-academic skills (WJLW and WJAP) and social-emotional competence (AKT). In these analyses, we controlled for several demographic characteristics, including children’s age, sex, and family income-to-needs ratio (calculated by dividing the participant reported annual family income by the federal poverty level in 2019).

Measurement Model

The bifactor model with one general and three specific factors (i.e., EF, behavioral self-regulation, emotion regulation), each of which were measured by three indicators, produced acceptable model fit, χ 2 (18) = 77.00, p < 0.001, RMSEA = 0.059, RMSEA 95% CI = [0.046, 0.073], CFI = 0.976. Next, we examined the factor loadings. All indicators except for the assessor report measure of the behavioral self-regulation (PSRA-AR) showed positive and statistically significant factor loadings to the general factor, providing support for the existence of an overarching factor. Since the PRSA-AR did not load significantly on the general factor (standardized factor loading = –0.047, SE = 0.071, p = 0.503, 95% CI = [–0.186, 0.091]), we removed this measure from the model and refit another bifactor model where behavioral self-regulation was measured with the remaining two indicators (i.e., CBRS and HTKS). This model produced good model fit, χ 2 (12) = 61.59, p < 0.001, RMSEA = 0.068, RMSEA 95% CI = [0.052, 0.086], CFI = 0.979. All indicators showed significant and positive loadings on the general factor, p s < 0.001, thus, we continued with this model (see Figure 2 ). Standardized factor loadings for the general factor ranged from 0.20 to 0.95 and are presented in Table 2 .

Figure 2. Tested bifactor model self-regulation.

Table 2. Standardized factor loadings from the bifactor model.

Controlling for the general factor, domain-specific factor loadings for the EF and emotion regulation factors were positive and statistically significant, p < 0.001. However, domain-specific factor loadings of the indicators of the behavioral self-regulation did not reach statistical significance indicating that the systematic variance in these measures was completely accounted for by the general factor.

Relative strength of the loadings to the general and specific factors for a given indicator informs how strongly the indicator measures the general and the respective domain-specific factor. The indicators of EF showed higher loadings to the domain-specific factor (0.72–0.97) than the general factor (0.23–0.25), implying that they are better measures of the domain-specific factor. Indicators of behavioral self-regulation showed statistically significant loadings only onto the general factor (0.34–0.95), implying that they are better measures of the general overarching self-regulation factor. Indicators of the emotion regulation factor showed comparable loadings to the general factor (0.38–0.49) and the specific factor (0.35–0.66), suggesting that they are equally good measures of the general and the domain-specific factors.

Next, we used this bifactor model to examine the unique relations of the domain-specific factors and the general factor with children‘s pre-academic and social-emotional competencies controlling for age, sex, and family income-to-needs ratio. Since behavioral self-regulation did not show significant loadings to the domain-specific factor once the general factor was controlled for, we excluded it from the prediction analyses. Specifically, we examined the degree to which the general factor that emerged in the bifactor model, as well as the specific factors, EF and emotion regulation, were related to pre-academic skills and social-emotional competence when controlling for the general factor.

Structural Equation Models

Woodcock johnson letter-word identification.

The model fit of the SEM regressing WJLW scores on the general factor and EF and emotion regulation specific factors in the bifactor model controlling for children’s age, sex, and income-to-needs ratio was acceptable, χ 2 (41) = 274.40, p < 0.001, RMSEA = 0.080, CFI = 0.91. The general factor significantly predicted WJLW scores, β = 0.24, 95% CI = [0.14, 0.33], SE = 0.05, z -value = 4.95, p < 0.001. Additionally, controlling for the covariates and the general factor, the EF domain-specific factor was also positively and significantly related to WJLW scores, β = 0.07, 95% CI = [0.02, 0.13], SE = 0.03, z -value = 2.54, p = 0.012. However, the remaining systematic variance in the emotion regulation specific factor was not significantly associated with WJLW scores, β = –0.01, 95% CI = [–0.12, 0.10], SE = 0.06, z -value = –0.10, p = 0.923. Among the covariates, age and income-to-needs ratio were significantly related to WJLW scores, whereas sex was not (see Table 3 ).

Table 3. Structural equation models between self-regulation factors and academic and social-emotional skills.

Woodcock Johnson Applied Problems

The model fit when regressing WJAP scores onto the general and domain-specific factors, controlling for the same covariates, was acceptable, χ 2 (41) = 292.40, p < 0.001, RMSEA = 0.081, CFI = 0.91. The general factor significantly predicted WJAP scores, = 0.42, 95% CI = [0.30, 0.54], SE = 0.06, z -value = 6.90, p < 0.001. Additionally, controlling for the covariates and the general factor, the EF domain-specific factor was also positively and significantly related to WJAP scores, β = 0.11, 95% CI = [0.05, 0.18], SE = 0.03, z -value = 3.31, p < 0.001. However, the remaining systematic variance in the emotion regulation specific factor was not significantly associated with WJAP scores, β = –0.11, 95% CI = [–0.30, 0.08], SE = 0.10, z -value = –1.14, p = 0.253. Among the covariates, age and income-to-needs were significantly related to WJAP scores, whereas sex was not (see Table 3 ).

Affect Knowledge Test

Regressing the AKT scores on the general factor and the EF and emotion regulation domain-specific factors in the bifactor model, controlling for the covariates, produced acceptable fit, χ 2 (41) = 261.21, p < 0.001, RMSEA = 0.078, CFI = 0.92. Controlling for the covariates, the general factor significantly predicted AKT scores, β = 0.15, 95% CI = [0.07, 0.24], SE = 0.04, z -value = 3.52, p < 0.001. Controlling for the covariates and the general factor, both the EF, β = 0.10, 95% CI = [0.04, 0.16], SE = 0.03, z -value = 3.10, p = 0.002, and emotion regulation, β = 0.10, 95% CI = [0.01, 0.20], SE = 0.05, z -value = 2.10, p = 0.037 specific factors were positively and significantly related to AKT scores. Among the covariates, age and income-to-needs were significantly related to AKT scores, whereas sex was not (see Table 3 ).

This study examined the extent to which different aspects of self-regulation constitute one overarching self-regulation construct while partialing out the degree to which the aspects were distinct. This study also examined the extent to which an overall self-regulation factor and its individual constructs were associated with children’s pre-academic and social-emotional competencies. Using a bifactor model, the analysis revealed an overarching self-regulation construct, and both the general self-regulation construct and the EF and emotion regulation specific constructs, were differentially related to pre-academic and social-emotional competencies, even after partialing out the general self-regulation construct. This study provides empirical support for theoretical models indicating that self-regulation is indeed a multifaceted construct that also encompasses multiple factors. A better understanding of the structural framework of self-regulation and how its constructs can be aggregated or disaggregated helps the field synthesize various ways of referencing the self-regulation construct. Our study also documented that the self-regulation constructs differentially relate to children’s outcomes, which can set the stage for better supporting certain outcomes through a broader overarching self-regulation construct or its specific factors.

Self-Regulation as an Overarching and Multifaceted Construct

Self-regulation has been identified as a pivotal skill in early childhood due to its malleability and importance for various short- and long-term outcomes ( Diamond, 2002 ). In line with the conceptualization of self-regulation, three of its constructs, namely EF, behavioral self-regulation, and emotion regulation, were tested in a bifactor model. Results showed that these three constructs of self-regulation significantly contributed to an overarching self-regulation factor. This is in line with the conceptual definition of self-regulation and supports the notion that there are common conceptual underpinnings of each of these self-regulation constructs ( Diamond and Lee, 2011 ; Hofmann et al., 2012 ; McClelland et al., 2018 ). Despite the vast amount of interest in this construct, a lack of conceptual clarity across various disciplines, as well as debate over its underlying constructs, make it challenging to study, measure, and support these skills in early childhood ( McClelland and Cameron, 2011 ; Morrison and Grammer, 2016 ). Our results contribute to this discussion by providing empirical support that the self-regulation construct is multifaceted and there is a common variance shared by its constructs.

Our results indicate that there is substantial shared variance across the three constructs of self-regulation. Although it is unknown what the common variance shared by all the constructs of self-regulation is, it could be attentional processes underlying self-regulated action. In fact, the executive attention network has been proposed to underlie the development of conscious control and be responsible for monitoring and resolving conflict between other brain networks ( Rothbart et al., 2007 ). Within this model, executive attention is defined as a limited capacity attentional resource underlying the goal-directed control of cognition, behavior, and emotion ( Rueda et al., 2012 ). Recent evidence has shown that executive attention is the common cognitive factor underlying the self-regulatory capacities captured by EF and effortful control ( Tiego et al., 2018 ). Executive attention is also related to emotion regulation in children ( Sheese et al., 2008 ; McClelland et al., 2015 ) and is considered to be a mechanism underlying the ability to regulate emotion in order to behave in socially acceptable ways ( Eisenberg et al., 2004 ). Children use various strategies to engage in emotion regulation, including distractive or cognitive strategies that involve redirecting attention or reframing the situation, and these rely on attention ( Zimmermann and Stansbury, 2003 ; McClelland et al., 2018 ). Thus, it is possible that executive attention and attentional control may be a common process among the various aspects of self-regulation.

It is also plausible that the general self-regulation factor is picking up on the behavioral self-regulation skills captured in the direct assessments and adult reports across the constructs. Indeed, results indicated that the behavioral self-regulation construct completely loaded onto the general self-regulation factor. Behavioral self-regulation is used while integrating and applying EF skills and emotion regulation in a variety of contexts ( McClelland et al., 2007 ). For instance, children need to remember instructions, stop an action to do another action, and flexibly switch between competing rules to complete EF tasks. Similarly, in a classroom setting, raising your hand before talking, switching from play to a clean-up activity, and waiting your turn before participating in a group setting necessitates using behavioral-self regulation skills for both top-down and bottom-up regulation of thoughts and feelings. Thus, it is a reasonable hypothesis that the general self-regulation factor may be picking up on the behavioral self-regulation skills that are represented across all tasks and measures in the current study; however, it will be important for future studies to attempt to identify this factor more precisely.

Individual Constructs of Self-Regulation

After accounting for the general overarching self-regulation construct, our results showed that the EF and emotion regulation constructs significantly loaded onto their respective factors, but behavioral self-regulation did not load onto its respective construct. These results mean that the systematic variance of behavioral self-regulation measures was fully accounted for by the general self-regulation factor. However, systematic variance in the EF and emotion regulation constructs remained even after accounting for the overarching self-regulation construct.

The remaining variance of EF, after accounting for the overarching self-regulation construct, may reflect the regulation of attention, memory, or thoughts in the absence of overt behavior or salient emotion. Although EF and self-regulation terms are sometimes used interchangeably ( Zelazo and Cunningham, 2007 ), EF is used for purposes other than self-regulation and should not be simply equated with self-regulation ( Nigg, 2017 ). For instance, solving a mental math problem requires EF, as documented in many studies showing a strong association between EF and math ( Clements et al., 2016 ; Schmitt et al., 2017 ). EF in this context is likely purely cognitive as solving a mental math problem typically doesn’t require behavioral or emotional control.

The other construct with remaining unique variance in the bifactor model after accounting for variance explained by the general factor was emotion regulation. Though emotion regulation has been studied as a complete area of itself, it has also been studied in relation to or as a component of self-regulation ( Eisenberg et al., 2004 ; Zelazo and Cunningham, 2007 ; Blair et al., 2016 ). In the current study, after the common variance between cognitive, behavioral, and emotional self-regulation is accounted for, what is left in the emotion regulation construct may be emotion-related processes. Emotion regulation involves attempts to influence which emotions a child has, when the child has them, and how the child experiences and expresses these emotions ( Gross, 2015 ). Thus, the unique variance associated with the emotion regulation aspect of self-regulation may be the processes used to manage both the frequency and the intensity of emotions, emotion related physiological states, and intrinsic regulation of emotions ( Eisenberg et al., 2007 ). In fact, the measure we used to assess emotion regulation was a teacher report that included items tapping into emotion related process such as “can say when feeling sad, angry or mad, fearful or afraid” and “is a cheerful child”, in addition to items tapping into emotion regulation such as “does not remain anxious or sad after emotionally distressing events”.

Predictions to Pre-academic Skills and Social-Emotional Competence

Overarching self-regulation construct.

Although it is not clear what the shared variance across the self-regulation constructs exactly represents, our results indicate that the general overarching construct of self-regulation predicts pre-academic (i.e., mathematics and literacy) and social-emotional skills, which is in line with extant literature ( Blair and Razza, 2007 ; Robson et al., 2020 ). Our results provide new empirical evidence that all the different constructs of self-regulation, including cognitive, behavioral, and emotional, share a common process, and this common process is positively and significantly associated with pre-academic and social-emotional skills controlling for children’s age, sex, and family income-to-needs ratio.

Even though empirical research exploring the overall and unique contributions of the cognitive, behavioral, and emotional self-regulation constructs at the same time is scarce, our findings support previous research examining the unique effects of EF and behavioral self-regulation on pre-academic skills. When examined simultaneously, EF contributed to children’s academic skills whereas behavioral self-regulation (called classroom self-regulation) did not ( Morgan et al., 2018 ; Finders et al., 2021 ). Our findings expand previous work by parsing out the common variance in the constructs of self-regulation and by exploring the unique predictive abilities of these constructs in a bifactor modeling approach. Our bifactor results showed that the remaining variance in EF is still significantly associated with pre-academic skills, including math and literacy, as well as social-emotional skills, even after its shared variance with the general overarching self-regulation construct has been accounted for. This is consistent with prior research that demonstrates relations between EF and pre-academic skills ( McClelland et al., 2007 ; Morrison et al., 2010 ; Allan et al., 2014 ; Schmitt et al., 2017 ), as well as social-emotional competence ( Riggs et al., 2006 ; Korucu et al., 2017 ).

Even though emotion regulation has been conceptually linked to children’s pre-academic skills, little research has empirically tested this association ( Sanson et al., 2004 ; Raver et al., 2007 ; Ursache et al., 2012 ). In contrast, prior evidence of relations between emotion regulation and social-emotional skills has been well-documented ( Eisenberg et al., 2005 ; Di Maggio et al., 2016 ). Our bifactor results showed that after accounting for the common variance in the constructs of self-regulation, the unique variance of emotion regulation was positively and significantly associated with children’s social-emotional competencies, but not with pre-academic skills. This is in line with studies documenting positive and significant associations between emotion regulation and social-emotional competence ( Housman et al., 2018 : Ornaghi et al., 2019 ). The non-significant finding between emotion regulation and pre-academic skills in this study is also in line with prior work showing only indirect associations between the two ( Howse et al., 2003 ). For instance, it is argued that emotion regulation may be associated with academic skills through other factors such as teacher-child relationships and motivation ( Graziano et al., 2007 ). Thus, there is need for more research to further disentangle the associations and mechanisms between emotion regulation and pre-academic skills.

Limitations and Future Directions

The current study contributes to our understanding of the common and unique aspects of self-regulation constructs and has several strengths. We utilized a large, diverse sample, and a statistical approach that enabled us to disentangle the sources of systematic variance in the domain-specific and general factors of the self-regulation construct. Using a bifactor model allowed us to examine the common and unique aspects of self-regulation constructs at the same time and their overall or unique associations with two important skills: pre-academic and social-emotional skills. Using a bifactor model overcame measurement challenges of total vs. individual score approaches by allowing us to consider measurement error in the models. Employing a bifactor model also helped us to overcome challenges with the reflective latent scoring approach, which assumes unique variance that is not common among the constructs is a measurement error. Finally, using a bifactor model overcame challenges with the second order models and allowed us to examine unique relations between the domain-specific factors with outcome variables above and beyond the general factor using standard SEM (since they are represented as latent factors as opposed to disturbances in the model; Chen et al., 2006 ; Reise, 2012 ).

Despite its strengths, the current study does have several limitations. First, even though we used multiple methods to assess various self-regulation constructs, including direct assessments, a teacher-report assessment, and an assessor report (observation during task administration), this only applies to the behavioral self-regulation construct, providing a deeper and more nuanced set of measurements for this construct than the others. The other self-regulation constructs, EF and emotion regulation, were each only assessed with one measure. Specifically, the task we used for assessing EF, the Day-Night task, taps primarily into inhibitory control and working memory. Future research should use multiple measures to assess EF and its components (e.g., cognitive flexibility) and emotion regulation as measure selection may have influenced our findings. Including multiple types of measurement for each of these constructs in future studies could strengthen the current study findings or suggest alternate relations between the distinct and overarching self-regulation constructs.

Further, task impurity problems in the field of self-regulation and EF may influence the conclusions that could be drawn from this study. Even though the measures used in the study have been found to reliably represent their constructs in previous studies, measures (e.g., HTKS) used to assess EF and behavioral self-regulation constructs have often been used interchangeably. Further, measures used to represent behavioral-self regulation could include aspects of emotion regulation depending on the context in which it is being evaluated. For instance, teachers’ rating of classroom self-regulation, considered as a behavioral self-regulation measure in the current study, may include ratings of subtle emotion regulation strategies (e.g., “attempts new challenging tasks”). Similarly, the task that has been used to represent EF in this study may have common components with the task that assesses behavioral self-regulation (e.g., inhibitory control). Thus, and as with any study, the findings observed may be an artifact of the measures used in this study, and it will be important for future research to replicate findings to determine whether the overall or unique associations of the self-regulation constructs and their associations with pre-academic and social-emotional skills will hold when different sets of measures are used.

Though this is a problem with any cognitive assessment in the field, it is difficult to identify what is common and shared between the various self-regulation constructs. What is shared among the self-regulation constructs used in the study might reflect another, non-cognitive, and non-measured ability (e.g., motivation) especially among the direct assessments. Thus, our conceptualization of a general overarching self-regulation construct may include such factors. Relatedly, not all of the potential self-regulation constructs were tested in the current study. Delay of gratification and effortful control could also be tested under the self-regulation construct ( McClelland et al., 2018 ), though task impurity may be a problem here as well.

Another limitation of the current study is that the data were collected at a single time point and thus the results are cross-sectional limiting application of results to change in self-regulation over time. It will be important for future research to replicate the findings with longitudinal data and to investigate the common and unique aspects of self-regulation constructs at different time points, as well as the unique and overlapping predictive abilities of these constructs with academic outcomes over time. Further, it is important to emphasize that the PSRA-AR assessment did not load significantly on the general overarching self-regulation factor, and thus was removed from the measurement model. Future research should replicate these findings and also consider using other measures to observe children’s behavioral self-regulation performance during task administration. Although the current study included racially and ethnically diverse children, results may not generalize to populations outside of the U.S. Finally, it is also important to note that although our methodology, the bifactor model, overcame challenges with the reflective scoring approach (by treating the unique variances as orthogonal factors as opposed to measurement error), there is an ongoing debate about using the reflective vs. formative scoring approach specifically with regards to EF and its components ( Willoughby, 2014 ; Camerota et al., 2020 ). Future research may benefit from examining these different approaches in alignment with research questions.

Research suggests that self-regulation is an important predictor of various outcomes in early childhood and beyond, including academic achievement, social-emotional skills, and health and other life outcomes, including earnings and criminal charges ( Moffitt et al., 2011 ; Robson et al., 2020 ). Although it is acknowledged that self-regulation is a multifaceted construct, it is unclear how its constructs that tap into cognitive, behavioral, and emotional aspects are connected and whether they constitute an overarching self-regulation construct. This study, to our knowledge, was the first to use a bifactor model to explore these relations. Findings indicated that self-regulation is indeed a multifaceted construct, yet the EF and emotion regulation constructs of self-regulation also have unique variances. Further, these constructs differentially predicted pre-academic and social-emotional skills, such that the overarching self-regulation factor and specific EF factor both predicted academic and social-emotional skills, and the emotion regulation factor predicted social-emotional skills. Study findings may have important implications for supporting children’s regulatory skills as well as their success in school. Specifically, identifying specific aspects of self-regulation most predictive of early academic achievement and social-emotional skills can help early childhood programs strategically and intentionally support targeted skill development, putting time and resources into fostering the most beneficial skills during the early childhood years.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, when the larger study is completed. The study is still ongoing. Requests to access the data should be directed to IK, [email protected] .

Ethics Statement

The studies involving human participants were reviewed and approved by the Yale University Institutional Review Board. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.

Author Contributions

IK, ST, and SS contributed to the conceptualization and design of the study. IK and EA contributed to the data analysis, results, and writing. JF, GS, and all others contributed to the writing and editing of the manuscript. All authors contributed to the article and approved the submitted version.

This study was supported by grants from the US Department of Education, Institute of Education Sciences to Yale University (#R305A180293).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords : executive function, behavioral self-regulation, emotion regulation, bifactor model, pre-academic skills, social-emotional competence

Citation: Korucu I, Ayturk E, Finders JK, Schnur G, Bailey CS, Tominey SL and Schmitt SA (2022) Self-Regulation in Preschool: Examining Its Factor Structure and Associations With Pre-academic Skills and Social-Emotional Competence. Front. Psychol. 12:717317. doi: 10.3389/fpsyg.2021.717317

Received: 30 May 2021; Accepted: 06 December 2021; Published: 18 January 2022.

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Copyright © 2022 Korucu, Ayturk, Finders, Schnur, Bailey, Tominey and Schmitt. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Irem Korucu, [email protected]

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Self-Regulation, Depletion, and Motivation Essay (Critical Writing)

Purpose of the study, methodology, results of the study.

There is a lack of information regarding the importance of motivation in self-regulation theories. Thus, the proponents of this study attempts to understand the role of motivation in the context of “strength, or limited-resource, model of self-control in several domains” (Baumeister & Vohs, 2007, p.1).

The proponents of this research discovered that a reduction in resources can be overcome by motivation even if ego depletion is not the direct consequence of a lack of motivation. Interestingly, the study also discovered that self-regulation is linked to physical fuel specifically glucose-rich foods.

Previous research has indicated that self-regulation is affected by at least three factors:

• monitoring;
• self-regulatory strength (Baumeister & Vohs, 2007).

Self-regulation must be linked to a particular standard because self-regulation at its core is altering behavioral response on account of a particular need or goal.

Thus, a person desiring food must satisfy that need and there is no inner-conflict that prevents the individual from seeking and consuming viable food resources. However, if eating food at a particular time and particular quantities can endanger the person’s health, then, self-regulation is needed.

The ability to self-regulate becomes weaker over time as the need to satisfy a particular urge grows stronger. This is countered by a monitoring scheme. For example, an accountability group helps a sex addict cope with his/her addiction knowing that there is a group of people monitoring his/her progress and interested in his/her success.

On the other hand all of these things are useless to the individual if he/she has no self-regulatory strength. Previous research has uncovered that “after making many choices, the chooser is less able to engage in good self-control, suggesting that making choices exhausts the self over time” (Baumeister & Vohs, 2007, p.9). This phenomenon is also known as ego depletion.

Previous research also pointed out that “physically tired people generally perform worse than others at strenuous tasks, but if the incentive is high enough, they can perform well despite their tiredness” (Baumeister & Vohs, 2007, p.10).

There is also the added revelation that “effective self-regulation seems to involve utilizing the glucose in the bloodstream to achieve what is a psychologically difficult and biologically costly task, such as stifling one’s behavioral impulses or making difficult choices … when glucose – the primary source of fuel for all brain processes – has been depleted, the person is temporarily less able to function at optimal levels” (Baumeister & Vohs, 2007, p.11).

It has been made clear that a person must not allow the self to reach a point of ego depletion and this means that the body must have continuous access to glucose-rich foods.

The proponents of this study wanted to add another factor to the self-regulation process and they asserted that motivation plays a vital role in helping the individual self-regulate. However, they were unable to develop an empirical study that would clearly explain the connection between motivation and self-regulation.

The proponent of the study spent a great deal of time explaining the significance of access to glucose-rich foods to help a person self-regulate rather than the ability of motivation to counteract the negative impact of ego depletion or fatigue.

The weakness of the argument can be seen in the experiment that they had cited to support their claim. It has to be pointed out that the proponents of this study did not bother to develop their own empirical research and instead used the research results of studies made by Muraven, Shmueli and Burkley. Even so, the chosen studies did not seem to demonstrate the ability of motivation to significantly affect self-regulation.

In one particular study the participants were asked to perform a depleting task. Afterwards they were asked to perform a second task with the added information that they would perform a third task. The study showed that the participants performed poorly on the second task.

Baumeister and Vohs (2007) interpreted the depleted state of the participants as the effect of a conservation process – they were conserving their energy while performing the second task in anticipation of the third task. Baumeister and Vohs (2007) went on to conclude that the participants were motivated to perform the third task and thus explaining the significant change in their efforts for the second task.

Baumeister and Vohs (2007) concluded that motivation plays a key role in self-regulation arguing that if the second task was deemed more important, then, the participants would have expended more resources. This is based on the assumption that the participants were highly motivated to perform the third task but there was no information given to support that view.

The argument made in the beginning of the study was that motivation should be an important factor in self-regulation. This may be true but Baumeister and Vohs did not perform a well-designed empirical research that would have proven their point. Instead, they tried to use the results of another study made by different group of researchers to fit their own assumptions.

For instance, Baumeister and Vohs could not establish the fact that the participants in their cited study were motivated to perform the third task. There was also no measurement made with regards to the degree of motivation whether the participants were simply motivated or highly-motivated to complete the tasks given them.

Baumeister and Vohs had a clear understanding of the problem but they were unable to show evidence that would support their hypothesis. The weakness of the research is its overreliance on previous experiments without going through the process of conducting a valid empirical study to validate their hypothesis.

There is a need to clearly define what motivation means and how it can be measured. Baumeister and Vohs must develop a control group and they must isolate the effect of physical strength and access to food as the main source of self-regulation. Nevertheless, the value of this study is in the realization that not much is known regarding the impact of motivation to self-regulation.

Baumeister and Vohs were unable to show evidence to support their argument that motivation is an important factor when it comes to self-regulation. Nevertheless, their study has provided excellent background information regarding self and personality.

The most important information that can be gleaned from the study is the impact of three factors: standard; monitoring; and self-regulatory strength, to achieve effective self-regulation. Another important piece of information is the linkage between energy from glucose-rich foods and the ability of the person to self-regulate.

Baumeister and Vohs have laid the foundation for an interesting research; they simply have to develop their own empirical research to clearly demonstrate that motivation can help boost a person’s ability to self-regulate in conjunction with the other three important factors mentioned earlier.

Baumeister, R. & K. Vohs. (2007). Self-regulation, ego depletion, and motivation . Social and Personality Psychology Compass, 1 . Web.

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Bibliography

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There is a high need of self-regulation at Operation Breakthrough (OB). Operation Breakthrough services children from the birth up to 13 years of age who all come from low income families. Research indicates that children who grow up in impoverished areas, struggle with self-regulation more than their same aged peers with more enriched socioeconomic circumstances (Jensen. E, 2009). The program promotes school readiness by enriching the social and cognitive development of children through the provision of education, health, nutrition, and social services. The building is located on the corner of 31st and Troost Ave, Kansas City, Missouri 64139. There are many stories of Troost and its dividing line in downtown Kansas City. The location is unique because it strives to appear to be the breakthrough in the dividedness. The building is fairly up to date, clean, and secured. However, less than 100 feet on the corner, there are people who appear to be highly intoxicated or under an illegal substance. Across the street there is an old building where people hang around and sleep with the clothes on their back, shoes on their feet as their only accessories.

Operation Breakthrough services children Monday through Friday between the hours 6:00 am – 6:00 pm for more than 400 children. More than 87% of enrolled families live below the federal poverty guidelines. Twenty percent of children are homeless, living in battered women’s or homeless shelters or transitional living programs. Ten to fifthteen percent of the children serviced are in foster care or other placements due to abuse, neglect, or other family crises. The average income of our families is $12, 898.00. It is one of the largest single site early education and social services facility in the state of Missouri.

The organizational vision is that all children have the opportunity to achieve their fullest potential. The mission is to provide a safe, loving and educational environment for children in poverty and to empower their families through advocacy, emergency aid and education. The behavioral intervention is 90-95% due to students living in toxic homes and lack of social skills to self-regulate. They lack structure and stability and many are unable to cope with big feelings that escalate to major behavioral challenges such as non-compliant when given a direction, doing something even when they do not want to, and being okay even when others are not. The organization began in 1971 by Sister Corita Bussanmas and Sister Sailer as a response to requests for quality child care of the working poor. Over the years Operation Breakthrough has included social services: Adult Therapy, Theraplay, Violence Prevention, Family Advocacy, Occupational Therapy, and an On-Site Children’s Mercy Urgent Care Clinic. Other programs offered by Operation Breakthrough: Before and after school programs, mentoring/tutoring, USDA_Approved Meal Program, Dental Clinic, Family nurturing program, Housing, Women Infants and Children.

Families are put on a waiting list, until a spot in a classroom becomes available. The family is established a Family advocate who helps the parent(s) create a plan for success in which they support 100% by providing them to resources within the facility and in the community as well. In the therapy department, the therapist provides a one on one session with the parent and child to help build and strengthen the connection whether it’s because the parent may lack parenting skills, or the child is in state custody and the child is new to a foster home. Anyone who works in the building is also a Mandated Reporter.

Because Operation Breakthrough is a non-for profit agency, the organization relies heavily on the generosity of the community to continue its work. Less than 40% comes from government sources, city state and federal. The other 60% are grants from foundations, corporate and individual donations make up the rest. The total of preschool enrollment is 267 students. There are 206 African American, 11 Hispanic, and 17 Caucasian. The proportional attendance rate, African American: 88.67%, Muti: 88.74%, White: 86.76% and Hispanic: 88.21%. The drop-out of students is 10%. A total of 26 disenrolled, due to either student moved on to a different program, or because of the attendance policy student was withdrawn. Staff ratios, students to classroom teacher in the birth – three years of age are 4:1. In the preschool rooms 2:17. In the school age program 1:17. About 95% of staff are African American, three percent Caucasian, two percent Hispanic. 72% of the staff have a degree from college in Early Childhood Education.

Building wide, Creative Curriculum is incorporated through student learning. It is based on five fundamental principles to help guide and understand the reasons for intentionally setting up and operating preschool programs in particular ways. Ages and Stages is another form assessment that is used to screen children, at the beginning of the year and the end of the year. Desired Results Developmental Profile is a system used to track the student’s progress so that they are rated three quarters of the school year on 56 measurements that tracks their progress and readiness for Kindergarten. Implementation

Based on the Devereux Early Childhood Assessment, which is an assessment and planning system that is designed to promote resilience in children, a small team has identified self-regulation as an area of need. The results showed that behavior rated at a class average of 64% as an area of need along with self-regulation rating at 48.46% as an area of need as well. I have created a team that consist of myself, an Occupational Therapist, and an Occupational student to put this study together. We have decided to implement the use of Social Emotional skills using the five senses in a small group format that will target the missing skills students do not have to manage high emotions. The intention of Social skills’ groups is to lower behavioral needs in the classroom that will increase student achievement. The two measurements and assessments that will be used in this study are Devereux Early Childhood Assessment, and Desired Rating Development Profile. A class of 16 preschool children will be used for this study.

A pre-test using the Ready Class Project Baseline Assessment will be conducted prior to the study and a post-test will be taken at the completion of the study. The pretest will be key to determine what terms are being used to identify an emotion, and how many of the emotions can the student identify correctly. It is important to get an idea of what exactly the students know early on so the children are not repeating information during the six-eight week study. Reports of student’s misbehavior will be documented, to analyze the impact of Social groups as well the intensity of the behavior. This study will compare and contrast areas in the DECA screening go from a need to a typical or a strength. To examine whether social skills group increased student achievement, I will run a report on Desired Rating Development Profiles that will show the percentile of where students are in their academic growth. This rating is also an assessment that is administered in natural strength t hrough teacher observations. It is an ongoing documentation of children’s knowledge and skills in everyday environments, mainly in the classroom setting. Desired Rating Development Profile is made up of eight domains. The focus of each domain is on the acquisition of knowledge, skills, or behaviors that reflect each domain. The two domains that will be focused on are Approaches to learning – Self regulation, and Social and Emotional Development.

Implementation

A pre-test using the Ready Class Project Baseline Assessment will be conducted prior to the study and a post-test will be taken at the completion of the study. The pretest will be key to determine what terms are being used to identify an emotion, and how many of the emotions can the student identify correctly. It is important to get an idea of what exactly the students know early on so the children are not repeating information during the six-eight week study. Reports of student’s misbehavior will be documented, to analyze the impact of Social groups as well the intensity of the behavior. This study will compare and contrast areas in the DECA screening go from a need to a typical or a strength. To examine whether social skills group increased student achievement, I will run a report on Desired Rating Development Profiles that will show the percentile of where students are in their academic growth. This rating is also an assessment that is administered in natural strength through teacher observations. It is an ongoing documentation of children’s knowledge and skills in everyday environments, mainly in the classroom setting. Desired Rating Development Profile is made up of eight domains. The focus of each domain is on the acquisition of knowledge, skills, or behaviors that reflect each domain. The two domains that will be focused on are Approaches to learning – Self regulation, and Social and Emotional Development. Literature Review

There is no person in this world that is born with a skill that allows them to be okay when others are not. Or even to able to manage an overwhelming feeling when challenges arise. Every day it gets harder to build courage to do something you know you have to, but have those contradictory thoughts. Every child is different, just like every adult grows up to be different. As an educator we find ourselves repeating phrases over and over such as “please don’t do that, keep your hands to yourself, I need you to calm your down, go to the think seat, pay attention”. In other escalating moments, we have to stop teaching and deal with a behavioral issue at hand. The ideal scene is you would like to have an easy transition from one activity to another, instead you must leave no idle time so that student who has little self-control finds something she or he is not supposed to do.

More children especially at the early years of school are exhibiting more behavioral issues than teachers can manage. In fact, Preschool teachers report children’s challenging behavior as their single greatest concern (Joseph and Strain, 2003). Educators often blame children for not being able to self-control their feelings and expect them to have those skills already installed, but refuse to consider what the factors are contributing to the behaviors being displayed. The study done on “How poverty affects behavior and academic performance”, indicated that the correlation between socio-economic status (SES) and life stress in adolescents found that children with lower SES had significantly greater levels of negative life change compared to higher SES children (Gad & Johnson, 1980). Negative changes can include lack of parenting skills, children living in poverty, nurturing and supportive qualities are low, and parents are less involved in a child’s lives. Low SES children are often left home to fend for themselves and their younger siblings while their caregivers work long hours, and are less likely to participate in after school activities (U.S Census Bureau, 2000). A child living in that circumstance will not come to school already having self-regulation drilled into their minds and bodies.

Children who are living in stressful environments will have very little self-regulation attributes if that more than likely none at all. Children raised in poverty rarely choose to behave differently, but they are faced daily with overwhelming challenges that affluent children never have to confront (Jensen, E., 2009). Many children are misunderstood by their social and emotional deficits as a lack of respect, and are held at a high expectation to be in school with suitable emotional responses. Children must learn to evaluate what they see, hear, touch, taste and smell and compare it to what they already know (Florex, I.R., 2011). They must also learn to use self-regulation to carry out the response in a self-controlled, and safe manner. If they come into school at any grade level not having or experienced any self-regulation skills, they are unable to apply it to any previously skills known.

In the classroom setting, it should hold a positive climate where social interactions are happening between children who are different from one another. The high SES children should not be sectioned off in a corner playing together because the low SES children are too complicated to play with. As an educator, that should automatically be an eye opener for you and there is a need for change in the classroom if it is happening. Hosting social groups, will allow children and adults to be more intimate with each other, process communication, identify unknown feelings, and practice negotiation skills. A study from “A school-wide tiered program of social skills intervention” indicated, students felt it was beneficial because they got to learn how others felt when they feel left out, and how other people would solve problems. Another student stated it helped them build more self-confidence and taught them how to help others when they are down (Albrecht, S.F., Mathur, S.R., Jones, R. E., & Alazemi, S 2015).

The Encyclopedia of Mental Disorders defines Social Skills Group, as a form of behavior therapy used by teachers, Therapists and trainers to help a person who has difficulty relating to other people. The group size can depend on the age of children, but smaller sessions are likely to be beneficial. It is critical to understand students’ behavior and then lay out clear behavioral expectations. When dealing with children who live in poverty, it’s almost as if you’re playing an emotional keyboard.

Children raised in inner city poverty are more likely to display behaviors such as acting out, impatience and impulsivity, social graces, limited behavioral, and inappropriate emotional responses (Jensen, E., 2009). Skills missing need to be identified early so that they can be reached during Social Skills groups. The ideal smooth day of class would include, sympathy, patience, shame, cooperation and gratitude, in which those are the skills children going to Operation Breakthrough have never experienced and need to be taught. It is great way to implement Conscious discipline through Social Skills groups. It is a classroom management program which incorporates social and emotional learning based on research and practices in child development. Hoffman, Hutchinson, and Reis (2009) reported that preschool children and elementary school teachers who practiced the tenets of Conscious Discipline perceived a better school climate. They dealt with student behavior issues as learning experiences using conflict resolution strategies rather than traditional methods of classroom management; rewards and punishment.

If self-regulation is established in the early years of a child’s life typically they will perform well academically and take more responsibility for their own learning. According to Theory and Practice (2012) the effects of implementing Social Competence increased concentration and attention skills and social emotional competence, as well as reduced aggression and disruptive behaviors. Teachers are less equipped with resources and strategies to defuse noncompliance behaviors that are also preventing children from reaching academic success.

Focusing on social emotional competence in an intimate social group setting, students will be able to identify feelings, practice skills and strategies taught through the teacher. According to Reading minds and building relationships, this also builds the relationship between the student and teacher. The goal of teaching self-regulation through social skills is to model so students can imitate what they see, by using hints and cues. Students can refer to a signal given by teacher when frustration starts to occur so they know they can follow up with a breathing strategy or different coping skill. Followed by withdrawing adult support, students are able to negotiate with each other by using expressive communication. The article Reading minds and building relationships showed that a student had trouble with organization and transitioning throughout the day. The teacher taught and practiced with student a calming routine and they came up with a hand signal that signified the student was becoming upset. It’s easier to teach a missing skill to students more effectively in a small setting versus large group. Again, Social groups provide those intimate relationships and connections that are also vital to a child’s success.

Many children are at risk for dropping out, because they are unable to maintain the academic requirements needed. The small groups will have now targeted missing skills in the children that prevented them from being able to pay attention to people and things in the learning environment. They also now have been taught different coping strategies to manage high emotions. With children being able to manage high emotions on their own, teachers will less likely be interrupted in student learning, and the increase in student achievement will go up!

Tools for Testing

My overall study for this project was to demonstrate and gather data to prove that social skill’s group could improve student achievement. As a part of our programming at Operation Breakthrough, we strive to support the development of self-regulation. First, it involves one’s ability to control one’s impulses and stop doing something. Second, it takes one’s capacity to start doing something even if one does not want to because it is needed or required. Self-regulation occurs with our emotions, attention, behavior, and alertness. In the classroom, appropriate self-regulation looks like waiting one’s turn, listening to a story, engaging in a lesson and managing one’s anger or frustration (Blackwell, 2014). The Ready Class Project, is an experiment, where students can use their bodies in comparison of a car engine. Providing students the opportunity to explore the meaning of what each term means and comparing it to the idea of a car engine, will increase the amount of strategies children can use to reduce the amount of out of control behaviors that prevent student achievement. The following describes the concept of the Ready Class Project:

“When I’m sad or have no energy, my engine is running low like a car with no gas. When I’m ready to learn and feel just right, my engine in great condition. When I’m angry or out of control, my engine is running high like a car going really really fast”.

– Angela Blackwell

Below you will find an eight week layout of what each small group consisted of, over the few weeks. The Speech Occupational therapist and I collaborated together, in which I lead the planning and the groups for the success of this study.

At the beginning of the study, each student was given a base line test. The test consisted of a first set of pictures that demonstrated the child in the picture (sad, happy, or mad). The student had to name the emotion each child was feeling from those three terms. The second set of pictures, the child was asked to choose one of the following terms to describe the emotion the child in the picture was feeling: low, just right, or high). At the end of the study, each student will complete the baseline test, and there will be a comparison between each baseline test to define if the child is able to use the correct term to determine an emotion when given a visual. Social skills group will be held twice a week, and at the beginning and end of each group, students will get the opportunity to voice “how their engine” is running. This will allow me to see which strategies to increase self-regulation, is working for the student. Behavioral Reports are documented as they happen, describing the situation and behavior of the child. I will be looking for a pattern, of the child’s behavior and if the behavior of the child is decreasing over time (ex. Level of aggression, behavior, and life skill). The members of the team and I met once a week, and planned a week’s worth of social skills group. This gave us much time to prepare any props that were used in the group, and have additional wiggle room to review the next week’s group ahead of page so each person was familiar with the plan. This also provided us a time to discuss what we felt went really well, and what we could possibly change next time, due to the outcome.

Collected Data Analyses

A week prior to the study each student took a pre baseline assessment. The pre base line assessment was over a few days due to students absences or early pick up. The assessment baseline shows 55% of the vocabulary words (angry, happy, sad, and high, middle, low) were used correctly to relate to the picture shown at the time of the test which was taken at the start of the study. Week one day one, we introduced the vocabulary. Children read introduction book, sang “My bodies like an engine, the teachers modeled each engine category and children acted out each emotion in small groups. Teachers noticed that the children picked up on the vocabulary quickly from the book and song. A child stated during group, “I like the fast car”. They were engaged, while some became frustrated with the puppets to act out engine emotion because it was difficult to make the puppets move. Week one, day two we repeated the introduction by singing the song and reading the book. Students were broken into three groups, the first group went outside to look at a car engine and talked about high/low/middle and related to emotions. The second group focused on breathing strategies already used in the classroom as tool to change how we feel, and the third group sorted emotion pictures into the correct engine terminology. Teachers felt three small groups were the right length of time and teachers felt all children participated well. Teachers liked staying at one activity and the children switched groups. Children transitioned from groups with ease, indicated this model of small groups may be successful agai n. Children seem to enjoy engine song as they continued to sing it throughout the morning. Having one group outside helped add movement for the children. Week two, day one, we introduced high engine, and emotion vocabulary. Children read high engine book, “sang my engine runs high”. Students were broken into three small groups, the first being high engine dancing, freezing, and breathing. The second group lotion and belly breathing, and the third group learning about how to use the calm down space. One child stated “she was sad today, and did not want to participate”. Three groups made it difficult to manage children behaviors. Most of the children were able to act out emotion for high engine. There was a rise in acting “high engine”. The children demonstrated more correct identification of their engine as it relates to their emotions. Week two, day two we reviewed high engine and emotion vocabulary. They sang “My engine runs high” and read book related to engine “My mouth is like a volcano”, followed by graphing how they felt using and X. As a large group, we made a volcano. Teachers thought activities went smoothly overall. One teacher “believed My Mouth is Like a Volcano” to be a long book for this group. Teachers reported children appeared to be taking turns and completing their art without prompting. One child took apart his volcano and needed support to return back to activity. ”. Another child who became frustrated stated “my engine is running high”. Children demonstrate more correct identifications of their “engine” as it relates to their emotions during check-in and teachers liked check-in chart. Most children (except 4) discussed their engine was in the middle, and the group reflected children being ready to learn.Week three, day one low engine vocabulary and song were introduced. Children sang “My Engine Runs Low,” and graphed how they felt using an X. As a large group, we did exercises, yoga poses, and drank water as a “fuel break”. Teachers thought activities went smoothly overall, but time spent on carpet checking in with children was long. Children demonstrate more correct identifications of their “engine” as it relates to their emotions during check-in and teachers liked check-in chart. Singing songs during transitions of the group seems to be good strategy for children to wait patiently. Finding spots for yoga positions was tricky. Few were able to verbalize engine feeling low after exercise. Children enthusiastic about water as a low engine to middle engine strategy. This part of the activity was the most calm and organized. Most children waited in line for water patiently. Week three, day two repeat of low engine introduction. Children played low engine bingo by crossing off pictures with an “X” if on their card. Took turns spinning the wheel after had a calm body. Teachers thought activities went smoothly overall. Teacher observed kids attention spans decreased. Teacher reported that redirection works well and singing songs keeps them engaged. Teacher liked follow-up questions after activity to get feedback from kids and gauge understanding. Most waited turn patiently to spin the wheel. A few needed verbal prompting to maintain calm body and wait their turn. A few were able to verbally ID calm down strategies and/or change engine when it is feeling low. Some children stated the following, “I can use my Namaste or my balloon,” “I can use lotion to get engine back to middle from low”, “I can use a calm down strategy”. Week four day one, children used small red, yellow, and green cars to describe engine levels. Cars were labeled with one capital letter and children matched this to the same one on a parking space on the rug. All children enjoyed the new car/road rug. Some were able to play with cars and match letter independently. Most children are still developing their turn-taking and direction-following skills, but the novelty of a new addition to choice time may have contributed as a distraction. Most were able to match the letter labeled on the car to the same letter labeled on the rug with few verbal prompts. One child was very challenged by identifying letter and matching. All children used functional fine motor grasps to move the small cars around the map, including pincer and tripod techniques. Some able to spontaneously associate car color (red, green, yellow) with an engine level (high, just right, low). Most needed prompting to identify the car color and engine level and/or characteristics of that level. One did not associate the car color with engine level. Week four day two, the middle engine vocabulary and song were introduced. Children sang “I’ve got self-control.” For the large group activity, the children went outside to clean the teacher’s cars to change their car engines from feeling stuck in the mud to right in the middle through washing it clean. Children enjoyed the new “self-control” song and getting movement in after sitting for story time. Most children able to demonstrate self-control or “stop” when the song said “stop.” Most children enjoyed washing the cars, however they needed multiple verbal prompts to wait in line to get sponge wet in water. A child verbalized frustration when friends did not form a line and stated “one at a time”. Transition from inside to outside had fewer re-directions and prompts in comparison to transition from outside to inside. Week five day one, children listened to Ready Class Project engine book read by the teacher. The group participated in self-control song and followed instructions for speeds/song actions. As a large group we made stoplight and apple car snack seated at table. Children demonstrated self-control throughout the morning. Most participated in self-control song with appropriate actions and few verbal prompts. A few needed individual support to follow song directions or calm their body. All children demonstrated independence and good task management during cooking activity. Children waited for directions prior to starting activity, and children waited prior to eating their completed snack. All children enjoyed making stoplight creatively. A few children made appropriate “X” marks on the check-in chart. Most made plus sign-type marks or other shapes and are developing the “X” motion. Week five day two children listened to Pete the Cat and His Magic Glasses book. The large group art activity was to create their own magic glasses by gluing on lenses, decorating frames, and identifying how what they see makes them feel. Children needed some verbal prompts to remain quiet during reading. All demonstrated self-control when waiting for glasses activity to begin. Teachers liked having peers pass out materials to their friends. All demonstrated attention to step-by-step instructions. Some needed assistance with glue sticks and understanding how to apply glue for glasses lenses. A few children were independent with gluing their glasses. One child self-advocated for the materials she wanted. All needed demonstration of where to fold glasses. Some were independent in folding. Others needed physical assistance to fold functionally. All would benefit from more activities with precise gluing/folding. A few children were able to verbalize how the glasses made them feel or how they glasses affected their engine level. Week six day one, children took turns trying to match items pertaining to engines. One group was completed during choice time. Children attended to groups assessed on ability to follow directions, take turns, and problem solve. Some students were able to follow directions, other students needed several verbal/physical cues to follow directions. Some students were able to take turns, other students needed verbal cues to end turn and allow next person to begin. Most students were able to correct behaviors with verbal/physical cues, others were unable to keep playing game. Only one child was asked to leave due to they were unable to follow directions the entire game. Most students were engaged in the activity and able to answer questions pertaining to “How an engine runs”. In the future the group may benefit from multiple smaller groups, and certain children in each group. Some of the students were distracted by other students in the group causing interruptions in following directions and taking turns. Week six day two, children listened to The Ear Book, listened mindfully to sounds with eyes closed while waiting for triangle ding to signal moving to next square, circled calm sounds that they liked/disliked, and listened to various sounds and marked them on a bingo card. Children maintained attention during activity with long periods of sitting. Most colored in bingo squares for listening bingo independently. Some did not complete this part of activity. Most sat quietly and listened to music, talked about how it made them feel. Most felt the music made them happy/brought their engine back to the middle. All but three followed directions throughout entire activity and had to leave to manage feelings. Week seven day one, Children will take turns trying to match items pertaining to engines. This activity was completed during choice time. Children attending group assessed on ability to follow directions, take turns, and problem solve. One student able to follow directions through entire activity, including setting up game cards himself. One student required verbal cues to follow game directions. Both students able to ID connection between car/object colors and engine levels/feelings. Both students understood matching concept and match correctly. Choice time cut short due to child behaviors. Unable to assess more children in activity. Week seven day two, children listened to The Nose Book. They took turns smelling essential oils (lavender, lemon, grapefruit, cinnamon, breathe, mint) and marked those they do/don’t like on a charted piece of paper. The whole class makes scented play-doh seated at tables. Most students able to follow directions throughout both activities. A few needed some redirection from adults. Most developing skills at choosing which scents they like/don’t like and indicating it with coloring/circling. Many circled both like/dislike for scents. A few struggled with indicating their preferences either way. All children assisted in cleaning up playdoh activity and remained engaged throughout the longer than usual group duration. Week eight day one, children listened to The Hand Book, and Touch Song. They took turns touching different objects and trying different “fidgets” and marked those they do/don’t like, to discuss how touch can change how you feel. Majority of children struggled to follow directions and listen to teachers directions. Most displayed “high engine” behavior, including hyperactivity. Some children independently colored or circled their choices for objects they liked/disliked touching. Most needed prompting to make choices and keep up with coloring in/circling choices. All students required redirection and prompting during small group transitions. Week eight day two, children listen to “My Five Senses” book. They completed small group rotations consisting of activities with breathing/mouth including feather blowing, pinwheel and breathing strategies, and cottonball/straw maze. All children followed directions independently and waited patiently to take turns at each station. Most children participated in loosely structured small groups using appropriate behaviors. A few used straws and cotton ball maze supplies inappropriately while waiting their turn for the maze. Most enjoyed the activities and completed smooth transitions between groups. All glued picture of him/herself on driver’s license appropriately and with limited assistance needed from adults. One week after the eight week study a baseline assessment was completed on all children. The post assessment baseline took a few days long within a week due to children’s absences or early pick up. The assessment baseline shows an outstanding increase at 92% of the vocabulary words being used correctly to relate to the same pictures used at the beginning to assess at the end of the study. There was an increase of 37% within eight weeks, with consistent use of vocabulary, and the children being able to relate the vocabulary words with their own emotions, and then translating it to visuals. What made part of the study a success was the constant use of vocabulary, introducing each vocabulary word and implementing different strategies associated with that vocabulary word or emotion. Cause and Effect

The first first few weeks of the study were rocky due to the experiment being new to both myself and the students. The most challenging part was becoming familiar with the new routine of meeting in small groups twice a week. I encourage anyone who is doing a research study in a similar format, which was a lesson learned for myself is to make sure that I coordinate with my Supervisor in the future and readily have a set day(s) of the week in the event of any future plans that may take place, so that it will not affect the studies course. Another factor that could have impacted the study, in which I would keep alternating is how big the groups were each week. Some weeks I lead small groups and other weeks I lead one large group. I felt at the time and it was a decision made in the moment that switching up the setting and incorporating the activity into a large group went well. Some days I felt like some activities should have been broken up, that they were more intimate and other students could focus on the content rather than doing other things that disrupted the group setting. I am certain that this would have most definitely made a difference in the dynamic of the classroom. During the study, another implementation that could have a better outcome in the future is to have all involved in the small groups prepared for the lesson. At my facility, we worked in co-teaching rooms where there were two-three teacher accompanying the group of students. I obviously went into the groups every week prepared but other teachers commented that they felt the least prepared by not knowing what the small groups were going to consist of for that day. This was an easy fix that we could see visually having an impact in the small groups taking place. At the end of the study, there was not a transition to compliment the end of the eight weeks. So I myself being in the classroom when the study was no longer happening I noticed two to three weeks out, behaviors began to rise in the classroom. I realized that I should not have cut the study off at the eight week mark, and felt like it would have been beneficial to do a follow up with the students such as providing them a closure to the study or possibly implementing the vocabulary and strategies used into the classroom.

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