Jason Jabbari, Yung Chun, Wenrui Huang, Stephen Roll
October 2023
Researchers found that program acceptance was significantly associated with increased earnings and probabilities of working in a science, technology, engineering, and math (STEM) profession.
Robert R. Martinez, Jr., James M. Ellis
September 2023
Researchers found that STEM-CR involves four related yet distinct dimensions of Think, Know, Act, and Go. Results also demonstrated soundness of these STEM-CR dimensions by race and gender (key learning skills and techniques/Act).
Rosemary J. Perez, Rudisang Motshubi, Sarah L. Rodriguez
April 2023
Researchers found that because participants did not attend to how racism and White supremacy fostered negative climate, their strategies (e.g., increased recruitment, committees, workshops) left systemic racism intact and (un)intentionally amplified labor for racially minoritized graduate students and faculty champions who often led change efforts with little support.
Kathleen Lynch, Lily An, Zid Mancenido
, July 2022
Researchers found an average weighted impact estimate of +0.10 standard deviations on mathematics achievement outcomes.
Luis A. Leyva, R. Taylor McNeill, B R. Balmer, Brittany L. Marshall, V. Elizabeth King, Zander D. Alley
, May 2022
Researchers address this research gap by exploring four Black queer students’ experiences of oppression and agency in navigating invisibility as STEM majors.
Angela Starrett, Matthew J. Irvin, Christine Lotter, Jan A. Yow
, May 2022
Researchers found that the more place-based workforce development adolescents reported, the higher their expectancy beliefs, STEM career interest, and rural community aspirations.
Matthew H. Rafalow, Cassidy Puckett
May 2022
Researchers found that educational resources, like digital technologies, are also sorted by schools.
Pamela Burnard, Laura Colucci-Gray, Carolyn Cooke
April 2022
This article makes a case for repositioning STEAM education as democratized enactments of transdisciplinary education, where arts and sciences are not separate or even separable endeavors.
Salome Wörner, Jochen Kuhn, Katharina Scheiter
, April 2022
Researchers conclude that for combining real and virtual experiments, apart from the individual affordances and the learning objectives of the different experiment types, especially their specific function for the learning task must be considered.
Seung-hyun Han, Eunjung Grace Oh, Sun “Pil” Kang
April 2022
Researchers found that the knowledge sharing mechanism and student learning outcomes can be explained in terms of their social capital within social networks.
Barbara Schneider, Joseph Krajcik, Jari Lavonen, Katariina Salmela-Aro, Christopher Klager, Lydia Bradford, I-Chien Chen, Quinton Baker, Israel Touitou, Deborah Peek-Brown, Rachel Marias Dezendorf, Sarah Maestrales, Kayla Bartz
March 2022
Researchers found that improving secondary school science learning is achievable with a coherent system comprising teacher and student learning experiences, professional learning, and formative unit assessments that support students in “doing” science.
Paulo Tan, Alexis Padilla, Rachel Lambert
, March 2022
Researchers found that studies continue to avoid meaningful intersectional considerations of race and disability.
Ta-yang Hsieh, Sandra D. Simpkins
March 2022
Researchers found patterns with overall high/low beliefs, patterns with varying levels of motivational beliefs, and patterns characterized by domain differentiation.
Jonté A. Myers, Bradley S. Witzel, Sarah R. Powell, Hongli Li, Terri D. Pigott, Yan Ping Xin, Elizabeth M. Hughes
, February 2022
Findings of meta-regression analyses showed several moderators, such as sample composition, group size, intervention dosage, group assignment approach, interventionist, year of publication, and dependent measure type, significantly explained heterogeneity in effects across studies.
Grace A. Chen, Ilana S. Horn
, January 2022
The findings from this review highlight the interconnectedness of structures and individual lives, of the material and ideological elements of marginalization, of intersectionality and within-group heterogeneity, and of histories and institutions.
Victor R. Lee, Michelle Hoda Wilkerson, Kathryn Lanouette
December 2021
Researchers offer an interdisciplinary framework based on literature from multiple bodies of educational research to inform design, teaching and research for more effective, responsible, and inclusive student learning experiences with and about data.
Ido Davidesco, Camillia Matuk, Dana Bevilacqua, David Poeppel, Suzanne Dikker
December 2021
This essay critically evaluates the value added by portable brain technologies in education research and outlines a proposed research agenda, centered around questions related to student engagement, cognitive load, and self-regulation.
Guan K. Saw, Charlotte A. Agger
December 2021
Researchers found that during high school rural and small-town students shifted away from STEM fields and that geographic disparities in postsecondary STEM participation were largely explained by students’ demographics and precollege STEM career aspirations and academic preparation.
Kyle M. Whitcomb, Sonja Cwik, Chandralekha Singh
November 2021
Researchers found that on average across all years of study, underrepresented minority (URM) students experience a larger penalty to their mean overall and STEM GPA than even the most disadvantaged non-URM students.
Lana M. Minshew, Amanda A. Olsen, Jacqueline E. McLaughlin
, October 2021
Researchers found that the CA framework is a useful and effective model for supporting faculty in cultivating rich learning opportunities for STEM graduate students.
Xin Lin, Sarah R. Powell
, October 2021
Findings suggested fluency in both mathematics and reading, as well as working memory, yielded greater impacts on subsequent mathematics performance.
Christine L. Bae, Daphne C. Mills, Fa Zhang, Martinique Sealy, Lauren Cabrera, Marquita Sea
, September 2021
This systematic literature review is guided by a complex systems framework to organize and synthesize empirical studies of science talk in urban classrooms across individual (student or teacher), collective (interpersonal), and contextual (sociocultural, historical) planes.
Toya Jones Frank, Marvin G. Powell, Jenice L. View, Christina Lee, Jay A. Bradley, Asia Williams
August/September 2021
Researchers found that teachers’ experiences of microaggressions accounted for most of the variance in our modeling of teachers’ thoughts of leaving the profession.
Ebony McGee, Yuan Fang, Yibin (Amanda) Ni, Thema Monroe-White
August 2021
Researchers found that 40.7% of the respondents reported that their career plans have been affected by Trump’s antiscience policies, 54.5% by the COVID-19 pandemic.
Martha Cecilia Bottia, Roslyn Arlin Mickelson, Cayce Jamil, Kyleigh Moniz, Leanne Barry
, May 2021
Consistent with cumulative disadvantage and critical race theories, findings reveal that the disproportionality of racially minoritized students in STEM is related to their inferior secondary school preparation; the presence of racialized lower quality educational contexts; reduced levels of psychosocial factors associated with STEM success; less exposure to inclusive and appealing curricula and instruction; lower levels of family social, cultural, and financial capital that foster academic outcomes; and fewer prospects for supplemental STEM learning opportunities. Policy implications of findings are discussed.
Iris Daruwala, Shani Bretas, Douglas D. Ready
April 2021
Researchers describe how teachers, school leaders, and program staff navigated institutional pressures to improve state grade-level standardized test scores while implementing tasks and technologies designed to personalize student learning.
Michael A. Gottfried, Jay Plasman, Jennifer A. Freeman, Shaun Dougherty
March 2021
Researchers found that students with learning disabilities were more likely to earn more units in CTE courses compared with students without disabilities.
Ebony Omotola McGee
December 2020
This manuscript also discusses how universities institutionalize diversity mentoring programs designed mostly to fix (read “assimilate”) underrepresented students of color while ignoring or minimizing the role of the STEM departments in creating racially hostile work and educational spaces.
Miray Tekkumru-Kisa, Mary Kay Stein, Walter Doyle
November 2020
The purpose of this article is to revisit theory and research on tasks, a construct introduced by Walter Doyle nearly 40 years ago.
Elizabeth S. Park, Federick Ngo
November 2020
Researchers found that lower math placement may have supported women, and to a lesser extent URM students, in completing transferable STEM credits.
Karisma Morton, Catherine Riegle-Crumb
August/September 2020
Results of regression analyses reveal that, net of school, teacher, and student characteristics, the time that teachers report spending on algebra and more advanced content in eighth grade algebra classes is significantly lower in schools that are predominantly Black compared to those that are not predominantly minority. Implications for future research are discussed.
Qi Zhang, Jessaca Spybrook, Fatih Unlu
, July 2020
Researchers consider strategies to maximize the efficiency of the study design when both student and teacher effects are of primary interest.
Jennifer Lin Russell, Richard Correnti, Mary Kay Stein, Ally Thomas, Victoria Bill, Laurie Speranzo
, July 20, 2020
Analysis of videotaped coaching conversations and teaching events suggests that model-trained coaches improved their capacity to use a high-leverage coaching practice—deep and specific prelesson planning conversations—and that growth in this practice predicted teaching improvement, specifically increased opportunities for students to engage in conceptual thinking.
Maithreyi Gopalan, Kelly Rosinger, Jee Bin Ahn
, April 21, 2020
The overarching purpose of this chapter is to explore and document the growth, applicability, promise, and limitations of quasi-experimental research designs in education research.
Thomas M. Philip, Ayush Gupta
, April 21, 2020
By bringing this collection of articles together, this chapter provides collective epistemic and empirical weight to claims of power and learning as co-constituted and co-constructed through interactional, microgenetic, and structural dynamics.
Steve Graham, Sharlene A. Kiuhara, Meade MacKay
, March 19, 2020
This meta-analysis examined if students writing about content material in science, social studies, and mathematics facilitated learning.
Janina Roloff, Uta Klusmann, Oliver Lüdtke, Ulrich Trautwein
, January 2020
Multilevel regression analyses revealed that agreeableness, high school GPA, and the second state examination grade predicted teachers’ instructional quality.
: Contemporary Views on STEM Subjects and Language With English Learners
Okhee Lee, Amy Stephens
, 2020
With the release of the consensus report , the authors highlight foundational constructs and perspectives associated with STEM subjects and language with English learners that frame the report.
Angela Calabrese Barton and Edna Tan
, 2020
This essay presents a rightful presence framework to guide the study of teaching and learning in justice-oriented ways.
Day Greenberg, Angela Calabrese Barton, Carmen Turner, Kelly Hardy, Akeya Roper, Candace Williams, Leslie Rupert Herrenkohl, Elizabeth A. Davis, Tammy Tasker
, 2020
Researchers report on how one community builds capacity for disrupting injustice and supporting each other during the COVID-19 crisis.
Tatiana Melguizo, Federick Ngo
, 2020
This study explores the extent to which “college-ready” students, by high school standards, are assigned to remedial courses in college.
Karisma Morton and Catherine Riegle-Crumb
, 2020
Results of regression analyses reveal that, net of school, teacher, and student characteristics, the time that teachers report spending on algebra and more advanced content in eighth grade algebra classes is significantly lower in schools that are predominantly Black compared to those that are not predominantly minority. Implications for future research are discussed.
Jonathan D. Schweig, Julia H. Kaufman, and V. Darleen Opfer
, 2020
Researchers found that there are both substantial fluctuations in students’ engagement in these practices and reported cognitive demand from day to day, as well as large differences across teachers.
David Blazar and Casey Archer
, 2020
Researchers found that exposure to “ambitious” mathematics practices is more strongly associated with test score gains of English language learners compared to those of their peers in general education classrooms.
Megan Hopkins, Hayley Weddle, Maxie Gluckman, Leslie Gautsch
, December 2019
Researchers show how both researchers and practitioners facilitated research use.
Adrianna Kezar, Samantha Bernstein-Sierra
, October 2019
Findings suggest that Association of American Universities’ influence was a powerful motivator for institutions to alter deeply ingrained perceptions and behaviors.
Denis Dumas, Daniel McNeish, Julie Sarama, Douglas Clements
, October 2019
While students who receive a short-term intervention in preschool may not differ from a control group in terms of their long-term mathematics outcomes at the end of elementary school, they do exhibit significantly steeper growth curves as they approach their eventual skill level.
Jessica Thompson, Jennifer Richards, Soo-Yean Shim, Karin Lohwasser, Kerry Soo Von Esch, Christine Chew, Bethany Sjoberg, Ann Morris
, September 2019
Researchers used data from professional learning communities to analyze pathways into improvement work and reflective data to understand practitioners’ perspectives.
Ross E. O’Hara, Betsy Sparrow
, September 2019
Results indicate that interventions that target psychosocial barriers experienced by community college STEM students can increase retention and should be considered alongside broader reforms.
Ran Liu, Andrea Alvarado-Urbina, Emily Hannum
, September 2019
Findings reveal disparate national patterns in gender gaps across the performance distribution.
Adam Kirk Edgerton
, September 2019
Through an analysis of 52 interviews with state, regional, and district officials in California, Texas, Ohio, Pennsylvania, and Massachusetts, the author investigates the decline in the popularity of K–12 standards-based reform.
Amy Noelle Parks
, September 2019
The study suggests that more research needs to represent mathematics lessons from the perspectives of children and youth, particularly those students who engage with teachers infrequently or in atypical ways.
Rajeev Darolia, Cory Koedel, Joyce B. Main, J. Felix Ndashimye, Junpeng Yan
, September 30, 2019
Researchers found that differential access to high school courses does not affect postsecondary STEM enrollment or degree attainment.
Laura A. Davis, Gregory C. Wolniak, Casey E. George, Glen R. Nelson
, August 2019
The findings point to variation in informational quality across dimensions ranging from clarity of language use and terminology, to consistency and coherence of visual displays, which accompany navigational challenges stemming from information fragmentation and discontinuity across pages.
Juan E. Saavedra, Emma Näslund-Hadley, Mariana Alfonso
, August 12, 2019
Researchers present results from the first randomized experiment of a remedial inquiry-based science education program for low-performing elementary students in a developing country.
F. Chris Curran, James Kitchin
, July 2019
Researchers found suggestive evidence in some models (student fixed effects and regression with observable controls) that time on science instruction is related to science achievement but little evidence that the number of science topics/skills covered are related to greater science achievement.
Kathleen Lynch, Heather C. Hill, Kathryn E. Gonzalez, Cynthia Pollard
, June 2019
Programs saw stronger outcomes when they helped teachers learn to use curriculum materials; focused on improving teachers’ content knowledge, pedagogical content knowledge, and/or understanding of how students learn; incorporated summer workshops; and included teacher meetings to troubleshoot and discuss classroom implementation. We discuss implications for policy and practice.
Elizabeth Stearns, Martha Cecilia Bottia, Jason Giersch, Roslyn Arlin Mickelson, Stephanie Moller, Nandan Jha, Melissa Dancy
, June 2019
Researchers found that relative advantages in college academic performance in STEM versus non-STEM subjects do not contribute to the gender gap in STEM major declaration.
Nicole Shechtman, Jeremy Roschelle, Mingyu Feng, Corinne Singleton
, May 2019
As educational leaders throughout the United States adopt digital mathematics curricula and adaptive, blended approaches, the findings provide a relevant caution.
Colleen M. Ganley, Robert C. Schoen, Mark LaVenia, Amanda M. Tazaz
, March 2019
Factor analyses support a distinction between components of general math anxiety and anxiety about teaching math.
Felicia Moore Mensah
, February 2019
The implications for practice in both teacher education and science education show that educational and emotional support for teachers of color throughout their educational and professional journey is imperative to increasing and sustaining Black teachers.
Herbert W. Marsh, Brooke Van Zanden, Philip D. Parker, Jiesi Guo, James Conigrave, Marjorie Seaton
, February 2019
Researchers evaluated STEM coursework selection by women and men in senior high school and university, controlling achievement and expectancy-value variables.
Yasemin Copur-Gencturk, Debra Plowman, Haiyan Bai
, January 2019
The results showed that a focus on curricular content knowledge and examining students’ work were significantly related to teachers’ learning.
Rebecca Colina Neri, Maritza Lozano, Louis M. Gomez
, 2019
Researchers found that teacher resistance to CRE as a multilevel learning problem stems from (a) limited understanding and belief in the efficacy of CRE and (b) a lack of know-how needed to execute it.
Russell T. Warne, Gerhard Sonnert, and Philip M. Sadler
, 2019
Researchers investigated the relationship between participation in AP mathematics courses (AP Calculus and AP Statistics) and student career interest in STEM.
Catherine Riegle-Crumb, Barbara King, and Yasmiyn Irizarry
, 2019
Results reveal evidence of persistent racial/ethnic inequality in STEM degree attainment not found in other fields.
Eben B. Witherspoon, Paulette Vincent-Ruz, and Christian D. Schunn
, 2019
Researchers found that high-performing women often graduate with lower paying, lower status degrees.
Bruce Fuller, Yoonjeon Kim, Claudia Galindo, Shruti Bathia, Margaret Bridges, Greg J. Duncan, and Isabel García Valdivia
, 2019
This article details the growing share of Latino children from low-income families populating schools, 1998 to 2010.
Rebekka Darner
, 2019
Drawing from motivated reasoning and self-determination theories, this essay builds a theoretical model of how negative emotions, thwarting of basic psychological needs, and the backfire effect interact to undermine critical evaluation of evidence, leading to science denial.
Okhee Lee
, 2019
As the fast-growing population of English learners (ELs) is expected to meet college- and career-ready content standards, the purpose of this article is to highlight key issues in aligning ELP standards with content standards.
Mark C. Long, Dylan Conger, and Raymond McGhee, Jr.
, 2019
The authors offer the first model of the components inherent in a well-implemented AP science course and the first evaluation of AP implementation with a focus on public schools newly offering the inquiry-based version of AP Biology and Chemistry courses.
Yasemin Copur-Gencturk, Joseph R. Cimpian, Sarah Theule Lubienski, and Ian Thacker
, 2019
Results indicate that teachers are not free of bias, and that teachers from marginalized groups may be susceptible to bias that favors stereotype-advantaged groups.
Geoffrey B. Saxe and Joshua Sussman
, 2019
Multilevel analysis of longitudinal data on a specialized integers and fractions assessment, as well as a California state mathematics assessment, revealed that the ELs in LMR classrooms showed greater gains than comparison ELs and gained at similar rates to their EP peers in LMR classrooms.
Jordan Rickles, Jessica B. Heppen, Elaine Allensworth, Nicholas Sorensen, and Kirk Walters
, 2019
The authors discuss whether it would have been appropriate to test for nominally equivalent outcomes, given that the study was initially conceived and designed to test for significant differences, and that the conclusion of no difference was not solely based on a null hypothesis test.
Soobin Kim, Gregory Wallsworth, Ran Xu, Barbara Schneider, Kenneth Frank, Brian Jacob, Susan Dynarski
, 2019
Using detailed Michigan high school transcript data, this article examines the effect of the MMC on various students’ course-taking and achievement outcomes.
Dario Sansone
, December 2018
Researchers found that students were less likely to believe that men were better than women in math or science when assigned to female teachers or to teachers who valued and listened to ideas from their students.
Ebony McGee
, December 2018
The authors argues that both racial groups endure emotional distress because each group responds to its marginalization with an unrelenting motivation to succeed that imposes significant costs.
Barbara Means, Haiwen Wang, Xin Wei, Emi Iwatani, Vanessa Peters
, November 2018
Students overall and from under-represented groups who had attended inclusive STEM high schools were significantly more likely to be in a STEM bachelor’s degree program two years after high school graduation.
Paulo Tan, Kathleen King Thorius
, November 2018
Results indicate identity and power tensions that worked against equitable practices.
Caesar R. Jackson
, November 2018
This study investigated the validity and reliability of the Motivated Strategies for Learning Questionnaire (MSLQ) for minority students enrolled in STEM courses at a historically black college/university (HBCU).
Tuan D. Nguyen, Christopher Redding
, September 2018
The results highlight the importance of recruiting qualified STEM teachers to work in high-poverty schools and providing supports to help them thrive and remain in the classroom.
Joseph A. Taylor, Susan M. Kowalski, Joshua R. Polanin, Karen Askinas, Molly A. M. Stuhlsatz, Christopher D. Wilson, Elizabeth Tipton, Sandra Jo Wilson
, August 2018
The meta-analysis examines the relationship between science education intervention effect sizes and a host of study characteristics, allowing primary researchers to access better estimates of effect sizes for a priori power analyses. The results of this meta-analysis also support programmatic decisions by setting realistic expectations about the typical magnitude of impacts for science education interventions.
Brian A. Burt, Krystal L. Williams, Gordon J. M. Palmer
, August 2018
Three factors are identified as helping them persist from year to year, and in many cases through completion of the doctorate: the role of family, spirituality and faith-based community, and undergraduate mentors.
Anna-Lena Rottweiler, Jamie L. Taxer, Ulrike E. Nett
, June 2018
Suppression improved mood in exam-related anxiety, while distraction improved mood only in non-exam-related anxiety.
Gabriel Estrella, Jacky Au, Susanne M. Jaeggi, Penelope Collins
, April 2018
Although an analysis of 26 articles confirmed that inquiry instruction produced significantly greater impacts on measures of science achievement for ELLs compared to direct instruction, there was still a differential learning effect suggesting greater efficacy for non-ELLs compared to ELLs.
Heather C. Hill, Mark Chin
, April 2018
In this article, evidence from 284 teachers suggests that accuracy can be adequately measured and relates to instruction and student outcomes.
Darrell M. Hull, Krystal M. Hinerman, Sarah L. Ferguson, Qi Chen, Emma I. Näslund-Hadley
, April 20, 2018
Both quantitative and qualitative evidence suggest students within this culture respond well to this relatively simple and inexpensive intervention that departs from traditional, expository math instruction in many developing countries.
Erika C. Bullock
, April 2018
The author reviews CME studies that employ intersectionality as a way of analyzing the complexities of oppression.
Angela Calabrese Barton, Edna Tan
, March 2018
Building a conceptual argument for an equity-oriented culture of making, the authors discuss the ways in which making with and in community opened opportunities for youth to project their communities’ rich culture knowledge and wisdom onto their making while also troubling and negotiating the historicized injustices they experience.
Sabrina M. Solanki, Di Xu
, March 2018
Researchers found that having a female instructor narrows the gender gap in terms of engagement and interest; further, both female and male students tend to respond to instructor gender.
Susanne M. Jaeggi, Priti Shah
, February 2018
These articles provide excellent examples for how neuroscientific approaches can complement behavioral work, and they demonstrate how understanding the neural level can help researchers develop richer models of learning and development.
Danyelle T. Ireland, Kimberley Edelin Freeman, Cynthia E. Winston-Proctor, Kendra D. DeLaine, Stacey McDonald Lowe, Kamilah M. Woodson
, 2018
Researchers found that (1) identity; (2) STEM interest, confidence, and persistence; (3) achievement, ability perceptions, and attributions; and (4) socializers and support systems are key themes within the experiences of Black women and girls in STEM education.
Ann Y. Kim, Gale M. Sinatra, Viviane Seyranian
, 2018
Findings indicate that young women experience challenges to their participation and inclusion when they are in STEM settings.
Guan Saw, Chi-Ning Chang, and Hsun-Yu Chan
, 2018
Results indicated that female, Black, Hispanic, and low SES students were less likely to show, maintain, and develop an interest in STEM careers during high school years.
Di Xu, Sabrina Solanki, Peter McPartlan, and Brian Sato
, 2018
This paper estimates the causal effects of a first-year STEM learning communities program on both cognitive and noncognitive outcomes at a large public 4-year institution.
Christina S. Chhin, Katherine A. Taylor, and Wendy S. Wei
, 2018
Data showed that IES has not funded any direct replications that duplicate all aspects of the original study, but almost half of the funded grant applications can be considered conceptual replications that vary one or more dimensions of a prior study.
Okhee Lee
, 2018
As federal legislation requires that English language proficiency (ELP) standards are aligned with content standards, this article addresses issues and concerns in aligning ELP standards with content standards in English language arts, mathematics, and science.
Jordan Rickles, Jessica B. Heppen, Elaine Allensworth, Nicholas Sorensen, and Kirk Walters
, 2018
Researchers found no statistically significant differences in longer term outcomes between students in the online and face-to-face courses. Implications of these null findings are discussed.
Colleen M. Ganley, Casey E. George, Joseph R. Cimpian, Martha B. Makowski
, December 2017
Researchers found that perceived gender bias against women emerges as the dominant predictor of the gender balance in college majors.
James P. Spillane, Megan Hopkins, Tracy M. Sweet
, December 2017
This article examines the relationship between teachers’ instructional ties and their beliefs about mathematics instruction in one school district working to transform its approach to elementary mathematics education.
Susan A. Yoon, Sao-Ee Goh, Miyoung Park
, December 6, 2017
Results revealed needs in five areas of research: a need to diversify the knowledge domains within which research is conducted, more research on learning about system states, agreement on the essential features of complex systems content, greater focus on contextual factors that support learning including teacher learning, and a need for more comparative research.
Candace Walkington, Virginia Clinton, Pooja Shivraj
, November 2017
Textual features that make problems more difficult to process appear to differentially negatively impact struggling students, while features that make language easier to process appear to differentially positively impact struggling students.
Rebecca L. Matz, Benjamin P. Koester, Stefano Fiorini, Galina Grom, Linda Shepard, Charles G. Stangor, Brad Weiner, Timothy A. McKay
, November 2017
Biology, chemistry, physics, accounting, and economics lecture courses regularly exhibit gendered performance differences that are statistically and materially significant, whereas lab courses in the same subjects do not.
Adam V. Maltese, Christina S. Cooper
, August 2017
The results reveal that although there is no singular pathway into STEM fields, self-driven interest is a large factor in persistence, especially for males, and females rely more heavily on support from others.
Brian R. Belland, Andrew E. Walker, Nam Ju Kim
, August 2017
Scaffolding has a consistently strong effect across student populations, STEM disciplines, and assessment levels, and a strong effect when used with most problem-centered instructional and educational levels.
Di Xu, Shanna Smith Jaggars
, July 2017
The findings indicate a robust negative impact of online course taking for both subjects.
Maisie L. Gholson, Charles E. Wilkes
, June 2017
This chapter reviews two strands of identity-based research in mathematics education related to Black children, exemplified by Martin (2000) and Nasir (2002).
Sarah Theule Lubienski, Emily K. Miller, and Evthokia Stephanie Saclarides
, November 2017
Using data from a survey of doctoral students at one large institution, this study finds that men submitted and published more scholarly works than women across many fields, with differences largest in natural/biological sciences and engineering.
David Blazar, Cynthia Pollard
, October 2017
Drawing on classroom observations and teacher surveys, researchers find that test preparation activities predict lower quality and less ambitious mathematics instruction in upper-elementary classrooms.
Nicole M. Joseph, Meseret Hailu, Denise Boston
, June 2017
This integrative review used critical race theory (CRT) and Black feminism as interpretive frames to explore factors that contribute to Black women’s and girls’ persistence in the mathematics pipeline and the role these factors play in shaping their academic outcomes.
Benjamin L. Wiggins, Sarah L. Eddy, Daniel Z. Grunspan, Alison J. Crowe
, May 2017
Researchers describe the results of a quasi-experimental study to test the apex of the ICAP framework (interactive, constructive, active, and passive) in this ecological classroom environment.
Sean Gehrke, Adrianna Kezar
, May 2017
This study examines how involvement in four cross-institutional STEM faculty communities of practice is associated with local departmental and institutional change for faculty members belonging to these communities.
Lawrence Ingvarson, Glenn Rowley
, May 2017
This study investigated the relationship between policies related to the recruitment, selection, preparation, and certification of new teachers and (a) the quality of future teachers as measured by their mathematics content and pedagogy content knowledge and (b) student achievement in mathematics at the national level.
Will Tyson, Josipa Roksa
, April 2017
This study examines how course grades and course rigor are associated with math attainment among students with similar eighth-grade standardized math test scores.
Anne K. Morris, James Hiebert
, March 2017
Researchers investigated whether the content pre-service teachers studied in elementary teacher preparation mathematics courses was related to their performance on a mathematics lesson planning task 2 and 3 years after graduation.
Laura M. Desimone, Kirsten Lee Hill
, March 2017
Researchers use data from a randomized controlled trial of a middle school science intervention to explore the causal mechanisms by which the intervention produced previously documented gains in student achievement.
Okhee Lee
, March 2017
This article focuses on how the Common Core State Standards (CCSS) and the Next Generation Science Standards (NGSS) treat “argument,” especially in Grades K–5, and the extent to which each set of standards is grounded in research literature, as claimed.
Cory Koedel, Diyi Li, Morgan S. Polikoff, Tenice Hardaway, Stephani L. Wrabel
, February 2017
Researchers estimate relative achievement effects of the four most commonly adopted elementary mathematics textbooks in the fall of 2008 and fall of 2009 in California.
Mary Kay Stein, Richard Correnti, Debra Moore, Jennifer Lin Russell, Katelynn Kelly
, January 2017
Researchers argue that large-scale, standards-based improvements in the teaching and learning of mathematics necessitate advances in theories regarding how teaching affects student learning and progress in how to measure instruction.
Alan H. Schoenfeld
, December 2016
The author begins by tracing the growth and change in research in mathematics education and its interdependence with research in education in general over much of the 20th century, with an emphasis on changes in research perspectives and methods and the philosophical/empirical/disciplinary approaches that underpin them.
Marcia C. Linn, Libby Gerard, Camillia Matuk, Kevin W. McElhaney
, December 2016
This chapter focuses on how investigators from varied fields of inquiry who initially worked separately began to interact, eventually formed partnerships, and recently integrated their perspectives to strengthen science education.
: Are Teachers’ Implicit Cognitions Another Piece of the Puzzle?
Almut E. Thomas
, December 2016
Drawing on expectancy-value theory, this study investigated whether teachers’ implicit science-is-male stereotypes predict between-teacher variation in males’ and females’ motivational beliefs regarding physical science.
: A By-Product of STEM College Culture?
Ebony O. McGee
, December 2016
The researcher found that the 38 high-achieving Black and Latino/a STEM study participants, who attended institutions with racially hostile academic spaces, deployed an arsenal of strategies (e.g., stereotype management) to deflect stereotyping and other racial assaults (e.g., racial microaggressions), which are particularly prevalent in STEM fields.
James Cowan, Dan Goldhaber, Kyle Hayes, Roddy Theobald
, November 2016
Researchers discuss public policies that contribute to teacher shortages in specific subjects (e.g., STEM and special education) and specific types of schools (e.g., disadvantaged) as well as potential solutions.
: A Sociological Analysis of Multimethod Data From Young Women Aged 10–16 to Explore Gendered Patterns of Post-16 Participation
Louise Archer, Julie Moote, Becky Francis, Jennifer DeWitt, Lucy Yeomans
, November 2016
Researchers draw on survey data from more than 13,000 year 11 (age 15/16) students and interviews with 70 students (who had been tracked from age 10 to 16), focusing in particular on seven girls who aspired to continue with physics post-16, discussing how the cultural arbitrary of physics requires these girls to be highly “exceptional,” undertaking considerable identity work and deployment of capital in order to “possibilize” a physics identity—an endeavor in which some girls are better positioned to be successful than others.
Jeremy Roschelle, Mingyu Feng, Robert F. Murphy, Craig A. Mason
, October 2016
In a randomized field trial with 2,850 seventh-grade mathematics students, researchers evaluated whether an educational technology intervention increased mathematics learning.
: Making Research Participation Instructionally Effective
Sherry A. Southerland, Ellen M. Granger, Roxanne Hughes, Patrick Enderle, Fengfeng Ke, Katrina Roseler, Yavuz Saka, Miray Tekkumru-Kisa
, October 2016
As current reform efforts in science place a premium on student sense making and participation in the practices of science, researchers use a close examination of 106 science teachers participating in Research Experiences for Teachers (RET) to identify, through structural equation modeling, the essential features in supporting teacher learning from these experiences.
Brian R. Belland, Andrew E. Walker, Nam Ju Kim, Mason Lefler
, October 2016
This review addresses the need for a comprehensive meta-analysis of research on scaffolding in STEM education by synthesizing the results of 144 experimental studies (333 outcomes) on the effects of computer-based scaffolding designed to assist the full range of STEM learners (primary through adult education) as they navigated ill-structured, problem-centered curricula.
Vaughan Prain, Brian Hand
, October 2016
Researchers claim that there are strong evidence-based reasons for viewing writing as a central but not sole resource for learning, drawing on both past and current research on writing as an epistemological tool and on their professional background in science education research, acknowledging its distinctive take on the use of writing for learning.
June Ahn, Austin Beck, John Rice, Michelle Foster
, September 2016
Researchers present analyses from a researcher-practitioner partnership in the District of Columbia Public Schools, where the researchers are exploring the impact of educational software on students’ academic achievement.
Barbara King
, September 2016
This study uses nationally representative data from a recent cohort of college students to investigate thoroughly gender differences in STEM persistence.
Ryan C. Svoboda, Christopher S. Rozek, Janet S. Hyde, Judith M. Harackiewicz, Mesmin Destin
, August 2016
This longitudinal study draws on identity-based and expectancy-value theories of motivation to explain the socioeconomic status (SES) and mathematics and science course-taking relationship.
Mathematics Course Placements in California Middle Schools, 2003–2013
Thurston Domina, Paul Hanselman, NaYoung Hwang, Andrew McEachin
, July 2016
Researchers consider the organizational processes that accompanied the curricular intensification of the proportion of California eighth graders enrolled in algebra or a more advanced course nearly doubling to 65% between 2003 and 2013.
Lina Shanley
, July 2016
Using a nationally representative longitudinal data set, this study compared various models of mathematics achievement growth on the basis of both practical utility and optimal statistical fit and explored relationships within and between early and later mathematics growth parameters.
Mimi Engel, Amy Claessens, Tyler Watts, George Farkas
, June 2016
Analyzing data from two nationally representative kindergarten cohorts, researchers examine the mathematics content teachers cover in kindergarten.
F. Chris Curran, Ann T. Kellogg
, June 2016
Researchers present findings from the recently released Early Childhood Longitudinal Study, Kindergarten Class of 2010–2011 that demonstrate significant gaps in science achievement in kindergarten and first grade by race/ethnicity.
Rachel Garrett, Guanglei Hong
, June 2016
Analyzing the Early Childhood Longitudinal Study–Kindergarten cohort data, researchers find that heterogeneous grouping or a combination of heterogeneous and homogeneous grouping under relatively adequate time allocation is optimal for enhancing teacher ratings of language minority kindergartners’ math performance, while using homogeneous grouping only is detrimental.
Jennifer Gnagey, Stéphane Lavertu
, May 2016
This study is one of the first to estimate the impact of “inclusive” science, technology, engineering, and mathematics (STEM) high schools using student-level data.
Hanna Gaspard, Anna-Lena Dicke, Barbara Flunger, Isabelle Häfner, Brigitte M. Brisson, Ulrich Trautwein, Benjamin Nagengast
, May 2016
Through data from a cluster-randomized study in which a value intervention was successfully implemented in 82 ninth-grade math classrooms, researchers address how interventions on students’ STEM motivation in school affect motivation in subjects not targeted by the intervention.
Rebecca M. Callahan, Melissa H. Humphries
, April 2016
Researchers employ multivariate methods to investigate immigrant college going by linguistic status using the Educational Longitudinal Study of 2002.
Federick Ngo, Tatiana Melguizo
, March 2016
Researchers take advantage of heterogeneous placement policy in a large urban community college district in California to compare the effects of math remediation under different policy contexts.
: An Analysis of German Fourth- and Sixth-Grade Classrooms
Steffen Tröbst, Thilo Kleickmann, Kim Lange-Schubert, Anne Rothkopf, Kornelia Möller
, February 2016
Researchers examined if changes in instructional practices accounted for differences in situational interest in science instruction and enduring individual interest in science between elementary and secondary school classrooms.
: A Mixed-Methods Study
David F. Feldon, Michelle A. Maher, Josipa Roksa, James Peugh
, February 2016
Researchers offer evidence of a similar phenomenon to cumulative advantage, accounting for differential patterns of research skill development in graduate students over an academic year and explore differences in socialization that accompany diverging developmental trajectories.
: The Influence of Time, Peers, and Place
Luke Dauter, Bruce Fuller
, February 2016
Researchers hypothesize that pupil mobility stems from the (a) student’s time in school and grade; (b) student’s race, class, and achievement relative to peers; (c) quality of schooling relative to nearby alternatives; and (4) proximity, abundance, and diversity of local school options.
: How Workload and Curricular Affordances Shape STEM Faculty Decisions About Teaching and Learning
Matthew T. Hora
, January 2016
In this study the idea of the “problem space” from cognitive science is used to examine how faculty construct mental representations for the task of planning undergraduate courses.
Jessaca Spybrook, Carl D. Westine, Joseph A. Taylor
, January 2016
This article provides empirical estimates of design parameters necessary for planning adequately powered cluster randomized trials (CRTs) focused on science achievement.
Paul L. Morgan, George Farkas, Marianne M. Hillemeier, Steve Maczuga
, January 2016
Researchers examined the age of onset, over-time dynamics, and mechanisms underlying science achievement gaps in U.S. elementary and middle schools.
: Opportunity Structures and Outcomes in Inclusive STEM-Focused High Schools
Lois Weis, Margaret Eisenhart, Kristin Cipollone, Amy E. Stich, Andrea B. Nikischer, Jarrod Hanson, Sarah Ohle Leibrandt, Carrie D. Allen, Rachel Dominguez
, December 2015
Researchers present findings from a three-year comparative longitudinal and ethnographic study of how schools in two cities, Buffalo and Denver, have taken up STEM education reform, including the idea of “inclusive STEM-focused schools,” to address weaknesses in urban high schools with majority low-income and minority students.
: How Do They Interact in Promoting Science Understanding?
Jasmin Decristan, Eckhard Klieme, Mareike Kunter, Jan Hochweber, Gerhard Büttner, Benjamin Fauth, A. Lena Hondrich, Svenja Rieser, Silke Hertel, Ilonca Hardy
, December 2015
Researchers examine the interplay between curriculum-embedded formative assessment—a well-known teaching practice—and general features of classroom process quality (i.e., cognitive activation, supportive climate, classroom management) and their combined effect on elementary school students’ understanding of the scientific concepts of floating and sinking.
: An International Perspective
William H. Schmidt, Nathan A. Burroughs, Pablo Zoido, Richard T. Houang
, October 2015
In this paper, student-level indicators of opportunity to learn (OTL) included in the 2012 Programme for International Student Assessment are used to explore the joint relationship of OTL and socioeconomic status (SES) to student mathematics literacy.
Xueli Wang
, September 2015
This study examines the effect of beginning at a community college on baccalaureate success in science, technology, engineering, and mathematics (STEM) fields.
: Trends and Predictors
David M. Quinn, North Cooc
, August 2015
With research on science achievement disparities by gender and race/ethnicity often neglecting the beginning of the pipeline in the early grades, researchers address this limitation using nationally representative data following students from Grades 3 to 8.
Shaun M. Dougherty, Joshua S. Goodman, Darryl V. Hill, Erica G. Litke, Lindsay C. Page
, May 2015
Researchers highlight a collaboration to investigate one district’s effort to increase middle school algebra course-taking.
David F. Feldon, Michelle A. Maher, Melissa Hurst, Briana Timmerman
, April 2015
This mixed-method study investigates agreement between student mentees’ and their faculty mentors’ perceptions of the students’ developing research knowledge and skills in STEM.
: Reviving Science Education for Civic Ends
John L. Rudolph
, December 2014
This article revisits John Dewey’s now-well-known address “Science as Subject-Matter and as Method” and examines the development of science education in the United States in the years since that address.
Dermot F. Donnelly, Marcia C. Linn Sten Ludvigsen
, December 2014
The National Science Foundation–sponsored report Fostering Learning in the Networked World called for “a common, open platform to support communities of developers and learners in ways that enable both to take advantage of advances in the learning sciences”; we review research on science inquiry learning environments (ILEs) to characterize current platforms.
: A Longitudinal Case Study of America’s Chemistry Teachers
Gregory T. Rushton, Herman E. Ray, Brett A. Criswell, Samuel J. Polizzi, Clyde J. Bearss, Nicholas Levelsmier, Himanshu Chhita, Mary Kirchhoff
, November 2014
Researchers perform a longitudinal case study of U.S. public school chemistry teachers to illustrate a diffusion of responsibility within the STEM community regarding who is responsible for the teacher workforce.
: Relations Between Early Mathematics Knowledge and High School Achievement
Tyler W. Watts, Greg J. Duncan, Robert S. Siegler, Pamela E. Davis-Kean
, October 2014
Researchers find that preschool mathematics ability predicts mathematics achievement through age 15, even after accounting for early reading, cognitive skills, and family and child characteristics.
T. Jared Robinson, Lane Fischer, David Wiley, John Hilton, III
, October 2014
The purpose of this quantitative study is to analyze whether the adoption of open science textbooks significantly affects science learning outcomes for secondary students in earth systems, chemistry, and physics.
: 1968–2009
Robert N. Ronau, Christopher R. Rakes, Sarah B. Bush, Shannon O. Driskell, Margaret L. Niess, David K. Pugalee
, October 2014
We examined 480 dissertations on the use of technology in mathematics education and developed a Quality Framework (QF) that provided structure to consistently define and measure quality.
Andrew D. Plunk, William F. Tate, Laura J. Bierut, Richard A. Grucza
, June 2014
Using logistic regression with Census and American Community Survey (ACS) data ( = 2,892,444), researchers modeled mathematics and science course graduation requirement (CGR) exposure on (a) high school dropout, (b) beginning college, and (c) obtaining any college degree.
Corey Drake, Tonia J. Land, Andrew M. Tyminski
, April 2014
Building on the work of Ball and Cohen and that of Davis and Krajcik, as well as more recent research related to teacher learning from and about curriculum materials, researchers seek to answer the question, How can prospective teachers (PTs) learn to read and use educative curriculum materials in ways that support them in acquiring the knowledge needed for teaching?
Lorraine M. McDonnell, M. Stephen Weatherford
, December 2013
This article draws on theories of political and policy learning and interviews with major participants to examine the role that the Common Core State Standards (CCSS) supporters have played in developing and implementing the standards, supporters’ reasons for mobilizing, and the counterarguments and strategies of recently emerging opposition groups.
: Motivation, High School Learning, and Postsecondary Context of Support
Xueli Wang
, October 2013
This study draws upon social cognitive career theory and higher education literature to test a conceptual framework for understanding the entrance into science, technology, engineering, and mathematics (STEM) majors by recent high school graduates attending 4-year institutions.
Philip M. Sadler, Gerhard Sonnert, Harold P. Coyle, Nancy Cook-Smith, Jaimie L. Miller
, October 2013
This study examines the relationship between teacher knowledge and student learning for 9,556 students of 181 middle school physical science teachers.
: Teaching Critical Mathematics in a Remedial Secondary Classroom
Andrew Brantlinger
, October 2013
The researcher presents results from a practitioner research study of his own teaching of critical mathematics (CM) to low-income students of color in a U.S. context.
Jason G. Hill, Ben Dalton
, October 2013
This study investigates the distribution of math teachers with a major or certification in math using data from the National Center for Education Statistics’ High School Longitudinal Study of 2009 (HSLS:09).
Kristin F. Butcher, Mary G. Visher
, September 2013
This study uses random assignment to investigate the impact of a “light-touch” intervention, where an individual visited math classes a few times during the semester, for a few minutes each time, to inform students about available services.
Janet M. Dubinsky, Gillian Roehrig, Sashank Varma
, August 2013
Researchers argue that the neurobiology of learning, and in particular the core concept of , have the potential to directly transform teacher preparation and professional development, and ultimately to affect how students think about their own learning.
: The Impact of Undergraduate Research Programs
M. Kevin Eagan, Jr., Sylvia Hurtado, Mitchell J. Chang, Gina A. Garcia, Felisha A. Herrera, Juan C. Garibay
, August 2013
Researchers’ findings indicate that participation in an undergraduate research program significantly improved students’ probability of indicating plans to enroll in a STEM graduate program.
Okhee Lee, Helen Quinn, Guadalupe Valdés
, May 2013
This article addresses language demands and opportunities that are embedded in the science and engineering practices delineated in “A Framework for K–12 Science Education,” released by the National Research Council (2011).
Liliana M. Garces
, April 2013
This study examines the effects of affirmative action bans in four states (California, Florida, Texas, and Washington) on the enrollment of underrepresented students of color within six different graduate fields of study: the natural sciences, engineering, social sciences, business, education, and humanities.
: Learning Lessons From Research on Diversity in STEM Fields
Shirley M. Malcom, Lindsey E. Malcom-Piqueux
, April 2013
Researchers argue that social scientists ought to look to the vast STEM education research literature to begin the task of empirically investigating the questions raised in the case.
Roslyn Arlin Mickelson, Martha Cecilia Bottia, Richard Lambert
, March 2013
This metaregression analysis reviewed the social science literature published in the past 20 years on the relationship between mathematics outcomes and the racial composition of the K–12 schools students attend.
Jeffrey Grigg, Kimberle A. Kelly, Adam Gamoran, Geoffrey D. Borman
, March 2013
Researchers examine classroom observations from a 3-year large-scale randomized trial in the Los Angeles Unified School District (LAUSD) to investigate the extent to which a professional development initiative in inquiry science influenced teaching practices in in 4th and 5th grade classrooms in 73 schools.
:
Angela Calabrese Barton, Hosun Kang, Edna Tan, Tara B. O’Neill, Juanita Bautista-Guerra, Caitlin Brecklin
, February 2013
This longitudinal ethnographic study traces the identity work that girls from nondominant backgrounds do as they engage in science-related activities across school, club, and home during the middle school years.
: A Review of the State of the Field
Shuchi Grover, Roy Pea
, January 2013
This article frames the current state of discourse on computational thinking in K–12 education by examining mostly recently published academic literature that uses Jeannette Wing’s article as a springboard, identifies gaps in research, and articulates priorities for future inquiries.
Catherine Riegle-Crumb, Barbara King, Eric Grodsky, Chandra Muller
, December 2012
This article investigates the empirical basis for often-repeated arguments that gender differences in entrance into science, technology, engineering, and mathematics (STEM) majors are largely explained by disparities in prior achievement.
Richard M. Ingersoll, Henry May
, December 2012
This study examines the magnitude, destinations, and determinants of mathematics and science teacher turnover.
: How Families Shape Children’s Engagement and Identification With Science
Louise Archer, Jennifer DeWitt, Jonathan Osborne, Justin Dillon, Beatrice Willis, Billy Wong
, October 2012
Drawing on the conceptual framework of Bourdieu, this article explores how the interplay of family habitus and capital can make science aspirations more “thinkable” for some (notably middle-class) children than others.
Erin Marie Furtak, Tina Seidel, Heidi Iverson, Derek C. Briggs
, September 2012
This meta-analysis introduces a framework for inquiry-based teaching that distinguishes between cognitive features of the activity and degree of guidance given to students.
Jaekyung Lee, Todd Reeves
, June 2012
This study examines the impact of high-stakes school accountability, capacity, and resources under NCLB on reading and math achievement outcomes through comparative interrupted time-series analyses of 1990–2009 NAEP state assessment data.
: Toward a Theory of Teaching
Paola Sztajn, Jere Confrey, P. Holt Wilson, Cynthia Edgington
, June 2012
Researchers propose a theoretical connection between research on learning and research on teaching through recent research on students’ learning trajectories (LTs).
: The Perspectives of Exemplary African American Teachers
Jianzhong Xu, Linda T. Coats, Mary L. Davidson
, February 2012
Researchers argue both the urgency and the promise of establishing a constructive conversation among different bodies of research, including science interest, sociocultural studies in science education, and culturally relevant teaching.
Rebecca M. Schneider, Kellie Plasman
, December 2011
This review examines the research on science teachers’ pedagogical content knowledge (PCK) in order to refine ideas about science teacher learning progressions and how to support them.
Brian A. Nosek, Frederick L. Smyth
, October 2011
Researchers examined implicit math attitudes and stereotypes among a heterogeneous sample of 5,139 participants.
Libby F. Gerard, Keisha Varma, Stephanie B. Corliss, Marcia C. Linn
, September 2011
Researchers’ findings suggest that professional development programs that engaged teachers in a comprehensive, constructivist-oriented learning process and were sustained beyond 1 year significantly improved students’ inquiry learning experiences in K–12 science classrooms.
: Teaching and Learning Impacts of Reading Apprenticeship Professional Development
Cynthia L. Greenleaf, Cindy Litman, Thomas L. Hanson, Rachel Rosen, Christy K. Boscardin, Joan Herman, Steven A. Schneider, Sarah Madden, Barbara Jones
, June 2011
This study examined the effects of professional development integrating academic literacy and biology instruction on science teachers’ instructional practices and students’ achievement in science and literacy.
Paul Cobb, Kara Jackson
, May 2011
The authors comment on Porter, McMaken, Hwang, and Yang’s recent analysis of the Common Core State Standards for Mathematics by critiquing their measures of the focus of the standards and the absence of an assessment of coherence.
P. Wesley Schultz, Paul R. Hernandez, Anna Woodcock, Mica Estrada, Randie C. Chance, Maria Aguilar, Richard T. Serpe
, March 2011
This study reports results from a longitudinal study of students supported by a national National Institutes of Health–funded minority training program, and a propensity score matched control.
: Three Large-Scale Studies
Jeremy Roschelle, Nicole Shechtman, Deborah Tatar, Stephen Hegedus, Bill Hopkins, Susan Empson, Jennifer Knudsen, Lawrence P. Gallagher
, December 2010
The authors present three studies (two randomized controlled experiments and one embedded quasi-experiment) designed to evaluate the impact of replacement units targeting student learning of advanced middle school mathematics.
: Examining Disparities in College Major by Gender and Race/Ethnicity
Catherine Riegle-Crumb, Barbara King
, December 2010
The authors analyze national data on recent college matriculants to investigate gender and racial/ethnic disparities in STEM fields, with an eye toward the role of academic preparation and attitudes in shaping such disparities.
Mary Kay Stein, Julia H. Kaufman
, September 2010
This article begins to unravel the question, “What curricular materials work best under what kinds of conditions?” The authors address this question from the point of view of teachers and their ability to implement mathematics curricula that place varying demands and provide varying levels of support for their learning.
Andy R. Cavagnetto
, September 2010
This study of 54 articles from the research literature examines how argument interventions promote scientific literacy.
Victoria M. Hand
, March 2010
The researcher examined how the teacher and students in a low-track mathematics classroom jointly constructed opposition through their classroom interactions.
Terrence E. Murphy, Monica Gaughan, Robert Hume, S. Gordon Moore, Jr.
, March 2010
Researchers evaluate the association of a summer bridge program with the graduation rate of underrepresented minority (URM) students at a selective technical university.
Quantitative research is an essential part of STEM (Science, Technology, Engineering, and Mathematics) fields. It involves collecting and analyzing numerical data to answer research questions and test hypotheses.
In 2023, STEM students have a wealth of exciting research opportunities in various disciplines. Whether you’re an undergraduate or graduate student, here are quantitative research topics to consider for your next project.
If you are looking for the best list of quantitative research topics for stem students, then you can check the given list in each field. It offers STEM students numerous opportunities to explore and contribute to their respective fields in 2023 and beyond.
Whether you’re interested in astrophysics, biology, engineering, mathematics, or any other STEM field.
Also Read: Most Exciting Qualitative Research Topics For Students
Table of Contents
Quantitative research is a type of research that focuses on the organized collection, analysis, and evaluation of numerical data to answer research questions, test theories, and find trends or connections between factors. It is an organized, objective way to do study that uses measurable data and scientific methods to come to results.
Quantitative research is often used in many areas, such as the natural sciences, social sciences, economics, psychology, education, and market research. It gives useful information about patterns, trends, cause-and-effect relationships, and how often things happen. Quantitative tools are used by researchers to answer questions like “How many?” and “How often?” “Is there a significant difference?” or “What is the relationship between the variables?”
In comparison to quantitative research, qualitative research uses non-numerical data like conversations, notes, and open-ended surveys to understand and explore the ideas, experiences, and points of view of people or groups. Researchers often choose between quantitative and qualitative methods based on their research goals, questions, and the type of thing they are studying.
Here’s a step-by-step guide on how to choose quantitative research topics for STEM:
Start by reflecting on your personal interests within STEM. What areas or subjects in STEM excite you the most? Choosing a topic you’re passionate about will keep you motivated throughout the research process.
Look through your coursework, textbooks, and class notes. Identify concepts, theories, or areas that you found particularly intriguing or challenging. These can be a source of potential research topics.
Discuss your research interests with professors, academic advisors, or mentors. They can provide valuable insights, suggest relevant topics, and guide you toward areas with research opportunities.
Explore recent research articles, journals, and publications in STEM fields. This will help you identify current trends, gaps in knowledge, and areas where further research is needed.
Once you have a broad area of interest, narrow it down to a specific research focus. Consider questions like:
Assess the resources available to you, including access to laboratories, equipment, databases, and funding. Ensure that your chosen topic aligns with the resources you have or can access.
Consider the feasibility of conducting research on your chosen topic. Are the data readily available, or will you need to collect data yourself? Can you complete the research within your available time frame?
Formulate a clear and specific research question or hypothesis. Your research question should guide your entire study and provide a focus for your data collection and analysis.
Dive deeper into the existing literature related to your chosen topic. This will help you understand the current state of research, identify gaps, and refine your research question.
Think about the potential impact of your research. How does your topic contribute to the advancement of knowledge in your field? Does it have practical applications or implications for society?
Determine the quantitative research methods and data collection techniques you plan to use. Consider whether you’ll conduct experiments, surveys, data analysis, simulations, or use existing datasets.
Share your research topic and ideas with peers, advisors, or mentors. They can provide valuable feedback and help you refine your research focus.
Consider ethical implications related to your research, especially if it involves human subjects, sensitive data, or potential environmental impacts. Ensure that your research adheres to ethical guidelines.
Once you’ve gone through these steps, finalize your research topic. Write a clear and concise research proposal that outlines your research question, objectives, methods, and expected outcomes.
Be open to adjusting your research topic as you progress. Sometimes, new insights or challenges may lead you to refine or adapt your research focus.
Following are the most interesting quantitative research topics for stem students. These are given below.
Following are the best Quantitative Research Topics For STEM Students in mathematics and statistics.
Robotics and automation, materials engineering, nuclear engineering, biomedical engineering, chemical engineering, renewable energy, astronomy and space sciences, psychology and cognitive science, geology and geological engineering, forensic science, cybersecurity, mathematical biology, chemical analysis, mathematics education, quantitative social research, computational neuroscience, quantitative research topics in transportation engineering, quantitative research topics in energy economics, topics in quantum information science, amazing quantitative research topics in human genetics, quantitative research topics in marine biology, what is a common goal of qualitative and quantitative research.
A common goal of both qualitative and quantitative research is to generate knowledge and gain a deeper understanding of a particular phenomenon or topic. However, they approach this goal in different ways:
Both types of research aim to understand and explain a specific phenomenon, whether it’s a social issue, a natural process, a human behavior, or a complex event.
Both qualitative and quantitative research can involve hypothesis testing. While qualitative research may not use statistical hypothesis tests in the same way as quantitative research, it often tests hypotheses or research questions by examining patterns and themes in the data.
Researchers in both approaches seek to contribute to the body of knowledge in their respective fields. They aim to answer important questions, address gaps in existing knowledge, and provide insights that can inform theory, practice, or policy.
Research findings from both qualitative and quantitative studies can be used to inform decision-making in various domains, whether it’s in academia, government, industry, healthcare, or social services.
Both approaches strive to enhance our understanding of complex phenomena by systematically collecting and analyzing data. They aim to provide evidence-based explanations and insights.
Research findings from both qualitative and quantitative studies can be applied to practical situations. For example, the results of a quantitative study on the effectiveness of a new drug can inform medical treatment decisions, while qualitative research on customer preferences can guide marketing strategies.
In academia, both types of research contribute to the development and refinement of theories in various disciplines. Quantitative research may provide empirical evidence to support or challenge existing theories, while qualitative research may generate new theoretical frameworks or perspectives.
So, selecting a quantitative research topic for STEM students is a pivotal decision that can shape the trajectory of your academic and professional journey. The process involves a thoughtful exploration of your interests, a thorough review of the existing literature, consideration of available resources, and the formulation of a clear and specific research question.
Your chosen topic should resonate with your passions, align with your academic or career goals, and offer the potential to contribute to the body of knowledge in your STEM field. Whether you’re delving into physics, biology, engineering, mathematics, or any other STEM discipline, the right research topic can spark curiosity, drive innovation, and lead to valuable insights.
Moreover, quantitative research in STEM not only expands the boundaries of human knowledge but also has the power to address real-world challenges, improve technology, and enhance our understanding of the natural world. It is a journey that demands dedication, intellectual rigor, and an unwavering commitment to scientific inquiry.
Quantitative research in this context is designed to improve our understanding of the science system’s workings, structural dependencies and dynamics.
Surveys and questionnaires serve as common examples of quantitative research. They involve collecting data from many respondents and analyzing the results to identify trends, patterns
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The Journal of STEM Education: Innovations and Research is a quarterly, peer-reviewed publication for educators in Science, Technology, Engineering, and Mathematics (STEM) education. The journal emphasizes real-world case studies that focus on issues that are relevant and important to STEM practitioners. These studies may showcase field research as well as secondary-sourced cases. The journal encourages case studies that cut across the different STEM areas and that cover non-technical issues such as finance, cost, management, risk, safety, etc. Case studies are typically framed around problems and issues facing a decision maker in an organization.
The Journal of STEM (Science, Technology, Engineering and Mathematics) Education: Innovations and Research publishes peer-reviewed:
The case studies may include color photographs, charts, and other visual aids in order to bring engineering topics alive. The research articles will focus on innovations that have been implemented in educational institutions. These case studies and articles are expected to be used by faculty members in universities, four-year colleges, two-year colleges, and high schools. In addition, the journal provides information that would help the STEM instructors in their educational mission by publishing:
To promote high-quality undergraduate education in science, Technology, Engineering and Mathematics through peer reviewed articles that provide:
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This study explored research trends in science, technology, engineering, and mathematics (STEM) education. Descriptive analysis and co-word analysis were used to examine articles published in Social Science Citation Index journals from 2011 to 2020. From a search of the Web of Science database, a total of 761 articles were selected as target samples for analysis. A growing number of STEM-related publications were published after 2016. The most frequently used keywords in these sample papers were also identified. Further analysis identified the leading journals and most represented countries among the target articles. A series of co-word analyses were conducted to reveal word co-occurrence according to the title, keywords, and abstract. Gender moderated engagement in STEM learning and career selection. Higher education was critical in training a STEM workforce to satisfy societal requirements for STEM roles. Our findings indicated that the attention of STEM education researchers has shifted to the professional development of teachers. Discussions and potential research directions in the field are included.
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Hsu, YS., Tang, KY. & Lin, TC. Trends and Hot Topics of STEM and STEM Education: a Co-word Analysis of Literature Published in 2011–2020. Sci & Educ 33 , 1069–1092 (2024). https://doi.org/10.1007/s11191-023-00419-6
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Primarily, STEM is an acronym for Science, Technology, Engineering, and Mathematics. It’s a study program that weaves all four disciplines for cross-disciplinary knowledge to solve scientific problems. STEM touches across a broad array of subjects as STEM students are required to gain mastery of four disciplines.
As a project-based discipline, STEM has different stages of learning. The program operates like other disciplines, and as such, STEM students embrace knowledge depending on their level. Since it’s a discipline centered around innovation, students undertake projects regularly. As a STEM student, your project could either be to build or write on a subject. Your first plan of action is choosing a topic if it’s written. After selecting a topic, you’ll need to determine how long a thesis statement should be .
Given that topic is essential to writing any project, this article focuses on research topics for STEM students. So, if you’re writing a STEM research paper or write my research paper , below are some of the best research topics for STEM students.
Quantitative research topics for stem students, qualitative research topics for stem students, what are the best experimental research topics for stem students, non-experimental research topics for stem students, capstone research topics for stem students, correlational research topics for stem students, scientific research topics for stem students, simple research topics for stem students, top 10 research topics for stem students, experimental research topics for stem students about plants, research topics for grade 11 stem students, research topics for grade 12 stem students, quantitative research topics for stem high school students, survey research topics for stem students, interesting and informative research topics for senior high school stem students.
Several research topics can be formulated in this field. They cut across STEM science, engineering, technology, and math. Here is a list of good research topics for STEM students.
For your quantitative research in STEM, you’ll need to learn how to cite a thesis MLA for the topic you’re choosing. Below are some of the best quantitative research topics for STEM students.
There are several practical research topics for STEM students. However, if you’re looking for qualitative research topics for STEM students, here are topics to explore.
Experimental research in STEM is a scientific research methodology that uses two sets of variables. They are dependent and independent variables that are studied under experimental research. Experimental research topics in STEM look into areas of science that use data to derive results.
Below are easy experimental research topics for STEM students.
Unlike experimental research, non-experimental research lacks the interference of an independent variable. Non-experimental research instead measures variables as they naturally occur. Below are some non-experimental quantitative research topics for STEM students.
STEM learning and knowledge grow in stages. The older students get, the more stringent requirements are for their STEM research topic. There are several capstone topics for research for STEM students .
Below are some simple quantitative research topics for stem students.
Correlations research is research where the researcher measures two continuous variables. This is done with little or no attempt to control extraneous variables but to assess the relationship. Here are some sample research topics for STEM students to look into bearing in mind how to cite a thesis APA style for your project.
There are several science research topics for STEM students. Below are some possible quantitative research topics for STEM students.
If you’re looking for a simple research topic, below are easy research topics for STEM students.
For your top 10 research topics for STEM students, here are interesting topics for STEM students to consider.
Below are possible research topics for STEM students about plants:
Below are some examples of quantitative research topics for STEM students in grade 11.
Here are some of the best qualitative research topics for STEM students in grade 12.
Here are topics to consider for your STEM-related research topics for high school students.
Below are some survey topics for qualitative research for stem students.
Here are some descriptive research topics for STEM students in senior high.
STEM topics cover areas in various scientific fields, mathematics, engineering, and technology. While it can be tasking, reducing the task starts with choosing a favorable topic. If you require external assistance in writing your STEM research, you can seek professional help from our experts.
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Fostering students’ competence in applying interdisciplinary knowledge to solve problems has been recognized as an important and challenging issue globally. This is why STEM (Science, Technology, Engineering, Mathematics) education has been emphasized at all levels in schools. Meanwhile, the use of robotics has played an important role in STEM learning design. The purpose of this study was to fill a gap in the current review of research on Robotics-based STEM (R-STEM) education by systematically reviewing existing research in this area. This systematic review examined the role of robotics and research trends in STEM education. A total of 39 articles published between 2012 and 2021 were analyzed. The review indicated that R-STEM education studies were mostly conducted in the United States and mainly in K-12 schools. Learner and teacher perceptions were the most popular research focus in these studies which applied robots. LEGO was the most used tool to accomplish the learning objectives. In terms of application, Technology (programming) was the predominant robotics-based STEM discipline in the R-STEM studies. Moreover, project-based learning (PBL) was the most frequently employed learning strategy in robotics-related STEM research. In addition, STEM learning and transferable skills were the most popular educational goals when applying robotics. Based on the findings, several implications and recommendations to researchers and practitioners are proposed.
Over the past few years, implementation of STEM (Science, Technology, Engineering, and Mathematics) education has received a positive response from researchers and practitioners alike. According to Chesloff ( 2013 ), the winning point of STEM education is its learning process, which validates that students can use their creativity, collaborative skills, and critical thinking skills. Consequently, STEM education promotes a bridge between learning in authentic real-life scenarios (Erdoğan et al., 2016 ; Kelley & Knowles, 2016 ). This is the greatest challenge facing STEM education. The learning experience and real-life situation might be intangible in some areas due to pre- and in-conditioning such as unfamiliarity with STEM content (Moomaw, 2012 ), unstructured learning activities (Sarama & Clements, 2009), and inadequate preparation of STEM curricula (Conde et al., 2021 ).
In response to these issues, the adoption of robotics in STEM education has been encouraged as part of an innovative and methodological approach to learning (Bargagna et al., 2019 ; Ferreira et al., 2018 ; Kennedy et al., 2015 ; Köse et al., 2015 ). Similarly, recent studies have reported that the use of robots in school settings has an impact on student curiosity (Adams et al., 2011 ), arts and craftwork (Sullivan & Bers, 2016 ), and logic (Bers, 2008 ). When robots and educational robotics are considered a core part of STEM education, it offers the possibility to promote STEM disciplines such as engineering concepts or even interdisciplinary practices (Okita, 2014 ). Anwar et. al. ( 2019 ) argued that integration between robots and STEM learning is important to support STEM learners who do not immediately show interest in STEM disciplines. Learner interest can elicit the development of various skills such as computational thinking, creativity and motivation, collaboration and cooperation, problem-solving, and other higher-order thinking skills (Evripidou et al., 2020 ). To some extent, artificial intelligence (AI) has driven the use of robotics and tools, such as their application to designing instructional activities (Hwang et al., 2020 ). The potential for research on robotics in STEM education can be traced by showing the rapid increase in the number of studies over the past few years. The emphasis is on critically reviewing existing research to determine what prior research already tells us about R-STEM education, what it means, and where it can influence future research. Thus, this study aimed to fill the gap by conducting a systematic review to grasp the potential of R-STEM education.
In terms of providing the core concepts of roles and research trends of R-STEM education, this study explored beyond the scope of previous reviews by conducting content analysis to see the whole picture. To address the following questions, this study analyzed published research in the Web of Science database regarding the technology-based learning model (Lin & Hwang, 2019 ):
In terms of research characteristic and features, what were the location, sample size, duration of intervention, research methods, and research foci of the R-STEM education research?
In terms of interaction between participants and robots, what were the participants, roles of the robot, and types of robot in the R-STEM education research?
In terms of application, what were the dominant STEM disciplines, contribution to STEM disciplines, integration of robots and STEM, pedagogical interventions, and educational objectives of the R-STEM research?
Previous studies have investigated the role of robotics in R-STEM education from several research foci such as the specific robot users (Atman Uslu et al., 2022 ; Benitti, 2012 ; Jung & Won, 2018 ; Spolaôr & Benitti, 2017 ; van den Berghe et al., 2019 ), the potential value of R-STEM education (Çetin & Demircan, 2020 ; Conde et al., 2021 ; Zhang et al., 2021 ), and the types of robots used in learning practices (Belpaeme et al., 2018 ; Çetin & Demircan, 2020 ; Tselegkaridis & Sapounidis, 2021 ). While their findings provided a dynamic perspective on robotics, they failed to contribute to the core concept of promoting R-STEM education. Those previous reviews did not summarize the exemplary practice of employing robots in STEM education. For instance, Spolaôr and Benitti ( 2017 ) concluded that robots could be an auxiliary tool for learning but did not convey whether the purpose of using robots is essential to enhance learning outcomes. At the same time, it is important to address the use and purpose of robotics in STEM learning, the connections between theoretical pedagogy and STEM practice, and the reasons for the lack of quantitative research in the literature to measure student learning outcomes.
First, Benitti ( 2012 ) reviewed research published between 2000 and 2009. This review study aimed to determine the educational potential of using robots in schools and found that it is feasible to use most robots to support the pedagogical process of learning knowledge and skills related to science and mathematics. Five years later, Spolaôr and Benitti ( 2017 ) investigated the use of robots in higher education by employing the adopted-learning theories that were not covered in their previous review in 2012. The study’s content analysis approach synthesized 15 papers from 2002 to 2015 that used robots to support instruction based on fundamental learning theory. The main finding was that project-based learning (PBL) and experiential learning, or so-called hands-on learning, were considered to be the most used theories. Both theories were found to increase learners’ motivation and foster their skills (Behrens et al., 2010 ; Jou et al., 2010 ). However, the vast majority of discussions of the selected reviews emphasized positive outcomes while overlooking negative or mixed outcomes. Along the same lines, Jung and Won ( 2018 ) also reviewed theoretical approaches to Robotics education in 47 studies from 2006 to 2017. Their focused review of studies suggested that the employment of robots in learning should be shifted from technology to pedagogy. This review paper argued to determine student engagement in robotics education, despite disagreements among pedagogical traits. Although Jung and Won ( 2018 ) provided information of teaching approaches applied in robotics education, they did not offer critical discussion on how those approaches were formed between robots and the teaching disciplines.
On the other hand, Conde et. al. ( 2021 ) identified PBL as the most common learning approach in their study by reviewing 54 papers from 2006 to 2019. Furthermore, the studies by Çetin and Demircan ( 2020 ) and Tselegkaridis and Sapounidis ( 2021 ) focused on the types of robots used in STEM education and reviewed 23 and 17 papers, respectively. Again, these studies touted learning engagement as a positive outcome, and disregarded the different perspectives of robot use in educational settings on students’ academic performance and cognition. More recently, a meta-analysis by Zhang et. al. ( 2021 ) focused on the effects of robotics on students’ computational thinking and their attitudes toward STEM learning. In addition, a systematic review by Atman Uslu et. al. ( 2022 ) examined the use of educational robotics and robots in learning.
So far, the review study conducted by Atman Uslu et. al. ( 2022 ) could be the only study that has attempted to clarify some of the criticisms of using educational robots by reviewing the studies published from 2006 to 2019 in terms of their research issues (e.g., interventions, interactions, and perceptions), theoretical models, and the roles of robots in educational settings. However, they failed to take into account several important features of robots in education research, such as thematic subjects and educational objectives, for instance, whether robot-based learning could enhance students’ competence of constructing new knowledge, or whether robots could bring either a motivational facet or creativity to pedagogy to foster students’ learning outcomes. These are essential in investigating the trends of technology-based learning research as well as the role of technology in education as a review study is aimed to offer a comprehensive discussion which derived from various angles and dimensions. Moreover, the role of robots in STEM education was generally ignored in the previous review studies. Hence, there is still a need for a comprehensive understanding of the role of robotics in STEM education and research trends (e.g., research issues, interaction issues, and application issues) so as to provide researchers and practitioners with valuable references. That is, our study can remedy the shortcomings of previous reviews (Additional file 1 ).
The above comments demonstrate how previous scholars have understood what they call “the effectiveness of robotics in STEM education” in terms of innovative educational tools. In other words, despite their useful findings and ongoing recommendations, there has not been a thorough investigation of how robots are widely used from all angles. Furthermore, the results of existing review studies have been less than comprehensive in terms of the potential role of robotics in R-STEM education after taking into account various potential dimensions based on the technology-based model that we propose in this study.
The studies in this review were selected from the literature on the Web of Science, our sole database due to its rigorous journal research and qualified studies (e.g., Huang et al., 2022 ), discussing the adoption of R-STEM education, and the data collection procedures for this study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Moher et al., 2009 ) as referred to by prior studies (e.g., Chen et al., 2021a , 2021b ; García-Martínez et al., 2020 ). Considering publication quality, previous studies (Fu & Hwang, 2018 ; Martín-Páez et al., 2019 ) suggested using Boolean expressions to search Web of Science databases. The search terms for “robot” are “robot” or “robotics” or “robotics” or “Lego” (Spolaôr & Benitti, 2017 ). According to Martín-Páez et. al. ( 2019 ), expressions for STEM education include “STEM” or “STEM education” or “STEM literacy” or “STEM learning” or “STEM teaching” or “STEM competencies”. These search terms were entered into the WOS database to search only for SSCI papers due to its wide recognition as being high-quality publications in the field of educational technology. As a result, 165 papers were found in the database. The search was then restricted to 2012–2021 as suggested by Hwang and Tsai ( 2011 ). In addition, the number of papers was reduced to 131 by selecting only publications of the “article” type and those written in “English”. Subsequently, we selected the category “education and educational research” which reduced the number to 60 papers. During the coding analysis, the two coders screened out 21 papers unrelated to R-STEM education. The coding result had a Kappa coefficient of 0.8 for both coders (Cohen, 1960 ). After the screening stage, a final total of 39 articles were included in this study, as shown in Fig. 1 . Also, the selected papers are marked with an asterisk in the reference list and are listed in Appendixes 1 and 2 .
PRISMA procedure for the selection process
This study comprised content analysis using a coding scheme to provide insights into different aspects of the studies in question (Chen et al., 2021a , 2021b ; Martín-Páez et al., 2019 ). The coding scheme adopted the conceptual framework proposed by Lin and Hwang ( 2019 ), comprising “STEM environments”, “learners”, and “robots”, as shown in Fig. 2 . Three issues were identified:
In terms of research issues, five dimensions were included: “location”, “sample size”, “duration of intervention”, (Zhong & Xia, 2020 ) “research methods”, (Johnson & Christensen, 2000 ) and “research foci”. (Hynes et al., 2017 ; Spolaôr & Benitti, 2017 ).
In terms of interaction issues, three dimensions were included: “participants”, (Hwang & Tsai, 2011 ), “roles of the robot”, and “types of robot” (Taylor, 1980 ).
In terms of application, five dimensions were included, namely “dominant STEM disciplines”, “integration of robot and STEM” (Martín‐Páez et al., 2019 ), “contribution to STEM disciplines”, “pedagogical intervention”, (Spolaôr & Benitti, 2017 ) and “educational objectives” (Anwar et al., 2019 ). Table 1 shows the coding items in each dimension of the investigated issues.
Model of R-STEM education theme framework
Figure 3 shows the distribution of the publications selected from 2012 to 2021. The first two publications were found in 2012. From 2014 to 2017, the number of publications steadily increased, with two, three, four, and four publications, respectively. Moreover, R-STEM education has been increasingly discussed within the last 3 years (2018–2020) with six, three, and ten publications, respectively. The global pandemic in the early 2020s could have affected the number of papers published, with only five papers in 2021. This could be due to the fact that most robot-STEM education research is conducted in physical classroom settings.
Number of publications on R-STEM education from 2012 to 2021
Table 2 displays the journals in which the selected papers were published, the number of papers published in each journal, and the journal’s impact factor. It can be concluded that most of the papers on R-STEM education research were published in the Journal of Science Education and Technology , and the International Journal of Technology and Design Education , with six papers, respectively.
The geographic distribution of the reviewed studies indicated that more than half of the studies were conducted in the United States (53.8%), while Turkey and China were the location of five and three studies, respectively. Taiwan, Canada, and Italy were indicated to have two studies each. One study each was conducted in Australia, Mexico, and the Netherlands. Figure 4 shows the distribution of the countries where the R-STEM education was conducted.
Locations where the studies were conducted ( N = 39)
Regarding sample size, there were four most common sample sizes for the selected period (2012–2021): greater than 80 people (28.21% or 11 out of 39 studies), between 41 and 60 (25.64% or 10 out of 39 studies), 1 to 20 people (23.08% or 9 out of 39), and between 21 and 40 (20.51% or 8 out of 39 studies). The size of 61 to 80 people (2.56% or 1 out of 39 studies) was the least popular sample size (see Fig. 5 ).
Sample size across the studies ( N = 39)
Regarding the duration of the study (see Fig. 6 ), experiments were mostly conducted for less than or equal to 4 weeks (35.9% or 14 out of 39 studies). This was followed by less than or equal to 8 weeks (25.64% or 10 out of 39 studies), less than or equal to 6 months (20.51% or 8 out 39 studies), less than or equal to 12 months (10.26% or 4 out of 39 studies), while less than or equal to 1 day (7.69% or 3 out of 39 studies) was the least chosen duration.
Duration of interventions across the studies ( N = 39)
Figure 7 demonstrates the trends in research methods from 2012 to 2021. The use of questionnaires or surveys (35.9% or 14 out of 39 studies) and mixed methods research (35.9% or 14 out of 39 studies) outnumbered other methods such as experimental design (25.64% or 10 out of 39 studies) and system development (2.56% or 1 out of 39 studies).
Frequency of each research method used in 2012–2021
In these studies, research foci were divided into four aspects: cognition, affective, operational skill, and learning behavior. If the study involved more than one research focus, each issue was coded under each research focus.
In terms of cognitive skills, students’ learning performance was the most frequently measured (15 out of 39 studies). Six studies found that R-STEM education brought a positive result to learning performance. Two studies did not find any significant difference, while five studies showed mixed results or found that it depends. For example, Chang and Chen ( 2020 ) revealed that robots in STEM learning improved students’ cognition such as designing, electronic components, and computer programming.
In terms of affective skills, just over half of the reviewed studies (23 out of 39, 58.97%) addressed the students’ or teachers’ perceptions of employing robots in STEM education, of which 14 studies showed positive perceptions. In contrast, nine studies found mixed results. For instance, Casey et. al. ( 2018 ) determined students’ mixed perceptions of the use of robots in learning coding and programming.
Five studies were identified regarding operational skills by investigating students’ psychomotor aspects such as construction and mechanical elements (Pérez & López, 2019 ; Sullivan & Bers, 2016 ) and building and modeling robots (McDonald & Howell, 2012 ). Three studies found positive results, while two reported mixed results.
In terms of learning behavior, five out of 39 studies measured students’ learning behavior, such as students’ engagement with robots (Ma et al., 2020 ), students’ social behavior while interacting with robots (Konijn & Hoorn, 2020 ), and learner–parent interactions with interactive robots (Phamduy et al., 2017 ). Three studies showed positive results, while two found mixed results or found that it depends (see Table 3 ).
Participants.
Regarding the educational level of the participants, elementary school students (33.33% or 13 studies) were the most preferred study participants, followed by high school students (15.38% or 6 studies). The data were similar for preschool, junior high school, in-service teachers, and non-designated personnel (10.26% or 4 studies). College students, including pre-service teachers, were the least preferred study participants. Interestingly, some studies involved study participants from more than one educational level. For example, Ucgul and Cagiltay ( 2014 ) conducted experiments with elementary and middle school students, while Chapman et. al. ( 2020 ) investigated the effectiveness of robots with elementary, middle, and high school students. One study exclusively investigated gifted and talented students without reporting their levels of education (Sen et al., 2021 ). Figure 8 shows the frequency of study participants between 2012 and 2021.
Frequency of research participants in the selected period
For the function of robots in STEM education, as shown in Fig. 9 , more than half of the selected articles used robots as tools (31 out of 39 studies, 79.49%) for which the robots were designed to foster students’ programming ability. For instance, Barker et. al. ( 2014 ) investigated students’ building and programming of robots in hands-on STEM activities. Seven out of 39 studies used robots as tutees (17.95%), with the aim of students and teachers learning to program. For example, Phamduy et. al. ( 2017 ) investigated a robotic fish exhibit to analyze visitors’ experience of controlling and interacting with the robot. The least frequent role was tutor (2.56%), with only one study which programmed the robot to act as tutor or teacher for students (see Fig. 9 ).
Frequency of roles of robots
Furthermore, in terms of the types of robots used in STEM education, the LEGO MINDSTORMS robot was the most used (35.89% or 14 out of 39 studies), while Arduino was the second most used (12.82% or 5 out of 39 studies), and iRobot Create (5.12% or 2 out of 39 studies), and NAO (5.12% or 2 out of 39 studies) ranked third equal, as shown in Fig. 10 . LEGO was used to solve STEM problem-solving tasks such as building bridges (Convertini, 2021 ), robots (Chiang et al., 2020 ), and challenge-specific game boards (Leonard et al., 2018 ). Furthermore, four out of 36 studies did not specify the robots used in their studies.
Frequency of types of robots used
The dominant disciplines and the contribution to stem disciplines.
As shown in Table 4 , the most dominant discipline in R-STEM education research published from 2012 to 2021 was technology. Engineering, mathematics, and science were the least dominant disciplines. Programming was the most common subject for robotics contribution to the STEM disciplines (25 out of 36 studies, 64.1%), followed by engineering (12.82%), and mathematical method (12.82%). We found that interdisciplinary was discussed in the selected period, but in relatively small numbers. However, this finding is relevant to expose the use of robotics in STEM disciplines as a whole. For example, Barker et. al. ( 2014 ) studied how robotics instructional modules in geospatial and programming domains could be impacted by fidelity adherence and exposure to the modules. The dominance of STEM subjects based on robotics makes it necessary to study the way robotics and STEM are integrated into the learning process. Therefore, the forms of STEM integration are discussed in the following sub-section to report how teaching and learning of these disciplines can have learning goals in an integrated STEM environment.
There are three general forms of STEM integration (see Fig. 11 ). Of these studies, robot-STEM content integration was commonly used (22 studies, 56.41%), in which robot activities had multiple STEM disciplinary learning objectives. For example, Chang and Chen ( 2020 ) employed Arduino in a robotics sailboat curriculum. This curriculum was a cross-disciplinary integration, the objectives of which were understanding sailboats and sensors (Science), the direction of motors and mechanical structures (Engineering), and control programming (Technology). The second most common form was supporting robot-STEM content integration (12 out of 39 studies, 30.76%). For instance, KIBO robots were used in the robotics activities where the mechanical elements content area was meaningfully covered in support of the main programming learning objectives (Sullivan & Bers, 2019 ). The least common form was robot-STEM context integration (5 out of 39 studies, 12.82%) which was implemented through the robot to situate the disciplinary content goals in another discipline’s practices. For example, Christensen et. al. ( 2015 ) analyzed the impact of an after-school program that offered robots as part of students’ challenges in a STEM competition environment (geoscience and programming).
The forms of robot-STEM integration
In terms of instructional interventions, as shown in Fig. 12 , project-based learning (PBL) was the preferred instructional theory for using robots in R-STEM education (38.46% or 15 out 39 studies), with the aim of motivating students or robot users in the STEM learning activities. For example, Pérez and López ( 2019 ) argued that using low-cost robots in the teaching process increased students’ motivation and interest in STEM areas. Problem-based learning was the second most used intervention in this dimension (17.95% or 7 out of 39 studies). It aimed to improve students’ motivation by giving them an early insight into practical Engineering and Technology. For example, Gomoll et. al. ( 2017 ) employed robots to connect students from two different areas to work collaboratively. Their study showed the importance of robotic engagement in preliminary learning activities. Edutainment (12.82% or 5 out of 39 studies) was the third most used intervention. This intervention was used to bring together students and robots and to promote learning by doing. Christensen et. al. ( 2015 ) and Phamduy et. al. ( 2017 ) were the sample studies that found the benefits of hands-on and active learning engagement; for example, robotics competitions and robotics exhibitions could help retain a positive interest in STEM activities.
The pedagogical interventions in R-STEM education
As far as the educational objectives of robots are concerned (see Fig. 13 ), the majority of robots are used for learning and transfer skills (58.97% or 23 out of 39 studies) to enhance students’ construction of new knowledge. It emphasized the process of learning through inquiry, exploration, and making cognitive associations with prior knowledge. Chang and Chen’s ( 2020 ) is a sample study on how learning objectives promote students’ ability to transfer science and engineering knowledge learned through science experiments to design a robotics sailboat that could navigate automatically as a novel setting. Moreover, it also explicitly aimed to examine the hands-on learning experience with robots. For example, McDonald and Howell ( 2012 ) described how robots engaged with early year students to better understand the concepts of literacy and numeracy.
Educational objectives of R-STEM education
Creativity and motivation were found to be educational objectives in R-STEM education for seven out of 39 studies (17.94%). It was considered from either the motivational facet of social trend or creativity in pedagogy to improve students’ interest in STEM disciplines. For instance, these studies were driven by the idea that employing robots could develop students’ scientific creativity (Guven et al., 2020 ), confidence and presentation ability (Chiang et al., 2020 ), passion for college and STEM fields (Meyers et al., 2012 ), and career choice (Ayar, 2015 ).
The general benefits of educational robots and the professional development of teachers were equally found in four studies each. The first objective, the general benefits of educational robotics, was to address those studies that found a broad benefit of using robots in STEM education without highlighting the particular focus. The sample studies suggested that robotics in STEM could promote active learning and improve students’ learning experience through social interaction (Hennessy Elliott, 2020 ) and collaborative science projects (Li et al., 2016 ). The latter, teachers’ professional development, was addressed by four studies (10.25%) to utilize robots to enhance teachers’ efficacy. Studies in this category discussed how teachers could examine and identify distinctive instructional approaches with robotics work (Bernstein et al., 2022 ), design meaningful learning instruction (Ryan et al., 2017 ) and lesson materials (Kim et al., 2015 ), and develop more robust cultural responsive self-efficacy (Leonard et al., 2018 ).
This review study was conducted using content analysis from the WOS collection of research on robotics in STEM education from 2012 to 2021. The findings are discussed under the headings of each research question.
RQ 1: In terms of research, what were the location, sample size, duration of intervention, research methods, and research foci of the R-STEM education research?
About half of the studies were conducted in North America (the USA and Canada), while limited studies were found from other continents (Europe and the Asia Pacific). This trend was identified in the previous study on robotics for STEM activities (Conde et al., 2021 ). Among 39 studies, 28 (71.79%) had fewer than 80 participants, while 11 (28.21%) had more than 80 participants. The intervention’s duration across the studies was almost equally divided between less than or equal to a month (17 out of 39 studies, 43.59%) and more than a month (22 out of 39 studies, 56.41%). The rationale behind the most popular durations is that these studies were conducted in classroom experiments and as conditional learning. For example, Kim et. al. ( 2018 ) conducted their experiments in a course offered at a university where it took 3 weeks based on a robotics module.
A total of four different research methodologies were adopted in the studies, the two most popular being mixed methods (35.89%) and questionnaires or surveys (35.89%). Although mixed methods can be daunting and time-consuming to conduct (Kucuk et al., 2013 ), the analysis found that it was one of the most used methods in the published articles, regardless of year. Chang and Chen ( 2022 ) embedded a mixed-methods design in their study to qualitatively answer their second research question. The possible reason for this is that other researchers prefer to use mixed methods as their research design. Their main research question was answered quantitatively, while the second and remaining research questions were reported through qualitative analysis (Casey et al., 2018 ; Chapman et al., 2020 ; Ma et al., 2020 ; Newton et al., 2020 ; Sullivan & Bers, 2019 ). Thus, it was concluded that mixed methods could lead to the best understanding and integration of research questions (Creswell & Clark, 2013 ; Creswell et al., 2003 ).
In contrast, system development was the least used compared to other study designs, as most studies used existing robotic systems. It should be acknowledged that the most common outcome we found was to enable students to understand these concepts as they relate to STEM subjects. Despite the focus on system development, the help of robotics was identified as increasing the success of STEM learning (Benitti, 2012 ). Because limited studies focused on system development as their primary purpose (1 out of 39 studies, 2.56%), needs analyses may ask whether the mechanisms, types, and challenges of robotics are appropriate for learners. Future research will need further design and development of personalized robots to fill this part of the research gap.
About half of the studies (23 studies, 58.97%) were focused on investigating the effectiveness of robots in STEM learning, primarily by collecting students’ and teachers’ opinions. This result is more similar to Belpaeme et al. ( 2018 ) finding that users’ perceptions were common measures in studies on robotics learning. However, identifying perceptions of R-STEM education may not help us understand exactly how robots’ specific features afford STEM learning. Therefore, it is argued that researchers should move beyond such simple collective perceptions in future research. Instead, further studies may compare different robots and their features. For instance, whether robots with multiple sensors, a sensor, or without a sensor could affect students’ cognitive, metacognitive, emotional, and motivational in STEM areas (e.g., Castro et al., 2018 ). Also, there could be instructional strategies embedded in R-STEM education that can lead students to do high-order thinking, such as problem-solving with a decision (Özüorçun & Bicen, 2017 ), self-regulated and self-engagement learning (e.g., Li et al., 2016 ). Researchers may also compare the robotics-based approach with other technology-based approaches (e.g., Han et al., 2015 ; Hsiao et al., 2015 ) in supporting STEM learning.
RQ 2: In terms of interaction, what were the participants, roles of the robots, and types of robots of the R-STEM education research?
The majority of reviewed studies on R-STEM education were conducted with K-12 students (27 studies, 69.23%), including preschool, elementary school, junior, and high school students. There were limited studies that involved higher education students and teachers. This finding is similar to the previous review study (Atman Uslu et al., 2022 ), which found a wide gap among research participants between K-12 students and higher education students, including teachers. Although it is unclear why there were limited studies conducted involving teachers and higher education students, which include pre-service teachers, we are aware of the critical task of designing meaningful R-STEM learning experiences which is likely to require professional development. In this case, both pre- and in-service teachers could examine specific objectives, identify topics, test the application, and design potential instruction to align well with robots in STEM learning (Bernstein et al., 2022 ). Concurrently, these pedagogical content skills in R-STEM disciplines might not be taught in the traditional pre-service teacher education and particular teachers’ development program (Huang et al., 2022 ). Thus, it is recommended that future studies could be conducted to understand whether robots can improve STEM education for higher education students and teachers professionally.
Regarding the role of robots, most were used as learning tools (31 studies, 79.48%). These robots are designed to have the functional ability to command or program some analysis and processing (Taylor, 1980 ). For example, Leonard et. al. ( 2018 ) described how pre-service teachers are trained in robotics activities to facilitate students’ learning of computational thinking. Therefore, robots primarily provide opportunities for learners to construct knowledge and skills. Only one study (2.56%), however, was found to program robots to act as tutors or teachers for students. Designing a robot-assisted system has become common in other fields such as language learning (e.g., Hong et al., 2016 ; Iio et al., 2019 ) and special education (e.g., Özdemir & Karaman, 2017 ) where the robots instruct the learning activities for students. In contrast, R-STEM education has not looked at the robot as a tutor, but has instead focused on learning how to build robots (Konijn & Hoorn, 2020 ). It is argued that robots with features as human tutors, such as providing personalized guidance and feedback, could assist during problem-solving activities (Fournier-Viger et al., 2013 ). Thus, it is worth exploring in what teaching roles the robot will work best as a tutor in STEM education.
When it comes to types of robots, the review found that LEGO dominated robots’ employment in STEM education (15 studies, 38.46%), while the other types were limited in their use. It is considered that LEGO tasks are more often associated with STEM because learners can be more involved in the engineering or technical tasks. Most researchers prefer to use LEGO in their studies (Convertini, 2021 ). Another interesting finding is about the cost of the robots. Although robots are generally inexpensive, some products are particularly low-cost and are commonly available in some regions (Conde et al., 2021 ). Most preferred robots are still considered exclusive learning tools in developing countries and regions. In this case, only one study offered a low-cost robot (Pérez & López, 2019 ). This might be a reason why the selected studies were primarily conducted in the countries and continents where the use of advanced technologies, such as robots, is growing rapidly (see Fig. 4 ). Based on this finding, there is a need for more research on the use of low-cost robots in R-STEM instruction in the least developed areas or regions of the world. For example, Nel et. al. ( 2017 ) designed a STEM program to build and design a robot which exclusively enabling students from low-income household to participate in the R-STEM activities.
RQ 3: In terms of application, what were the dominant STEM disciplines, contribution to STEM disciplines, integration of robots and STEM, pedagogical interventions, and educational objectives of the R-STEM research?
While Technology and Engineering are the dominant disciplines, this review found several studies that directed their research to interdisciplinary issues. The essence of STEM lies in interdisciplinary issues that integrate one discipline into another to create authentic learning (Hansen, 2014 ). This means that some researchers are keen to develop students’ integrated knowledge of Science, Technology, Engineering, and Mathematics (Chang & Chen, 2022 ; Luo et al., 2019 ). However, Science and Mathematics were given less weight in STEM learning activities compared to Technology and Engineering. This issue has been frequently reported as a barrier to implementing R-STEM in the interdisciplinary subject. Some reasons include difficulties in pedagogy and classroom roles, lack of curriculum integration, and a limited opportunity to embody one learning subject into others (Margot & Kettler, 2019 ). Therefore, further research is encouraged to treat these disciplines equally, so is the way of STEM learning integration.
The subject-matter results revealed that “programming” was the most common research focus in R-STEM research (25 studies). Researchers considered programming because this particular topic was frequently emphasized in their studies (Chang & Chen, 2020 , 2022 ; Newton et al., 2020 ). Similarly, programming concepts were taught through support robots for kindergarteners (Sullivan & Bers, 2019 ), girls attending summer camps (Chapman et al., 2020 ), and young learners with disabilities (Lamptey et al., 2021 ). Because programming simultaneously accompanies students’ STEM learning, we believe future research can incorporate a more dynamic and comprehensive learning focus. Robotics-based STEM education research is expected to encounter many interdisciplinary learning issues.
Researchers in the reviewed studies agreed that the robot could be integrated with STEM learning with various integration forms. Bryan et. al. ( 2015 ) argued that robots were designed to develop multiple learning goals from STEM knowledge, beginning with an initial learning context. It is parallel with our finding that robot-STEM content integration was the most common integration form (22 studies, 56.41%). In this form, studies mainly defined their primary learning goals with one or more anchor STEM disciplines (e.g., Castro et al., 2018 ; Chang & Chen, 2020 ; Luo et al., 2019 ). The learning goals provided coherence between instructional activities and assessments that explicitly focused on the connection among STEM disciplines. As a result, students can develop a deep and transferable understanding of interdisciplinary phenomena and problems through emphasizing the content across disciplines (Bryan et al., 2015 ). However, the findings on learning instruction and evaluation in this integration are inconclusive. A better understanding of the embodiment of learning contexts is needed, for instance, whether instructions are inclusive, socially relevant, and authentic in the situated context. Thus, future research is needed to identify the quality of instruction and evaluation and the specific characteristics of robot-STEM integration. This may place better provision of opportunities for understanding the form of pedagogical content knowledge to enhance practitioners’ self-efficacy and pedagogical beliefs (Chen et al., 2021a , 2021b ).
Project-based learning (PBL) was the most used instructional intervention with robots in R-STEM education (15 studies, 38.46%). Blumenfeld et al. ( 1991 ) credited PBL with the main purpose of engaging students in investigating learning models. In the case of robotics, students can create robotic artifacts (Spolaôr & Benitti, 2017 ). McDonald and Howell ( 2012 ) used robotics to develop technological skills in lower grades. Leonard et. al. ( 2016 ) used robots to engage and develop students’ computational thinking strategies in another example. In the aforementioned study, robots were used to support learning content in informal education, and both teachers and students designed robotics experiences aligned with the curriculum (Bernstein et al., 2022 ). As previously mentioned, this study is an example of how robots can cover STEM content from the learning domain to support educational goals.
The educational goal of R-STEM education was the last finding of our study. Most of the reviewed studies focused on learning and transferable skills as their goals (23 studies, 58.97%). They targeted learning because the authors investigated the effectiveness of R-STEM learning activities (Castro et al., 2018 ; Convertini, 2021 ; Konijn & Hoorn, 2020 ; Ma et al., 2020 ) and conceptual knowledge of STEM disciplines (Barak & Assal, 2018 ; Gomoll et al., 2017 ; Jaipal-Jamani & Angeli 2017 ). They targeted transferable skills because they require learners to develop individual competencies in STEM skills (Kim et al., 2018 ; McDonald & Howell, 2012 ; Sullivan & Bers, 2016 ) and to master STEM in actual competition-related skills (Chiang et al., 2020 ; Hennessy Elliott, 2020 ).
The majority of the articles examined in this study referred to theoretical frameworks or certain applications of pedagogical theories. This finding contradicts Atman Uslu et. al. ( 2022 ), who concluded that most of the studies in this domain did not refer to pedagogical approaches. Although we claim the employment pedagogical frameworks in the examined articles exist, those articles primarily did not consider a strict instructional design when employing robots in STEM learning. Consequently, the discussions in the studies did not include how the learning–teaching process affords students’ positive perceptions. Therefore, both practitioners and researchers should consider designing learning instruction using robots in STEM education. To put an example, the practitioners may regard students’ zone of proximal development (ZPD) when employing robot in STEM tasks. Giving an appropriate scaffolding and learning contents are necessary for them to enhance their operational skills, application knowledge and emotional development. Although the integration between robots and STEM education was founded in the reviewed studies, it is worth further investigating the disciplines in which STEM activities have been conducted. This current review found that technology and engineering were the subject areas of most concern to researchers, while science and mathematics did not attract as much attention. This situation can be interpreted as an inadequate evaluation of R-STEM education. In other words, although those studies aimed at the interdisciplinary subject, most assessments and evaluations were monodisciplinary and targeted only knowledge. Therefore, it is necessary to carry out further studies in these insufficient subject areas to measure and answer the potential of robots in every STEM field and its integration. Moreover, the broadly consistent reporting of robotics generally supporting STEM content could impact practitioners only to employ robots in the mainstream STEM educational environment. Until that point, very few studies had investigated the prominence use of robots in various and large-scale multidiscipline studies (e.g., Christensen et al., 2015 ).
Another finding of the reviewed studies was the characteristic of robot-STEM integration. Researchers and practitioners must first answer why and how integrated R-STEM could be embodied in the teaching–learning process. For example, when robots are used as a learning tool to achieve STEM learning objectives, practitioners are suggested to have application knowledge. At the same time, researchers are advised to understand the pedagogical theories so that R-STEM integration can be flexibly merged into learning content. This means that the learning design should offer students’ existing knowledge of the immersive experience in dealing with robots and STEM activities that assist them in being aware of their ideas, then building their knowledge. In such a learning experience, students will understand the concept of STEM more deeply by engaging with robots. Moreover, demonstration of R-STEM learning is not only about the coherent understanding of the content knowledge. Practitioners need to apply both flexible subject-matter knowledge (e.g., central facts, concepts and procedures in the core concept of knowledge), and pedagogical content knowledge, which specific knowledge of approaches that are suitable for organizing and delivering topic-specific content, to the discipline of R-STEM education. Consequently, practitioners are required to understand the nature of robots and STEM through the content and practices, for example, taking the lead in implementing innovation through subject area instruction, developing collaboration that enriches R-STEM learning experiences for students, and being reflective practitioners by using students’ learning artifacts to inform and revise practices.
Overall, future research could explore the great potential of using robots in education to build students’ knowledge and skills when pursuing learning objectives. It is believed that the findings from this study will provide insightful information for future research.
The articles reviewed in this study were limited to journals indexed in the WOS database and R-STEM education-related SSCI articles. However, other databases and indexes (e.g., SCOPUS, and SCI) could be considered. In addition, the number of studies analyzed was relatively small. Further research is recommended to extend the review duration to cover the publications in the coming years. The results of this review study have provided directions for the research area of STEM education and robotics. Specifically, robotics combined with STEM education activities should aim to foster the development of creativity. Future research may aim to develop skills in specific areas such as robotics STEM education combined with the humanities, but also skills in other humanities disciplines across learning activities, social/interactive skills, and general guidelines for learners at different educational levels. Educators can design career readiness activities to help learners build self-directed learning plans.
Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.
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The authors would like to express their gratefulness to the three anonymous reviewers for providing their precious comments to refine this manuscript.
This study was supported by the Ministry of Science and Technology of Taiwan under contract numbers MOST-109-2511-H-011-002-MY3 and MOST-108-2511-H-011-005-MY3; National Science and Technology Council (TW) (NSTC 111-2410-H-031-092-MY2); Soochow University (TW) (111160605-0014). Any opinions, findings, conclusions, and/or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of Ministry of Science and Technology of Taiwan.
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Darmawansah Darmawansah, Gwo-Jen Hwang & Jia-Cing Liang
Department of English Language and Literature, Soochow University, Q114, No. 70, Linhsi Road, Shihlin District, Taipei, 111, Taiwan
Mei-Rong Alice Chen
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Gwo-Jen Hwang
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DD, MR and GJ conceptualized the study. MR wrote the outline and DD wrote draft. DD, MR and GJ contributed to the manuscript through critical reviews. DD, MR and GJH revised the manuscript. DD, MR and GJ finalized the manuscript. DD edited the manuscript. MR and GJ monitored the project and provided adequate supervision. DD, MR and JC contributed with data collection, coding, analyses and interpretation. All authors read and approved the final manuscript.
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Additional file 1..
Coded papers.
# | Authors | Dimension | ||||
---|---|---|---|---|---|---|
Location | Sample size | Duration of intervention | Research methods | Research foci | ||
1 | Convertini ( ) | Italy | 21–40 | ≤ 1 day | Experimental design | Problem solving, collaboration or teamwork, and communication |
2 | Lamptey et. al. ( ) | Canada | 41–60 | ≤ 8 weeks | Mixed method | Satisfaction or interest, and learning perceptions |
3 | Üçgül and Altıok ( ) | Turkey | 41–60 | ≤ 1 day | Questionnaire or survey | Attitude and motivation, learning perceptions |
4 | Sen et. al. ( ) | Turkey | 1–20 | ≤ 4 weeks | Experimental design | Problem solving, critical thinking, logical thinking, creativity, collaboration or teamwork, and communication |
5 | Stewart et. al. ( ) | USA | > 80 | ≤ 6 months | Mixed method | Higher order thinking skills, problem-solving, technology acceptance, attitude and motivation, and learning perceptions |
6 | Bernstein et. al. ( ) | USA | 1–20 | ≤ 1 day | Questionnaire or survey | Attitude and motivation, and learning perceptions |
7 | Chang and Chen ( ) | Taiwan | 41–60 | ≤ 8 weeks | Mixed method | Learning performance, problem-solving, satisfaction or interest, and operational skill |
8 | Chang and Chen ( ) | Taiwan | 41–60 | ≤ 8 weeks | Experimental design | Learning perceptions, and operational skill |
9 | Chapman et al. ( ) | USA | > 80 | ≤ 8 weeks | Mixed method | Learning performance, and learning perceptions |
10 | Chiang et. al. ( ) | China | 41–60 | ≤ 4 weeks | Questionnaire or survey | Creativity, and self-efficacy and confidence |
11 | Guven et. al. ( ) | Turkey | 1–20 | ≤ 6 months | Mixed method | Creativity, technology acceptance, attitude and motivation, self-efficacy or confidence, satisfaction or interest, and learning perception |
12 | Hennessy Elliott ( ) | USA | 1–20 | ≤ 12 months | Experimental design | Collaboration, communication, and preview situation |
13 | Konijn and Hoorn ( ) | Netherlands | 41–60 | ≤ 4 weeks | Experimental design | Learning performance, and learning behavior |
14 | Ma et. al. ( ) | China | 41–60 | ≤ 6 months | Mixed method | Learning performance, learning perceptions, and learning behavior |
15 | Newton et. al. ( ) | USA | > 80 | ≤ 6 months | Mixed method | Attitude and motivation, and self-efficacy and confidence |
16 | Luo et. al. ( ) | USA | 41–60 | ≤ 4 weeks | Questionnaire or survey | Technology acceptance, attitude and motivation, and self-efficacy |
17 | Pérez and López ( ) | Mexico | 21–40 | ≤ 6 months | System development | Operational skill |
18 | Sullivan and Bers ( ) | USA | > 80 | ≤ 8 weeks | Mixed method | Attitude and motivation, satisfaction or interest, and learning behavior |
19 | Barak and Assal ( ) | Israel | 21–40 | ≤ 6 months | Mixed method | Learning performance, technology acceptance, self-efficacy, and satisfaction or interest |
20 | Castro et. al. ( ) | Italy | > 80 | ≤ 8 weeks | Questionnaire or survey | Learning performance, and self-efficacy |
21 | Casey et. al. ( ) | USA | > 80 | ≤ 12 months | Questionnaire or survey | Learning satisfaction |
22 | Kim et. al. ( ) | USA | 1–20 | ≤ 4 weeks | Questionnaire or survey | Problem solving, and preview situation |
23 | Leonard et. al. ( ) | USA | 41–60 | ≤ 12 months | Questionnaire or survey | Learning performance, self-efficacy, and learning perceptions |
24 | Taylor ( ) | USA | 1–20 | ≤ 1 day | Experimental design | Learning performance, and preview situation |
25 | Gomoll et. al. ( ) | USA | 21–40 | ≤ 8 weeks | Experimental design | Problem solving, collaboration, communication |
26 | Jaipal-Jamani and Angeli ( ) | Canada | 21–40 | ≤ 4 weeks | Mixed method | Learning performance, self-efficacy, and satisfaction or interest |
27 | Phamduy et. al. ( ) | USA | > 80 | ≤ 4 weeks | Mixed method | Satisfaction or interest, and learning behavior |
28 | Ryan et. al. ( ) | USA | 1–20 | ≤ 12 months | Questionnaire or survey | Learning perceptions |
29 | Gomoll et. al. ( ) | USA | 21–40 | ≤ 6 months | Experimental design | Satisfaction or interest, and learning perceptions |
30 | Leonard et. al. ( ) | USA | 61–80 | ≤ 4 weeks | Mixed method | Attitude and motivation, and self-efficacy |
31 | Li et. al. ( ) | China | 21–40 | ≤ 8 weeks | Experimental design | Learning performance, and problem-solving, |
32 | Sullivan and Bers ( ) | USA | 41–60 | ≤ 8 weeks | Experimental design | Learning performance, and operational skill |
33 | Ayar ( ) | Turkey | > 80 | ≤ 4 weeks | Questionnaire or survey | Attitude and motivation, satisfaction or interest, and learning perceptions |
34 | Christensen et. al. ( ) | USA | > 80 | ≤ 6 months | Questionnaire or survey | Technology acceptance, satisfaction or interest, and learning perceptions |
35 | Kim et al. ( ) | USA | 1–20 | ≤ 4 weeks | Mixed method | Learning performance, satisfaction or interest, and learning perceptions |
36 | Barker et. al. ( ) | USA | 21–40 | ≤ 4 weeks | Questionnaire or survey | Technology acceptance, attitude and motivation, and learning perceptions |
37 | Ucgul and Cagiltay ( ) | Turkey | 41–60 | ≤ 4 weeks | Questionnaire or survey | Learning performance, satisfaction or interest, and learning perceptions |
38 | McDonald and Howell ( ) | Australia | 1–20 | ≤ 8 weeks | Mixed method | Learning performance, operational skills, and learning behavior |
39 | Meyers et. al. ( ) | USA | > 80 | ≤ 4 weeks | Questionnaire or survey | Learning perceptions |
# | Authors | Interaction | Application | ||||||
---|---|---|---|---|---|---|---|---|---|
Participants | Role of robot | Types of robot | Dominant STEM discipline | Contribution to STEM | Integration of robot and STEM | Pedagogical intervention | Educational objectives | ||
1 | Convertini ( ) | Preschool or Kindergarten | Tutee | LEGO (Mindstorms) | Engineering | Structure and construction | Context integration | Active construction | Learning and transfer skills |
2 | Lamptey et. al. ( ) | Non-specified | Tool | LEGO (Mindstorms) | Technology | Programming | Supporting content integration | Problem-based learning | Learning and transfer skills |
3 | Üçgül and Altıok ( ) | Junior high school students | Tool | LEGO (Mindstorms) | Technology | Programming | Content integration | Project-based learning | Creativity and motivation |
4 | Sen et. al. ( ) | Others (gifted and talented students) | Tutee | LEGO (Mindstorms) | Technology | Programming, and Mathematical methods | Supporting content integration | Problem-based learning | Learning and transfer skills |
5 | Stewart et. al. ( ) | Elementary school students | Tool | Botball robot | Technology | Programming, and power and dynamical system | Content integration | Project-based learning | Learning and transfer skills |
6 | Bernstein et. al. ( ) | In-service teachers | Tool | Non-specified | Science | Biomechanics | Content integration | Project-based learning | Teachers’ professional development |
7 | Chang and Chen ( ) | High school students | Tool | Arduino | Interdisciplinary | Basic Physics, Programming, Component design, and mathematical methods | Content integration | Project-based learning | Learning transfer and skills |
8 | Chang and Chen ( ) | High school students | Tool | Arduino | Interdisciplinary | Basic Physics, Programming, Component design, and mathematical methods | Content integration | Project-based learning | Learning transfer and skills |
9 | Chapman et. al. ( ) | Elementary, middle, and high school students | Tool | LEGO (Mindstorms) and Maglev trains | Engineering | Engineering | Content integration | Engaged learning | Learning transfer and skills |
10 | Chiang et. al. ( ) | Non-specified | Tool | LEGO (Mindstorms) | Technology | Non-specified | Context integration | Edutainment | Creativity and motivation |
11 | Guven et. al. ( ) | Elementary school students | Tutee | Arduino | Technology | Programming | Content integration | Constructivism | Creativity and motivation |
12 | Hennessy Elliott ( ) | Students and teachers | Tool | Non-specified | Technology | Non-specified | Supporting content integration | Collaborative learning | General benefits of educational robotics |
13 | Konijn and Hoorn ( ) | Elementary school students | Tutor | Nao robot | Mathematics | Mathematical methods | Supporting content integration | Engaged learning | Learning and transfer skills |
14 | Ma et. al. ( ) | Elementary school students | Tool | Microduino and Makeblock | Engineering | Non-specified | Content integration | Experiential learning | Learning and transfer skills |
15 | Newton et. al. ( ) | Elementary school students | Tool | LEGO (Mindstorms) | Technology | Programming | Supporting content integration | Active construction | Learning and transfer skills |
16 | Luo et. al. ( ) | Junior high or middle school | Tool | Vex robots | Interdisciplinary | Programming, Engineering, and Mathematics | Content integration | Constructivism | General benefits of educational robots |
17 | Pérez and López ( ) | High school students | Tutee | Arduino | Engineering | Programming, and mechanics | Content integration | Project-based learning | Learning and transfer skills |
18 | Sullivan and Bers ( ) | Kindergarten and Elementary school students | Tool | KIBO robots | Technology | Programming | Context integration | Project-based learning | Learning and transfer skills |
19 | Barak and Assal ( ) | High school students | Tool | Non-specified | Technology | Programming, mathematical methods | Content integration | Problem-based learning | Learning and transfer skills |
20 | Castro et. al. ( ) | Lower secondary | Tool | Bee-bot | Technology | Programming | Content integration | Problem-based learning | Learning and transfer skills |
21 | Casey et. al. ( ) | Elementary school students | Tool | Roamers robot | Technology | Programming | Content integration | Metacognitive learning | Learning and transfer skills |
22 | Kim et. al. ( ) | Pre-service teachers | Tool | Non-specified | Technology | Programming | Supporting content integration | Problem-based learning | Learning and transfer skills |
23 | Leonard et. al. ( ) | In-service teachers | Tool | LEGO (Mindstorms) | Technology | Programming | Supporting content integration | Project-based learning | Teachers’ professional development |
24 | Taylor ( ) | Kindergarten and elementary school students | Tool | Dash robot | Technology | Programming, | Content integration | Problem-based learning | Learning and transfer skills |
25 | Gomoll et. al. ( ) | Middle school students | Tool | iRobot create | Technology | Programming, and structure and construction | Content integration | Problem-based learning | Learning and transfer skills |
26 | Jaipal-Jamani and Angeli ( ) | Pre-service teachers | Tool | LEGO WeDo | Technology | Programming | Supporting content integration | Project-based learning | Learning and transfer skills |
27 | Phamduy et. al. ( ) | Non-specified | Tutee | Arduino | Science | Biology | Context integration | Edutainment | Diversity and broadening participation |
28 | Ryan et. al. ( ) | In-service teachers | Tool | LEGO (Mindstorms) | Engineering | Engineering | Content integration | Constructivism | Teacher’s professional development |
29 | Gomoll et. al. ( ) | Non-specified | Tool | iRobot create | Technology | Programming | Content integration | Project-based learning | Learning and transfer skill |
30 | Leonard et. al. ( ) | Middle school students | Tool | LEGO (Mindstorms) | Technology | Programming | Content integration | Project-based learning | Learning and transfer skill |
31 | Li et. al. ( ) | Elementary school students | Tool | LEGO Bricks | Engineering | Structure and construction | Supporting content integration | Project-based learning | General benefits of educational robotics |
32 | Sullivan and Bers ( ) | Kindergarten and Elementary school students | Tool | Kiwi Kits | Engineering | Digital signal process | Content integration | Project-based learning | Learning and transfer skill |
33 | Ayar ( ) | High school students | Tool | Nao robot | Engineering | Component design | Content integration | Edutainment | Creativity and 34motivation |
34 | Christensen et. al. ( ) | Middle and high school students | Tutee | Non-specified | Engineering | Engineering | Context integration | Edutainment | Creativity and motivation |
35 | Kim et. al. ( ) | Pre-service teachers | Tool | RoboRobo | Technology | Programming | Supporting content integration | Engaged learning | Teachers’ professional development |
36 | Barker et. al. ( ) | In-service teachers | Tool | LEGO (Mindstorms) | Technology | Geography information system, and programming | Supporting content integration | Constructivism | Creativity and motivation |
37 | Ucgul and Cagiltay ( ) | Elementary and Middle school students | Tool | LEGO (Mindstorms) | Technology | Programming, mechanics, and mathematics | Content integration | Project-based learning | General benefits of educational robots |
38 | McDonald and Howell ( ) | Elementary school students | Tool | LEGO WeDo | Technology | Programming, and students and construction | Content integration | Project-based learning | Learning and transfer skills |
39 | Meyers et. al. ( ) | Elementary school students | Tool | LEGO (Mindstorms) | Engineering | Engineering | Supporting content integration | Edutainment | Creativity and motivation |
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Darmawansah, D., Hwang, GJ., Chen, MR.A. et al. Trends and research foci of robotics-based STEM education: a systematic review from diverse angles based on the technology-based learning model. IJ STEM Ed 10 , 12 (2023). https://doi.org/10.1186/s40594-023-00400-3
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Accepted : 13 January 2023
Published : 10 February 2023
DOI : https://doi.org/10.1186/s40594-023-00400-3
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Science isn’t merely for scientists. Understanding science is part of being a well-rounded and informed citizen. Science, technology, engineering, and mathematics (STEM) education research is dedicated to studying the nature of learning, the impact of different science teaching strategies, and the most effective ways to recruit and retain the next generation of scientists.
Center for Astrophysics | Harvard & Smithsonian STEM education researchers are engaged in a number of projects:
Developing research-based tests for use in evaluating students’ knowledge of science concepts. These tests are designed to check for common differences in the way non-scientists understand a subject as compared to scientists. When offered at the beginning and end of science courses, they assess whether instruction has resulted in students' conceptual growth. The tests are freely available for education researchers and teachers, and cover the full range of elementary, secondary, and university courses in science. Misconception-Orientation Standard-Based Assessment Resources for Teachers (MOSART)
Studying ways to improve students’ preparation for introductory STEM courses in college. Students arrive at college with varying pre-college educational experiences, which often influence how well they do in their first STEM classes. To keep interested students in STEM programs, researchers look at measurable factors that predict improved performance. Factors Influencing College Success in STEM (FICS)
Discerning factors that strengthen students’ interest in pursuing a STEM career. Education researchers look at a whole range of pre-college experiences in and out of school that can affect students’ interest in pursuing STEM careers, in order to see both what encourages and what drives them away. Persistence in STEM (PRiSE)
Examining predictors of student outcomes in MOOCs. Many universities have implemented MOOCs to provide academic resources beyond the university, but the research on how well they perform compared with ordinary classes is scant. In addition, MOOCs are frequently plagued by students dropping out. By studying actual implementations of MOOCs, SED researchers hope to gather evidence to explain why many students don’t stick with the course through the end. Massive Open Online Courses (MOOCs)
Public understanding of science is essential for our democratic society. At the same time, white female students and students of color are underrepresented across STEM fields, which is a problem both from equity and workforce demand perspectives. For these reasons, researchers at the Center for Astrophysics | Harvard & Smithsonian study how to improve science teaching and learning.
The Science Education Department (SED) at the Center for Astrophysics is dedicated to researching how people learn, and identifying measurable ways to evaluate learning for students in STEM classes. SED researchers have developed assessment tools designed to evaluate students’ conceptual knowledge for all levels from elementary school through university. These tests are freely available for teachers and other education specialists. Experts in the program also study the educational outcomes of massive open online courses (MOOCs) , which are widely used by universities despite the current lack of evidence on their effectiveness.
A current challenge of STEM education is the substantial underrepresentation of white female scientists and scientists of color across STEM fields, which limits the potential for innovation and excellence in scientific research. To address this problem, SED researchers study variables that predict persistence of students within the STEM pipeline, factors that impact achievement by students in STEM courses, and the development of science identity.
In addition to pursuing fundamental STEM education research, Harvard and Smithsonian educators translate these findings into practice by developing innovative science programs, curricula, interactive media, and technology-based tools for STEM learning. These research-based resources are used by educational audiences in the United States and around the world. The significance of SED’s work has been recognized in the form of grants from the National Science Foundation, NASA, and the National Institutes of Health.
Cambridge Explores the Universe 2018, held at the Center for Astrophysics | Harvard & Smithsonian in Cambridge, MA.
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New grant supports teen air quality studies, michael foley elected first grad student on aas education committee, cfa job shadow event makes astronomy more accessible, to navigate the heavens, take a seat, thousands of new astronomical images highlighted in latest release of worldwide telescope, astronomy educators awarded $2.8m to inspire minority youth to pursue stem careers, factors influencing college success in stem (fics), massive open online courses (moocs), misconception-oriented standards-based assessment resources for teachers (mosart), persistence in stem (prise), sensing the dynamic universe, worldwide telescope (wwt), youthastronet, telescopes and instruments, microobservatory telescope network, spitzer space telescope.
Explore compelling qualitative research topics for STEM students, delving into personal narratives, ethical dilemmas, and educational impacts across science, technology, engineering, and mathematics.
STEM disciplines traditionally focus on equations, experiments, and empirical evidence. Yet, the human dimension of these fields profoundly shapes their evolution and application.
Qualitative research thus becomes pivotal in unraveling the motivations behind scientific breakthroughs, examining personal stories, perspectives, and educational influences that mold STEM practices.
From uncovering the inspirations driving young scientists to navigating ethical quandaries in technological advancements, and exploring how science education impacts diverse communities, qualitative research offers a rich tapestry of insights into STEM’s human aspect.
This guide curates intriguing qualitative research topics that illuminate the personal narratives within science, technology, engineering, and mathematics. Embark on a journey to uncover the human stories behind STEM!
Table of Contents
Qualitative research topics for stem students.
Check out qualitative research topics for STEM students:-
Project Idea: Explore how cities impact bird populations. Use birdwatching and community surveys to track species diversity in urban areas versus natural habitats.
Innovative Approach: Create a citizen science project where local residents and schools monitor bird populations in their neighborhoods using a mobile app.
Project Idea: Investigate ethical dilemmas in animal research. Interview scientists and activists to understand perspectives on humane treatment and alternative methods.
Innovative Approach: Organize a debate or public forum where students role-play different stakeholders (scientists, ethicists, animal rights advocates) to discuss and propose solutions.
Project Idea: Document traditional uses of medicinal plants. Interview healers and botanists to explore their knowledge and conservation efforts.
Innovative Approach: Create an interactive digital archive showcasing interviews, plant specimens , and stories from local communities about medicinal plants.
Project Idea: Study community perceptions of conservation efforts. Interview residents and conservationists to assess awareness and participation in local wildlife conservation projects.
Innovative Approach: Host a virtual reality (VR) experience where participants explore a simulated wildlife reserve, learning about conservation challenges and solutions.
Project Idea: Research factors contributing to pollinator decline. Analyze pesticide use and habitat loss impacts on bee populations through fieldwork and stakeholder interviews.
Innovative Approach: Develop an educational board game where players must balance farming practices with bee conservation efforts, raising awareness through interactive gameplay.
Project Idea: Survey public attitudes towards chemical safety in household products. Analyze labeling and consumer preferences for eco-friendly alternatives.
Innovative Approach: Create an Instagram campaign where participants share photos and reviews of safe household products, promoting awareness and informed consumer choices.
Project Idea: Interview small business owners adopting green chemistry practices. Analyze case studies of successful eco-friendly startups and their impact on sustainability.
Innovative Approach: Organize a “Green Shark Tank” event where students pitch eco-friendly product ideas to local entrepreneurs and sustainability experts for feedback and support.
Project Idea: Investigate chemical waste recycling practices. Interview engineers and policymakers to understand challenges and innovations in recycling technologies.
Innovative Approach: Design a virtual reality experience where users explore a recycling plant, learning about chemical waste processes and environmental benefits.
Project Idea: Evaluate educational resources in chemistry. Interview teachers and students to assess the effectiveness of hands-on experiments and digital simulations.
Innovative Approach: Develop a mobile app featuring interactive chemistry tutorials and virtual labs, making learning engaging and accessible outside the classroom.
Project Idea: Explore ethical considerations in chemical research. Interview researchers to discuss issues like data integrity and public trust in scientific studies.
Innovative Approach: Host a podcast series where scientists share personal stories and ethical dilemmas encountered in their research, encouraging open dialogue and critical thinking.
Project Idea: Engage the public in space exploration. Host workshops where participants design and build model Mars rovers, learning about planetary exploration challenges.
Innovative Approach: Collaborate with local artists to create a mural depicting humanity’s journey into space, sparking curiosity and wonder in the community.
Project Idea: Investigate public perceptions of renewable energy. Interview engineers and policymakers about solar and wind power adoption and community benefits.
Innovative Approach: Organize a renewable energy fair where students showcase DIY solar panel projects and energy-efficient designs, promoting sustainable practices in everyday life.
Project Idea: Explore applications of quantum mechanics. Interview physicists and tech innovators to understand quantum computing and cryptography advancements.
Innovative Approach: Create an augmented reality (AR) experience where users interact with quantum particles, learning about their unique properties and potential applications.
Project Idea: Discuss ethical dilemmas in particle physics. Host a mock UN summit where students negotiate international agreements on particle accelerator safety and collaboration.
Innovative Approach: Organize a live-streamed virtual tour of CERN, featuring interviews with physicists and behind-the-scenes footage of particle research, engaging global audiences in scientific exploration.
Project Idea: Explore public understanding of scientific methods. Survey community attitudes towards physics concepts like energy conservation and climate change solutions.
Innovative Approach: Create a YouTube channel featuring physics experiments and explanations in everyday contexts, making complex concepts accessible and engaging for viewers of all ages.
Virtual ventures: designing immersive experiences in virtual reality.
Project Idea: Develop user-friendly VR applications. Conduct user tests to improve interface design and user engagement in virtual environments for education and entertainment.
Innovative Approach: Collaborate with local museums to create VR exhibits where visitors explore historical landmarks or futuristic cities, blending technology with cultural heritage.
Project Idea: Interview urban planners and engineers about green infrastructure. Analyze case studies of eco-friendly buildings and transportation projects promoting urban sustainability.
Innovative Approach: Partner with city officials to host a hackathon where students propose green tech solutions like smart traffic lights and energy-efficient public spaces, fostering creativity and civic engagement.
Project Idea: Investigate ethical issues in medical technology. Interview biomedical engineers and healthcare professionals about patient privacy and ethical treatment in device development.
Innovative Approach: Create a podcast series featuring interviews with medical innovators discussing breakthroughs in prosthetics and bioengineering, inspiring ethical considerations in healthcare.
Project Idea: Evaluate engineering education programs. Survey students and educators to identify effective teaching methods and technological tools for promoting hands-on learning and career readiness.
Innovative Approach: Launch a student-led engineering club focused on building sustainable solutions for local challenges, fostering collaboration and real-world problem-solving skills.
Project Idea: Interview robotics experts about automation’s impact. Analyze case studies of robotic applications in industries like manufacturing and healthcare, exploring technological advancements and societal benefits.
Innovative Approach: Organize a robotics expo where students showcase DIY robots and automation projects, demonstrating their practical applications in improving daily tasks and industry efficiency.
Cyber sleuths: protecting online privacy and security.
Project Idea: Investigate cybersecurity awareness. Conduct workshops and simulations to educate users about phishing scams and data protection strategies in digital environments.
Innovative Approach: Design an interactive mobile app where players solve cybersecurity puzzles and learn encryption techniques, promoting digital literacy and safe online practices.
Project Idea: Develop intuitive mobile applications. Conduct usability tests and gather feedback from diverse users to enhance app functionality and user experience.
Innovative Approach: Collaborate with local businesses to create an app promoting sustainable shopping habits or community events, integrating social features and real-time updates for users.
Project Idea: Discuss ethical dilemmas in AI research. Host a virtual panel discussion where experts debate topics like bias in algorithms and AI’s impact on job markets and privacy.
Innovative Approach: Create an AI chatbot that educates users about ethical AI practices and prompts discussions on social media platforms, encouraging ethical considerations in technology use.
Project Idea: Evaluate online learning tools. Survey students and educators to assess the effectiveness of digital resources like interactive tutorials and virtual labs in enhancing STEM education.
Innovative Approach: Develop a gamified learning platform where students collaborate on coding challenges and STEM projects, earning points and badges for problem-solving skills and teamwork.
Project Idea: Investigate public perceptions of digital transformation. Interview tech leaders and policymakers about innovations like smart cities and digital healthcare solutions.
Innovative Approach: Host a virtual reality tour of a futuristic city, showcasing sustainable technologies and smart infrastructure designs, inspiring communities to embrace digital advancements for a more connected future.
Math masters: exploring creative problem-solving techniques.
Project Idea: Engage students in math challenges. Organize math competitions or puzzle-solving events to promote teamwork and critical thinking in solving real-world problems.
Innovative Approach: Create an online platform where users solve daily math puzzles and earn rewards, fostering a community of math enthusiasts and lifelong learners.
Project Idea: Explore mathematical beauty. Host an art exhibit featuring mathematical patterns and sculptures, educating visitors about symmetry and fractals in nature and art.
Innovative Approach: Develop an augmented reality app where users interact with virtual mathematical sculptures, exploring their aesthetic qualities and historical significance.
Project Idea: Discuss ethical issues in mathematical research. Host a webinar series where mathematicians and scholars debate topics like data privacy and intellectual property rights in mathematical discoveries.
Innovative Approach: Create a podcast series featuring interviews with mathematicians sharing stories of ethical challenges and breakthroughs in their research, promoting ethical awareness and academic integrity.
Project Idea: Evaluate math education strategies. Survey teachers and students about effective learning methods like interactive lessons and peer tutoring in improving math comprehension and engagement.
Innovative Approach: Develop a virtual classroom platform where students attend math workshops and practice sessions with AI tutors, receiving personalized feedback and progress reports.
Project Idea: Investigate math applications. Collaborate with engineers and scientists to analyze case studies of mathematical modeling in fields like climate science and financial forecasting.
Innovative Approach: Launch a YouTube channel featuring animated videos explaining mathematical concepts and their practical applications in everyday life and global issues.
: |
STEM fields (Science, Technology, Engineering, and Mathematics) focus on data and experiments, but qualitative research adds crucial depth by:
It explores motivations and challenges within STEM, like why students lose interest in science or how ethics affect engineering decisions.
By understanding diverse perspectives, it helps create inclusive environments in STEM, addressing issues like gender disparities in engineering.
It studies public perceptions of technologies (e.g., AI) and ethical concerns in STEM, guiding responsible development.
It complements quantitative research by explaining reasons behind trends, like declining interest in science among students.
By focusing on human insights, it inspires new technologies and strategies to support future STEM leaders.
In conclusion, qualitative research in STEM enriches understanding by exploring human dimensions, ensuring advancements are ethical, inclusive, and impactful.
There are several benefits to integrating qualitative studies with quantitative approaches in research, especially in STEM fields. Here are the key advantages:
Quantitative data provides “what” and “how much,” while qualitative research (interviews, focus groups) uncovers “why” and “how.” This combination offers a holistic view, revealing underlying factors behind trends like declining student interest in science.
Quantitative data can lack context. Qualitative research adds meaning by exploring motivations, challenges, and perspectives, helping to interpret quantitative results accurately.
Quantitative studies identify trends, and qualitative research refines findings and generates new research questions. For instance, survey data on poor science teaching can be explored qualitatively to identify effective teaching methods.
Quantitative research quantifies problems, while qualitative insights guide interventions. For example, understanding student interests can shape more relevant science curricula.
Quantitative findings are statistically generalizable, and qualitative research provides insights into specific experiences, helping to assess applicability across different contexts.
Qualitative research offers a unique perspective on the human aspects of STEM fields (Science, Technology, Engineering, and Mathematics), focusing on experiences and meanings rather than numbers. Here’s a simplified breakdown:
Methods: Uses interviews, focus groups, and observations.
Focus: Explores experiences, perceptions, and contexts.
Approach: Inductive, allowing themes to emerge naturally.
Quantitative: Deals with measurable data and hypotheses.
Qualitative: Focuses on meanings and narratives.
Understanding Motivations: Explores why people choose STEM careers or public perceptions of new technologies.
Social Context: Examines how culture, gender, and background affect STEM participation.
Ethical Analysis: Studies societal impacts of technologies like AI and genetic engineering.
Educational Insights: Evaluates teaching methods and student experiences in STEM.
In summary, qualitative research complements quantitative methods by providing insights into the human dimensions of science and technology.
STEM students excel in numbers and equations, yet science is deeply intertwined with human experience. Qualitative research explores this intersection, uncovering the “why” and “how” behind scientific phenomena. Here’s how to choose an engaging topic:
Find Your Passion: Identify what excites you in STEM, like robotics or clean energy.
Explore Human Impact: Consider how your STEM interest connects with human behavior or societal impacts. For instance, public views on robots in healthcare.
Identify Gaps: Look for unexplored areas in STEM education or technology development.
Motivations and challenges.
What drives students into STEM careers?
Challenges faced by minorities in STEM fields.
Impact of teaching methods on student interest.
Strategies for scientific literacy in diverse communities.
Ethical influences on AI development.
Bridging the digital divide for equitable technology access.
Focus & Feasibility: Choose a specific yet manageable topic.
Data Collection: Plan interviews, focus groups, or observations.
Ethics: Respect participant privacy and consent.
Selecting a compelling topic in qualitative research can offer valuable insights into STEM’s evolving landscape.
Qualitative research helps STEM students explore how science, technology, engineering, and mathematics connect with people’s lives and society.
By studying experiences and stories, students gain a deeper understanding of ethics and societal impacts. This not only boosts their research skills but also prepares them to innovate thoughtfully for a more inclusive future in STEM.
Remember, choose a topic that truly interests you and sparks curiosity—something that can uncover meaningful insights!
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May 30, 2023
Scrambling to find technology research topics for the assignment that’s due sooner than you thought? Take a scroll down these 54 interesting technology essay topics in 10 different categories, including controversial technology topics, and some example research questions for each.
Whether you have active profiles on every social media platform, you’ve taken a social media break, or you generally try to limit your engagement as much as possible, you probably understand how pervasive social technologies have become in today’s culture. Social technology will especially appeal to those looking for widely discussed, mainstream technology essay topics.
Following cryptocurrency and blockchain technology has been a rollercoaster the last few years. And since Bitcoin’s conception in 2009, cryptocurrency has consistently showed up on many lists of controversial technology topics.
We started 2023 with M3GAN’s box office success, and now we’re fascinated (or horrified) with ChatGPT , voice cloning , and deepfakes . While people have discussed artificial intelligence for ages, recent advances have really pushed this topic to the front of our minds. Those searching for controversial technology topics should pay close attention to this one.
Throughout human history, people in many cultures have gone to extreme lengths to capture and maintain a youthful beauty. But technology has taken the pursuit of beauty and youth to another level. For those seeking technology essay topics that are both timely and timeless, this one’s a gold mine.
An umbrella term, geoengineering refers to large-scale technologies that can alter the earth and its climate. Typically, these types of technologies aim to combat climate change. Those searching for controversial technology topics should consider looking into this one.
While tensions often arise between artists and technology, they’ve also maintained a symbiotic relationship in many ways. It’s complicated. But of course, that’s what makes it interesting. Here’s another option for those searching for timely and timeless technology essay topics.
And another route for those drawn to controversial technology topics: cellular agriculture. You’ve probably heard about popular plant-based meat options from brands like Impossible and Beyond Meat . While products made with cellular agriculture also don’t require the raising and slaughtering of livestock, they are not plant-based. Cellular agriculture allows for the production of animal-sourced foods and materials made from cultured animal cells.
For decades, we’ve expected flying cars to carry us into a techno-utopia, where everything’s shiny, digital, and easy. We’ve heard promises of super fast trains that can zap us across the country or even across the world. We’ve imagined spring breaks on the moon, jet packs, and teleportation. Who wouldn’t love the option to go anywhere, anytime, super quickly? Transportation technology is another great option for those seeking widely discussed, mainstream technology essay topics.
A recent study involving over 2000 children found links between video game play and enhanced cognitive abilities. While many different studies have found the impacts of video games to be positive or neutral, we still don’t fully understand the impact of every type of video game on every type of brain. Regardless, most people have opinions on video gaming. So this one’s for those seeking widely discussed, mainstream, and controversial technology topics.
Advancements in healthcare have the power to change and save lives. In the last ten years, countless new medical technologies have been developed, and in the next ten years, countless more will likely emerge. Always relevant and often controversial, this final technology research topic could interest anyone.
Now that you’ve picked from this list of technology essay topics, you can do a deep dive and immerse yourself in new ideas, new information, and new perspectives. And of course, now that these topics have motivated you to change the world, look into the best computer science schools , the top feeders to tech and Silicon Valley , the best summer programs for STEM students , and the best biomedical engineering schools .
Mariya holds a BFA in Creative Writing from the Pratt Institute and is currently pursuing an MFA in writing at the University of California Davis. Mariya serves as a teaching assistant in the English department at UC Davis. She previously served as an associate editor at Carve Magazine for two years, where she managed 60 fiction writers. She is the winner of the 2015 Stony Brook Fiction Prize, and her short stories have been published in Mid-American Review , Cutbank , Sonora Review , New Orleans Review , and The Collagist , among other magazines.
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NSF EDU invites your input regarding important research questions that explore frontier topics in education and workforce development for the industries of tomorrow, including the use of emerging technologies in the workplace. Participants will be encouraged to share insights from the field, new approaches to evolving questions, and to connect with others exploring similar topics. The conversations are not intended as a basis for recommendations to NSF, but to think aloud with NSF about the changing nature of STEM workforce development research.
The NSF Research Traineeship (NRT) program supports projects that explore ways for graduate students in research-based master’s and doctoral degree programs to develop the skills, knowledge, and competencies needed to pursue a range of STEM careers. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas, through a comprehensive traineeship model that is innovative, evidence-based, and aligned with changing workforce and research needs.
Science, technology, engineering, and mathematics (STEM) graduate education is poised to undergo major transformations. There are multiple drivers for such change including: (i) recent major national reports on the state of STEM graduate education; (ii) the accelerating pace of science and engineering discoveries and technological innovations, (iii) national STEM workforce and demographic trends; (iv) the growing globalization of science and engineering; and (v) the potential to align graduate education practices and models with an increasing understanding of how people learn. In addition, there is increasing recognition that addressing the grand challenges in science and engineering requires interdisciplinary and convergent approaches, as well as broader professional training that is not characteristic of most graduate programs.
These realities and the increasing calls for new approaches to STEM graduate education represent an extraordinary opportunity. Accordingly, the NRT program encourages researchers to test, develop, and implement innovative and effective STEM graduate education models, promote interdisciplinary and broad professional training of graduate students, broaden participation in the STEM workforce , and foster fundamental research advances in support of national priorities.
Learn more about registering for this event.
Earth & climate, the solar system, the universe, aeronautics.
Nasa funds research projects advancing stem career development.
Nasa headquarters.
NASA has awarded $6 million to 20 teams from emerging research institutions across the United States supporting projects that offer career development opportunities for science, technology, engineering, and mathematics (STEM) students.
This is the third round of seed funding awarded through the agency’s MOSAICS (Mentoring and Opportunities in STEM with Academic Institutions for Community Success) program, formerly the Science Mission Directorate Bridge Program. The program seeks to expand access to NASA research opportunities in the science and engineering disciplines, as well as to NASA’s workforce.
“The STEM workforce continues to grow, and today’s students, studying at a variety of higher-education institutions — community colleges, primarily undergraduate institutions, and minority-serving institutions — are the STEM workforce of tomorrow, who will work to solve some of our biggest challenges at home while answering some of our biggest questions about our universe,” said Padi Boyd, director of MOSAICS at NASA Headquarters in Washington. “Exposing today’s students to the incredibly inspiring and cutting-edge discoveries made through NASA’s space science people and resources ensures that these students get the training they need to persist in STEM careers, while fostering enduring collaborations between NASA researchers and faculty at a wide range of institutions.”
NASA’s Science Mission Directorate MOSAICS program funds research projects building relationships between college faculty and researchers at the agency while providing mentorship and training for students in STEM disciplines. The projects support teams at academic institutions that historically have not been part of the agency’s research enterprise — including Hispanic-serving institutions, historically Black colleges and universities, Asian American and Native American Pacific Islander-serving institutions, and primarily undergraduate institutions.
The program previously awarded seed funding to 11 teams in February and 13 teams in April. This third cohort brings the total number of projects funded to 44 teams at 36 academic institutions in 21 U.S. states and territories, including Washington and Puerto Rico, in collaboration with seven NASA centers. A new opportunity to apply for seed funding is now open until March 28, 2025.
The following projects were selected as the third cohort to receive seed funding:
“Bridging Fundamental Ice Chemistry Studies and Ocean World Explorations” Principal investigator: Chris Arumainayagam, Wellesley College, Massachusetts NASA center: NASA’s Jet Propulsion Laboratory (JPL), Southern California
“Planetary Analog Field Science Experiences for Undergraduates: Advancing Fundamental Research and Testing Field Instrument Operations” Principal investigator: Alice Baldridge, Saint Mary’s College of California NASA center: NASA’s Goddard Space Flight Center, Greenbelt, Maryland
“Building an FSU-JPL Partnership to Advance Science Productivity Through Applications of Deep Learning” Principal investigator: Sambit Bhattacharya, Fayetteville State University, North Carolina NASA center: NASA JPL
“CSTAT: Establishing Center for Safe and Trustworthy Autonomous Technologies” Principal investigator: Moitrayee Chatterjee, New Jersey City University NASA center: NASA Goddard
“Development of Biomechanics Simulation Tool for Muscle Mechanics in Reduced Gravity to Enhance Astronaut Mission Readiness” Principal investigator: Ji Chen, University of the District of Columbia NASA center: NASA’s Johnson Space Center, Houston
“NASA Next Level” Principal investigator: Teresa Ciardi, Santa Clarita Community College District, California NASA center: NASA JPL
“Controlled Assembly of Amphiphilic Janus Particles in Polymer Matrix for Novel 3D Printing Applications in Space ” Principal investigator: Ubaldo Cordova-Figueroa, Recinto Universitario Mayaguez NASA center: NASA’s Glenn Research Center, Cleveland
“Development of a Non-Invasive Sweat Biosensor for Traumatic Brain Injury Compatible With In-Space Manufacturing to Monitor the Health of Astronauts” Principal investigator: Lisandro Cunci, University of Puerto Rico, Rio Pedras NASA center: NASA’s Ames Research Center, Silicon Valley, California
“Examining Climate Impacts of Cirrus Clouds Through Past, Present, and Future NASA Airborne Campaigns” Principal investigator: Minghui Diao, San Jose State University Research Foundation, California NASA center: NASA Ames
“CSUN-JPL Collaboration to Study Ocean Fronts Using Big Data and Open Science Structures in Coastal North America” Principal investigator: Mario Giraldo, California State University, Northridge NASA center: NASA JPL
“Accelerating Electric Propulsion Development for Planetary Science Missions With Optical Plasma Diagnostics” Principal investigator: Nathaniel Hicks, University of Alaska, Anchorage NASA center: NASA JPL
“Advancing Students Through Research Opportunities in Los Angeles (ASTRO-LA)” Principal investigator: Margaret Lazzarini, California State University, Los Angeles NASA center: NASA JPL
“Bridging Toward a More Inclusive Learning Environment Through Gamma-ray Burst Studies With Machine Learning and Citizen Science” Principal investigator: Amy Lien, University of Tampa, Florida NASA center: NASA Goddard
“Hampton University STEM Experience With NASA Langley Research Center: Polarimetry for Aerosol Characterization” Principal investigator: Robert Loughman, Hampton University, Virginia NASA center: NASA’s Langley Research Center, Hampton, Virginia
“Aerocapture Analysis and Development for Uranus and Neptune Planetary Missions” Principal investigator: Ping Lu, San Diego State University NASA center: NASA Langley
“Pathways from Undergraduate Research to the Habitable Worlds Observatory” Principal investigator: Ben Ovryn, New York Institute of Technology NASA center: NASA Goddard
“Point-Diffraction Interferometer for Digital Holography” Principal investigator: James Scire, New York Institute of Technology NASA center: NASA Goddard
“From Sunbeams to Career Dreams: Illuminating Pathways for NMSU Students in Solar-Terrestrial Physics in Partnership With NASA GSFC” Principal investigator: Juie Shetye, New Mexico State University NASA center: NASA Goddard
“CONNECT-SBG: Collaborative Nexus for Networking, Education, and Career Training in Surface Biology and Geology” Principal investigator: Gabriela Shirkey, Chapman University, California NASA center: NASA JPL
“Multiplexed Phytohormone and Nitrate Sensors for Real-Time Analysis of Plant Responses to Pathogenic Stress in Spaceflight-Like Conditions” Principal investigator: Shawana Tabassum, University of Texas, Tyler NASA center: NASA’s Kennedy Space Center, Florida
Learn more about the MOSAICS program at:
https://science.nasa.gov/researchers/smd-bridge-program
Alise Fisher Headquarters, Washington 202-358-2546 [email protected]
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Early-career scientists shared some of their plans, hopes and dreams about being a principal investigator at the 2024 annual meeting of the International Society for Stem Cell Research.
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Marx, V. Stem cell science starters. Nat Methods (2024). https://doi.org/10.1038/s41592-024-02398-0
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Early-stage trials in Alzheimer’s disease patients and studies in mouse models of the disease have suggested positive impacts on pathology and symptoms from exposure to light and sound presented at the “gamma” band frequency of 40 hertz (Hz). A new study zeroes in on how 40Hz sensory stimulation helps to sustain an essential process in which the signal-sending branches of neurons, called axons, are wrapped in a fatty insulation called myelin. Often called the brain’s “white matter,” myelin protects axons and insures better electrical signal transmission in brain circuits.
“Previous publications from our lab have mainly focused on neuronal protection,” says Li-Huei Tsai , Picower Professor in The Picower Institute for Learning and Memory and the Department of Brain and Cognitive Sciences at MIT and senior author of the new open-access study in Nature Communications . Tsai also leads MIT’s Aging Brain Initiative. “But this study shows that it’s not just the gray matter, but also the white matter that’s protected by this method.”
This year Cognito Therapeutics, the spinoff company that licensed MIT’s sensory stimulation technology, published phase II human trial results in the Journal of Alzheimer’s Disease indicating that 40Hz light and sound stimulation significantly slowed the loss of myelin in volunteers with Alzheimer’s. Also this year, Tsai’s lab published a study showing that gamma sensory stimulation helped mice withstand neurological effects of chemotherapy medicines, including by preserving myelin. In the new study, members of Tsai’s lab led by former postdoc Daniela Rodrigues Amorim used a common mouse model of myelin loss — a diet with the chemical cuprizone — to explore how sensory stimulation preserves myelination.
Amorim and Tsai’s team found that 40Hz light and sound not only preserved myelination in the brains of cuprizone-exposed mice, it also appeared to protect oligodendrocytes (the cells that myelinate neural axons), sustain the electrical performance of neurons, and preserve a key marker of axon structural integrity. When the team looked into the molecular underpinnings of these benefits, they found clear signs of specific mechanisms including preservation of neural circuit connections called synapses; a reduction in a cause of oligodendrocyte death called “ferroptosis;” reduced inflammation; and an increase in the ability of microglia brain cells to clean up myelin damage so that new myelin could be restored.
“Gamma stimulation promotes a healthy environment,” says Amorim, who is now a Marie Curie Fellow at the University of Galway in Ireland. “There are several ways we are seeing different effects.”
The findings suggest that gamma sensory stimulation may help not only Alzheimer’s disease patients but also people battling other diseases involving myelin loss, such as multiple sclerosis, the authors wrote in the study.
Maintaining myelin
To conduct the study, Tsai and Amorim’s team fed some male mice a diet with cuprizone and gave other male mice a normal diet for six weeks. Halfway into that period, when cuprizone is known to begin causing its most acute effects on myelination, they exposed some mice from each group to gamma sensory stimulation for the remaining three weeks. In this way they had four groups: completely unaffected mice, mice that received no cuprizone but did get gamma stimulation, mice that received cuprizone and constant (but not 40Hz) light and sound as a control, and mice that received cuprizone and also gamma stimulation.
After the six weeks elapsed, the scientists measured signs of myelination throughout the brains of the mice in each group. Mice that weren’t fed cuprizone maintained healthy levels, as expected. Mice that were fed cuprizone and didn’t receive 40Hz gamma sensory stimulation showed drastic levels of myelin loss. Cuprizone-fed mice that received 40Hz stimulation retained significantly more myelin, rivaling the health of mice never fed cuprizone by some, but not all, measures.
The researchers also looked at numbers of oligodendrocytes to see if they survived better with sensory stimulation. Several measures revealed that in mice fed cuprizone, oligodendrocytes in the corpus callosum region of the brain (a key point for the transit of neural signals because it connects the brain’s hemispheres) were markedly reduced. But in mice fed cuprizone and also treated with gamma stimulation, the number of cells were much closer to healthy levels.
Electrophysiological tests among neural axons in the corpus callosum showed that gamma sensory stimulation was associated with improved electrical performance in cuprizone-fed mice who received gamma stimulation compared to cuprizone-fed mice left untreated by 40Hz stimulation. And when researchers looked in the anterior cingulate cortex region of the brain, they saw that MAP2, a protein that signals the structural integrity of axons, was much better preserved in mice that received cuprizone and gamma stimulation compared to cuprizone-fed mice who did not.
A key goal of the study was to identify possible ways in which 40Hz sensory stimulation may protect myelin.
To find out, the researchers conducted a sweeping assessment of protein expression in each mouse group and identified which proteins were differentially expressed based on cuprizone diet and exposure to gamma frequency stimulation. The analysis revealed distinct sets of effects between the cuprizone mice exposed to control stimulation and cuprizone-plus-gamma mice.
A highlight of one set of effects was the increase in MAP2 in gamma-treated cuprizone-fed mice. A highlight of another set was that cuprizone mice who received control stimulation showed a substantial deficit in expression of proteins associated with synapses. The gamma-treated cuprizone-fed mice did not show any significant loss, mirroring results in a 2019 Alzheimer’s 40Hz study that showed synaptic preservation. This result is important, the researchers wrote, because neural circuit activity, which depends on maintaining synapses, is associated with preserving myelin. They confirmed the protein expression results by looking directly at brain tissues.
Another set of protein expression results hinted at another important mechanism: ferroptosis. This phenomenon, in which errant metabolism of iron leads to a lethal buildup of reactive oxygen species in cells, is a known problem for oligodendrocytes in the cuprizone mouse model. Among the signs was an increase in cuprizone-fed, control stimulation mice in expression of the protein HMGB1, which is a marker of ferroptosis-associated damage that triggers an inflammatory response. Gamma stimulation, however, reduced levels of HMGB1.
Looking more deeply at the cellular and molecular response to cuprizone demyelination and the effects of gamma stimulation, the team assessed gene expression using single-cell RNA sequencing technology. They found that astrocytes and microglia became very inflammatory in cuprizone-control mice but gamma stimulation calmed that response. Fewer cells became inflammatory and direct observations of tissue showed that microglia became more proficient at clearing away myelin debris, a key step in effecting repairs.
The team also learned more about how oligodendrocytes in cuprizone-fed mice exposed to 40Hz sensory stimulation managed to survive better. Expression of protective proteins such as HSP70 increased and as did expression of GPX4, a master regulator of processes that constrain ferroptosis.
In addition to Amorim and Tsai, the paper’s other authors are Lorenzo Bozzelli, TaeHyun Kim, Liwang Liu, Oliver Gibson, Cheng-Yi Yang, Mitch Murdock, Fabiola Galiana-Meléndez, Brooke Schatz, Alexis Davison, Md Rezaul Islam, Dong Shin Park, Ravikiran M. Raju, Fatema Abdurrob, Alissa J. Nelson, Jian Min Ren, Vicky Yang and Matthew P. Stokes.
Fundacion Bancaria la Caixa, The JPB Foundation, The Picower Institute for Learning and Memory, the Carol and Gene Ludwig Family Foundation, Lester A. Gimpelson, Eduardo Eurnekian, The Dolby Family, Kathy and Miguel Octavio, the Marc Haas Foundation, Ben Lenail and Laurie Yoler, and the U.S. National Institutes of Health provided funding for the study.
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As radioisotopes power the Perseverance rover to explore Mars, perseverance “powered” three winners to write essays each year till they achieved their mission goal of winning NASA’s Power to Explore Challenge . These students explored behind the scenes at NASA's Glenn Research Center and Great Lakes Science Center (GLSC) in Cleveland after writing the top essays in the national contest.
The competition for kindergarten through 12th grade students focuses on the enabling power of radioisotopes. Students were challenged to learn how NASA has powered some of its most famous science missions and to dream up how their personal “superpower” would energize their own radioisotope-powered science mission.
Judges narrowed down over a seventeen hundred creative essays to 45 semi-finalists, who received prize packs, nine finalists, who participated in a videoconference with NASA experts, and three winners, who were awarded with a visit to NASA Glenn.
Dr. Wanda Peters
Acting Deputy Director, NASA's Glenn Research Center
“I’m so impressed by the work of these talented young students,” said Dr. Wanda Peters, acting deputy center director at NASA Glenn. “It’s wonderful to see their interest, innovation, and creativity at this stage in their lives. Our future is bright!”
Rainie Lin , the kindergarten through fourth grade winner; Aadya Karthik , the fifth through eighth grade winner, and Thomas Liu , the ninth through 12th grade winner, toured several research facilities including the Electric Propulsion and Power Laboratory , Telescience Support Center , Graphics and Visualization Lab , and Simulated Lunar Operations Lab . Along the way, they met with engineers and researchers to learn about NASA’s missions and the technologies that are innovating exploration.
The next day students and their families traveled to GLSC, which houses NASA Glenn’s Visitor Center. Accompanied by members of NASA’s Radioisotope Power Systems (RPS) team, the group toured the visitor center and explored the many interactive displays.
“It was our pleasure to host the three student winners of The Power to Explore Challenge, and I hope that this visit will further inspire and motivate them to pursue their interests in science and exploration,” said Carl Sandifer, manager for NASA’s RPS Program. "We are so impressed by the ideas and quality of the essays submitted this year and we can’t wait to what new ideas student come up with for next year’s challenge!”
The Power to Explore Challenge asked students to learn about the RPS, one of NASA’s “nuclear batteries” it uses to explore some of the most extreme destinations in our solar system and beyond. Students then wrote about their own power to achieve goals in 250 words or less.
NASA will hold its fourth-annual Power to Explore Challenge later this fall. For more information on the challenge visit: The Power to Explore Writing Challenge homepage .
ABOUT THE CHALLENGE:
Power to Explore is a national essay challenge that asks students in grades K-12 to learn about Radioisotope Power Systems (RPS), a type of “nuclear battery” that NASA uses to explore some of the most extreme destinations in our solar system and beyond, and then write about, in 250 words or less, an RPS-powered space mission that would energize their space exploration dreams.
ABOUT FUTURE ENGINEERS:
Future Engineers hosts online contests and challenges for K-12 students. Previous challenges have helped produce historic achievements – from naming NASA’s Perseverance rover to manufacturing the first student-designed 3D print in space. All challenges are offered free for student and classroom participation. For more information, visit futureengineers.org . Follow Future Engineers on Twitter , Facebook , and Instagram .
Media Contact: Kristin Jansen Public Affairs Specialist Office of Communications NASA RPS Program Phone: 216-296-2203 Email: [email protected]
Radioisotope Power Systems
About Plutonium-238
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Here are 10 qualitative research topics for STEM students: Exploring the experiences of female STEM students in overcoming gender bias in academia. Understanding the perceptions of teachers regarding the integration of technology in STEM education. Investigating the motivations and challenges of STEM educators in underprivileged schools.
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A revolutionary, bold educational endeavor for Belize. Itz'at STEAM Academy, an effort between MIT and the Belize Ministry of Education, Culture, Science, and Technology, pushes the boundaries of education through innovative methodologies. March 26, 2024. Read full story.
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This study explored research trends in science, technology, engineering, and mathematics (STEM) education. Descriptive analysis and co-word analysis were used to examine articles published in Social Science Citation Index journals from 2011 to 2020. From a search of the Web of Science database, a total of 761 articles were selected as target samples for analysis. A growing number of STEM ...
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Technology can be a robust tool to transform STEM learning. To help school and district staff implement new, research-based approaches for using technology effectively in STEM learning, the Office of Educational Technology, in partnership with Digital Promise, conducted a systematic review of the research literature on the impact of integrating innovative digital technology in STEM and ...
Science, technology, engineering, and mathematics (STEM) drives innovation, promotes economic development, and enhances our understanding of the world, making STEM education a national priority. High-quality STEM education provides students with the knowledge and skills to solve problems, gather and evaluate evidence, and make sense of ...
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The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas, through a comprehensive traineeship model that is innovative, evidence-based, and aligned with changing workforce and research needs. Science, technology, engineering, and mathematics (STEM) graduate ...
NASA has awarded $6 million to 20 teams from emerging research institutions across the United States supporting projects that offer career development opportunities for science, technology, engineering, and mathematics (STEM) students.
Early-career scientists shared some of their plans, hopes and dreams about being a principal investigator at the 2024 annual meeting of the International Society for Stem Cell Research.
Early-stage trials in Alzheimer's disease patients and studies in mouse models of the disease have suggested positive impacts on pathology and symptoms from exposure to light and sound presented at the "gamma" band frequency of 40 hertz (Hz). A new study zeroes in on how 40Hz sensory stimulation helps to sustain an essential process in which the signal-sending branches of neurons, called ...
As radioisotopes power the Perseverance rover to explore Mars, perseverance "powered" three winners to write essays each year till they achieved their mission goal of winning NASA's Power to Explore Challenge.These students explored behind the scenes at NASA's Glenn Research Center and Great Lakes Science Center (GLSC) in Cleveland after writing the top essays in the national contest.