research paper about second language learning

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Factors influencing second language learning based on the research of Lightbown and Spada

Deep insights into the factors influencing second language learners can positively impact learners’ self-intervention and guide language teachers in selecting appropriate teaching materials and strategies. Drawing from Lightbown and Spada’s framework encompassing motivation, aptitude, personality, intelligence, and learner preferences, this paper examines the relationship between individual learners’ characteristics and second language learning effects across five aspects by dialectically considering the research methods suitable for different learner variables. By incorporating recent research and offering practical implications, this paper has the potential to contribute valuable insights to both researchers and practitioners in the field of language education.

1. Introduction

The dynamic and intricate nature of second language acquisition involves a complex interrelation between individual physiological and psychological traits and the resulting outcomes of language acquisition ( Alanen, 2003 ; Dörnyei, 2013 ; Dörnyei, 2014 ; Banaruee et al., 2023a , b ). Individuals’ anticipation of success in second language acquisition can be gauged to some extent by considering information on their personalities, specific intellectual abilities, motivation, or age ( Candlin and Mercer, 2001 ). Lightbown and Spada assert that these beliefs typically stem from anecdotal evidence, often derived from personal experiences. Therefore, the primary objective of their study is to examine the validation of anecdotal evidence through research findings. They listed 12 typical characteristics contributing to language learning and organized them into five categories: intelligence, aptitude, motivation, personality, and learner preferences ( Lightbown and Spada, 2000 ).

Lightbown and Spada acknowledge the intricate interplay of various factors influencing frustration in second language learners. Consequently, by amalgamating diverse scholars’ perspectives and research methodologies, they offer critical insights into the limitations and challenges inherent in studying the factors influencing second language acquisition. Based on their study, this review article amalgamates recent research advancements and provides recommendations to alleviate the concerns they highlighted to contribute valuable insights to both researchers and practitioners within the domain of language education.

2. Factors influencing second language learning

2.1. intelligence.

Relying on Genesee’s empirical data from 1976 regarding the connection between intelligence and language sub-skills, Lightbown and Spada suggested that intelligence, as assessed through verbal IQ tests, plays a significant role in learning tasks related to language analysis and rules, such as reading and grammar. However, when it comes to spoken language emphasizing communication and interaction, the impact of intelligence is less apparent ( Lightbown and Spada, 2000 ).

While the notion that intelligence factors significantly influence logical and rule-like language skills, such as reading and grammar is widely embraced within the academic community ( Jimenez et al., 2003 ; Maftoon and Sarem, 2012 ; Salehi and Sadighi, 2012 ), some scholars assert that the verbal IQ test employed by Lightbown and Spada possesses certain limitations ( Chowdhury, 2010 ; Kakhramonov, 2020 ). Consequently, these researchers utilize non-verbal intelligence tests to gauge participants’ IQ, arriving at conclusions akin to those by Lightbown and Spada. Furthermore, their investigations into how IQ factors impact language skills, such as reading and grammar, have substantially broadened the depth of the field. Nonetheless, the diverse range of intelligence criteria challenges traditional intelligence (IQ) tests in capturing the full complexity of intellect ( Ellis, 1994 ). Consequently, the research on the impact of intelligence on second language acquisition remains controversial. Some studies have also indicated that students without high IQ levels have succeeded in second-language learning ( Brown, 2014 ).

Given the intricate nature of intelligence and the potential drawbacks associated with traditional measures, Gardner’s “Multiple Intelligence Model” has garnered increasing attention from researchers. Departing from the conventional perspective that confines intelligence to cognitive abilities linked to verbal and numerical skills, Gardner expanded the concept to encompass linguistic, logical-mathematical, spatial, musical, bodily-kinesthetic, intrapersonal, interpersonal, and naturalistic intelligence ( Gardner, 2008 ). This multifaceted approach empowers students by recognizing diverse forms of intelligence to foster their confidence. As intelligence manifests in various ways, each individual possesses a unique combination of these intelligences, offering valuable insights into studying learner preferences.

2.2. Aptitude

The aptitude for second language (L2) learning is characterized by the strengths exhibited by individual learners in cognitive abilities pertinent to information processing during L2 acquisition. This encompasses their performance in diverse contexts and at different stages of the learning process, in comparison to the broader population ( Harley and Hart, 1997 ; Robinson, 2005 ). Drawing on the language learning experience of CJ, a boy with exceptional language talents in Au et al., (1989) case study, Lightbown and Spada suggested that learning quickly stands out as a distinctive characteristic of aptitude.

Within the framework of the Modern Language Ability Test (MLAT) and Pimel Language Ability Test (PLAR), the assessment criteria for language ability predominantly hinge on vocabulary retention and comprehension of grammatical rules. While this proficiency was validly assessed in the early stages of grammar translation or audiolingual methods, the shift toward communicative teaching methods has led educators and researchers to observe that the capacity to recognize and memorize new sounds may transition from an advantage to a limitation in meaning-oriented instruction ( Lightbown and Spada, 2000 ). In recent years, a growing number of scholars have undertaken a thorough examination of the relationship between aptitude and second language acquisition ( Skehan, 2012 ). Their discussions span various perspectives, investigating the content and characteristics of aptitude, along with its associations with factors like age, instructional methods, and other pivotal aspects of language learning, including the distinction between explicit and implicit knowledge ( Robinson, 2005 ; Doughty and Mackey, 2021 ; Li and Zhao, 2021 ). Among these factors, investigating age and learning ability has consistently been a focal point of empirical research in this field. Researchers such as Birgit Harley and Doug Hart observed a positive correlation between second language outcomes and memory in early immersion second language acquisition, particularly in first-grade students. For late (adolescent) second language outcomes, they noted a positive correlation with the analytical dimension of language ability ( Harley and Hart, 1997 ). ShaoFeng Li’s research revealed that high school students were more prone to draw on aptitude than university students. Additionally, aptitude correlated more strongly with explicit treatments than implicit treatments in the language learning context ( Li and Zhao, 2021 ). These empirical studies build upon Lightbown and Spada’s earlier hypothesis, suggesting that language ability, as assessed by traditional aptitude tests, comprises a set of cognitive abilities that play a more prominent role in the initial stages of second language development and conscious learning conditions ( Candlin and Mercer, 2001 ; Li and Zhao, 2021 ).

Nevertheless, ongoing debates persist in the realm of competence and second language acquisition. Key points of contention include whether aptitude represents the “upper limit” of language learning and whether the components of aptitude play distinct roles in various learning stages of second language learners, such as the beginning and proficiency stage. These unresolved issues warrant further research and exploration ( Kakhramonov, 2020 ; Doughty and Mackey, 2021 ).

2.3. Motivation

Motivation for second language learning is a multifaceted phenomenon that defined by two key factors: learners’ communicative needs and attitudes toward the second language community. Lightbown and Spada argued that an individual’s identity and social dynamics, including power relationships, significantly influence language motivation. Both children and adults are sensitive to these social dynamics and power relationships, which can impact their motivation in the language-learning process ( Lightbown and Spada, 2000 ). Lightbown and Spada’s perspectives are influenced by social cognitive theory, where motivation has consistently played a prominent role from early modeling studies to its contemporary conceptualization involving agencies. Within the profound integration of second language acquisition and social cognitive theory, various theoretical frameworks for second language learner motivation have emerged, including attribution theory ( Weiner, 1972 ), self-efficacy theory ( Bandura, 1977 ), the L2 motivation self-system ( Dörnyei and Taguchi, 2009 ), and self-determination theory ( McEown and Oga-Baldwin, 2019 ).

Lightbown and Spada made another significant contribution by integrating theories from educational psychology into the realm of second language acquisition. They examined the interplay between teachers’ classroom instruction and motivation in the second language classroom, proposing that teachers should diversify activities, tasks, and materials. This approach involves the adoption of teaching strategies like cooperative and non-competitive goals to enhance students’ motivation for learning ( Lightbown and Spada, 2000 ). However, Lightbown and Spada’s research primarily concentrated on the impact of external factors, such as the social environment and teachers. The self-model of second language acquisition still needs to be explored in their work. Dörnyei’s latest study specifically addresses this question, delving into the self-model and its role in second language acquisition motivation ( Dörnyei, 2013 ). By refining and expanding the psychological theory of motivation, he introduced a groundbreaking conceptual framework called the bilingual motivational self-system. This model utilizes a process-oriented approach to scrutinize the various stages of motivation. Notably, the new motivational model displays an apparent inclination toward personality psychology, representing a shift in perspective on the nature of motivation from external behaviors to internal cores ( Dörnyei and Ushioda, 2009 ; Dörnyei, 2014 ). Furthermore, the model successfully addresses the challenge posed by the absence of a language community in society and offers a fresh perspective on studying motivation. It serves as a framework that can delineate both the starting and ending points of motivational behavior by referencing both authentic and possible selves ( Dörnyei, 2020 ). Concerning motivation assessment, Gardner and Lambert introduced the synthesis dimension and tool dimension, developing a motivation assessment tool named the Attitude/Motivation Test Battery (AMTB). This tool has profoundly influenced on subsequent research in the field ( Gardner, 2008 ).

2.4. Personality

While some linguists and psychologists argue that personality plays a significant role in the success of second language acquisition, identifying and measuring personality remains challenging ( Lalonde and Gardner, 1984 ; Robinson et al., 1994 ; Novikova et al., 2020 ). Personality is often intertwined with other factors influencing second language acquisition, complicating the determination of its specific impact. Lightbown and Spada highlighted two primary challenges in personality research affecting progress. Firstly, there needs to be more consensus on the relationship between personality and language success. Some studies suggest that individuals with an extroverted personality may be more likely to succeed due to the self-confidence and adventurous spirit required. At the same time, other research indicates that many successful language learners do not necessarily exhibit high levels of extroversion. Secondly, the measurement and evaluation criteria for language learning success need to be more consistent. In the realm of language acquisition, researchers delving into communicative competence may wield criteria that differ from those who focus on grammatical accuracy or metalinguistic knowledge, and this variance in measurement standards can potentially engender confusion when assessing success in language acquisition ( Lightbown and Spada, 2000 ).

Advancements in modern medicine and neurolinguistics have begun to shed light on the challenges previously encountered in understanding the role of personality in second language acquisition. Researchers such as Grzegorz Dogil and Susanne Maria Reiterer employed functional magnetic resonance imaging to observe differences in brain activity among individuals with varying linguistic abilities during phonological tasks, including phonological differential perception, imitation, and reading ( Dogil and Reiterer, 2009 ). David Robinson and Norman Gabriel utilized the Eysenck Personality Questionnaire (EPQ) to investigate the connection between personality traits and language learning abilities. Their findings indicated that individuals with high neuroticism and high extraversion scores tended to perform better on oral tests than on written tests. In contrast, those with high neuroticism and low extraversion scores showed better performance on written tests than on verbal tests ( Robinson, et al., 1994 ). While results from these studies may still vary, the interdisciplinary research perspectives undeniably offer more possibilities for addressing the complexities of these issues.

2.5. Learner preferences and styles

Individuals demonstrate a range of learning preferences and styles, advancing at different rates owing to inherent biological and psychological distinctions ( Reiff, 1992 ). Based on learners’ learning characteristics in a specific domain, Lightbown and Spada categorized them as “visual,” “aural,” “and “kinaesthetic” ( Lightbown and Spada, 2000 ). Because learning styles are multidimensional, researchers have devised various instruments to assess and measure these diverse learner preferences ( Dunn and Dunn, 1972 ; Schmeck et al., 1977 ). Among these instruments, field independence (FI)/field dependence (FD), which relates to how individuals perceive and memorize information ( Kheirzadeh and Kassaian, 2011 ), has been the subject of extensive investigation. Furthermore, an increasing number of researchers have focused on studying the alignment of learner styles with teaching styles and learning strategies ( Ehrman and Oxford, 1990 ). Aligning students’ learning styles with appropriate teaching approaches can significantly enhance their motivation, performance, and achievements ( Brown, 1973 ). Another noteworthy observation is that adult second language learners frequently articulate their learning beliefs more explicitly than their learning styles ( Gregorc, 1979 ). The acknowledged mediating role of learner beliefs in the classroom further underscores their significance. Additionally, when these beliefs (or metacognitive knowledge) act as mediators, they possess the capacity to influence both learners and teachers, shaping their behavior ( Alanen, 2003 ; Banaruee et al., 2022 ).

As observed by Lightbown and Spada, investigations into learner beliefs have traditionally leaned heavily on quantitative and descriptive research methods. Nevertheless, a discernible shift emerged in the 2000s, witnessing a pronounced inclination towards a qualitative approach. Researchers during this period exhibited a proclivity for embracing a contextual perspective in their exploration of learner beliefs ( Barcelos and Kalaja, 2011 ). Situated within the socio-cultural framework, some scholars meticulously investigate the intricate mechanisms and trajectories that characterize the transformation between learners and their educational milieu ( Negueruela-Azarola, 2011 ). Findings underscore that educators wield substantial influence in enhancing students’ adaptability to second language acquisition through the judicious deployment of varied pedagogical strategies and the establishment of an optimal learning environment ( Reiff, 1992 ; Sims and Sims, 1995 ; Peng, 2011 ).

2.6. Other factors

In contrast to the intricate task of defining and measuring various factors that impact second language acquisition, the role of age as an explanatory factor for differences in second language acquisition benefits from more accessible definitions and measurement methods. Since the introduction of Lenneberg’s Critical Period Hypothesis (CPH) for first language (L1) acquisition in 1967, numerous researchers have delved into investigating the impact of age factors on various language groups and language skills ( Patkowski 2013 ; Muñoz, 2014 ). There has been a prevalent assumption that young children predominantly depend on memory-based processes, while adults are more notably characterized by rule-based learning ( Nikolov and Djigunović, 2006 ). The reduction in procedural memory for language compels adults learning a second language to depend on explicit learning, leading to the engagement of a cognitive system distinct from the one supporting their native language ( Paradis, 2004 ). Nevertheless, the adverse impacts of phonological difficulties stemming from missed critical periods and diminished memory in adult learners may not be decisive factors for success in second language acquisition. Learners’ motivation to acquire a second foreign language and their aspiration to integrate into the social life of the target language can mitigate the negative effects associated with age ( Widyaningsih et al., 2022 ). Some recent studies are introducing innovative approaches to interindividual variation from a neurocognitive perspective. Their research delves into the intricate relationship between the cognitive levels of second language learners and their age as well as second language proficiency ( Faretta-Stutenberg, 2023 ; Fromont, 2023 ).

Lightbown and Spada’s study neglected to account for the impact of culture on second language acquisition. Language is not merely a product of culture, it also serves as a symbol of culture, which establishes an intrinsic connection between language and literature ( Gleason, 1955 ). In the design of language courses, it is crucial for teachers to consider cultural diversity, employ suitable teaching strategies, and harness the enriching tension arising from cultural differences to enhance language learning ( Tseng, 2002 ; Kuo and Lai, 2006 ). Currently, there is a growing emphasis on investigating the impact of the socio-cultural background of both teachers and learners on the language learning process. Enhancing the cultural awareness of language learners and educators has emerged as a crucial focal point in contemporary research ( Banaruee et al., 2023a , b ).

The findings indicate that when learners actively engage with the culture associated with the language they are acquiring, it significantly enhances their academic performance and fosters a more profound understanding of the language ( Arabski and Wojtaszek, 2011 ; Pourkalhor and Esfandiari, 2017 ).

3. Implications and suggestions for further research

Despite certain limitations inherent in Lightbown and Spada’s study on the factors influencing second language acquisition, I contend that it retains its illuminating value for contemporary research, particularly in the following three facets. Initially, Lightbown and Spada astutely observed that certain researchers were oblivious to distinctions in various behavioral characteristics. They employed identical labels to depict dissimilar behavioral traits or haphazardly scrutinized factors that could not be directly observed and measured through questionnaires ( Lightbown and Spada, 2000 ). They exemplified this issue with motivational studies with the aim of cautioning researchers about potential pitfalls in subsequent investigations. According to them, deducing the relationship between individual characteristics and language learning from a questionnaire or a single variable is challenging. Firstly, learner variables interact in intricate ways, and certain traits, like motivation and extraversion, are interdependent and intricate. This makes direct observation and measurement challenging. Secondly, individual elements exert distinct effects and responses to specific aspects of language skills. For instance, highly motivated learners excel in informal situations but may lag behind in meta-linguistic knowledge. Furthermore, the relationship between learners’ characteristics and language learning outcomes does not always imply a causal connection. Considering high motivation levels contributing to a successful language learner, a concept supported by Gardner and Lambert who argued that elevated motivation in a formal learning environment could predict a learner’s effectiveness ( Gardner et al., 1989 ). Nonetheless, ascribing an individual’s success in language acquisition exclusively to motivation may be precipitous, given the potential oversight of other contributory factors ( Li and Wang, 2018 ). Lightbown and Spada conduct a thoughtful and dialectical analysis of individual learner characteristics and their influence on the effectiveness of second language learning. They emphasize the nuanced understanding that learner variables interact in complex ways, presenting a comparative analysis of issues in existing research. This provides valuable insights for future investigations.

Secondly, Lightbown and Spada highlight distinctions between factors influencing the effectiveness of second language acquisition, such as intelligence and motivation, and various language skills, such as reading ability and oral communication proficiency. They challenge the unidimensional claim that success in one language skill defines overall success in second language acquisition. This stance, they argue, can yield perplexing and even contradictory research results. For instance, in an informal language learning setting, motivated learners might excel if aptitude tests focus on measuring oral communication skills. However, in other studies, highly motivated learners may not exhibit greater success if the test primarily assesses language knowledge. Lightbown and Spada’s research have paved the way for empirical studies investigating the correlation between diverse influencing factors and various language skills.

Finally, Lightbown and Spada adopt an interdisciplinary perspective, providing a comprehensive review and critical reflection on various factors and research methods influencing second language acquisition. Their research not only offers valuable insights to expand the study of factors influencing second language acquisition but also highlights certain bottlenecks and challenges within this field. Nevertheless, the challenges raised by Lightbown and Spada have found innovative solutions through the integration of current developments in other disciplines. For example, in the realm of motivation, Dörnyei draws on concepts from personality psychology and social psychology to reexamine integrative motivation, introducing a new conceptual framework—the bilingual motivational self-system ( Dörnyei, 2013 , 2014 ). By amalgamating Lightbown and Spada’s research with advancements by other scholars on pertinent issues, this study not only delves into the highlights and obstacles in their work but also provides insights for interpreting these challenges and bottlenecks from an interdisciplinary perspective.

Author contributions

CQ: Writing – original draft.

Funding Statement

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The study was supported by the Education Science Project of the Hubei Academy of Education Science, under grant No. 2021GA074 and No. 2019GA057.

Conflict of interest

The author declares 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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Second Language Research is an international peer-reviewed, quarterly journal, publishing original theory-driven research concerned with second (and additional) language acquisition and second language performance. This includes both experimental studies and contributions aimed at exploring conceptual issues. In addition to providing a forum for investigators in the field of non-native language learning, it seeks to promote interdisciplinary research which links acquisition studies to related non-applied fields such as neurolinguistics, psycholinguistics, theoretical linguistics, bilingualism, and first language developmental psycholinguistics.

Note that studies of foreign language teaching and learning are outside the scope of Second Language Research , unless they make a substantial contribution to understanding the process and nature of second language acquisition. Types of publications include full-length research articles (about 9,000 words), research notes (about 4,000 words), review articles of recent books or timely topics (about 5,000 words), discussion and commentary (about 5,000 words), invited keynote articles (about 11,000 words) and guest-edited, thematic issues.

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Second Language Research is available to browse on SAGE Journals Online.

“ Second Language Research is a central resource in the field, especially for cutting-edge work on linguistic and cognitive issues in SLA. It is clearly among our first-tier journals.” Professor Michael Long University of Maryland, USA

Second Language Research publishes theoretical papers, original research and review articles on simultaneous or consecutive second and additional language acquisition in children and adults. In addition to providing a forum for investigators in the field of non-native language learning, the journal seeks to promote interdisciplinary research which links second language acquisition studies to related non-applied fields such as:

* Theoretical linguistics focused on second and additional language acquisition * Neuroscience and cognitive science * First language developmental psycholinguistics * Heritage language studies * Psycholinguistics.

The journal does not publish papers that focus on educational and pedagogical issues in language teaching and language testing.

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Manuscript Submission Guidelines: Second Language Research

This Journal is a member of the Committee on Publication Ethics

Please read the guidelines below then visit the Journal’s submission site http://mc.manuscriptcentral.com/SLR to upload your manuscript. Please note that manuscripts not conforming to these guidelines may be returned.

Only manuscripts of sufficient quality that meet the aims and scope of Second Language Research will be reviewed. The editorial team is proud that in 2020, the average time to first decision was  31 days  and the average time to a final decision was  48 days .

There are no fees payable to submit or publish in this Journal. Open Access options are available - see section 3.3 below.

As part of the submission process you will be required to warrant that you are submitting your original work, that you have the rights in the work, that you are submitting the work for first publication in the Journal and that it is not being considered for publication elsewhere and has not already been published elsewhere, and that you have obtained and can supply all necessary permissions for the reproduction of any copyright works not owned by you.

Please see our guidelines on prior publication and note that Second Language Research  may accept submissions of papers that have been posted on pre-print servers; please alert the Editorial Office when submitting (contact details are at the end of these guidelines) and include the DOI for the preprint in the designated field in the manuscript submission system. Authors should not post an updated version of their paper on the preprint server while it is being peer reviewed for possible publication in the journal. If the article is accepted for publication, the author may re-use their work according to the journal's author archiving policy.

If your paper is accepted, you must include a link on your preprint to the final version of your paper.

• What do we publish? 1.1 Aims & Scope 1.2 Article types 1.3 Writing your paper
• Editorial policies 2.1 Peer review policy 2.2 Authorship 2.3 Acknowledgements 2.4 Funding 2.5 Declaration of conflicting interests
• Publishing policies 3.1 Publication ethics 3.2 Contributor's publishing agreement 3.3 Open access and author archiving
• Preparing your manuscript 4.1 Formatting 4.2 Artwork, figures and other graphics 4.3 Supplementary material 4.4 Reference style 4.5 English language editing services 4.6 Statistical Guidelines
• Submitting your manuscript 5.1 ORCID 5.2 Information required for completing your submission 5.3 Permissions
• On acceptance and publication 6.1 Sage Production 6.2 Online First publication 6.3 Access to your published article 6.4 Promoting your article
• Further information

1. What do we publish?

1.1 Aims & Scope

Before submitting your manuscript to Second Language Research , please ensure you have read the  Aims & Scope .

1.2 Article Types

The Journal considers the following kinds of articles for publication. Any submission that does not respect the word limit will be sent back to the author without review. Please note that the manuscript length described below includes only the main body of the text, footnotes and all citations within it. The manuscript length does not include abstract, section titles, figure and table captions, funding statements, acknowledgments and references in the bibliography. 

  (a) Full Articles   (9,000 words) 

Full research reports must include original experimental findings related to an area of relevance to second language acquisition research and theory. Authors must clearly state their hypotheses or research questions and the results must include a quantitative presentation of the data. Research reports must make an important contribution to the field of Second Language Research and demonstrate rigorous methodology and statistical analysis of the results. We do not discourage contributions that present null results if the authors clearly state the hypothesis tested and the meaning and relevance of the null results themselves.  

All research reports must include an introduction (brief and focused), methods, discussion and conclusions. The conclusion must address the broader implications of the results and clearly state how the study contributed to the field of SLA.

(b) Research Notes  (4,000 words) 

Research notes are short reports and discussion papers of interest to the Second Language Research community. Research notes also include original research and follow the same outline as above but should be highly focused on one specific question related to SLA. Research notes may include replications of previously published studies.

(c) Review Articles   (5,000 words) 

Review articles that provide a synthesis in areas covered by the journal, or which assess methods, professional resources (including publications), or conceptual advances in the field. Normally, review articles are broader in focus than research notes and do not include original research.

All books for the review articles section should be sent to the review editor:

Margaret Thomas  Program in Linguistics  Lyons Hall  Boston College  Chestnut hill, MA 02467  USA

E-mail:  [email protected]    

(d) Keynote Articles   with commentaries (11,000 words)

Keynote articles are normally commissioned by the Editors. They present a relevant new theory or model, or address a specific topic that is being currently debated in the field and take a clear position on one side of the debate. The goal of a keynote article is to present the issues most relevant to the topic, take a particular perspective on this topic and situate it in the broader field of SLA. Once a keynote is submitted, other experts on the topic will be invited to comment on the keynote article from their particular perspective.

(e) Discussion and Commentary    (5, 000 words)  

Discussion and commentary are short articles addressing questions and concerns of a theoretical nature. Their goal is to initiate a conversation on a particular burning issue related to second language acquisition and encourage exchange of ideas, opinions and perspectives on that issue among researchers in the field.

(f) Registered Reports

Registered Reports are submissions that go through a two-phase review process. In Stage 1, the methods and proposed analyses are reviewed before data are collected and the study is pre-registered. In Stage 2, reviewers consider the full study, including results and interpretation. This format of article seeks to avoid a variety of inappropriate research practices, including inadequate statistical power, selective reporting of results, and publication bias, but still offers the flexibility to conduct subsequent exploratory (unregistered) analyses.

Starting in 2021, Second Language Research accepts Registered Report submissions. Detailed instructions for this format are available here and on the journal’s submission site, with instructions for authors and instructions for reviewers. Those can also be obtained by email from the editorial office.

Note that Registered Reports are different from preprints. A preprint is an online only, pre-peer reviewed version of a manuscript that is made openly available on a preprint server. They are not peer reviewed, and a preprint is not considered to be published, although they are often assigned DOIs. Preprints provide a unique benefit to the research community by allowing authors to rapidly disseminate their research before their papers are peer reviewed and published. They also allow researchers to work on their paper with the input of others in the research community before it is submitted for journal publication. However, they do not guarantee publication of the article. Since June 2018, SLR collects the DOIs for any preprint versions of the published articles to link a preprint version of an article to the final published version, providing increased transparency for readers.

1.3 Writing your paper

The Sage Author Gateway has some general advice and on  how to get published , plus links to further resources. Sage Author Services also offers authors a variety of ways to improve and enhance their article including English language editing, plagiarism detection, and video abstract and infographic preparation.

1.3.1 Make your article discoverable

When writing up your paper, think about how you can make it discoverable. The title, keywords and abstract are key to ensuring readers find your article through search engines such as Google. For information and guidance on how best to title your article, write your abstract and select your keywords, have a look at this page on the Gateway: How to Help Readers Find Your Article Online

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2. Editorial policies

2.1 Peer review policy

Each submission is subject to an in-house evaluation process and once this is completed, the article is either determined unsuitable for publication in SLR or sent for external review. This process of initial editorial evaluation may take up to two weeks. Once this review has been conducted, the manuscript is either returned to the author or assigned to an acting editor who sends it out to reviewers. 

The Editors of  Second Language Research  typically ask for 3 independent reviews of submissions they judge to be potentially publishable. Guidelines for  reviewers  can be found  here .

Submissions must be submitted in a format that will allow double-blind reviewing of the manuscript. 

• The author's name(s) should not be included in headers or footers or in any part of the file (such as in 'Properties') which can reveal her/his/their identity. All funding sources should also be anonymized if they can be used to identify the author(s).
• Any references to previous work by the same author within the text or in the references themselves should use the formant ‘Author XXX’.

2.2 Authorship

All parties who have made a substantive contribution to the article should be listed as authors. Principal authorship, authorship order, and other publication credits should be based on the relative scientific or professional contributions of the individuals involved, regardless of their status. A student is usually listed as principal author on any multiple-authored publication that substantially derives from the student’s dissertation or thesis.

Please note that AI chatbots, for example ChatGPT, should not be listed as authors. For more information see the policy on Use of ChatGPT and generative AI tools .

2.3 Acknowledgements

All contributors who do not meet the criteria for authorship should be listed in an Acknowledgements section. Examples of those who might be acknowledged include a person who provided purely technical help, or a department chair who provided only general support.

Please supply any personal acknowledgements separately to the main text to facilitate anonymous peer review.

2.3.1 Third party submissions

Where an individual who is not listed as an author submits a manuscript on behalf of the author(s), a statement must be included in the Acknowledgements section of the manuscript and in the accompanying cover letter. The statements must:

• Disclose this type of editorial assistance – including the individual’s name, company and level of input
• Identify any entities that paid for this assistance
• Confirm that the listed authors have authorized the submission of their manuscript via third party and approved any statements or declarations, e.g. conflicting interests, funding, etc.

Where appropriate, Sage reserves the right to deny consideration to manuscripts submitted by a third party rather than by the authors themselves .

2.3.2 Writing assistance

Individuals who provided writing assistance, e.g. from a specialist communications company, do not qualify as authors and so should be included in the Acknowledgements section. Authors must disclose any writing assistance – including the individual’s name, company and level of input – and identify the entity that paid for this assistance. It is not necessary to disclose use of language polishing services.

2.4 Funding

Second Language Research requires all authors to acknowledge their funding in a consistent fashion under a separate heading.  Please visit the Funding Acknowledgements page on the Sage Journal Author Gateway to confirm the format of the acknowledgment text in the event of funding, or state that: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. 

2.5 Declaration of conflicting interests

Second Language Research encourages authors to include a declaration of any conflicting interests and recommends you review the good practice guidelines on the Sage Journal Author Gateway

3. Publishing Policies

3.1 Publication ethics

Sage is committed to upholding the integrity of the academic record. We encourage authors to refer to the Committee on Publication Ethics’ International Standards for Authors and view the Publication Ethics page on the Sage Author Gateway

3.1.1 Plagiarism

Second Language Research and Sage take issues of copyright infringement, plagiarism or other breaches of best practice in publication very seriously. We seek to protect the rights of our authors and we always investigate claims of plagiarism or misuse of published articles. Equally, we seek to protect the reputation of the journal against malpractice. Submitted articles may be checked with duplication-checking software. Where an article, for example, is found to have plagiarised other work or included third-party copyright material without permission or with insufficient acknowledgement, or where the authorship of the article is contested, we reserve the right to take action including, but not limited to: publishing an erratum or corrigendum (correction); retracting the article; taking up the matter with the head of department or dean of the author's institution and/or relevant academic bodies or societies; or taking appropriate legal action.

3.1.2 Prior publication

If material has been previously published it is not generally acceptable for publication in a Sage journal. However, there are certain circumstances where previously published material can be considered for publication. Please refer to the guidance on the Sage Author Gateway or if in doubt, contact the Editor at the address given below.

3.2 Contributor's publishing agreement

Before publication, Sage requires the author as the rights holder to sign a Journal Contributor’s Publishing Agreement. Sage’s Journal Contributor’s Publishing Agreement is an exclusive licence agreement which means that the author retains copyright in the work but grants Sage the sole and exclusive right and licence to publish for the full legal term of copyright. Exceptions may exist where an assignment of copyright is required or preferred by a proprietor other than Sage. In this case copyright in the work will be assigned from the author to the society. For more information please visit the Sage Author Gateway

3.3 Open access and author archiving

Second Language Research offers optional open access publishing via the Sage Choice programme and Open Access agreements, where authors can publish open access either discounted or free of charge depending on the agreement with Sage. Find out if your institution is participating by visiting Open Access Agreements at Sage . For more information on Open Access publishing options at Sage please visit Sage Open Access . For information on funding body compliance, and depositing your article in repositories, please visit Sage’s Author Archiving and Re-Use Guidelines and Publishing Policies .

4. Preparing your manuscript for submission

4.1 Formatting

The preferred format for your manuscript is Word. Templates are available on the Manuscript Submission Guidelines page of our Author Gateway.

4.2 Artwork, figures and other graphics

For guidance on the preparation of illustrations, pictures and graphs in electronic format, please visit Sage’s Manuscript Submission Guidelines   

Figures supplied in colour will appear in colour online regardless of whether or not these illustrations are reproduced in colour in the printed version. For specifically requested colour reproduction in print, you will receive information regarding the costs from Sage after receipt of your accepted article.

4.3 Supplementary material

Second Language Research  does not currently accept supplemental files.

4.4 Reference style

Second Language Research adheres to the Sage Harvard reference style. View the Sage Harvard guidelines to ensure your manuscript conforms to this reference style.

If you use EndNote to manage references, you can download the Sage Harvard EndNote output file

4.5 English language editing services

Authors seeking assistance with English language editing, translation, or figure and manuscript formatting to fit the journal’s specifications should consider using Sage Language Services. Visit Sage Language Services on our Journal Author Gateway for further information.

4.6 Statistical Guidelines

Authors should follow the general guidelines for statistical analysis and representation of statistical results as outlined here .

5. Submitting your manuscript

Second Language Research is hosted on Sage Track, a web based online submission and peer review system powered by ScholarOne™ Manuscripts. Visit http://mc.manuscriptcentral.com/SLR  to login and submit your article online.

Manuscripts should have a separate title page with the author's name, full postal address and email address. The first page of the text should carry the title of the article without the name of the author (see also section on Anonymity above). Each article must be accompanied by an abstract of about 200 words.

If you are a new user, you will first need to create an account. Submissions should be made by logging in and selecting the ‘Author Center’ and the 'Click here to Submit a New Manuscript' option. Follow the instructions on each page, clicking the 'Next' button on each screen to save your work and advance to the next screen. If at any stage you have any questions or require the user guide, please use the ‘Online Help’ button at the top right of every screen.

IMPORTANT: Please check whether you already have an account in the system before trying to create a new one. If you have reviewed or authored for the journal in the past year it is likely that you will have had an account created. For further guidance on submitting your manuscript online please visit ScholarOne Online Help .

As part of our commitment to ensuring an ethical, transparent and fair peer review process Sage is a supporting member of ORCID , the Open Researcher and Contributor ID. ORCID provides a persistent digital identifier that distinguishes researchers from every other researcher and, through integration in key research workflows such as manuscript and grant submission, supports automated linkages between researchers and their professional activities ensuring that their work is recognised.

The collection of ORCID IDs from corresponding authors is now part of the submission process of this journal. If you already have an ORCID ID you will be asked to associate that to your submission during the online submission process. We also strongly encourage all co-authors to link their ORCID ID to their accounts in our online peer review platforms. It takes seconds to do: click the link when prompted, sign into your ORCID account and our systems are automatically updated. Your ORCID ID will become part of your accepted publication’s metadata, making your work attributable to you and only you. Your ORCID ID is published with your article so that fellow researchers reading your work can link to your ORCID profile and from there link to your other publications.

If you do not already have an ORCID ID please follow this link to create one or visit our ORCID homepage to learn more.

5.2 Information required for completing your submission

You will be asked to provide contact details and academic affiliations for all co-authors via the submission system and identify who is to be the corresponding author. These details must match what appears on your manuscript. At this stage please ensure you have included all the required statements and declarations and uploaded any additional supplementary files (including reporting guidelines where relevant).

5.3 Permissions

Please also ensure that you have obtained any necessary permission from copyright holders for reproducing any illustrations, tables, figures or lengthy quotations previously published elsewhere. For further information including guidance on fair dealing for criticism and review, please see the Copyright and Permissions page on the Sage Author Gateway

6. On acceptance and publication

6.1 Sage Production

Your Sage Production Editor will keep you informed as to your article’s progress throughout the production process. Proofs will be sent by PDF to the corresponding author and should be returned promptly.  Authors are reminded to check their proofs carefully to confirm that all author information, including names, affiliations, sequence and contact details are correct, and that Funding and Conflict of Interest statements, if any, are accurate.

6.2 Online First publication

Online First allows final articles (completed and approved articles awaiting assignment to a future issue) to be published online prior to their inclusion in a journal issue, which significantly reduces the lead time between submission and publication. Visit the Sage Journals help page for more details, including how to cite Online First articles.

6.3 Access to your published article

Sage provides authors with online access to their final article.

6.4 Promoting your article

Publication is not the end of the process! You can help disseminate your paper and ensure it is as widely read and cited as possible. The Sage Author Gateway has numerous resources to help you promote your work. Visit the Promote Your Article page on the Gateway for tips and advice.

7. Further information

Any correspondence, queries or additional requests for information on the manuscript submission process should be sent to the Second Language Research editorial office as follows:

Silvina Montrul  University of Illinois at Urbana-Champaign Department of Spanish, Italian & Portuguese 4080 Foreign Languages Building, MC-176 707 S. Mathews Ave Urbana, IL 61801 USA

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• Studies in Second Language Acquisition

Studies in Second Language Acquisition

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• Contains open access

• ISSN: 0272-2631 (Print) , 1470-1545 (Online)
• Editor: Luke Plonsky Northern Arizona University, USA
• Editorial board

Albert Valdman Award 2023

We are pleased to announce that the winner of the Albert Valdman Award for outstanding publication in 2023 is:

"Text reading in English as a second language: Evidence from the Multilingual Eye-Movements Corpus" by Victor Kuperman, Noam Siegelman, Sascha Schroeder , Cengiz Acartürk , Svetlana Alexeeva , Simona Amenta, Raymond Bertram, Rolando Bonandrini, Marc Brysbaert, Daria Chernova, Sara Maria Da Fonseca, Nicolas Dirix, Wouter Duyck, Argyro Fella, Ram Frost, Carolina A. Gattei, Areti Kalaitzi, Kaidi Lõo, Marco Marelli, Kelly Nisbet , Timothy C. Papadopoulos, Athanassios Protopapas, Satu Savo, Diego E. Shalom, Natalia Slioussar, Roni Stein, Longjiao Sui, Analí Taboh, Veronica Tønnesen and Kerem Alp Usal

Please join us in congratulating these authors on their contribution to the journal and to the field.

A note from this year’s winners:

We would like to express our gratitude to the review board of SSLA for selecting our article (“Text reading in English as a second language: Evidence from the Multilingual Eye-Movements Corpus,” March 2023) for this year’s Albert Valdman award for outstanding publication. This recognition illustrates that multi-lab research projects like ours – inspired by tenets of Open Science and fueled by the partners’ good-will and generosity – are feasible, even in the absence of centralized funding or formal agreements. This article presents the new corpus of L1 and L2 text reading in English, including eye-tracking and reading comprehension data, as well as performance in the tests of component skills of English proficiency and detailed language background and use information. The reliable data from university students representing 12 countries and L1 backgrounds (N=543) makes possible the large-scale comparison of L1 and advanced L2 readers of English. Specifically, we found that an achievement of an L1-like level of reading comprehension is more common than reaching an L1 level of reading fluency. We also observed that L2 comprehension relies on a different set of skills and abilities than L2 fluency: the former has a particularly strong demand for language skills in L2, and the latter is dominated by L1 fluency. The MECO data source is available for mining and in-depth research in second language reading, and we plan to continue this exciting collaboration with new samples and partners joining the project.

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FREQUENCY EFFECTS IN LANGUAGE PROCESSING: A Review with Implications for Theories of Implicit and Explicit Language Acquisition

• Nick C. Ellis
• Studies in Second Language Acquisition , Volume 24 , Issue 2

ORIGINAL RESEARCH article

The effect of language learning strategies on proficiency, attitudes and school achievement.

• Institute of Education, University of Szeged, Szeged, Hungary

This study examines language learning strategy (LLS) use in connexion with foreign language attitude, proficiency and general school achievement among lower secondary students in Years 5 and 8 ( n = 868) in Hungary. An adapted version of the Strategies Inventory for Language Learning questionnaire was used for data collection. The results showed that Hungarian students mainly engage in metacognitive strategies in both years. Differences between more and less proficient language learners’ strategy use have also been found. With regard to the effect of LLS on foreign language attitude, the foreign language mark and school achievement, path analysis indicated a good fit in both years. The metacognitive, social and memory strategies primarily influenced foreign language attitudes and marks in Year 5. The metacognitive strategies had a slight impact on school achievement as well as on foreign language marks. We demonstrated the dominant effect of metacognitive strategies and the low effect of memory strategies in Year 8. In addition, metacognitive strategies also influenced foreign language marks. The effect of foreign language marks on school achievement was also remarkable. There was a strong impact on the children’s attitudes through these variables.

Introduction

In recent decades, a number of studies have focused on foreign language learning, with the emphasis often having been placed on language learning strategies (LLS; Wong and Nunan, 2011 ; Oxford, 2016 ). Several studies have confirmed that these strategies aid students in becoming more effective learners inside the classroom and foster more efficient development of students’ mastery of the target language after leaving school ( Wong and Nunan, 2011 ). However, less is known about the structure and relationship between LLS, foreign language attitude, the foreign language mark and general school achievement (GA). Recent studies have mainly dealt with LLS among university students and upper secondary students, with only a few investigations having been conducted among lower secondary students. In the present study, we aim to examine young Hungarian students’ LLS use and its connexion to foreign language attitude, the foreign language mark and school achievement at the beginning and end of lower secondary school. We believe that it adds value to the article that we have investigated a young age group, as the beginning period of language learning can establish the success of the entire process. Another advantage of our research is that we analysed the whole language learning process in connexion with several other factors to represent the complexity of the language learning process.

Theoretical Background

Studies on LLS in recent decades have identified a large number of strategies which are employed by English as a foreign/second language (EFL/ESL) learners and several strategy categorisation patterns have also been established. The most frequently used taxonomy was developed by Oxford (1990) . She identified three direct and three indirect strategy types. Direct strategies are specific means of language use: memory, cognitive and compensatory (or compensation) strategies. Indirect strategies, such as metacognitive, affective and social strategies, support LLS indirectly. Recently, Oxford revisited her strategy categories and developed a model with four different strategy categories: cognitive, affective and sociocultural-interactive as well as a master category of “metastrategies.” Metastrategies comprise metacognitive, meta-affective and meta-sociocultural-interactive strategies ( Griffith and Oxford, 2014 ; Oxford, 2016 ). However, she did not elaborate on this strategy classification, and thus our study relied on her original taxonomy.

Various studies have focused on LLS use and aimed to identify the strategies most frequently employed by language learners ( Chamot, 2004 ; Magogwe and Oliver, 2007 ; Wu, 2008 ; Chen, 2009 ; Al-Qahtani, 2013 ; Charoento, 2016 ; Alhaysony, 2017 ; Dawadi, 2017 ). Overall, it can be concluded that the most commonly used LLS in these studies were metacognitive, compensation and cognitive strategies. However, Chamot (2004) pointed out that different strategy preferences were reported by students in different cultural contexts. Chinese and Singaporean students reported a higher level preference for social strategies and lower use of affective strategies than European students.

Some studies have dealt with the implementation of the SILL with a focus on school-aged students ( Magogwe and Oliver, 2007 ; Chen, 2009 , 2014 ; Gunning and Oxford, 2014 ; Platsidou and Kantaridou, 2014 ; Pfenninger and Singleton, 2017 ). The overall conclusion of these studies has been that young learners mostly used social, affective and compensation strategies. The use of memory strategies was relatively low ( Doró and Habók, 2013 ). The attitudes of learners at this age toward language learning are particularly important since they can greatly determine motivation, learning outcomes and later success in language learning ( Platsidou and Kantaridou, 2014 ; Platsidou and Sipitanou, 2014 ).

As the purpose of investigating LLS is to foster learning processes and improve language level, research projects often deal with LLS use in relation to language learning proficiency ( Khaldieh, 2000 ; Magogwe and Oliver, 2007 ; Wu, 2008 ; Chen, 2009 ; Liu, 2010 ; Al-Qahtani, 2013 ; Platsidou and Kantaridou, 2014 ; Charoento, 2016 ; Rao, 2016 ). The notion of proficiency has been defined and involved in analysis in a multitude of ways by various researchers. Charoento (2016) involved self-ratings, Wu (2008) used the results from language proficiency and achievement tests, Magogwe and Oliver (2007) incorporated language course grades into their analysis of their results. Most studies have shown a positive relationship between LLS and proficiency, but the direction of their connexion was often different. Some researchers have stressed that strategy use was mainly specified by proficiency. More proficient students engaged in LLS more frequently and also employed a broader range of strategies overall compared to less proficient students ( Khaldieh, 2000 ; Wu, 2008 ; Rao, 2016 ). Al-Qahtani (2013) and Charoento (2016) demonstrated that successful students mainly used cognitive strategies, while Wu (2008) emphasised significant utilisation of cognitive, metacognitive and social strategies among more proficient university students. Chen (2009) pointed to the use of fewer communication strategies among proficient learners, but noted that they employed them more efficiently than less proficient learners. In addition, Magogwe and Oliver (2007) also established that the basic difference in LLS use between proficient and less proficient learners was that more successful students not only used certain LLS significantly more often, but were also able to select the most adequate strategies depending on the goal of their task.

Some studies have dealt with the effect of LLS use on language proficiency. Both Liu (2010) and Platsidou and Kantaridou (2014) pointed out that learning strategy influences language use and that it plays a significant role in anticipating perceived language performance. Wu (2008) noted that cognitive strategies have the most dominant influence on proficiency. Rao (2016) found that students’ English proficiency significantly affected their learning strategy use and also observed that high-level students avail themselves of more strategies more frequently than low-level students.

Another essential area of LLS research is the study of strategy use in relation to affective variables, such as attitude and motivation ( Shang, 2010 ; Jabbari and Golkar, 2014 ; Platsidou and Kantaridou, 2014 ). Most of these studies have found that learners with a positive attitude employed LLS more frequently compared to learners with a negative attitude. Platsidou and Kantaridou (2014) reported that attitudes toward second language learning influence both direct and indirect strategy uses and that changing learners’ attitudes toward language learning can thus foster their strategy practises. Jabbari and Golkar (2014) established that learners with a positive attitude employ cognitive, compensation, metacognitive and social strategies more frequently.

It can be concluded that LLS use has been studied extensively in recent decades. Most research has found that LLS cannot be analysed separately; it must be examined in relation to certain other factors, among which foreign language attitudes and proficiency play a central role ( Griffiths and Incecay, 2016 ). However, most previous studies preferred university students or adults to primary or secondary school-aged students. Furthermore, a limited amount of research has investigated the relationship of LLS with attitude toward foreign language learning and the foreign language mark. There has also been a dearth of scholarship on how language proficiency and school achievement are determined by LLS use and attitude. Our study aims to fill this gap and attempts to present a comprehensive view of the relationship between LLS use and language attitude and between proficiency and general school achievement by focusing on school children at the beginning and end of lower secondary school. Our specific research question we focus on in this paper is the following:

What are the lower secondary school children’s strategy use preferences and how these are connected with their foreign language attitude, proficiency and general school achievement? Based on the relevant literature we assume that students of this age mainly employ indirect strategies, such as affective, metacognitive and social strategies and these have a significant impact on their foreign language learning attitude, proficiency and general school achievement.

Materials and Methods

Participants.

The participants in the present study were lower secondary students (11- and 14-year-olds) in Hungary ( n Year5 = 450, n Year8 = 418). Participation in the study was voluntary both for schools and students. This study was carried out in accordance with the recommendations of the University of Szeged, the Hungarian law and the municipalities that maintain the schools. The IRB of the Doctoral School (University of Szeged) specifically approved this research project. The agreements are documented and stored in written form in the schools.

Our target group generally started learning a foreign language in Year 4. As one portion of our sample have been learning a foreign language for at least four years, they must have experience of how they learn language. In Hungary, the primary level of education is composed of the elementary and lower secondary school levels; hence, the transition occurs with relatively few major changes, and children have the same language teacher during these school levels. While the foreign language teacher does not change, the other school subjects are taught by specialist teachers as of Year 5. Learning difficulties and differences among children grow considerably from the beginning of lower secondary school; hence, diagnosing language learning attitude is particularly essential.

Instruments

The Strategy Inventory for Language Learning (SILL, Oxford, 1990 ) was administered to investigate the children’s LLS use. The SILL is a standardised measurement tool, and it is applicable to various foreign languages. The complex questionnaire is clustered into six strategy fields: (1) memory (9 items); (2) cognitive (14 items); (3) compensation (6 items); (4) metacognitive (9 items); (5) affective (6 items); and (6) social strategies (6 items). The participants were asked to respond to each statement on a five-point Likert scale. The answers ranged from ‘1 = never or almost never true of me’ to ‘5 = always or almost always true of me.’ The reported internal consistency reliabilities of the questionnaires ranged between 0.91 and 0.94 (Cronbach’s alpha) ( Oxford and Burry-Stock, 1995 ; Ardasheva and Tretter, 2013 ). The questionnaire was conducted in Hungarian to eliminate differences in English knowledge and make it suitable for the language levels in these age groups. The reliability of the Hungarian version was confirmed in previous research ( Doró and Habók, 2013 ). In addition, the children were asked to self-report their foreign language attitude, foreign language mark (indicating students’ foreign language knowledge) and general school achievement (grade point average, which includes students’ achievement in all subjects) on a five-point scale. In Hungarian schools, the different proficiency levels are rated on a five-point scale: 1 is the weakest mark, and 5 is the most excellent.

Design and Procedure

Quantitative research design was employed through online survey methodology. The SILL questionnaire was administered via the eDia online testing platform, which was developed by the Centre for Research on Learning and Instruction for assessing Year 1–6 children’s foreign language knowledge and attitudes. One school lesson was provided for data collection; however, the children needed approximately 20 min to hand in their ratings. Both the children and teachers are familiar with this system because the online platform has been in use since 2009.

Data were handled confidentially during the testing procedure; the children used an identification code provided by research administrators. The researchers were only able to see the codes, and only the teachers were able to identify their students with the codes. All the instructions were in the online questionnaire, so the children were able to answer the questions individually. The teachers were also requested to report the children’s questions, remarks and difficulties during testing. Finally, the teachers reported no misunderstandings or problematic items during data collection.

The data analyses were twofold. First, SPSS for Microsoft Windows 20.0 was employed for classical test analysis, which included an estimation of frequencies, means and standard deviations. The significance of differences among the variables was determined by ANOVA analysis. Second, path analysis was managed by the SPSS AMOS v20 software package to analyse the effect of strategy use on the variables under observation ( Arbuckle, 2008 ). The model fit was indicated by the Tucker–Lewis index (TLI), the normed fit index (NFI), the comparative fit index (CFI) and the root mean square error of approximation (RMSEA) ( Byrne, 2010 ; Kline, 2015 ).

Descriptive Analysis

General strategy uses among lower secondary school children.

The mean scores and standard deviations showed moderate LLS use, with the use of metacognitive, affective and social strategies being the highest in Year 5 (Table 1 ). Compensatory strategies were employed significantly the lowest. In Year 8, besides metacognitive and social strategies, cognitive strategies were relied on the most. Metacognitive strategy use was similarly high in both age groups. Significant differences were found between the age groups in memory, compensation and affective strategies ( p ≤ 0.01). While the use of affective strategies was relatively high in Year 5, it was the least frequently employed in Year 8.

TABLE 1. The strategy use results for the sample.

Differences in Strategy Use among Students with Different Proficiency Levels

One of our goals was to identify students’ LLS use preferences according to their proficiency levels. To implement this goal, we grouped the children into categories according to their proficiency, which was derived from their foreign language marks.

We combined the foreign language marks for those children who were evaluated with a 1 or a 2. These children showed a very low knowledge level and demonstrated a large number of difficulties and misunderstandings in foreign language learning. The next group was formed of children who were assessed at mark 3. This mark indicated an average knowledge level with gaps. Children who were evaluated with a mark 4 had fewer significant deficits. Children who received a mark 5 were the highest performers in school. Tables 2 , 3 summarise our results on strategy use according to foreign language marks. The number of children is also indicated according to each category.

TABLE 2. Means of strategy users according to their foreign language mark in Year 5.

TABLE 3. Means of strategy users according to their foreign language mark in Year 8.

Multivariate Analyses

The relationships between lls and foreign language attitude, lls and foreign language marks, and lls and general school achievement.

Our results demonstrated that the sample was evaluated at an approximate level of mark 4 ( M Year5 = 3.84, SD Year5 = 1.17; M Year8 = 3.62, SD Year8 = 1.17); however, Year 5 children achieved significantly higher ( p < 0.01). As regards children’s attitudes, we found no significant differences between the years ( M Year5 = 3.53, SD Year5 = 1.35; M Year8 = 3.43, SD Year8 = 1.23; p < 0.05). On the whole, it can be stated that children’s foreign language marks are higher than their attitude toward foreign language. The average school achievement showed significantly higher means than foreign language marks in both years ( M Year5 = 3.82, SD Year5 = 0.87, p < 0.001; M Year8 = 3.62, SD Year8 = 1.17, p < 0.001).

We also examined the correlation between LLS and attitude toward foreign languages, LLS and the foreign language mark, and LLS and general school achievement. We observed the most significant estimates between language learning strategy use and attitude in Year 5 ( r = 0.53–0.20; p < 0.001–0.05). The correlational coefficient between attitude and the foreign language mark was also significant ( r = 0.37; p < 0.001). We noted that children who achieved higher in foreign languages showed a more positive attitude toward them. We also noticed a significantly strong effect for the foreign language mark and strategy use ( r = 0.49–0.13; p < 0.001–0.05).

In Year 8, we found significant ( r Year5 = 0.70–0.12; p < 0.001–0.01; r Year8 = 0.82–0.66; p < 0.001–0.01) relationships between overall strategy use and foreign language marks, attitudes and general school achievement. However, the relationship between affective strategies and school achievement was not significant. We observed that children who use LLS have positive attitudes toward language learning, except for compensation and affective strategies.

The Effect of Language Learning Strategies on Attitude, School Marks and General School Achievement

We analysed the effect of LLS on foreign language attitude, school marks and general achievement using AMOS. We were looking for causalities between questionnaire fields and further variables by constructing a theoretical model on the basis of Oxford’s strategy taxonomy and children’s background data. We hypothesised that strategy factors largely influence children’s attitude toward language learning and through this the other variables. The model we created showed appropriate fit indices for the final model and indicated a good fit to our data in both years (Figures 1 , 2 ).

FIGURE 1. The path model for LLS influence on foreign language mark through foreign language attitude and general school achievement (GA) in Year 5.

FIGURE 2. The path model for LLS influence on foreign language mark through foreign language attitude and general school achievement (GA) in Year 8.

Year 5 : χ 2 (13) = 18,309, p = 0.146; Year 8 : χ 2 (13) = 23,893, p = 0.18. An analysis of the hypothesised path model indicated a comparative fit index (CFI) of 0.998 in Year 5 and 0.994 in Year 8. The RMSEA (root mean squared error of approximation) was also good in both years, 0.030 in Year 5 and.049 in Year 8. Both the Tucker–Lewis index (TLI Year5 = 0.992; TLI Year8 = 0.981) and the normed fit index (NFI Year8 = 0.992; NFI Year8 = 0.989) confirmed that the model we constructed was a good fit to our data.

The main aim of the present study was to investigate our understanding of LLS in a foreign language learning context. Therefore, first, we identified the strategy use preferences in the sample and specified the most and least often used strategies among children with different proficiency levels. Second, we examined the children’s LLS use in connexion with their foreign language attitude, proficiency and general school achievement. Our results confirmed some results from previous studies and also established new relationships among the variables.

Regarding the general strategy use preferences of the sample, the students reported moderate use of the six strategy categories. The use of indirect strategies, more precisely, metacognitive, affective and social strategies, was the highest in Year 5, while metacognitive, cognitive and social strategies were the most frequently employed in Year 8. These findings shed light on the different preferences among the different ages and proficiency levels. While affective strategies play a significant role in Year 5, cognitive strategies become more dominant later. Metacognitive and social strategies remained the most frequently used in both Years. Our result is consistent with those reported by Dawadi (2017) who discovered similar strategy preferences. We can also reinforce Alhaysony’s (2017) results that high school sample did not engage in affective strategies, and Charoento’s (2016) findings about the low use of memory strategies.

We also examined the differences in strategy use among students with different proficiency levels in both Years. In Year 5 the research findings analysis demonstrated significant differences among strategy uses in four areas: the memory, cognitive, metacognitive and social fields. We noted no significant differences among children in compensation and affective strategies. As regards memory strategies, we observed that low-achieving children rarely employed them. Low achievers used cognitive strategies significantly less often than good and high performers. As our results showed, the most excellent learners are also metacognitive strategy users, and they engage in social strategies significantly very often. In Year 8, we observed significant differences in every field among children with different proficiencies. As in Year 5, the use of metacognitive and social strategies was the most frequent among the high-achieving students; however, cognitive strategy use was also relatively high. Charoento (2016) and Rao (2016) reported the same results, so we can confirm his previous research outcomes that high achievers avail themselves of strategies significantly more frequently than low-performing learners.

We also investigated the relationship between LLS and foreign language attitude, LLS and the foreign language mark, and LLS and general school achievement. According to our results, we found that children who prefer foreign language learning reported significantly higher strategy use. As regards foreign language marks, the relationships between different kinds of strategy users and their foreign language marks were low. Children with high proficiency did not necessarily employ each of the strategies at a higher rate. The same result was reached by Chen (2009) . The relationship between affective strategies and school achievement was not significant. We observed that children who use LLS have positive attitudes toward language learning. So our findings partly confirmed previous results reported by Jabbari and Golkar (2014) and Platsidou and Kantaridou (2014) .

Concerning the impact of strategy use on foreign language learning attitudes, proficiency and general school achievement. In Year 5 the effect of the questionnaire fields on foreign language attitude was considerably high; attitudes were strongly influenced by metacognitive strategies, and the effect of social strategies was also high. While memory and cognitive strategies showed positive paths to attitudes, compensation and affective strategies indicated negative effects on attitudes. Foreign language attitudes signified the same effect on foreign language marks as these marks did on general achievement. A lower but significant effect of metacognitive strategies was found on general school achievement in Year 5.

In Year 8, we found similar tendencies. The effect of metacognitive strategies on foreign language attitudes was very high, while that of memory strategies was low. The effect of social strategies was lost in Year 8. The impact of foreign language attitude on the foreign language mark was almost the same as in Year 5, but that of the foreign language mark on general school achievement was twice as high. Shawer (2016) likewise highlighted what our results have also shown: strategy use has a significant effect on general school achievement. Metacognitive strategies also had a direct effect on foreign language marks. On the whole, not only did we observe a strong use of metacognitive strategies, but the effect of metacognitive strategies on attitudes was also dominant in both years. Moreover, metacognitive strategies influenced school achievement in Year 5 and foreign language marks in Year 8.

To sum up, our results demonstrated that like other studies, our Hungarian sample showed significant preferences for metacognitive strategy use. Compensatory strategies were the least frequently preferred in Year 5 and memory strategies were the least common in Year 8, a finding which also reinforced previous research outcomes ( Doró and Habók, 2013 ). We observed significant differences between more and less proficient students in strategy use. In line with other research ( Platsidou and Kantaridou, 2014 ), we conclude that more proficient learners avail themselves of a broader range of strategies than less proficient students and strategy use has a significant effect on foreign language marks.

The research focused on the whole language process in connexion with several other factors among young students. The added value of our research is not only that we discovered relationships between factors required for foreign language learning, but direct and indirect underlying effects have also been brought to light through path analysis. These analyses provide a comprehensive view both of the dominant role of metacognitive strategies and of the foreign language learning process generally.

In spite of its value, the study has certain limitations. First, we employed a self-report instrument for data collection which does not address students’ deeper views on learning. Qualitative methods would make it possible to gain a more detailed understanding of foreign language learning through interviews, including think-aloud procedures and classroom observations. Second, the current research into LLS and proficiency among Hungarian students was conducted with participants from two different years at the lower secondary school level, so generalisation of the results is limited. In addition, our sample was not representative. Further research would be necessary to fully examine the relationship between language learning strategies, language learning attitudes, foreign language proficiency and general achievement among Hungarian students in a variety of years and in a larger sample.

Third, the current research only used two measurement points of proficiency, the foreign language mark and general achievement, which are evaluated by different teachers. In future, we will collect a wider range of language proficiency data, including language proficiency test and interviews. Fourth, a comparison of LLS and general learning strategies would produce a more nuanced overview of students’ strategy use.

Conclusion and Pedagogical Implications

The main purpose of the present study was to ascertain the effect of LLS on other variables, such as foreign language attitude, foreign language proficiency and general school achievement among secondary school children in Hungary at the beginning and end of lower secondary school. In the beginner phase of learning foreign languages, it is important to better understand the relationship between language learning and related factors. Hence, our main objective was to provide a complex overview of these measurement points and to examine how LLS can support children in the first phase of the language learning process.

We used the Hungarian translation of Oxford’s Strategy Inventory for Language Learning questionnaire and supplemented it with the children’s self-reports of their foreign language attitudes and proficiency indicated by their foreign language mark and school achievement. This provided the basis for our research.

Past research has demonstrated that students with more frequent LLS use have better chances to become more proficient language learners. It has been pointed out that students that are more proficient engage in a wider range of strategies and select learning strategies dependent on learning tasks. Thus, teachers are encouraged to introduce a range of strategies for children to be able to select those that are most appropriate to features of their personality and relevant to learning tasks. At this age, introducing LLS is significant, particularly for children with low and average foreign language marks. It would be essential to motivate children to discover a variety of ways to practise their foreign language and find opportunities to read and engage in conversations with others. Children who are able to recognise the significance of language learning and use a broad range of strategies can find new ways and opportunities to practise language and to improve their proficiency. Hence, it would be highly recommended to integrate LLS consciously into foreign language lessons.

Ethics Statement

This study was carried out in accordance with the recommendations of the University of Szeged. According to these recommendations participation in the study was voluntary both for schools and students. The participating schools had consent with the parents in allowing their students’ engagement in the research. According to the Hungarian law, the schools’ responsibility to conduct a written agreement with the parents about their consent to allow their children to take part in researches. The whole process is permitted and coordinated by the school holding municipalities. The agreements are documented and stored in written forms in the schools. The authors declare that data collection and handling strictly adhered to the usual standards of research ethics as approved by the University of Szeged.

Author Contributions

AH and AM substantially contributed to the conception and design of the study, data collection, analysis and interpretation of data for the research. Both have written the manuscript and reviewed all parts of the manuscript. AH and AM have given final approval of the final version to be published. AH and AM agree to be accountable for all aspects of the work.

The research was founded by the University of Szeged.

Conflict of Interest Statement

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.

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Keywords : language learning strategy, foreign language attitude, foreign language mark, general school achievement, lower secondary students

Citation: Habók A and Magyar A (2018) The Effect of Language Learning Strategies on Proficiency, Attitudes and School Achievement. Front. Psychol. 8:2358. doi: 10.3389/fpsyg.2017.02358

Received: 06 July 2017; Accepted: 26 December 2017; Published: 11 January 2018.

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Copyright © 2018 Habók and Magyar. 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) or licensor 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: Anita Habók, [email protected]

Disclaimer: 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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What are the Benefits of Learning a Second Language?

Bilingualism, which means speaking more than one language, allows a person to communicate with a larger number of people. Some research suggests that speaking more than one language may also improve brain function. We wanted to see whether the relationship between improved brain function and being bilingual differed based on how well or how much a person uses their second language. To ask our question, we recruited a group of high school students who spoke both Mandarin and English. Because speaking two languages is thought to improve how well a person performs on certain tasks, we thought that the students who were better at their second language would have better performance on those tasks. Our findings support the idea that developing your second language, especially if you speak it well, can improve the way your brain functions. Keep reading to learn about our research!

Why Use Your Second Language?

Most people on Earth can speak at least two languages—they are bilingual . Speaking more than one language allows a person to communicate with a larger number of people. Bilingual people have an easier time when they travel to other parts of the world. They can also work and study outside of their home countries. Research shows that both languages a bilingual person speaks are active in the brain at the same time [ 1 ]. This means a bilingual person must inhibit or “turn off” an unneeded language to communicate successfully. The experience of inhibiting an unneeded but active language may actually help the brain by improving a person’s executive function , which is a set of mental processes that coordinate our thinking and behavior [ 2 ] (To learn more about executive function, see this Frontiers for Young Minds article .). Scientists who study this topic call this brain boost the bilingual advantage .

Not all scientists agree that speaking two languages helps the brain [ 3 ]. Even those that do agree are not exactly sure how being bilingual improves brain function. Some claim that bilingual people have better inhibition . In other words, they are better at ignoring distractions like noise when they are having a conversation. Others say bilingual people are better at monitoring , which means they are better at paying attention to their environments. For example, they might be better at noticing when a person switches from using one language to another. The way that speaking two languages improves brain function seems to depend a lot on the person and their individual language experience [ 4 ].

Do People Have Different Language Experiences?

It turns out that bilingual people differ a lot in their language experiences including how well they use their languages and how much they use them. For example, a teen from China who speaks Chinese (Mandarin) and English might never use English in their home country. However, they would use it a lot if they attended school in the UK. Bilingual people in the same city also differ a lot in their language habits. A Mandarin-English bilingual person studying in the UK might have a group of friends who always speak Mandarin, while another might have more diverse friends and may communicate in English more often. We wanted to see if these differences between bilingual people influenced executive functions. This means we had to find a way to measure language experience.

How did we Measure Language Experience?

There are many ways to measure language experience. We used a survey called the Language History Questionnaire [ 5 ]. This survey requires a person to answer questions about each language they use. These questions ask things like how well the person can speak, listen, read, or write in each language. The survey also asks how many hours each day the person uses a language. This survey gave us three separate scores that we used to measure language experience: 1) proficiency —how well a person can speak, listen, read, or write in a language; 2) immersion —how long a person has used or been exposed to a language, and; 3) dominance —how often a person uses a language. Together, these scores allowed us to describe a person’s language experience in a lot of detail.

How did we Measure Executive Function?

To test for differences in executive function, we used two popular tasks. The Simon task requires a person to press a button as quickly and accurately as possible when a certain color shape is shown on a screen ( Figure 1 ). For example, a person might be told to press the “Q” button on a computer keyboard with their left hand when they see a brown square, or the “P” button with their right hand when they see a blue square. What makes this task tricky is that the shapes are shown on either the left or right side of the screen. This means that sometimes a person will have to press a button with their right hand when a shape is on the same (right) side of the screen. These congruent trials are easy. However, sometimes a person will have to press a button with their right hand when a shape is on the left side of the screen. The conflict between the side of the screen the shape is on and the response key makes these incongruent trials more difficult. The flanker task is similar to the Simon task, only the conflict is due to a center arrow pointing in the opposite direction of the four surrounding arrows ( Figure 2 ).

• Figure 1 - (A) On the Simon task, students had to press the left button when a blue square appeared.
• This is easy when the square is on the same side as the button. (B) However, this task is harder when the square is on the opposite side as the button! Dashed lines show the response button location.

• Figure 2 - (A) On the flanker task, students had to press the left button if the center arrow was pointing to the left.
• This is easy when all the arrows face the same direction. (B) However, this task is harder when the center arrow is pointing in the opposite direction from the other arrows! Solid lines show the information the student needed to pay attention to, and dashed lines show the information that may help (A) or distract (B) the student.

How did we Answer our Question?

We worked with an international high school in Southern China to conduct our study. This school is special because all the students are native Mandarin speakers, but all their courses are taught in English. We recruited 41 students between the ages of 13–19 and had them complete a few tasks on the Internet. First, each participant filled in the Language History Questionnaire and answered other questions about how often they play video games or musical instruments. Next, they completed the Simon and flanker tasks in random order. Even though these tasks are very similar, studies like ours normally ask people to do more than one task to see if the results are the same. Finally, the students answered a few questions about their stress levels. For each task, we measured how quickly students gave their responses, and whether their responses were correct or not. We included video game and musical instrument experience as well as other variables like age and stress in our analyses to control for their influence on task performance. This helps us to be sure that the results we see have to do with language experience and are not due to other factors.

What did we Find?

Our results were different for each task and each measure of language experience. On the Simon task, higher English proficiency was related to better inhibition, even when we controlled for the influence of other variables ( Figure 3 ). This means students with better English ability were faster on the more difficult, incongruent trials. In other words, they were better at inhibiting the automatic response of pressing the button that matched the side of the screen the shape was presented on. When controlling for other variables, we found the same result when we looked at the number of hours people spent playing musical instruments. This means playing an instrument might further improve inhibition. For the flanker task, higher English proficiency was related to improved monitoring. This means students with higher English proficiency were faster on congruent, incongruent, and neutral trials. In other words, they were better at monitoring the task in order to identify which response was appropriate.

• Figure 3 - (A) Higher English proficiency was associated with better inhibition (faster responses on incongruent trials) on the Simon task.
• (B) Higher English proficiency was also associated with better monitoring (faster response on all trial types) on the flanker task. The colored lines represent the trial types. The blue lines show the difficult, incongruent trials. If we conducted our study again, we are 95% confident that our results would be somewhere in the shaded area around each line.

Surprisingly, students who reported using English more were slower on the flanker task. We did not expect to see this! We think this finding might mean that people using English more are trying to improve their proficiency and might pay more attention to the words they use—which would slow them down. However, this is just our best guess. We will need to conduct another study to see if our guess is correct. Finally, our results were a little different between the Simon and flanker tasks, even though these tasks are very similar. This finding also requires more research because it suggests that these tasks might be measuring slightly different things.

Why Are Our Findings Important?

Our results show that developing proficiency in a second language may improve executive function. We also saw additional improvements in executive function from playing musical instruments. This suggests that bilingualism is just one of many possible experiences that can benefit the brain. These findings are important for young people, especially those in bilingual homes. Sometimes, children do not feel like learning their family’s home language. This might be because it is not the language that the child uses when they go to school. More research is needed to better understand the benefits that using a second language has on the brain. This is especially true for high-school-age bilinguals because only a few studies have been done. We hope that our results highlight the potential benefits of learning a second language. While becoming bilingual is not easy, it is likely worth your time and energy. Who knows? You might even make a new friend!

Bilingual : ↑ A person who can use at least two different languages.

Executive Function : ↑ A set of mental processes, like updating, inhibition, and monitoring, that coordinate a person’s thoughts and actions.

Bilingual Advantage : ↑ A benefit in brain function from speaking two languages.

Inhibition : ↑ Component of executive function that helps people ignore distractions.

Monitoring : ↑ The ability to pay attention to the environment.

Congruent : ↑ Trials where there is no conflict between the stimulus and the response such as a flanker task trial where all arrows are pointing in the same direction.

Incongruent : ↑ Trials where the stimulus and the response conflict such as a flanker task trial where the center arrow is pointing in the opposite direction as the surrounding arrows.

Variable : ↑ A characteristic, like language proficiency, that can change and be measured.

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.

Original Source Article

↑ Privitera, A. J., Momenian, M., and Weekes, B. S. 2022. Task-specific bilingual effects in Mandarin-English speaking high school students in China. Curr. Res. Behav. Sci. 3:100066. doi: 10.1016/j.crbeha.2022.100066

[1] ↑ Kroll, J. F., and Bialystok, E. 2013. Understanding the consequences of bilingualism for language processing and cognition. J. Cogn. Psychol. 25:497–514. doi: 10.1080/20445911.2013.799170

[2] ↑ Friedman, N. P., and Miyake, A. 2017. Unity and diversity of executive functions: individual differences as a window on cognitive structure. Cortex. 86:186–204. doi: 10.1016/j.cortex.2016.04.023

[3] ↑ Paap, K. 2019. “The bilingual advantage debate: quantity and quality of the evidence,” in The Handbook of the Neuroscience of Multilingualism , 701–35.

[4] ↑ Privitera, A. J., Momenian, M., and Weekes, B. 2022. Graded bilingual effects on attentional network function in Chinese high school students. Bilingual. Lang. Cogn . 1–11. doi: 10.1017/S1366728922000803

[5] ↑ Li, P., Zhang, F., Yu, A., and Zhao, X. 2020. Language history questionnaire (LHQ3): an enhanced tool for assessing multilingual experience. Bilingual. Lang. Cogn. 23:938–44. doi: 10.1017/S1366728918001153

Why it’s never too late to learn a language as an adult

The long-held idea that language learning is better before adulthood is up for debate. Adults have a number of advantages when it comes to learning a second language, and it comes with major benefits.

For those looking to learn a new language, the process can feel daunting, especially as an adult.

It’s long been thought that the earlier you learn new skills, the easier they are to pick up . The idea that age can play a huge role in a person’s language learning ability is one of the reasons why early childhood was once considered the best time to introduce a second language. But whether that holds true has been heavily debated in the scientific community.  

Unfortunately, the idea has helped perpetuate doubt in older individuals’ ability to quickly adapt to new grammar, syntax, and semantics, thwarting the rise of many potential polyglots.  

A complex organ capable of constant evolution, the human brain has potential for higher learning after puberty, research suggests—adults and children simply absorb and learn things differently.  

“Research says that adults are better learners at everything because we have a lot of self-regulation and we're very intent when we want to learn something,” says Lourdes Ortega, a professor of linguistics at Georgetown University, who herself speaks four languages. “Adults all over the world arrive at different proficiencies, fluencies, capacities for what they want to do with language, but there is no ceiling to it.”

People who can communicate outside their mother tongue also experience a number of cognitive benefits, suggesting that it may be well worth expanding your verbal horizons.  

What it takes to learn a second language

According to the U.S. Census Bureau, about 20 percent of the U.S. population speaks another language other than English, compared to 59 percent of Europeans who can speak at least a second language, illustrating how different regions value language learning.    

Yet Ortega, who specializes in how people learn new languages beyond childhood, says that factors beyond age, like immersion, make a bigger difference in language learning success. “Without [the] opportunity to be exposed to the language, there's no learning that can happen, early or late,” she says.  

For most, it can take years to reach proficiency in a foreign language, says Ortega. According to The Foreign Service Institute (FSI) , factors like a person’s natural ability, their previous linguistic experience, and the consistency of their lessons affect the language learning process.    

The FSI says languages that native English speakers would find similar to their own, such as Spanish or French, can be taught relatively quickly in about 24-30 weeks. In contrast, languages that have significant cultural differences from English, like Greek or Russian, will take about 44 weeks. Learning time could double that for languages considered exceptionally hard, such as Arabic or Mandarin.  

Such estimates reflect a stringent study model, with a dedicated number of hours spent practicing for multiple days per week, says Ortega. It’s impossible and unlikely to expect one individual to follow such a strict schedule on their own, especially as the rise of language learning apps like Babbel and Duolingo has widened accessibility to foreign education by allowing people the time and confidence to reach certain goalposts at their own pace.  

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“No one can learn, as an adult, a new language unless they love it and unless they make it part of their life,” says Ortega. “In theory, it's a great thing, but you need to have reasons for it and the time to invest [in] it.”

That said, children and adults do have their own unique strengths and weaknesses when it comes to grasping new connections. Children tend to learn new languages more intuitively , may have more opportunities to play and experiment with new languages, and may be forced to adapt without the aid of translation apps or other resources. Adults can employ custom strategies to hone their language learning experience, like creating their own memorization systems or visualization techniques.  

Still, Joshua Hartshorne, a research associate professor at the MGH Institute of Health Professions, says scientists are finding that a lot more is going on at ages that they weren't really thinking about before.  

“People have been assuming that you more or less have gotten as good as you're going to get in a new language within four or five years,” says Hartshorne. “What we saw was actually, [as] people continue learning for about 30 years, they’ll continue to get better.”  

How a second language nourishes the mind    

Increasingly, longer-lived generations are looking to enhance their cognitive health and social lives, and the growing demand to learn another language has quickly proven to be a great way to accomplish it.  

“There are all sorts of cognitive benefits of being bilingual,“ says Boaz Keysar , a professor of psychology at The University of Chicago. “The more languages you learn, the more you realize what an important part [that] language is for our life. We take it for granted.”

For older adults, possible benefits include an increase in memory retention and obtaining a more expansive vocabulary. What’s more, many studies suggest learning another language as an adult could even help stave off dementia . Language learning enables students to become more flexible thinkers, says Keysar.

“You're more willing to take risks when you use a foreign language,” he says. “The words don't connect as much to your emotions.” Additionally, multilingual people are better at perspective-taking , meaning that they’re more tuned in to the intention of the speaker, says Keysar. It’s an ability that allows for smoother cross-cultural social interaction, and another facet of language that adults seem to be better equipped for.  

Despite language-bonding being a fantastic tool to expand a person’s social network, there’s still a lack of research surrounding the challenges older adults face when aiming to learn a new language.

According to one 2019 study that investigated the struggles they can face in classroom settings, older individuals may find themselves forced to use textbooks that don't consider their needs, like ones that utilize examples and activities that might be too childish or inappropriate for them to take seriously—and be reluctant to speak up to avoid making mistakes.

Nevertheless, discovering a language other than your own can be very rewarding. The best way to reap the bulk of those rewards is to start today.  

“It would be wonderful if people would be more open to the idea that it can bring a lot of richness to your life,” says Ortega. ‘If nothing else, don't just try one language, try at least two because each of them feels very different.”

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Swain, M. (1995). Three functions of output in second language learning. In G. Cook, & B. Seidlhofer (Eds.), Principle and practice in applied linguistics: Studies in honour of H. G. Widdowson (pp. 125-144). Oxford: Oxford University Press.

has been cited by the following article:

TITLE: Corrective Feedback, Negotiation of Meaning and Grammar Development: Learner-Learner and Learner-Native Speaker Interaction in ESL

KEYWORDS: Corrective Feedback; Negotiation of Meaning; Grammar Learning; ESL; Interaction

JOURNAL NAME: Open Journal of Modern Linguistics , Vol.2 No.2 , June 27, 2012

ABSTRACT: This study aims to investigate the role of corrective feedback and negotiation of meaning within an Interactionist Approach (Long, 1996) in native speaker-Second Language learner and L2 learner-L2 learner interactions. While negotiation of meaning (NoM) and corrective feedback (CF) between native and nonnative speakers has been shown to be helpful for the nonnatives, it remains unclear whether CF and NoM between learners of equivalent or different proficiency produce greater negotiation of meaning and successful uptake of corrective feedback compared to the more traditional native-nonnative interaction. The key issue in this study is whether CF and NoM in different interactional combinations of interlocutors make a difference, in quantitative and qualitative terms. The study adopts a pretest-treatment-posttest design with six participants: two native English speakers, two Chinese L1 NNSs of high English proficiency level (NNS High) and two Chinese L1 NNSs of low English proficiency level (NNS Low). These informants generated 14 different dyads and produced 2377 turns while engaging in task-based interaction. By introducing the notions of group (i.e., NS-NNS versus NNS-NNS groups), combinations (e.g., NS-NNS High versus NNS High-NNS Low), and dyads, it is possible to compare results across groups, combinations and individuals. Results confirm that CF and NoM happen in NNS-NNS interaction yet they differ, qualitatively and quantitatively, according to the type of combination. Significantly, the best rate of success was obtained in the combination of learners with different proficiency levels i.e., the NNS High-NNS Low combination. In addition, error rates decreased from pre-test to post-test in all learners, especially NNS Low, which lends support to the notion that CF and NoM promote second language development also in interaction between learners.

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• Published: 02 May 2024

Effectiveness of social media-assisted course on learning self-efficacy

• Jiaying Hu 1 ,
• Yicheng Lai 2 &
• Xiuhua Yi 3  

Scientific Reports volume  14 , Article number:  10112 ( 2024 ) Cite this article

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• Human behaviour

The social media platform and the information dissemination revolution have changed the thinking, needs, and methods of students, bringing development opportunities and challenges to higher education. This paper introduces social media into the classroom and uses quantitative analysis to investigate the relation between design college students’ learning self-efficacy and social media for design students, aiming to determine the effectiveness of social media platforms on self-efficacy. This study is conducted on university students in design media courses and is quasi-experimental, using a randomized pre-test and post-test control group design. The study participants are 73 second-year design undergraduates. Independent samples t-tests showed that the network interaction factors of social media had a significant impact on college students learning self-efficacy. The use of social media has a significant positive predictive effect on all dimensions of learning self-efficacy. Our analysis suggests that using the advantages and value of online social platforms, weakening the disadvantages of the network, scientifically using online learning resources, and combining traditional classrooms with the Internet can improve students' learning self-efficacy.

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Introduction.

Social media is a way of sharing information, ideas, and opinions with others one. It can be used to create relationships between people and businesses. Social media has changed the communication way, it’s no longer just about talking face to face but also using a digital platform such as Facebook or Twitter. Today, social media is becoming increasingly popular in everyone's lives, including students and researchers 1 . Social media provides many opportunities for learners to publish their work globally, bringing many benefits to teaching and learning. The publication of students' work online has led to a more positive attitude towards learning and increased achievement and motivation. Other studies report that student online publications or work promote reflection on personal growth and development and provide opportunities for students to imagine more clearly the purpose of their work 2 . In addition, learning environments that include student publications allow students to examine issues differently, create new connections, and ultimately form new entities that can be shared globally 3 , 4 .

Learning self-efficacy is a belief that you can learn something new. It comes from the Latin word “self” and “efficax” which means efficient or effective. Self-efficacy is based on your beliefs about yourself, how capable you are to learn something new, and your ability to use what you have learned in real-life situations. This concept was first introduced by Bandura (1977), who studied the effects of social reinforcement on children’s learning behavior. He found that when children were rewarded for their efforts they would persist longer at tasks that they did not like or had low interest in doing. Social media, a ubiquitous force in today's digital age, has revolutionized the way people interact and share information. With the rise of social media platforms, individuals now have access to a wealth of online resources that can enhance their learning capabilities. This access to information and communication has also reshaped the way students approach their studies, potentially impacting their learning self-efficacy. Understanding the role of social media in shaping students' learning self-efficacy is crucial in providing effective educational strategies that promote healthy learning and development 5 . Unfortunately, the learning curve for the associated metadata base modeling methodologies and their corresponding computer-aided software engineering (CASE) tools have made it difficult for students to grasp. Addressing this learning issue examined the effect of this MLS on the self-efficacy of learning these topics 6 . Bates et al. 7 hypothesize a mediated model in which a set of antecedent variables influenced students’ online learning self-efficacy which, in turn, affected student outcome expectations, mastery perceptions, and the hours spent per week using online learning technology to complete learning assignments for university courses. Shen et al. 8 through exploratory factor analysis identifies five dimensions of online learning self-efficacy: (a) self-efficacy to complete an online course (b) self-efficacy to interact socially with classmates (c) self-efficacy to handle tools in a Course Management System (CMS) (d) self-efficacy to interact with instructors in an online course, and (e) self-efficacy to interact with classmates for academic purposes. Chiu 9 established a model for analyzing the mediating effect that learning self-efficacy and social self-efficacy have on the relationship between university students’ perceived life stress and smartphone addiction. Kim et al. 10 study was conducted to examine the influence of learning efficacy on nursing students' self-confidence. The objective of Paciello et al. 11 was to identify self-efficacy configurations in different domains (i.e., emotional, social, and self-regulated learning) in a sample of university students using a person-centered approach. The role of university students’ various conceptions of learning in their academic self-efficacy in the domain of physics is initially explored 12 . Kumar et al. 13 investigated factors predicting students’ behavioral intentions towards the continuous use of mobile learning. Other influential work includes 14 .

Many studies have focused on social networking tools such as Facebook and MySpace 15 , 16 . Teachers are concerned that the setup and use of social media apps take up too much of their time, may have plagiarism and privacy issues, and contribute little to actual student learning outcomes; they often consider them redundant or simply not conducive to better learning outcomes 17 . Cao et al. 18 proposed that the central questions in addressing the positive and negative pitfalls of social media on teaching and learning are whether the use of social media in teaching and learning enhances educational effectiveness, and what motivates university teachers to use social media in teaching and learning. Maloney et al. 3 argued that social media can further improve the higher education teaching and learning environment, where students no longer access social media to access course information. Many studies in the past have shown that the use of modern IT in the classroom has increased over the past few years; however, it is still limited mainly to content-driven use, such as accessing course materials, so with the emergence of social media in students’ everyday lives 2 , we need to focus on developing students’ learning self-efficacy so that they can This will enable students to 'turn the tables and learn to learn on their own. Learning self-efficacy is considered an important concept that has a powerful impact on learning outcomes 19 , 20 .

Self-efficacy for learning is vital in teaching students to learn and develop healthily and increasing students' beliefs in the learning process 21 . However, previous studies on social media platforms such as Twitter and Weibo as curriculum support tools have not been further substantiated or analyzed in detail. In addition, the relationship between social media, higher education, and learning self-efficacy has not yet been fully explored by researchers in China. Our research aims to fill this gap in the topic. Our study explored the impact of social media on the learning self-efficacy of Chinese college students. Therefore, it is essential to explore the impact of teachers' use of social media to support teaching and learning on students' learning self-efficacy. Based on educational theory and methodological practice, this study designed a teaching experiment using social media to promote learning self-efficacy by posting an assignment for post-course work on online media to explore the actual impact of social media on university students’ learning self-efficacy. This study examines the impact of a social media-assisted course on university students' learning self-efficacy to explore the positive impact of a social media-assisted course.

Theoretical background

• Social media

Social media has different definitions. Mayfield (2013) first introduced the concept of social media in his book-what is social media? The author summarized the six characteristics of social media: openness, participation, dialogue, communication, interaction, and communication. Mayfield 22 shows that social media is a kind of new media. Its uniqueness is that it can give users great space and freedom to participate in the communication process. Jen (2020) also suggested that the distinguishing feature of social media is that it is “aggregated”. Social media provides users with an interactive service to control their data and information and collaborate and share information 2 . Social media offers opportunities for students to build knowledge and helps them actively create and share information 23 . Millennial students are entering higher education institutions and are accustomed to accessing and using data from the Internet. These individuals go online daily for educational or recreational purposes. Social media is becoming increasingly popular in the lives of everyone, including students and researchers 1 . A previous study has shown that millennials use the Internet as their first source of information and Google as their first choice for finding educational and personal information 24 . Similarly, many institutions encourage teachers to adopt social media applications 25 . Faculty members have also embraced social media applications for personal, professional, and pedagogical purposes 17 .

Social networks allow one to create a personal profile and build various networks that connect him/her to family, friends, and other colleagues. Users use these sites to stay in touch with their friends, make plans, make new friends, or connect with someone online. Therefore, extending this concept, these sites can establish academic connections or promote cooperation and collaboration in higher education classrooms 2 . This study defines social media as an interactive community of users' information sharing and social activities built on the technology of the Internet. Because the concept of social media is broad, its connotations are consistent. Research shows that Meaning and Linking are the two key elements that make up social media existence. Users and individual media outlets generate social media content and use it as a platform to get it out there. Social media distribution is based on social relationships and has a better platform for personal information and relationship management systems. Examples of social media applications include Facebook, Twitter, MySpace, YouTube, Flickr, Skype, Wiki, blogs, Delicious, Second Life, open online course sites, SMS, online games, mobile applications, and more 18 . Ajjan and Hartshorne 2 investigated the intentions of 136 faculty members at a US university to adopt Web 2.0 technologies as tools in their courses. They found that integrating Web 2.0 technologies into the classroom learning environment effectively increased student satisfaction with the course and improved their learning and writing skills. His research focused on improving the perceived usefulness, ease of use, compatibility of Web 2.0 applications, and instructor self-efficacy. The social computing impact of formal education and training and informal learning communities suggested that learning web 2.0 helps users to acquire critical competencies, and promotes technological, pedagogical, and organizational innovation, arguing that social media has a variety of learning content 26 . Users can post digital content online, enabling learners to tap into tacit knowledge while supporting collaboration between learners and teachers. Cao and Hong 27 investigated the antecedents and consequences of social media use in teaching among 249 full-time and part-time faculty members, who reported that the factors for using social media in teaching included personal social media engagement and readiness, external pressures; expected benefits; and perceived risks. The types of Innovators, Early adopters, Early majority, Late majority, Laggards, and objectors. Cao et al. 18 studied the educational effectiveness of 168 teachers' use of social media in university teaching. Their findings suggest that social media use has a positive impact on student learning outcomes and satisfaction. Their research model provides educators with ideas on using social media in the education classroom to improve student performance. Maqableh et al. 28 investigated the use of social networking sites by 366 undergraduate students, and they found that weekly use of social networking sites had a significant impact on student's academic performance and that using social networking sites had a significant impact on improving students' effective time management, and awareness of multitasking. All of the above studies indicate the researcher’s research on social media aids in teaching and learning. All of these studies indicate the positive impact of social media on teaching and learning.

• Learning self-efficacy

For the definition of concepts related to learning self-efficacy, scholars have mainly drawn on the idea proposed by Bandura 29 that defines self-efficacy as “the degree to which people feel confident in their ability to use the skills they possess to perform a task”. Self-efficacy is an assessment of a learner’s confidence in his or her ability to use the skills he or she possesses to complete a learning task and is a subjective judgment and feeling about the individual’s ability to control his or her learning behavior and performance 30 . Liu 31 has defined self-efficacy as the belief’s individuals hold about their motivation to act, cognitive ability, and ability to perform to achieve their goals, showing the individual's evaluation and judgment of their abilities. Zhang (2015) showed that learning efficacy is regarded as the degree of belief and confidence that expresses the success of learning. Yan 32 showed the extent to which learning self-efficacy is viewed as an individual. Pan 33 suggested that learning self-efficacy in an online learning environment is a belief that reflects the learner's ability to succeed in the online learning process. Kang 34 believed that learning self-efficacy is the learner's confidence and belief in his or her ability to complete a learning task. Huang 35 considered self-efficacy as an individual’s self-assessment of his or her ability to complete a particular task or perform a specific behavior and the degree of confidence in one’s ability to achieve a specific goal. Kong 36 defined learning self-efficacy as an individual’s judgment of one’s ability to complete academic tasks.

Based on the above analysis, we found that scholars' focus on learning self-efficacy is on learning behavioral efficacy and learning ability efficacy, so this study divides learning self-efficacy into learning behavioral efficacy and learning ability efficacy for further analysis and research 37 , 38 . Search the CNKI database and ProQuest Dissertations for keywords such as “design students’ learning self-efficacy”, “design classroom self-efficacy”, “design learning self-efficacy”, and other keywords. There are few relevant pieces of literature about design majors. Qiu 39 showed that mobile learning-assisted classroom teaching can control the source of self-efficacy from many aspects, thereby improving students’ sense of learning efficacy and helping middle and lower-level students improve their sense of learning efficacy from all dimensions. Yin and Xu 40 argued that the three elements of the network environment—“learning content”, “learning support”, and “social structure of learning”—all have an impact on university students’ learning self-efficacy. Duo et al. 41 recommend that learning activities based on the mobile network learning community increase the trust between students and the sense of belonging in the learning community, promote mutual communication and collaboration between students, and encourage each other to stimulate their learning motivation. In the context of social media applications, self-efficacy refers to the level of confidence that teachers can successfully use social media applications in the classroom 18 . Researchers have found that self-efficacy is related to social media applications 42 . Students had positive experiences with social media applications through content enhancement, creativity experiences, connectivity enrichment, and collaborative engagement 26 . Students who wish to communicate with their tutors in real-time find social media tools such as web pages, blogs, and virtual interactions very satisfying 27 . Overall, students report their enjoyment of different learning processes through social media applications; simultaneously, they show satisfactory tangible achievement of tangible learning outcomes 18 . According to Bandura's 'triadic interaction theory’, Bian 43 and Shi 44 divided learning self-efficacy into two main elements, basic competence, and control, where basic competence includes the individual's sense of effort, competence, the individual sense of the environment, and the individual's sense of control over behavior. The primary sense of competence includes the individual's Sense of effort, competence, environment, and control over behavior. In this study, learning self-efficacy is divided into Learning behavioral efficacy and Learning ability efficacy. Learning behavioral efficacy includes individuals' sense of effort, environment, and control; learning ability efficacy includes individuals' sense of ability, belief, and interest.

In Fig.  1 , learning self-efficacy includes learning behavior efficacy and learning ability efficacy, in which the learning behavior efficacy is determined by the sense of effort, the sense of environment, the sense of control, and the learning ability efficacy is determined by the sense of ability, sense of belief, sense of interest. “Sense of effort” is the understanding of whether one can study hard. Self-efficacy includes the estimation of self-effort and the ability, adaptability, and creativity shown in a particular situation. One with a strong sense of learning self-efficacy thinks they can study hard and focus on tasks 44 . “Sense of environment” refers to the individual’s feeling of their learning environment and grasp of the environment. The individual is the creator of the environment. A person’s feeling and grasp of the environment reflect the strength of his sense of efficacy to some extent. A person with a shared sense of learning self-efficacy is often dissatisfied with his environment, but he cannot do anything about it. He thinks the environment can only dominate him. A person with a high sense of learning self-efficacy will be more satisfied with his school and think that his teachers like him and are willing to study in school 44 . “Sense of control” is an individual’s sense of control over learning activities and learning behavior. It includes the arrangement of individual learning time, whether they can control themselves from external interference, and so on. A person with a strong sense of self-efficacy will feel that he is the master of action and can control the behavior and results of learning. Such a person actively participates in various learning activities. When he encounters difficulties in learning, he thinks he can find a way to solve them, is not easy to be disturbed by the outside world, and can arrange his own learning time. The opposite is the sense of losing control of learning behavior 44 . “Sense of ability” includes an individual’s perception of their natural abilities, expectations of learning outcomes, and perception of achieving their learning goals. A person with a high sense of learning self-efficacy will believe that he or she is brighter and more capable in all areas of learning; that he or she is more confident in learning in all subjects. In contrast, people with low learning self-efficacy have a sense of powerlessness. They are self-doubters who often feel overwhelmed by their learning and are less confident that they can achieve the appropriate learning goals 44 . “Sense of belief” is when an individual knows why he or she is doing something, knows where he or she is going to learn, and does not think before he or she even does it: What if I fail? These are meaningless, useless questions. A person with a high sense of learning self-efficacy is more robust, less afraid of difficulties, and more likely to reach their learning goals. A person with a shared sense of learning self-efficacy, on the other hand, is always going with the flow and is uncertain about the outcome of their learning, causing them to fall behind. “Sense of interest” is a person's tendency to recognize and study the psychological characteristics of acquiring specific knowledge. It is an internal force that can promote people's knowledge and learning. It refers to a person's positive cognitive tendency and emotional state of learning. A person with a high sense of self-efficacy in learning will continue to concentrate on studying and studying, thereby improving learning. However, one with low learning self-efficacy will have psychology such as not being proactive about learning, lacking passion for learning, and being impatient with learning. The elements of learning self-efficacy can be quantified and detailed in the following Fig.  1 .

Learning self-efficacy research structure in this paper.

Research participants

All the procedures were conducted in adherence to the guidelines and regulations set by the institution. Prior to initiating the study, informed consent was obtained in writing from the participants, and the Institutional Review Board for Behavioral and Human Movement Sciences at Nanning Normal University granted approval for all protocols.

Two parallel classes are pre-selected as experimental subjects in our study, one as the experimental group and one as the control group. Social media assisted classroom teaching to intervene in the experimental group, while the control group did not intervene. When selecting the sample, it is essential to consider, as far as possible, the shortcomings of not using randomization to select or assign the study participants, resulting in unequal experimental and control groups. When selecting the experimental subjects, classes with no significant differences in initial status and external conditions, i.e. groups with homogeneity, should be selected. Our study finally decided to select a total of 44 students from Class 2021 Design 1 and a total of 29 students from Class 2021 Design 2, a total of 74 students from Nanning Normal University, as the experimental subjects. The former served as the experimental group, and the latter served as the control group. 73 questionnaires are distributed to measure before the experiment, and 68 are returned, with a return rate of 93.15%. According to the statistics, there were 8 male students and 34 female students in the experimental group, making a total of 44 students (mirrors the demographic trends within the humanities and arts disciplines from which our sample was drawn); there are 10 male students and 16 female students in the control group, making a total of 26 students, making a total of 68 students in both groups. The sample of those who took the course were mainly sophomores, with a small number of first-year students and juniors, which may be related to the nature of the subject of this course and the course system offered by the university. From the analysis of students' majors, liberal arts students in the experimental group accounted for the majority, science students and art students accounted for a small part. In contrast, the control group had more art students, and liberal arts students and science students were small. In the daily self-study time, the experimental and control groups are 2–3 h. The demographic information of research participants is shown in Table 1 .

Research procedure

Firstly, the ADDIE model is used for the innovative design of the teaching method of the course. The number of students in the experimental group was 44, 8 male and 35 females; the number of students in the control group was 29, 10 male and 19 females. Secondly, the classes are targeted at students and applied. Thirdly, the course for both the experimental and control classes is a convenient and practice-oriented course, with the course title “Graphic Design and Production”, which focuses on learning the graphic design software Photoshop. The course uses different cases to explain in detail the process and techniques used to produce these cases using Photoshop, and incorporates practical experience as well as relevant knowledge in the process, striving to achieve precise and accurate operational steps; at the end of the class, the teacher assigns online assignments to be completed on social media, allowing students to post their edited software tutorials online so that students can master the software functions. The teacher assigns online assignments to be completed on social media at the end of the lesson, allowing students to post their editing software tutorials online so that they can master the software functions and production skills, inspire design inspiration, develop design ideas and improve their design skills, and improve students' learning self-efficacy through group collaboration and online interaction. Fourthly, pre-tests and post-tests are conducted in the experimental and control classes before the experiment. Fifthly, experimental data are collected, analyzed, and summarized.

We use a questionnaire survey to collect data. Self-efficacy is a person’s subjective judgment on whether one can successfully perform a particular achievement. American psychologist Albert Bandura first proposed it. To understand the improvement effect of students’ self-efficacy after the experimental intervention, this work questionnaire was referenced by the author from “Self-efficacy” “General Perceived Self Efficacy Scale” (General Perceived Self Efficacy Scale) German psychologist Schwarzer and Jerusalem (1995) and “Academic Self-Efficacy Questionnaire”, a well-known Chinese scholar Liang 45 .  The questionnaire content is detailed in the supplementary information . A pre-survey of the questionnaire is conducted here. The second-year students of design majors collected 32 questionnaires, eliminated similar questions based on the data, and compiled them into a formal survey scale. The scale consists of 54 items, 4 questions about basic personal information, and 50 questions about learning self-efficacy. The Likert five-point scale is the questionnaire used in this study. The answers are divided into “completely inconsistent", “relatively inconsistent”, “unsure”, and “relatively consistent”. The five options of “Completely Meet” and “Compliant” will count as 1, 2, 3, 4, and 5 points, respectively. Divided into a sense of ability (Q5–Q14), a sense of effort (Q15–Q20), a sense of environment (Q21–Q28), a sense of control (Q29–Q36), a sense of Interest (Q37–Q45), a sense of belief (Q46–Q54). To demonstrate the scientific effectiveness of the experiment, and to further control the influence of confounding factors on the experimental intervention. This article thus sets up a control group as a reference. Through the pre-test and post-test in different periods, comparison of experimental data through pre-and post-tests to illustrate the effects of the intervention.

Reliability indicates the consistency of the results of a measurement scale (See Table 2 ). It consists of intrinsic and extrinsic reliability, of which intrinsic reliability is essential. Using an internal consistency reliability test scale, a Cronbach's alpha coefficient of reliability statistics greater than or equal to 0.9 indicates that the scale has good reliability, 0.8–0.9 indicates good reliability, 7–0.8 items are acceptable. Less than 0.7 means to discard some items in the scale 46 . This study conducted a reliability analysis on the effects of the related 6-dimensional pre-test survey to illustrate the reliability of the questionnaire.

From the Table 2 , the Cronbach alpha coefficients for the pre-test, sense of effort, sense of environment, sense of control, sense of interest, sense of belief, and the total questionnaire, were 0.919, 0.839, 0.848, 0.865, 0.852, 0.889 and 0.958 respectively. The post-test Cronbach alpha coefficients were 0.898, 0.888, 0.886, 0.889, 0.900, 0.893 and 0.970 respectively. The Cronbach alpha coefficients were all greater than 0.8, indicating a high degree of reliability of the measurement data.

The validity, also known as accuracy, reflects how close the measurement result is to the “true value”. Validity includes structure validity, content validity, convergent validity, and discriminative validity. Because the experiment is a small sample study, we cannot do any specific factorization. KMO and Bartlett sphericity test values are an important part of structural validity. Indicator, general validity evaluation (KMO value above 0.9, indicating very good validity; 0.8–0.9, indicating good validity; 0.7–0.8 validity is good; 0.6–0.7 validity is acceptable; 0.5–0.6 means poor validity; below 0.45 means that some items should be abandoned.

Table 3 shows that the KMO values of ability, effort, environment, control, interest, belief, and the total questionnaire are 0.911, 0.812, 0.778, 0.825, 0.779, 0.850, 0.613, and the KMO values of the post-test are respectively. The KMO values are 0.887, 0.775, 0.892, 0.868, 0.862, 0.883, 0.715. KMO values are basically above 0.8, and all are greater than 0.6. This result indicates that the validity is acceptable, the scale has a high degree of reasonableness, and the valid data.

In the graphic design and production (professional design course), we will learn the practical software with cases. After class, we will share knowledge on the self-media platform. We will give face-to-face computer instruction offline from 8:00 to 11:20 every Wednesday morning for 16 weeks. China's top online sharing platform (APP) is Tik Tok, micro-blog (Micro Blog) and Xiao hong shu. The experiment began on September 1, 2022, and conducted the pre-questionnaire survey simultaneously. At the end of the course, on January 6, 2023, the post questionnaire survey was conducted. A total of 74 questionnaires were distributed in this study, recovered 74 questionnaires. After excluding the invalid questionnaires with incomplete filling and wrong answers, 68 valid questionnaires were obtained, with an effective rate of 91%, meeting the test requirements. Then, use the social science analysis software SPSS Statistics 26 to analyze the data: (1) descriptive statistical analysis of the dimensions of learning self-efficacy; (2) Using correlation test to analyze the correlation between learning self-efficacy and the use of social media; (3) This study used a comparative analysis of group differences to detect the influence of learning self-efficacy on various dimensions of social media and design courses. For data processing and analysis, use the spss26 version software and frequency statistics to create statistics on the basic situation of the research object and the basic situation of the use of live broadcast. The reliability scale analysis (internal consistency test) and use Bartlett's sphericity test to illustrate the reliability and validity of the questionnaire and the individual differences between the control group and the experimental group in demographic variables (gender, grade, Major, self-study time per day) are explained by cross-analysis (chi-square test). In the experimental group and the control group, the pre-test, post-test, before-and-after test of the experimental group and the control group adopt independent sample T-test and paired sample T-test to illustrate the effect of the experimental intervention (The significance level of the test is 0.05 two-sided).

Results and discussion

Comparison of pre-test and post-test between groups.

To study whether the data of the experimental group and the control group are significantly different in the pre-test and post-test mean of sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief. The research for this situation uses an independent sample T-test and an independent sample. The test needs to meet some false parameters, such as normality requirements. Generally passing the normality test index requirements are relatively strict, so it can be relaxed to obey an approximately normal distribution. If there is serious skewness distribution, replace it with the nonparametric test. Variables are required to be continuous variables. The six variables in this study define continuous variables. The variable value information is independent of each other. Therefore, we use the independent sample T-test.

From the Table 4 , a pre-test found that there was no statistically significant difference between the experimental group and the control group at the 0.05 confidence level ( p  > 0.05) for perceptions of sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief. Before the experiment, the two groups of test groups have the same quality in measuring self-efficacy. The experimental class and the control class are homogeneous groups. Table 5 shows the independent samples t-test for the post-test, used to compare the experimental and control groups on six items, including the sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief.

The experimental and control groups have statistically significant scores ( p  < 0.05) for sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief, and the experimental and control groups have statistically significant scores (t = 3.177, p  = 0.002) for a sense of competence. (t = 3.177, p  = 0.002) at the 0.01 level, with the experimental group scoring significantly higher (3.91 ± 0.51) than the control group (3.43 ± 0.73). The experimental group and the control group showed significance for the perception of effort at the 0.01 confidence level (t = 2.911, p  = 0.005), with the experimental group scoring significantly higher (3.88 ± 0.66) than the control group scoring significantly higher (3.31 ± 0.94). The experimental and control groups show significance at the 0.05 level (t = 2.451, p  = 0.017) for the sense of environment, with the experimental group scoring significantly higher (3.95 ± 0.61) than the control group scoring significantly higher (3.58 ± 0.62). The experimental and control groups showed significance for sense of control at the 0.05 level of significance (t = 2.524, p  = 0.014), and the score for the experimental group (3.76 ± 0.67) would be significantly higher than the score for the control group (3.31 ± 0.78). The experimental and control groups showed significance at the 0.01 level for sense of interest (t = 2.842, p  = 0.006), and the experimental group's score (3.87 ± 0.61) would be significantly higher than the control group's score (3.39 ± 0.77). The experimental and control groups showed significance at the 0.01 level for the sense of belief (t = 3.377, p  = 0.001), and the experimental group would have scored significantly higher (4.04 ± 0.52) than the control group (3.56 ± 0.65). Therefore, we can conclude that the experimental group's post-test significantly affects the mean scores of sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief. A social media-assisted course has a positive impact on students' self-efficacy.

Comparison of pre-test and post-test of each group

The paired-sample T-test is an extension of the single-sample T-test. The purpose is to explore whether the means of related (paired) groups are significantly different. There are four standard paired designs: (1) Before and after treatment of the same subject Data, (2) Data from two different parts of the same subject, (3) Test results of the same sample with two methods or instruments, 4. Two matched subjects receive two treatments, respectively. This study belongs to the first type, the 6 learning self-efficacy dimensions of the experimental group and the control group is measured before and after different periods.

Paired t-tests is used to analyze whether there is a significant improvement in the learning self-efficacy dimension in the experimental group after the experimental social media-assisted course intervention. In Table 6 , we can see that the six paired data groups showed significant differences ( p  < 0.05) in the pre and post-tests of sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief. There is a level of significance of 0.01 (t = − 4.540, p  = 0.000 < 0.05) before and after the sense of ability, the score after the sense of ability (3.91 ± 0.51), and the score before the Sense of ability (3.41 ± 0.55). The level of significance between the pre-test and post-test of sense of effort is 0.01 (t = − 4.002, p  = 0.000). The score of the sense of effort post-test (3.88 ± 0.66) will be significantly higher than the average score of the sense of effort pre-test (3.31 ± 0.659). The significance level between the pre-test and post-test Sense of environment is 0.01 (t = − 3.897, p  = 0.000). The average score for post- Sense of environment (3.95 ± 0.61) will be significantly higher than that of sense of environment—the average score of the previous test (3.47 ± 0.44). The average value of a post- sense of control (3.76 ± 0.67) will be significantly higher than the average of the front side of the Sense of control value (3.27 ± 0.52). The sense of interest pre-test and post-test showed a significance level of 0.01 (− 4.765, p  = 0.000), and the average value of Sense of interest post-test was 3.87 ± 0.61. It would be significantly higher than the average value of the Sense of interest (3.25 ± 0.59), the significance between the pre-test and post-test of belief sensing is 0.01 level (t = − 3.939, p  = 0.000). Thus, the average value of a post-sense of belief (4.04 ± 0.52) will be significantly higher than that of a pre-sense of belief Average value (3.58 ± 0.58). After the experimental group’s post-test, the scores for the Sense of ability, effort, environment, control, interest, and belief before the comparison experiment increased significantly. This result has a significant improvement effect. Table 7 shows that the control group did not show any differences in the pre and post-tests using paired t-tests on the dimensions of learning self-efficacy such as sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief ( p  > 0.05). It shows no experimental intervention for the control group, and it does not produce a significant effect.

The purpose of this study aims to explore the impact of social media use on college students' learning self-efficacy, examine the changes in the elements of college students' learning self-efficacy before and after the experiment, and make an empirical study to enrich the theory. This study developed an innovative design for course teaching methods using the ADDIE model. The design process followed a series of model rules of analysis, design, development, implementation, and evaluation, as well as conducted a descriptive statistical analysis of the learning self-efficacy of design undergraduates. Using questionnaires and data analysis, the correlation between the various dimensions of learning self-efficacy is tested. We also examined the correlation between the two factors, and verifies whether there was a causal relationship between the two factors.

Based on prior research and the results of existing practice, a learning self-efficacy is developed for university students and tested its reliability and validity. The scale is used to pre-test the self-efficacy levels of the two subjects before the experiment, and a post-test of the self-efficacy of the two groups is conducted. By measuring and investigating the learning self-efficacy of the study participants before the experiment, this study determined that there was no significant difference between the experimental group and the control group in terms of sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief. Before the experiment, the two test groups had homogeneity in measuring the dimensionality of learning self-efficacy. During the experiment, this study intervened in social media assignments for the experimental group. The experiment used learning methods such as network assignments, mutual aid communication, mutual evaluation of assignments, and group discussions. After the experiment, the data analysis showed an increase in learning self-efficacy in the experimental group compared to the pre-test. With the test time increased, the learning self-efficacy level of the control group decreased slightly. It shows that social media can promote learning self-efficacy to a certain extent. This conclusion is similar to Cao et al. 18 , who suggested that social media would improve educational outcomes.

We have examined the differences between the experimental and control group post-tests on six items, including the sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief. This result proves that a social media-assisted course has a positive impact on students' learning self-efficacy. Compared with the control group, students in the experimental group had a higher interest in their major. They showed that they liked to share their learning experiences and solve difficulties in their studies after class. They had higher motivation and self-directed learning ability after class than students in the control group. In terms of a sense of environment, students in the experimental group were more willing to share their learning with others, speak boldly, and participate in the environment than students in the control group.

The experimental results of this study showed that the experimental group showed significant improvement in the learning self-efficacy dimensions after the experimental intervention in the social media-assisted classroom, with significant increases in the sense of ability, sense of effort, sense of environment, sense of control, sense of interest and sense of belief compared to the pre-experimental scores. This result had a significant improvement effect. Evidence that a social media-assisted course has a positive impact on students' learning self-efficacy. Most of the students recognized the impact of social media on their learning self-efficacy, such as encouragement from peers, help from teachers, attention from online friends, and recognition of their achievements, so that they can gain a sense of achievement that they do not have in the classroom, which stimulates their positive perception of learning and is more conducive to the awakening of positive effects. This phenomenon is in line with Ajjan and Hartshorne 2 . They argue that social media provides many opportunities for learners to publish their work globally, which brings many benefits to teaching and learning. The publication of students' works online led to similar positive attitudes towards learning and improved grades and motivation. This study also found that students in the experimental group in the post-test controlled their behavior, became more interested in learning, became more purposeful, had more faith in their learning abilities, and believed that their efforts would be rewarded. This result is also in line with Ajjan and Hartshorne's (2008) indication that integrating Web 2.0 technologies into classroom learning environments can effectively increase students' satisfaction with the course and improve their learning and writing skills.

We only selected students from one university to conduct a survey, and the survey subjects were self-selected. Therefore, the external validity and generalizability of our study may be limited. Despite the limitations, we believe this study has important implications for researchers and educators. The use of social media is the focus of many studies that aim to assess the impact and potential of social media in learning and teaching environments. We hope that this study will help lay the groundwork for future research on the outcomes of social media utilization. In addition, future research should further examine university support in encouraging teachers to begin using social media and university classrooms in supporting social media (supplementary file 1 ).

The present study has provided preliminary evidence on the positive association between social media integration in education and increased learning self-efficacy among college students. However, several avenues for future research can be identified to extend our understanding of this relationship.

Firstly, replication studies with larger and more diverse samples are needed to validate our findings across different educational contexts and cultural backgrounds. This would enhance the generalizability of our results and provide a more robust foundation for the use of social media in teaching. Secondly, longitudinal investigations should be conducted to explore the sustained effects of social media use on learning self-efficacy. Such studies would offer insights into how the observed benefits evolve over time and whether they lead to improved academic performance or other relevant outcomes. Furthermore, future research should consider the exploration of potential moderators such as individual differences in students' learning styles, prior social media experience, and psychological factors that may influence the effectiveness of social media in education. Additionally, as social media platforms continue to evolve rapidly, it is crucial to assess the impact of emerging features and trends on learning self-efficacy. This includes an examination of advanced tools like virtual reality, augmented reality, and artificial intelligence that are increasingly being integrated into social media environments. Lastly, there is a need for research exploring the development and evaluation of instructional models that effectively combine traditional teaching methods with innovative uses of social media. This could guide educators in designing courses that maximize the benefits of social media while minimizing potential drawbacks.

In conclusion, the current study marks an important step in recognizing the potential of social media as an educational tool. Through continued research, we can further unpack the mechanisms by which social media can enhance learning self-efficacy and inform the development of effective educational strategies in the digital age.

Data availability

The data that support the findings of this study are available from the corresponding authors upon reasonable request. The data are not publicly available due to privacy or ethical restrictions.

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Acknowledgements

This work is supported by the 2023 Guangxi University Young and middle-aged Teachers' Basic Research Ability Enhancement Project—“Research on Innovative Communication Strategies and Effects of Zhuang Traditional Crafts from the Perspective of the Metaverse” (Grant Nos. 2023KY0385), and the special project on innovation and entrepreneurship education in universities under the “14th Five-Year Plan” for Guangxi Education Science in 2023, titled “One Core, Two Directions, Three Integrations - Strategy and Practical Research on Innovation and Entrepreneurship Education in Local Universities” (Grant Nos. 2023ZJY1955), and the 2023 Guangxi Higher Education Undergraduate Teaching Reform General Project (Category B) “Research on the Construction and Development of PBL Teaching Model in Advertising” (Grant Nos.2023JGB294), and the 2022 Guangxi Higher Education Undergraduate Teaching Reform Project (General Category A) “Exploration and Practical Research on Public Art Design Courses in Colleges and Universities under Great Aesthetic Education” (Grant Nos. 2022JGA251), and the 2023 Guangxi Higher Education Undergraduate Teaching Reform Project Key Project “Research and Practice on the Training of Interdisciplinary Composite Talents in Design Majors Based on the Concept of Specialization and Integration—Taking Guangxi Institute of Traditional Crafts as an Example” (Grant Nos. 2023JGZ147), and the2024 Nanning Normal University Undergraduate Teaching Reform Project “Research and Practice on the Application of “Guangxi Intangible Cultural Heritage” in Packaging Design Courses from the Ideological and Political Perspective of the Curriculum” (Grant Nos. 2024JGX048),and the 2023 Hubei Normal University Teacher Teaching Reform Research Project (Key Project) -Curriculum Development for Improving Pre-service Music Teachers' Teaching Design Capabilities from the Perspective of OBE (Grant Nos. 2023014), and the 2023 Guangxi Education Science “14th Five-Year Plan” special project: “Specialized Integration” Model and Practice of Art and Design Majors in Colleges and Universities in Ethnic Areas Based on the OBE Concept (Grant Nos. 2023ZJY1805), and the 2024 Guangxi University Young and Middle-aged Teachers’ Scientific Research Basic Ability Improvement Project “Research on the Integration Path of University Entrepreneurship and Intangible Inheritance - Taking Liu Sanjie IP as an Example” (Grant Nos. 2024KY0374), and the 2022 Research Project on the Theory and Practice of Ideological and Political Education for College Students in Guangxi - “Party Building + Red”: Practice and Research on the Innovation of Education Model in College Student Dormitories (Grant Nos. 2022SZ028), and the 2021 Guangxi University Young and Middle-aged Teachers’ Scientific Research Basic Ability Improvement Project - "Research on the Application of Ethnic Elements in the Visual Design of Live Broadcast Delivery of Guangxi Local Products" (Grant Nos. 2021KY0891).

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The contribution of H. to this paper primarily lies in research design and experimental execution. H. was responsible for the overall framework design of the paper, setting research objectives and methods, and actively participating in data collection and analysis during the experimentation process. Furthermore, H. was also responsible for conducting literature reviews and played a crucial role in the writing and editing phases of the paper. L.'s contribution to this paper primarily manifests in theoretical derivation and the discussion section. Additionally, author L. also proposed future research directions and recommendations in the discussion section, aiming to facilitate further research explorations. Y.'s contribution to this paper is mainly reflected in data analysis and result interpretation. Y. was responsible for statistically analyzing the experimental data and employing relevant analytical tools and techniques to interpret and elucidate the data results.

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Hu, J., Lai, Y. & Yi, X. Effectiveness of social media-assisted course on learning self-efficacy. Sci Rep 14 , 10112 (2024). https://doi.org/10.1038/s41598-024-60724-0

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DOI : https://doi.org/10.1038/s41598-024-60724-0

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Title: is in-context learning a type of gradient-based learning evidence from the inverse frequency effect in structural priming.

Abstract: Large language models (LLMs) have shown the emergent capability of in-context learning (ICL). One line of research has explained ICL as functionally performing gradient descent. In this paper, we introduce a new way of diagnosing whether ICL is functionally equivalent to gradient-based learning. Our approach is based on the inverse frequency effect (IFE) -- a phenomenon in which an error-driven learner is expected to show larger updates when trained on infrequent examples than frequent ones. The IFE has previously been studied in psycholinguistics because humans show this effect in the context of structural priming (the tendency for people to produce sentence structures they have encountered recently); the IFE has been used as evidence that human structural priming must involve error-driven learning mechanisms. In our experiments, we simulated structural priming within ICL and found that LLMs display the IFE, with the effect being stronger in larger models. We conclude that ICL is indeed a type of gradient-based learning, supporting the hypothesis that a gradient component is implicitly computed in the forward pass during ICL. Our results suggest that both humans and LLMs make use of gradient-based, error-driven processing mechanisms.

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Shreya Maji

Shreya Maji is a consulting intern at MarktechPost. She is pursued her B.Tech at the Indian Institute of Technology (IIT), Bhubaneswar. An AI enthusiast, she enjoys staying updated on the latest advancements. Shreya is particularly interested in the real-life applications of cutting-edge technology, especially in the field of data science.

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