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.
“Did you know only 28% of college graduates in the Philippines get degrees in STEM fields? Finding good research topics is vital to getting more Filipino students curious about quantitative studies.
With limited research money and resources, it can be hard for STEM students to find quantitative projects that are possible, new, and impactful. Often, researchers end up feeling apart from local issues and communities.
This blog post offers a unique collection of quantitative research topics for STEM students in the Philippines. Thus, drawing from current events, social issues, and the country’s needs, these project ideas will feel relevant and help students do research that creates positive change.
Philippines students can find inspiration for quantitative studies that make a difference at home through many examples across science, technology, engineering, and math.
Read Our Blog: 120+ Best Quantitative Research Topics for Nursing Students (2024 Edition)
Table of Contents
Here are the top quantitative research topics for STEM students in the Philippines in 2024
1. Impact of Climate Change on Farming
Analyze how changing weather affects the growth of crops like rice and corn in different parts of the Philippines. Use numbers to find ways and suggest ways farmers can adapt.
2. Using Drones to Watch Nature
See how well drones with special sensors can watch over forests and coasts in the Philippines. Look at the data they gather to figure out how to save these places.
3. Making Solar Panels Work Better
Experiment with various ways to make more power with solar panels in sunny, humid places like the Philippines. Utilize math to guess how well they’ll work.
4. Checking How Pollution Hurts Coral Reefs
Count how much damage pollution does to coral reefs in the Philippines. Try to predict how bad it’ll get if we don’t stop polluting.
5. Watching Traffic to Fix Roads
Look at how cars move in big cities like Manila. Use math to figure out how to make traffic flow better and help people get around faster.
6. at Air and Sick People
Measure how clean the air is in various parts of the Philippines and see if it affects how many people get sick. Find out which areas need help to stay healthy.
7. Guessing When Earthquakes Might Happen
Look at data from sensors all over the Philippines to see if we can tell when earthquakes might come. Try to guess where they’ll occur next.
8. Making Water Pipes Better
Use math tricks to design cheap pipes that bring clean water to small towns in the Philippines. Think about things like hills and how many people need water.
9. Checking If Planting Trees Helps
Measure if planting trees helps stop the shore from washing away during storms. Use photos from far away and math to see if it’s working.
10. Teaching Computers to Find Sickness
Teach computers to look at pictures and records from hospitals to see if people are sick. Check if they’re good at spotting problems in the Philippines.
11. Finding Better Bags That Break Down
Test different materials like banana leaves to see which ones can be made into bags that don’t hurt the environment. Compare them to regular plastic bags.
12. Making Gardens in the City
See if we can grow vegetables in tall buildings in big cities like Manila. Use numbers to figure out if it’s a good idea.
13. Checking If Bugs Spread Easily in Crowded Places
Use computers to see if diseases spread fast in busy places in the Philippines. Look at how people move around to stop diseases from spreading.
14. Storing Energy for Islands Without Power
Think about ways to save power for small islands without electricity. Try out different ways to save energy and see which one works best.
15. Seeing How Much Storms Hurt Farms
Calculate how much damage storms do to farms in the Philippines. Use numbers to see how much money farmers lose.
16. Testing Ways to Stop Dirt from Washing Away
Try out different ways to stop dirt from being washed away when it rains. Use math to see which way works best on hills in the Philippines.
17. Checking How Healthy Local Food Is
Look at the vitamins and minerals in local foods like sweet potatoes and moringa leaves. See if eating them is good for people in the Philippines.
18. Making Cheap Water Cleaners
Build simple machines that clean dirty water in small towns. Notice if they work better than expensive ones.
19. Seeing How Hot Cities Get
Use satellites to see how hot cities like Manila get compared to places with more trees. Think about how this affects people.
20. Thinking About Trash in Cities
Look at how much trash cities in the Philippines make and find ways to deal with it. Consider what people can do to make less trash.
21. Checking If We Can Use Hot Rocks for Power
Look at rocks under the ground to see if we can get power from them. Consider whether it is beneficial for the environment.
22. Counting Animals in the Forest
Use cameras to count how many animals are in forests in the Philippines. Notice which places need the most help to keep animals safe.
23. Making Fishing Fair
Look at how many fish are caught in the Philippines and see if it’s fair. Think about ways to make sure there will always be enough fish to catch.
24. Making Power Lines Smarter
Design power lines that can change how much power they use. Try to make sure power goes where it’s needed most.
25. Looking at Dirty Water
Find out if chopping down trees and building things by rivers makes the water dirty. Think about what this means for people and animals.
26. Thinking About Big Waves
Use computers to see if big waves could hit the Philippines and what might happen. Think about how to keep people safe.
27. Seeing If Parks Help Cities
Ask people if they like having parks in their city and see what animals live there. Think about if parks make cities better.
28. Making Houses That Don’t Break in Storms
Make houses that don’t fall when there are big storms. Try to make them cheap so more people can have them.
29. Stopping Food from Going Bad
Look at how food gets from farms to people’s houses and see if we can stop it from going bad. Think about how to make sure people have enough to eat.
30. Seeing How Hot Cities Get
Put machines around cities to see how hot they get. Consider how this affects people and what we can do to help.
These topics will help you to make a good project that assists you in getting better scores.
Read why quantitative research matters to Filipino students.
It’s time to see what challenges students face with their quantitative research.
Here are the common challenges that students face with their quantitative research topics:
Doing quantitative research needs access to equipment, software , datasets etc, which can be costly. Many students lack funding and access to these resources.
Quantitative research relies heavily on math and statistical skills. However, many students haven’t developed strong enough skills in these areas yet.
Students need access to academic journals and databases for literature reviews. However, these can be costly for people to access.
Many of the academic literature is in English. This can make reading and learning complex statistical concepts more difficult.
Having an experienced mentor to provide guidance is invaluable. However, not all students have access to mentorship in quantitative research.
Collecting, cleaning and analyzing large datasets requires advanced technical skills. Students may struggle without proper guidance.
Learning how to visualize and communicate statistical findings effectively is an important skill that takes practice.
Ensuring quantitative studies are designed ethically can be difficult for novice researchers.
Adopting the formal, precise writing style required in quantitative research is challenging initially.
Quantitative research is complex and time-consuming. Students may lose motivation without a strong support network.
While quantitative research presents many challenges, Philippines STEM students can overcome these through access to proper resources and support. With hard work, mentorship and collaborative opportunities, students can build essential skills and contribute to the quantitative research landscape.
When conducting research in a new cultural context like the Philippines, it is vital to take time to understand local norms and build trust. Approaching research openly and collaboratively will lead to more meaningful insights.
1. Get Required Approvals
Be sure to get any necessary ethics reviews or approvals from local governing boards before conducting the analysis. It is wise to follow proper protocols and permissions.
2. Hire Local Assistants
Hire local research helpers to help navigate logistics, translation, and cultural sensitivities. This provides jobs and insider insights.
3. Use Multiple Research Methods
Triangulate findings using interviews, focus groups, surveys, participant observation, etc. Multiple methods provide more potent and well-rounded results.
4. Verify Information
Politely verify information collected from interviews before publication. Follow up to ensure accurate representation and context.
5. Share Results
Report back to participants and communities on research findings and next steps. This shows respect and accountability for their contributions.
6. Acknowledge Limitations
Openly acknowledge the limitations of perspective and methods as an outside researcher. Remain humble and keep improving approaches.
Keep in mind, when entering a new community to conduct research, taking an open, patient, and collaborative approach leads to more ethical and meaningful results. Thus, making the effort to understand and work within cultural norms demonstrates respect.
STEM students in the Philippines have many possible research topics using numbers. They could look at renewable energy, sustainability, pollution, environment, disease prevention, farming improvements, preparing for natural disasters, building projects, transportation, and technology access.
By carefully analyzing statistics and creating mathematical models, young Filipino researchers can provide key ideas to guide future policies and programs. Quantitative research allows real observations and suggestions based on evidence to make the country better now and later.
Number-based methods help young researchers in the Philippines give tangible recommendations to improve their communities.
Think about what you enjoy and what you’re skilled at. Consider if your topic is meaningful and if you have the resources to study it. Get advice from teachers or friends to help you decide.
Problems might include: 1. Finding data. 2. Make sure your measurements are correct. 3. Following rules about ethics. 4. Handling big sets of data.
Plan your study carefully, use the correct methods and tools, write down everything you do, and think about the strengths and weaknesses of your work.
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To identify the research trends in studies related to STEM Clubs, 56 publications that met the inclusion and extraction criteria were identified from the online databases ERIC and WoS in this study. These studies were analysed by using the descriptive content analysis research method based on the Paper Classification Form (PCF), which includes publishing years, keywords, research methods, sample levels and sizes, data collection tools, data analysis methods, durations, purposes, and findings. The findings showed that, the keywords in the studies were used under six different categories: disciplines, technological concepts, academic community, learning experiences, core elements of education, and psychosocial factors (variables). Case studies were frequently employed, with middle school students serving as the main participants in sample groups ranging from 11–15, 16–20, and 201–250. Surveys, questionnaires, and observations were the primary methods of data collection, and descriptive analysis was commonly used for data analysis. STEM Clubs had sessions ranging from 2 to 16 weeks, with each session commonly lasting 60 to 120 min. The study purposes mainly focused on four themes: the impact of participation on various aspects such as attitudes towards STEM disciplines, career paths, STEM major selection, and academic achievement; the development and implementation of a sample STEM Club program, including challenges and limitations; the examination of students' experiences, perceptions, and factors influencing their involvement and choice of STEM majors; the identification of some aspects such as attitudinal effects and non-academic skills; and the comparison of STEM experiences between in-school and out-of-school settings. The study results mainly focused on three themes: the increase in various aspects such as academic achievement, STEM major choice, engagement in STEM clubs, identity, interest in STEM, collaboration-communication skills; the design of STEM Clubs, including sample implementations, design principles, challenges, and factors affecting their success and sustainability; and the identification of factors influencing participation, motivation, and barriers. Overall, this study provides a comprehensive understanding of STEM Clubs, leading the way for more targeted and informed future research endeavours.
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Worldwide, STEM education, which integrates the disciplines of science, technology, engineering, and math, is gaining popularity in K-12 settings due to its capacity to enhance 21st-century skills such as adaptability, problem-solving, and creative thinking (National Research Council [NRC], 2015 ). In STEM lessons, students are frequently guided by the engineering design process, which involves identifying problems or technical challenges and creating and developing solutions. Furthermore, higher achievement in STEM education has been linked to increased enrolment in post-secondary STEM fields, offering students greater opportunities to pursue careers in these domains (Merrill & Daugherty, 2010 ). However, STEM activities require dedicated time and the restructuring of integrated curricula, necessitating careful organization of lessons. Recognizing the complexity of developing 21st-century STEM proficiency, schools are not expected to tackle this challenge alone. In addition to regular STEM classes, there exists a diverse range of extended education programs, activities, and out-of-school learning environments (Baran et al., 2016 ; Kalkan & Eroglu, 2017 ; Schweingruber et al., 2014 ). In this paper, out-of-school learning environments, informal learning environments, extended education, and afterschool programs were used synonymously. It is worth noting that the literature lacks a universally accepted definition for out-of-school learning environments, leading to the use of various interchangeable terms (Donnelly et al., 2019 ). Some of these terms include informal learning environments, extended education, afterschool programs, all-day school, extracurricular activities, out-of-school time learning, extended schools, expanded learning, and leisure-time activities. These terms refer to optional programs and clubs offered by schools that exist outside of the standard academic curriculum (Baran et al., 2016 ; Cooper, 2011 ; Kalkan & Eroglu, 2017 ; Schweingruber et al., 2014 ).
Out-of-school learning, in contrast to traditional in-school learning, offers greater flexibility in terms of time and space, as it is not bound by the constraints of the school schedule, national or state standards, and standardized tests (Cooper, 2011 ). Out-of-school learning experiences typically involve collaborative engagement, the use of tools, and immersion in authentic environments, while school environments often emphasize individual performance, independent thinking, symbolic representations, and the acquisition of generalized skills and knowledge (Resnick, 1987 ). They encompass everyday activities such as family discussions, pursuing hobbies, and engaging in daily conversations, as well as designed environments like museums, science centres, and afterschool programs (Civil, 2007 ; Hein, 2009 ). On the other hand, extended education refers to intentionally structured learning and development programs and activities that are not part of regular classes. These programs are typically offered before and after school, as well as at locations outside the school (Bae, 2018 ). As a result, out-of-school learning environments encompass a wide range of experiences, including social, cultural, and technical excursions around the school, field studies at museums, zoos, nature centres, aquariums, and planetariums, project-based learning, sports activities, nature training, and club activities (Civil, 2007 ; Donnelly et al., 2019 ; Hein, 2009 ). At this point, STEM clubs are a specialized type of extracurricular activity that engage students in hands-on projects, experiments, and learning experiences related to scientific, technological, engineering, and mathematical disciplines. STEM Clubs, described as flexible learning environments unconstrained by time or location, offer an effective approach to conducting STEM studies outside of school (Blanchard et al., 2017 ; Cooper, 2011 ; Dabney et al., 2012 ).
Out-of-school learning environments, extended education or afterschool programs, hold tremendous potential for enhancing student learning and providing them with a diverse and enriching educational experience (Robelen, 2011 ). Extensive research supports the notion that these alternative educational programs not only contribute to students' academic growth but also foster their social, emotional, and intellectual development (NRC, 2015 ). Studies have consistently shown that after-school programs play a vital role in boosting students' achievement levels (Casing & Casing, 2024 ; Pastchal-Temple, 2012 ; Shernoff & Vandell, 2007 ), and contributing to positive emotional development, including improved self-esteem, positive attitudes, and enhanced social behaviour (Afterschool Alliance, 2015 ; Durlak & Weissberg, 2007 ; Lauer et al., 2006 ; Little et al., 2008 ). Moreover, engaging in various activities within these programs allows students to develop meaningful connections, expand their social networks, enhance leadership skills (Lipscomb et al., 2017 ), and cultivate cooperation, effective communication, and innovative problem-solving abilities (Mahoney et al., 2007 ).
Implementing STEM activities in out-of-school learning environments not only supports students in making career choices and fostering meaningful learning and interest in science, but also facilitates deep learning experiences (Bybee, 2001 ; Dabney et al., 2012 ; Sahin et al., 2018 ). Furthermore, STEM Clubs enhance students' emotional skills, such as a sense of belonging and peer-to-peer communication, while also fostering 21st-century skills, facilitating the acquisition of current content, and promoting career awareness and interest in STEM professions (Blanchard et al., 2017 ). In summary, engaging in STEM activities through social club activities not only addresses time constraints but also complements formal education and contributes to students' overall development. Hence, STEM Clubs, which are part of extended education, can be defined as dynamic and flexible learning environments that provide an effective approach to conducting STEM studies beyond traditional classroom settings. These clubs offer flexibility in terms of time and location, with intentionally structured programs and activities that take place outside of regular classes. They provide students with unique opportunities to explore and deepen their understanding of STEM subjects through collaborative engagement, hands-on use of tools, and immersive experiences in authentic environments (Bae, 2018 ; Blanchard, et al., 2017 ; Bybee, 2001 ; Cooper, 2011 ; Dabney et al., 2012 ). STEM Clubs have gained immense popularity worldwide, providing students with invaluable opportunities to explore and cultivate their interests and knowledge in these crucial fields (Adams et al., 2014 ; Bell et al., 2009 ). According to America After 3PM, nearly 75% of afterschool program participants, around 5,740,836 children, have access to STEM learning opportunities (Afterschool Alliance, 2015 ).
STEM Clubs as after-school programs come in various forms and provide diverse tutoring and instructional opportunities. For instance, the Boys and Girls Club of America (BGCA) operates in numerous cities across the United States, annually serving 4.73 million students (Boys and Girls Club of America, 2019 ). This program offers students the chance to engage in activities like sports, art, dance, field trips, and addresses the underrepresentation of African Americans in STEM. Another example is the Science Club for Girls (SCFG), established by concerned parents in Cambridge to address gender inequity in math, science, and technology courses and careers. SCFG brings together girls from grades K–7 through free after-school or weekend clubs, science explorations during vacations, and community science fairs, with approximately 800 to 1,000 students participating each year. The primary goal of these clubs is to increase STEM literacy and self-confidence among K–12 girls from underrepresented groups in these fields. More examples can be found in the literature, such as the St. Jude STEM Club (SJSC), where students conducted a 10-week paediatric cancer research project using accurate data (Ayers et al., 2020 ), and After School Matters, based in Chicago, offers project-based learning that enhances students' soft skills and culminates in producing a final project based on their activities (Hirsch, 2011 ).
The literature on STEM Clubs indicates a diverse range of such clubs located worldwide, catering to different student groups, operating on varying schedules, implementing diverse activities, and employing various strategies, methodologies, experiments, and assessments (Ayers et al., 2020 ; Blanchard et al., 2017 ; Boys and Girls Club of America, 2019 ; Hirsch, 2011 ; Sahin et al., 2018 ). However, it was previously unknown which specific sample groups were most commonly studied, which analytical methods were used frequently, and which results were primarily reported, even though the overall topic of STEM Clubs has gained significant attention. Therefore, organizing and categorizing this expansive body of literature is necessary to gain deeper insights into the current state of knowledge and practices in STEM Clubs. By systematically reviewing and synthesizing the diverse range of studies on this topic, we can develop a clearer understanding of the focus areas, methodologies, and key findings that have emerged from the existing research (Fraenkel et al., 2012 ). At this point, using a content analysis method is appropriate for this purpose because this method is particularly useful for examining trends and patterns in documents (Stemler, 2000 ). Similarly, some previous research on STEM education has conducted content analyses to examine existing studies and construct holistic patterns to understand trends (Bozkurt et al., 2019 ; Chomphuphra et al., 2019 ; Irwanto et al., 2022 ; Li et al., 2020 ; Lin et al., 2019 ; Martín-Páez et al., 2019 ; Noris et al., 2023 ). However, there is a lack of content analysis specifically focused on studies of STEM Clubs in the literature and showing the trends in this topic. Analysing research trends in STEM Clubs can help build upon existing knowledge, identify gaps, explore emerging topics, and highlight successful methodologies and strategies (Fraenkel et al., 2012 ; Noris et al., 2023 ; Stemler, 2000 ). This information can be valuable for researchers, educators, and policymakers to stay up-to-date and make informed decisions regarding curriculum design (Bozkurt et al., 2019 ; Chomphuphra et al., 2019 ; Irwanto et al., 2022 ; Li et al., 2020 ; Lin et al., 2019 ; Martín-Páez et al., 2019 ; Noris et al., 2023 ), the development of effective STEM Club programs, resource allocation, and policy formulation (Blanchard et al., 2017 ; Cooper, 2011 ; Dabney et al., 2012 ). Therefore, the identification of research trends in STEM Clubs was the aim of this study.
To identify research trends, studies commonly analysed documents by considering the dimensions of articles such as keywords, publishing years, research designs, purposes, sample levels, sample sizes, data collection tools, data analysis methods, and findings (Bozkurt et al., 2019 ; Chomphuphra et al., 2019 ; Irwanto et al., 2022 ; Li et al., 2020 ; Sozbilir et al., 2012 ). Using these dimensions as a framework is a useful and common approach in content analysis because this framework allows researchers to systematically examine the key aspects of existing studies and uncover patterns, relationships, and trends within the research data (Sozbilir et al., 2012 ). Hence, since the aim of this study is to identify and analyse research trends in STEM Clubs, it focused on publishing years, keywords, research designs, purposes, sample levels, sample sizes, data collection tools, data analysis methods, and findings of the studies on STEM Clubs.
As a conclusion, the main problem of this study is “What are the characteristics of the studies on STEM Clubs?”. The following sub-questions are addressed in this study:
What is the distribution of studies on STEM Clubs by year?
What are the frequently used keywords in studies on STEM Clubs?
What are the commonly employed research designs in studies on STEM Clubs?
What are the typical purposes explored in studies on STEM Clubs?
What are the commonly observed sample levels in studies on STEM Clubs?
What are the commonly observed sample sizes in studies on STEM Clubs?
What are the commonly utilized data collection tools in studies on STEM Clubs?
What are the commonly utilized data analysis methods in studies on STEM Clubs?
What are the typical durations reported in studies on STEM Clubs?
What are the commonly reported findings in studies on STEM Clubs?
In this study, the descriptive content analysis research method was employed, which allows for a systematic and objective examination of the content within articles, and description of the general trends and research results in a particular subject matter (Lin et al., 2014 ; Suri & Clarke, 2009 ; Sozbilir et al., 2012 ; Stemler, 2000 ). Given the aim of examining research trends in STEM Clubs, the utilization of this method was appropriate, as it provides a structured approach to identify patterns and trends (Gay et al., 2012 ). To implement the content analysis method, this study followed the three main phases proposed by Elo and Kyngäs ( 2008 ): preparation, organizing, and reporting. In the preparation phase, the unit of analysis, such as a word or theme, is selected as the starting point. So, in this study, the topic of STEM Clubs was carefully selected. During the organizing process, the researcher strives to make sense of the data and to learn "what is going on" and obtain a sense of the whole. So, in this study, during the analysis process, the content analysis framework (sample levels, sample sizes, data collection tools, research designs, etc.) was used to question the collected studies. Finally, in the reporting phase, the analyses are presented in a meaningful and coherent manner. So, the analyses were presented meaningfully with visual representations such as tables, graphs, etc. By adopting the content analysis research method and following the suggested phases, this study aimed to gain insights into research trends in STEM Clubs, identify recurring themes, and provide a comprehensive analysis of the collected data.
The online databases ERIC and Web of Science were searched using keywords derived from a database thesaurus. These databases were chosen because of their widespread recognition and respect in the fields of education and academic research, and they offer a substantial amount of high-quality, peer-reviewed literature. The search process involved several steps. Firstly, titles, abstracts, and keywords were searched using Boolean operators for the keywords "STEM Clubs," "STEAM Clubs," "science-technology-engineering-mathematics clubs," "after school STEM program" and "extracurricular STEM activities" in the databases (criterion-1). Secondly, studies were collected beginning from November to the end of December 2023. So, the studies published until the end of December 2023 were included in the search, without a specific starting date restriction (criterion-2). Thirdly, the search was limited to scientific journal articles, book chapters, proceedings, and theses, excluding publications such as practices, letters to editors, corrections, and (guest) editorials (criterion-3). Fourthly, studies published in languages other than English were excluded, focusing exclusively on English language publications (criterion-4). Fifthly, duplicate articles found in both databases were identified and removed. Next, the author read the contents of all the studies, including those without full articles, with a particular focus on the abstract sections. After that, studies related to after school program and extracurricular activities that did not specifically involve the terms STEM or clubs were excluded, even though “extracurricular STEM activities” and “after school STEM program” were used in the search process, and there were studies related to after school program or extracurricular activities but not STEM (criterion-5). Additionally, studies conducted in formal and informal settings within STEM clubs were included, while studies conducted in settings such as museums or trips were excluded (criterion-6). Because STEM Clubs are a subset of informal STEM education settings, which also include museums and field trips, the main focus of this study is to show the trends specifically related to STEM Clubs. Moreover, studies focusing solely on technology without incorporating other STEM components were also excluded (criterion-7). Finally, 56 publications that met the inclusion and extraction criteria were identified. These publications comprised two dissertations, seven proceedings, and 47 articles from 36 different journals. By applying these criteria, the search process aimed to ensure the inclusion of relevant studies while excluding those that did not meet the specified criteria as shown in Fig. 1 .
Flowchart of article process selection
Two different approaches were followed in the content analysis process of this study. In the first part, deductive content analysis was used, and a priori coding was conducted as the categories were established prior to the analysis. The categorization matrix was created based on the Paper Classification Form (PCF) developed by Sozbilir et al. ( 2012 ). The coding scheme devised consisted of eight classification groups for the sections of publication years, keywords, research designs, sample levels, sample sizes, data collection tools, data analysis methods, and durations, with sub-categories for each section. For example, under the research designs section, the sub-categories included qualitative and quantitative methods, case study, design-case study, comparative-case study, ethnographic study, phenomenological study, survey study, experimental study, mixed and longitudinal study, and literature review study. These sub-categories were identified prior to the analysis. Coding was then applied to the data using spreadsheets in the Excel program, based on the categorization matrix. Frequencies for the codes and categories created were calculated and presented in the findings section with tables. Line charts were used for the publication years section, while word clouds, which visually represent word frequency, were used for the keywords section. Word clouds display the most frequently used words in different sizes and colours based on their frequencies (DePaolo & Wilkinson, 2014 ). So, in this part, the analysis was certain since the studies mostly provided related information in their contents.
In the second part, open coding and the creation of categories and abstraction phases were followed for the purposes and findings sections. Firstly, the stated purposes and findings of the studies were written as text. The written text was then carefully reviewed, and any necessary terms were written down in the margins to describe all aspects of the content. Following this open coding, the lists of categories were grouped under higher order headings, taking into consideration their similarities or dissimilarities. Each category was named using content-characteristic words. The abstraction process was repeated to the extent that was reasonable and possible. In this coding process, two individuals independently reviewed ten studies, considering the coding scheme for the first part and conducting open coding for the second part. They then compared their notes and resolved any differences that emerged during their initial checklists. Inter-rater reliability was calculated as 0.84 using Cohen's kappa analysis. Once coding reliability was ensured, the remaining articles were independently coded by the author. After completing the coding process, consensus was reached through discussions regarding any disagreements among the researchers regarding the codes, as well as the codes and categories constructed for the purpose and findings sections. At this point, there were mostly agreements in the coding process since the studies had already clearly stated their key characteristics, such as research design, sample size, sample level, and data collection tools. Additionally, when coding the studies' stated purposes and results, the researchers closely referred to the original sentences in the studies, which led to a high level of consistency in the coded content between the two raters.
Studies related to the STEM Clubs were initially conducted in 2009 (Fig. 2 ). The noticeable increase in the number of studies conducted each year is remarkable. It can be seen that the majority of the 47 articles that were examined (56 articles) were published after 2015, despite a decrease in the year 2018. Additionally, it was observed that the articles were most frequently published (8) in the years 2019 and 2022, least frequently (1) in the years 2009, 2010, and 2014, and there were no publications in 2012.
Number of articles by years
Word clouds were utilized to present the most frequently used keywords in the articles, as shown in Fig. 3 . However, due to the lack of reported keywords in the ERIC database, only 30 articles were included for these analyses. The keywords that exist in these studies were represented in a word cloud in Fig. 3 . The most frequently appearing keywords, such as "STEM," "education" and "learning" were identified. Additionally, by using a content analysis method, these keywords were categorized into six different groups: disciplines, technological concepts, academic community, learning experiences, core elements of education, and psychosocial factors (variables) in Table 1 .
Word cloud of the keywords used in articles
The purposes of the identified studies identified were classified into six main themes: “effects of participation in STEM Clubs on” (25), “evolution of a sample program for STEM Clubs and its implementation” (25), “examination of” (11), “identification of” (3), “comparison of in-school and out-school STEM experiences” (2) and “others” (6). Table 2 presents the distribution of the articles’ purposes based on the classification regarding these themes. Therefore, it can be seen that purposes of “effects of participation in STEM Clubs on,” and “evolution of a sample program for STEM Clubs and its implementation” were given the highest and equal consideration, while the purposes related to "identification of" (3) and "comparison of in-school and out-of-school STEM experiences" (2) were given the least consideration among them.
Within the theme of "effects of participation in STEM Clubs on" there are 11 categories. The aims of the studies in this section are to examine the effect of participation in STEM Clubs on various aspects such as attitudes towards STEM disciplines or career paths, STEM major choice/career aspiration, achievement in math, science, STEM disciplines, or content knowledge, perception of scientists, strategies used, value of clubs, STEM career paths, enjoyment of physics, use of complex and scientific language, interest in STEM, creativity, critical thinking about STEM texts, images of mathematics, or climate-change beliefs/literacy. It is evident that the majority of research in this section focuses on the effects of participation in STEM Clubs on STEM major choice/career aspiration (5), achievement (4), perception of something (4), and interest in STEM (3).
Within the theme of "evolution of a sample program for STEM Clubs and its implementation" there are three categories: development of program/curriculum/activity (14), identification of program's challenges and limitations (3), and implementation of program/activity (8). The studies in this section aim to develop a sample program for STEM Clubs and describe its implementation. It can be seen that the most preferred purpose among them is the development of program/curriculum/activity (14), while the least preferred purpose is the identification of program's challenges and limitations (3). In addition, studies that focus on the development of the program, curriculum, or activity were classified under the "general" category (10). Sub-categories were created for studies specifically expressing the development of the program with a focus on a particular area, such as the maker movement or Arduino-assisted robotics and coding. Similarly, studies that explicitly mentioned the development of the program based on presented ideas and experiences formed another sub-category. Furthermore, the category related to the implementation of program/activity was divided into eight sub-categories, each indicating the specific centre of implementation, such as problem-based learning-centred and representation of blacks-centred.
The theme of "examination of" refers to studies that aim to examine certain aspects, such as the experiences and perceptions of students (7) and the factors influencing specific subjects (4). Studies focusing on examining the experiences and perceptions of students were labelled as "general" (4), while studies exploring their experiences and perceptions regarding specific content, such as influences and challenges to participation in STEM clubs (2) and assessment (1), were labelled accordingly. Additionally, studies that focused on examining factors affecting the choice of STEM majors (2), participation in STEM clubs (1), and motivation to develop interest in STEM (1) were categorized in line with their respective focuses. As shown in Table 2 , it is evident that studies focusing on examining the experiences and perceptions of students (7) were more frequently conducted compared to studies focusing on examining the factors affecting specific subjects (4).
The theme of "identification of" refers to studies that aim to identify certain aspects, such as the types of attitudinal effects (1), types of changes in affect toward engineering (1), and non-academic skills (1). Additionally, the theme of "comparison of in-school and out-of-school STEM experiences" (2) refers to studies that aim to compare STEM experiences within school and outside of school. Lastly, studies that did not fit into the aforementioned categories were included in the "others" theme (6) as no clear connection could be identified among them.
The research designs employed in the examined articles were identified as follows: qualitative methods (36), including case study (20), design-case study (6), comparative-case study (4), ethnographic study (2), phenomenological study (2), and survey study (2); quantitative methods (7), including survey study (4) and experimental study (3); mixed methods and longitudinal studies (10); and literature review (3), as illustrated in Table 3 . It can be observed that among these methods, case study was the most commonly utilized. Furthermore, it is evident that quantitative methods (7) and literature reviews (3) were employed less frequently compared to qualitative (36) and mixed methods (10). Additionally, survey studies were utilized in both quantitative and qualitative studies.
The frequencies and percentages of sample levels in the examined articles are presented in Table 4 . The studies involved participants at different educational levels, including elementary school (8), middle school (23), high school (14), pre-service teachers or undergraduate students (6), teachers (4), parents (3), and others (1). It is apparent that middle school students (23) were the most commonly utilized sample among them, while high school students (14) were more frequently chosen compared to elementary school students (8). It should be noted that while grade levels were specified for both elementary and middle school students, separate grade levels were not identified for high school students in these studies. Additionally, studies that involved mixed groups were labelled as 3-5th and 6-8th grades. However, when the mixed groups included participants from different educational levels such as elementary, middle, or high school, teachers, parents, etc., they were counted as separate levels. Furthermore, the studies conducted with participants such as pre-service teachers, undergraduates, teachers, and parents were less frequently employed compared to K-12 students.
The frequencies of sample sizes in the examined articles are presented in Table 5 . It was observed that in 15 studies, the number of sample sizes was not provided. The intervals for the sample size were not equally separated; instead, they were arranged with intervals of 5, 10, 50, and 100. This choice was made to allow for a more detailed analysis of smaller samples, as smaller intervals can provide a more granular examination of data instead of cumulative amounts. The analysis reveals that the studies primarily prioritized sample groups with 11–15 (f:8) participants, followed by groups of 16–20 (f:4) and 201–250 (f:4). Additionally, it is evident that sample sizes of 6–10, 21–25, 41–50, 50–100, and more than 2000 (f:1) were the least commonly studied.
The frequencies and percentages of data collection tools in the examined articles are presented in Table 6 . The analysis reveals that the studies primarily employed survey or questionnaires (31.6%) and observations (30.5%) as data collection methods, followed by interviews (15.8%), documents (13.7%), tests (4.2%), and field notes (4.2%). Regarding survey/questionnaires, Likert-type scales (f:23) were more commonly employed compared to open-ended questions (f:7). Tests were predominantly used as achievement tests (f:2) and assessments (f:2), representing the least preferred data collection tools. Furthermore, the table illustrates that multiple data collection tools were frequently employed, as the total number of tools (95) is nearly twice the number of studies (56).
The frequencies and percentages of data analysing methods in the examined articles are presented in Table 7 . The table reveals that the studies predominantly employed descriptive analysis (f:33, 41.25%), followed by inferential statistics (f:16, 20%), descriptive statistics (f:15, 18.75%), content analysis (f:14, 17.5%), and the constant-comparative method (f:2, 2.5%). It is notable that qualitative methods (f:49, 61.25%) were preferred more frequently than quantitative methods (f:31, 38.75%) in the examined studies related to STEM Clubs. Within the qualitative methods, descriptive analysis (f:33) was utilized nearly twice as often as content analysis (f:14), while within the quantitative methods, descriptive statistics (f:15) and inferential statistics (f:16), including t-tests, ANOVA, regression, and other methods, were used with comparable frequency.
The durations of STEM Clubs in the examined studies are presented in Table 8 . Based on the analysis, there are more studies (f:37) that do not state the duration of STEM Clubs than studies (f:19) that do provide information on the durations. Additionally, among the studies that do state the durations, there is no common period of time for STEM Clubs, as they were implemented for varying numbers of weeks and sessions, with session durations ranging from several minutes. Therefore, it can be observed that STEM Clubs were conducted over the course of 3 semesters (academic year and summer), 5 months, 2 to 16 weeks, with session durations ranging from 60 to 120 min. Furthermore, the durations of "3 semesters," "10 weeks with 90-min sessions per week," and "unknown weeks with 60-min sessions per week" were used more than once in the studies.
The content analysis of the findings of the identified examined articles are presented by their frequencies in Table 9 . Although the studies cover a diverse range of topics, the analysis indicates that the results can be broadly classified into three themes, namely, the "development of or increase in certain aspects" (f:68), "design of STEM Clubs" (f:17), and "identification of various aspects" (f:16). Based on the analysis, the findings in the studies are associated with the development of certain aspects such as skills or the increase in specific outcomes like academic achievement. Furthermore, the studies explore the design of STEM Clubs through the description of specific cases, such as sample implementations and challenges. Additionally, the studies focus on the identification of various aspects, such as factors and perceptions.
It is evident from the findings that the studies predominantly yield results related to the development of or increase in certain aspects (f:68). Within this theme, the most commonly observed result is the development of STEM or academic achievement or STEM competency (f:11). This is followed by an increase in STEM major choice or career aspiration (f:9), an increase in engagement or participation in STEM clubs (f:5), the development of identity including STEM, science, engineering, under-representative groups (f:5), the development of interest in STEM (f:4), an increase in enjoyment (f:4), and the development of collaboration, leadership, or communication skills (f:4). Furthermore, it can be observed that there are some results, such as the development of critical thinking, perseverance and the teachers’ profession, that were yielded less frequently (f:1). The results of 16 studies were found with a frequency of 1.
Within the design of STEM Clubs, the sample implementation or design model for different purposes such as the usage of robotic program or students with disabilities (f:7), design principles or ideas for STEM clubs, activities or curriculum (f:4), challenges or factors effecting STEM Clubs success and sustainability (f:3) were presented as a result. Additionally, the comparison was made between in-school and out-of-school learning environments (f:3), highlighting the contradictions of STEM clubs and science classes, as well as the differences in STEM activities and continues-discontinues learning experiences in mathematics. Within the identification of various aspects, the most commonly gathered result was the identification of factors affecting participation or motivation to STEM clubs (f:5). This was followed by the identification of barriers to participation (f:2). The identification of other aspects, such as parents' roles and perspectives on STEM, was comparatively less frequent.
Considering the wide variety of STEM Clubs found in different regions around the world, this study aimed to investigate the current state of research on STEM Clubs. It is not surprising to observe an increase in the number of studies conducted on STEM Clubs over the years. This can be attributed to the overall growth in research on STEM education (Zhan et al., 2022 ), as STEM education often includes activities and after-school programs as integral components (Blanchard et al., 2017 ). Identifying relevant keywords and incorporating them into a search strategy is crucial for conducting a comprehensive and rigorous systematic review (Corrin et al., 2022 ). To gain a broader understanding of keyword usage in the context of STEM Clubs, a word cloud analysis was performed (McNaught & Lam, 2010 ). Additionally, based on the content analysis method, six different categories for keywords were immerged: disciplines, technological concepts, academic community, learning experiences, core elements of education, and psychosocial factors (variables). The analysis revealed that the keyword "STEM" was used most frequently in the studies examined. This may be because authors want their studies to be easily found and widely searchable by others, so they use "STEM" as a general term for their studies (Corrin et al., 2022 ). Similarly, the frequent use of keywords like "education" and "learning" from the "core elements of education" category could be attributed to authors' desire to use broad, searchable terms to make their studies more discoverable (Corrin et al., 2022 ). Additionally, it was observed that from the STEM components, only "science" and "engineering" were used as keywords, while "mathematics" and "technology" were not present. This finding aligns with claims in the literature that mathematics is often underemphasized in STEM integration (Fitzallen, 2015 ; Maass et al., 2019 ; Stohlmann, 2018 ). Although the specific term "technology" did not appear in the word cloud, technology-related keywords such as "arduino," "robots," "coding," and "innovative" were present. Furthermore, the analysis revealed that authors preferred to use keywords related to their sample populations, such as "middle (school students)," "elementary (students)," "high school students," or "teachers." Additionally, keywords describing learning experiences, such as "extracurricular," "informal," "afterschool," "out-of-school," "social," "clubs," and "practice" were commonly used. This preference may stem from the fact that STEM clubs are often part of informal learning environments, out-of-school programs, or afterschool activities, and these concepts are closely related to each other (Baran et al., 2016 ; Cooper, 2011 ; Kalkan & Eroglu, 2017 ; Schweingruber et al., 2014 ). Moreover, the analysis showed that keywords related to psychosocial factors (variables), such as "disabilities," "skills," "interest," "attainment," "enactment," "expectancy-value," "self-efficacy," "engagement," "motivation," "career," "gender," "cognitive," and "identity" were also prevalent. This suggests that the articles investigated the effects of STEM club practices on these psychosocial variables. To sum up, by using these keywords, researchers can gain valuable insights and effectively search for relevant articles related to STEM clubs, enabling them to locate appropriate resources for their research (Corrin et al., 2022 ).
The popularity of case studies as a research design, based on the analysis, can be attributed to the fact that studies on STEM Clubs were conducted in diverse learning environments, highlighting sample implementation designs (Adams et al., 2014 ; Bell et al., 2009 ; Robelen, 2011 ). At this point, case studies offer the opportunity to present practical applications and real-world examples (Hamilton & Corbett-Whittier, 2012 ), which is highly valuable in the context of STEM Clubs. Additionally, the observation that quantitative methods were not as commonly utilized as qualitative methods in studies related to STEM Clubs contrasts with the predominant reliance on quantitative methods in STEM education research (Aslam et al., 2022 ; Irwanto et al., 2022 ; Lin et al., 2019 ). This suggests a lack of quantitative studies specifically focused on STEM Clubs, indicating a need for more research in this area employing quantitative approaches. Therefore, it is important to prioritize and conduct additional quantitative studies to further enhance our understanding of STEM Clubs and their impact. In studies on STEM Club, there is a higher frequency of research involving K-12 students, particularly middle school students, parallel to some studies on literature (Aslam et al., 2022 ), compared to other groups such as pre-service teachers, undergraduate students, teachers, and parents. This can be attributed to the fact that STEM Clubs are designed for K-12 students, and middle school is a crucial period for introducing them to STEM concepts and careers. Middle school students are developmentally ready for hands-on and inquiry-based learning, commonly used in STEM education. Additionally, time constraints, especially for high school students preparing for university, may limit their involvement in extensive STEM activities. Furthermore, STEM Clubs were primarily employed with sample groups ranging from 11–15, 16–20, and 201–250 participants. The preference for 11–20 participants, rather than less than 10, may be attributed to the collaborative nature of STEM activities, which often require a larger team for effective teamwork and group dynamics (Magaji et al., 2022 ). Utilizing small groups as samples can result in the case study research design being the most frequently employed approach due to its compatibility with smaller sample sizes. On the other hand, the inclusion of larger groups (201–250) is suitable for survey studies, as this number can represent the total student population attending STEM Clubs throughout a semester with multiple sessions (Boys & Girls Club of America, 2019 ).
According to studies on STEM Clubs, surveys or questionnaires and observations were predominantly used as data collection methods. This preference can be attributed to the fact that surveys or questionnaires allow researchers to gather data on diverse aspects, including students' attitudes, perceptions, and experiences related to STEM Clubs, facilitating generalization and comparison (McLafferty, 2016 ). Furthermore, observations were frequently employed because they can offer a deeper understanding of the lived experiences and actual practices within STEM Clubs (Baker, 2006 ). Along with data collection tools, descriptive analysis was predominantly utilized in studies on STEM Clubs, with quantitative methods including descriptive statistics and inferential statistics being used to a similar extent. The preference for descriptive analysis may arise from its effectiveness in describing activities, experiences, and practices within STEM Clubs. Given the predominance of case study research in the analysed studies, it is not surprising to observe a high frequency of descriptive statistics in the findings. On the other hand, the extensive use of quantitative analysing methods can be attributed to the need for statistical analysis of surveys and questionnaires (Young, 2015 ). Consequently, future studies on STEM Clubs could benefit from considering the use of tests and field notes as additional data collection tools, along with surveys, observations and interviews. Additionally, the development of tests specifically designed to assess aspects related to STEM could provide valuable insights (Capraro & Corlu, 2013 ; Grangeat et al., 2021 ). Moreover, increasing the utilization of content analysis and constant comparative analysis methods could further enhance the depth and richness of data analysis in STEM Club research (White & Marsh, 2006 ). In the studies on STEM Clubs, the duration and scheduling of the clubs varied considerably. While there was no common period of time for STEM Clubs, they were implemented for different numbers of weeks and sessions, with session durations ranging from several minutes to 60 to 120 min. However, it was observed that STEM Clubs were predominantly conducted over the course of three semesters, including the academic year and summer, or for durations of 2 to 16 weeks. This scheduling pattern can be attributed to the fact that STEM Clubs were often implemented as after-school programs, and they were designed to align with the academic semesters and summer school periods to effectively reach students. Additionally, the number of weeks in these studies may have been arranged according to the duration of academic semesters, although some studies were conducted for less than a semester (Gutierrez, 2016 ). The most common use of multiple sessions with a time range of 60 to 120 min can be attributed to the nature of the activities involved in STEM Clubs. These activities often require more time than regular class hours, and splitting them into separate sessions allows students to effectively concentrate on their work and engage in more in-depth learning experiences (Vennix et al., 2017 ).
The purposes of the studies on STEM Clubs were mostly related to effects of participation in STEM Clubs on various aspects such as attitudes towards STEM disciplines or career paths, STEM major choice/career aspiration, achievement etc., evolution of a sample program for STEM Clubs and its implementation including the development of program/activity, identification of program's challenges and limitations, and implementation of it, followed by the examination of certain aspects such as the experiences and perceptions of students and the factors influencing specific subjects, identification of such as the types of attitudinal effects and non-academic skills, and comparison of in-school and out-school STEM experiences. Therefore, the results of the studies parallel to the purposes were mostly related to development of or increase in certain aspects such as STEM or academic achievement or STEM competency STEM major choice or career aspiration engagement or participation in STEM Clubs, identity, interest in STEM, enjoyment, collaboration, communication skills, critical thinking, the design of STEM Clubs including the sample implementation or design model for different purposes such as the usage of robotic program or students with disabilities, design principles or ideas for STEM clubs or activities, challenges or factors effecting STEM Clubs success and sustainability, and the comparison between in-school and out-of-school learning environments. Also, they are related to the identification of various aspects such as factors affecting participation or motivation to STEM clubs, barriers to participation. At this point, it is evident that these identified categories align with the findings of studies in the literature. These studies claim that after-school programs, such as STEM Clubs, have positive impacts on students' achievement levels (NRC, 2015 ; Kazu & Kurtoglu Yalcin, 2021 ; Shernoff & Vandell, 2007 ), communication, and innovative problem-solving abilities (Mahoney et al., 2007 ), leadership skills (Lipscomb et al., 2017 ), career decision-making (Bybee, 2001 ; Dabney et al., 2012 ; Sahin et al., 2018 ; Tai et al., 2006 ), creativity (Wan et al., 2023 ), 21st-century skills (Hirsch, 2011 ; Zeng et al., 2018 ), interest in STEM professions (Blanchard et al., 2017 ; Chittum et al., 2017 ; Wang et al., 2011 ), and knowledge in STEM fields (Adams et al., 2014 ; Bell et al., 2009 ). Furthermore, it can be inferred that the studies on STEM Clubs paid significant attention to the design descriptions of programs or activities (Nation et al., 2019 ). This may be because there is a need for studies that focus on designing program models for different cases (Calabrese Barton & Tan, 2018 ; Estrada et al., 2016 ). These studies can serve as examples and provide guidance for the development of STEM clubs in various settings. By creating sample models, researchers can contribute to the improvement and expansion of STEM clubs across different environments (Cakir & Guven, 2019 ; Estrada et al., 2016 ).
In conclusion, as the studies on the trends in STEM education (Bozkurt et al., 2019 ; Chomphuphra et al., 2019 ; Irwanto et al., 2022 ; Li et al., 2020 ; Lin et al., 2019 ; Martín-Páez et al., 2019 ; Noris et al., 2023 ), the analysis of prevailing research trends specifically in STEM Clubs, which are implemented in diverse environments with varying methods and purposes, can provide a comprehensive understanding of these clubs as a whole.
It can also serve as a valuable resource for guiding future investigations in this field. By identifying common approaches and identifying gaps in methods and results, a holistic perspective on STEM Clubs can be achieved, leading to a more informed and targeted direction for future research endeavours.
Future research on STEM Clubs should consider the trends identified in the study and address methodological gaps. For instance, there is a lack of research in this area that employs quantitative approaches. Therefore, it is important for future studies to incorporate quantitative methods to enhance the understanding of STEM Clubs and their impact. This includes exploring underrepresented populations, investigating the long-term impacts of STEM Clubs, and examining the effectiveness of specific pedagogical approaches or interventions within these clubs. Researchers should conduct an analysis to identify common approaches used in STEM Clubs across different settings. This analysis can help uncover effective strategies, best practices, and successful models that can be replicated or adapted in various contexts. By undertaking these efforts, researchers can contribute to a more comprehensive understanding of STEM Clubs, leading to advancements in the field of STEM education.
It is important to consider the limitations of the study when interpreting its findings. The study's findings are based on the literature selected from two databases, which may introduce biases and limitations. Additionally, the study's findings are constrained by the timeframe of the literature review, and new studies may have emerged since the cut-off date, potentially impacting the representation and generalizability of the research trends identified. Another limitation lies in the construction of categories during the coding process. The coding scheme used may not have fully captured or represented all relevant terms or concepts. Some relevant terms may have been inadequately represented or identified using different words or phrases, potentially introducing limitations to the analysis. While efforts were made to ensure validity and reliability, there is still a possibility of unintended biases or inconsistencies in the categorization process.
The datasets (documents, excel analysis) utilized in this article are available upon request from the corresponding author.
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Financial literacy to develop complex thinking skills: quantitative measurement in mexican women entrepreneurs.
The objective of the study was to validate the construction of a financial literacy measurement instrument aligned with complex thinking competencies in Mexican women entrepreneurs. By means of the construct validation method, the content was validated by expert judgment, validation by exploratory and confirmatory factor analysis, as well as internal consistency by means of a pilot test applied to a sample of 189 participants. A highly valid and reliable version was obtained, organized in four dimensions with a total of 23 items. This study examines and estimates the determinants of financial literacy for the first time under the light of complex reasoning.
Entrepreneurship, as the mainstay of the economy in a complex and constantly changing environment, deserves to be studied not only about the threats it faces or the identification of opportunities and their viability analysis, but also about the characteristics and decision-making skills of those who undertake them, especially women, one of the economically vulnerable sectors of the population. Financial literacy is an essential skill in modern life in both developed and emerging economies ( García-Mata, 2021b ) because, with the increasing complexity of the financial world, the ability to understand and properly manage money has become a pressing need directly related to the success of female entrepreneurship ( Baporikar and Akino, 2020 ). Through the acquisition of knowledge, skills and positive attitudes regarding money management, the female entrepreneur will be better prepared to face recurrent economic crises that threaten the survival of her business ( Niwaha et al., 2016 ; Rachapaettayakom et al., 2020 ). However, few efforts are directed at addressing the need for financial literacy of adult women who are on the path of entrepreneurship.
Beyond theoretical knowledge about financial instruments and services, women entrepreneurs require support for the development of competencies aimed at putting this knowledge into practice in contexts such as scenario analysis, risk assessment, the search for solutions, as well as informed decision making. The promotion of financial literacy initiatives under the scheme of complex thinking can give the entrepreneur the ability to improve her decision-making process for an effective, innovative and efficient management of her business resources ( Dzwigol et al., 2020 ; Ramos et al., 2021 ). The objective of this research is the design and validation of the construction of an instrument to measure the complex thinking sub-competencies of Mexican women entrepreneurs aligned to their level of financial literacy, presenting an original approach as it is the first of its kind. The result has demonstrated that it is possible to evaluate the level of financial literacy of women entrepreneurs in the context of complex thinking, so that future initiatives in this field can be developed.
Financial literacy, as a discipline of study, awakened interest only at the beginning of the 21st century as a result of the financial crises that have characterized it up to now, resulting in questions about the influence of attitudes, behaviors and knowledge on individuals' decision making with respect to the management of their money and the impact of these decisions on their general wellbeing. Starting with the work of Lusardi (2001) , who was a pioneer in questioning the reasons for the factors underlying the lack of a savings culture and its impact on long-term financial planning, and the subsequent posing of a first set of questions aimed at measuring financial literacy ( Lusardi, 2008 , 2011 ; Lusardi and Mitchell, 2009 ), as well as the work of different governments and institutions, among which the effort of the Organization for Economic Cooperation and Development (OECD) in the development of measurement instruments such as the PISA test (Programme for International Student Assessment), which includes the measurement of basic knowledge on money management among young people ( OECD, 2018 ), stands out, it was in 2012 when the Mexican Government launched a first measurement initiative, the National Survey on Financial Inclusion (ENIF) ( CNBV, 2012 ). The results of these measurements consistently point to the existence of a significant gender gap where women not only show lower rates of financial literacy but also of access to useful and affordable financial products and services ( UNESCO, 2020 ; UN Women, 2021 ). Now, beyond the impact that financial literacy has on women's individual wellbeing, it is time to focus on the influence of this level of financial literacy on the success of female entrepreneurship, especially in micro and small businesses where planning, management and financing decisions are usually made by a single person.
A first approach to the object of study is to establish what is understood as financial literacy, both individually and in the management of the enterprise or business. Although there is diverse literature on the subject, the definition of the construct is heterogeneous and there is no agreement ( Anshika and Mallik, 2021 ). This represents an important challenge when trying to propose a model for its measurement. According to the OECD, financial literacy is defined as the process by which financial consumers improve their understanding of financial products, related concepts, as well as the underlying risks and, through information, instruction and/or objective advice, develop the skills and confidence to become more aware of financial risks and opportunities, make informed decisions, know where to go for help and take any effective action to improve their economic wellbeing ( Raccanello and Guzmán, 2014 ). Another more technical approach establishes the financial literacy of the entrepreneur as the ability to understand the functioning of the business in terms of possessing knowledge about recording income and expenses, separation between personal and business money, as well as financial planning ( Ali et al., 2018 ). Given the above, we can add that, in a business context, this definition can be complemented with the execution of actions aimed at the stable growth and financial viability of the business over time. It is important to note the importance of the ability to make timely and informed decisions according to individual circumstances.
Globally, there is an unequal race for business survival. In Latin America, and especially in the case of Mexico, this inequality is extremely marked by the proportion distributed between large and small companies. According to the 2019 Economic Censuses, 99.8% of the country's establishments are micro, small or medium-sized ( INEGI, 2020 ). These micro and small enterprises (MSMEs) are the pillar of economic growth for developing countries in addition to allowing the generation of employment and self-employment for women, one of the vulnerable groups recognized by both the OECD and UNESCO, which in the framework of the 2030 Agenda points out the need for the integration of women not only in productive processes, but also in social and economic ones ( UNESCO, 2017 ), inequality in terms of financial inclusion in Mexico prevents women from accessing savings and investment mechanisms to ensure a decent standard of living in retirement ( INEGI, 2021 ; INMUJERES, 2022 ). Entrepreneurship allows women not only to contribute to the economic wellbeing of the country, but also to guarantee the generation of income for their personal and family wellbeing while facilitating compatibility with care and household tasks.
Despite this, this sector faces enormous barriers in accessing funding and financing sources, as well as financial products and services through formal institutions, in addition to the lack of ability of entrepreneurs for financial management and long-term business planning. Without the understanding of basic financial concepts, people lack the equipment to make decisions related to the management of their resources ( Vanegas et al., 2020 ; Anshika and Mallik, 2021 ) which is reflected in low performance rates and a high mortality rate of MSMEs in Mexico, which until before the COVID-19 pandemic, resulted in an average life time for this sector of 7.8 years ( INEGI, 2020 ). Empowering women entrepreneurs by developing competencies to improve financial decision-making through innovative financial literacy initiatives can translate, over time, into a determining factor for an improvement in the population's wellbeing indexes.
Decision making is a reflective process that involves analyzing and discerning between different alternatives, a decision implies knowledge, understanding and analysis of a problem in order to generate the right decision. Some authors suggest that correct decision making is linked to greater cognitive capacity, and this is a requirement for financial literacy, also establishing that the greater the cognitive capacity, the greater the gender gap in financial inclusion ( Muñoz-Murillo et al., 2020 ). In addition to the above, studies have shown that financial literacy is neither stable nor constant, nor can it be assumed that once acquired it will affect people's decision making, since it changes according to time and circumstances, being related to the experiences, contexts and skills of the individual or the social situations that surround him/her ( Bay and Catasús, 2014 ). It becomes, then, a personal process in which the individual needs to take responsibility for his or her self-training in order to prepare him or herself for changing economic environments ( Vanegas et al., 2020 ). Technological evolution and the speed with which large volumes of information are transferred have evolved the business world, demanding from its managers the ability to make decisions quickly, to be self-taught, capable of interpreting reality, systematizing their decisions and learning from their own mistakes ( Pacheco-Velázquez et al., 2023 ). In other words, the entrepreneur must not only acquire knowledge related so far to financial literacy, but simultaneously requires the development of complex thinking skills.
Unlike simple reasoning, which focuses on solving problems with a single correct answer, complex reasoning involves the consideration of multiple perspectives and the integration of multiple sources of information to find effective solutions. Complex thinking is defined as the competence acquired by individuals that allows them to develop a holistic view of the world, enabling them to carry out cognitive activities, analysis and synthesis to face challenges and solve problems ( Vázquez-Parra et al., 2022a , b ). According to the complex thinking competency it integrates four sub-competencies:
a) Systemic: allows the identification of the elements and interconnections that make up an environmental problem or situation.
b) Critical: analyzes and evaluates the reasoning considering its validity and its differentiation with existing knowledge and structures.
c) Scientific: provides methodologies that allow the construction of objective reasoning to make decisions.
d) Innovative: provides creative and novel elements to evaluate the environment and the problems faced by the individual.
These sub-competencies are related to financial literacy in that they frame the knowledge of theoretical concepts and the skills to generate behaviors and attitudes for their application based on the experience and understanding of the environment as a consequence of business activities ( Manzanera-Román and Brändle, 2016 ; García-González et al., 2020 ; Oggero et al., 2020 ; Cruz-Sandoval et al., 2023 ). From the literature review it is clear that, although there are measurement instruments regarding the application of financial literacy aimed at micro and small business management, there is no evidence of the existence of measurement instruments that relate the field of financial literacy in the female sector to the subcompetencies of complex thinking. Table 1 summarizes some studies on financial literacy in entrepreneurs that have addressed the operationalization of financial literacy related to entrepreneurship, which have served as the basis for the development of the instrument that we present in the framework of this research.
Table 1 . Previous studies.
The method of the study was the construct validation through the convergent and discriminant validity of a measurement instrument by means of a three-stage process. In the first stage, a literature review was carried out in order to construct the operationalization of variables based on previous research on financial literacy and its relationship with complex thinking competencies. Derived from the review, and given the non-existence of instruments that addressed both constructs, it was decided to proceed with the adaptation of the instrument: “OECD/INFE Survey Instrument to Measure the Financial Literacy of MSMEs” ( Escobar-Pérez and Martínez, 2008 ; OECD, 2019 ) by reformulating items based on four sub-competencies of complex thinking: critical thinking, systems thinking, innovative thinking and scientific thinking according to the framework proposed by Vázquez-Parra et al. (2023) , as well as translation and cultural adaptation ensuring the use of language oriented to favor women's financial inclusion ( Agnew et al., 2018 ; Whitehouse, 2018 ; Osei-Tutu and Weill, 2021 ; Bertrand and Osei-Tutu, 2022 ). Next, a content validation process was carried out by expert judgment followed by the application of Aiken's V concordance test and a qualitative review of observations made by the experts. Finally, once the corrections derived from the previous process were attended to, progress was made toward the piloting of the instrument and its validation by means of exploratory factor analysis, confirmatory factor analysis and, finally, the internal consistency test by calculating Cronbach's Alpha coefficient.
A group of seven expert judges was formed with proven experience in the field of financial literacy, as well as professional experience in direct contact with women entrepreneurs. As part of the experience of this group of experts we can highlight that three of them are authors of two or more books of international circulation on the subject of personal finance, three occupy management positions in financial institutions where they actively participate in the development of financial products and training aimed at women, and finally, one expert directs, at a national level, an initiative dedicated to the area of support for entrepreneurs in the post-acceleration stage of their business. The average number of years of experience in the area of personal finance and/or female entrepreneurship in this group is 11.3 years.
This group received the first version of the questionnaire with 40 items grouped into five domains of interest: Attitude, Behavior, Knowledge, correct financial management decision and Training, and four subdomains corresponding to the sub-competencies of Complex Thinking: systemic, innovative, critical and scientific. The experts received the questionnaire via the Google Forms tool, and were asked to evaluate each item based on clarity (the item is understood, correctly worded), coherence (the item is related to the dimension it measures), relevance (the item is important and should be included) and sufficiency (items belonging to the same dimension and sufficient to measure it) ( Matsumoto-Royo et al., 2021 ; Ramírez-Montoya et al., 2022 ; OECD, (n/d)) using a Likert-type polytomous scale from 1 to 5, as well as the inclusion of qualitative comments on the items. The criterion for the acceptance of items as valid was defined as those with a concordance index >0.71 according to the estimate using Alkien's V coefficient test ( Escurra, 1988 ; Penfield and Giacobbi, 2004 ), as well as the content analysis of the comments made by the group of experts.
Participants.
The questionnaire received responses during February and March 2023 using a convenience sampling of women entrepreneurs between 18 and 69 years of age ( n = 189). From the total number of observations, those where the participant stated that she was not directly involved in the financial decisions of the business or did not own the business (88) were eliminated, thus reducing the sample to 101 women entrepreneurs distributed as follows: 18–19 years ( n = 9), 20–29 years ( n = 37), 30–39 years ( n = 13), 40–49 years ( n = 20), 50–59 years ( n = 14), and 60–69 years ( n = 8), with businesses employing one person ( n = 42) and employing between 2 and 50 people ( n = 59). All of them agreed to participate in the sample collection by expressing their consent for data collection ( Valenzuela and Flores Fahara, 2013 ), declaring to be involved in making both investment and financing decisions for their business.
Once the results obtained during the validation process by expert judgment were integrated, a new version of the questionnaire was integrated with 23 items grouped into four dimensions associated with the sub-competences of complex thinking: (1) Scientific Thinking (SCT) with items R-01, R-02, R-05 and R-10, (2) Critical Thinking (CRT) with items R-06, R-12, R-13 and R15, (3) Innovative Thinking (INT) with items R-09, R-14, R-16, R-17, R-19 and R-23, and finally (4) Systematic Thinking (SYT) with items R-03, R-04, R-07, R-08, R-11, R-18, R-20, R-21 and R-22.
The questionnaire was applied online using the Google Forms tool. The results validation process consisted of performing an exploratory factor analysis in order to identify the relationships between the variables of interest and group them into latent factors or underlying constructs, as well as confirmatory factor analysis to confirm the underlying structure identified in a previous exploratory factor analysis ( García and Caro, 2009 ; García-González et al., 2020 ). This statistical technique was performed using the SSPS tool in order to validate the dimensionality of the data set and its latent factors. The Kaiser–Meyer–Olkin (KMO) test was also performed as a measure of sampling adequacy used as a prior evaluation of data in terms of their adequacy to perform a factor analysis with an expected value between 0 and 1. The reliability of the instrument was calculated using Cronbach's alpha as a measure of reliability or internal consistency of the set of items included in the questionnaire. Cronbach's alpha ranges from 0 to 1, with values >0.7 being considered acceptable for most research purposes ( González and Pazmiño, 2015 ). The data collection and analysis process took care of ethical aspects such as the confidentiality of the participants, their individual responses and the care of the personal data provided. The methodological quality, data management and interpretations of the results were taken care of throughout the research process.
Through the calculation of Aiken's V coefficient ( Aiken, 1985 ), the relevance of the items with respect to a content domain was quantified based on the evaluations of the seven expert judges, with a result of total agreement among the judges for 39 of the 40 items evaluated, that is, they obtained a score higher than 0.71 in terms of clarity, relevance, coherence and correspondence. The content analysis of the qualitative observations made by the expert judges was also carried out, finding that all the observations corresponded to the Clarity dimension in nine of the items. In this sense, the observations were grouped in terms of suggestions for modification or elimination. As a result of this analysis, a second version of the questionnaire was constructed with the 23 items best evaluated by the group of expert judges, the results of which are shown in Table 2 , which summarizes the value of Aiken's V coefficient calculated for each item and moves toward the reliability validity stage by piloting the instrument.
Table 2 . Result of the calculation of the Aiken V coefficient.
The suitability of the data for factor analysis was verified by obtaining a KMO value equal to 0.928, whose reading indicates having an excellent sample to perform the factor analysis of the data. The results obtained from Bartlett's test of sphericity indicate that the value of the chi-square test statistic is 2,129.689 with 253 degrees of freedom and a significance level of <0.001, which allows rejecting the null hypothesis that the observed correlation matrix is equal to the expected correlation matrix for independent and uncorrelated variables and indicates that there is sufficient evidence to conclude that the variables are correlated. These statistical indicators reinforce that the sample size is adequate for the methodological objective of the study, in addition to what MacCallum et al. (1999) establish as a recommendation to ensure the validity and reliability of the results obtained, where sample sizes of between 100 and 200 participants are considered adequate for factor analyses in instrument validation studies.
In the next stage of the factor analysis, the principal components table was analyzed with Kaiser normalization rotation and Varimax rotation, which seeks to maximize the variance explained by each component and minimize the variance shared among the components. Table 3 shows that it is possible to group four common factors that explain 74.076% of the accumulated variance.
Table 3 . Total variance explained.
The extraction of four principal components shows in Table 4 the variables that are significantly associated with each of them when having loadings ≥0.3.
Table 4 . Rotated component matrix.
With respect to the data obtained during the piloting of the instrument, descriptive statistics were calculated for each item. Table 5 shows that the highest mean was 3.754 for item R-02, while the lowest mean was 2.257 for R-11.
Table 5 . Descriptive statistics of the pilot test.
The confirmatory factor analysis establishes a model of relationships that empirically confirms the modeled structure of the instrument after the reclassification of the items as a result of the rotated component matrix analysis. The model fit indices are as follows:
• Comparative Fit Index (CFI): CFI value is 0.839. A CFI >0.90 generally indicates a good model fit, while values >0.80 can be considered acceptable.
• Tucker-Lewis Index (TLI): The TLI value is 0.818. Similar to CFI, a TLI >0.90 is indicative of a good model fit, while values >0.80 may be considered acceptable.
• Root Mean Square Error of Approximation (RMSEA): The RMSEA value is 0.122. An RMSEA ≤ 0.05 indicates a good model fit, while values between 0.05 and 0.08 indicate an acceptable fit. In this case, the RMSEA value suggests an acceptable model fit.
• Chi-square by degrees of freedom ( X 2 /df): The X 2 value is 558.472 and there are 224 degrees of freedom, resulting in an X 2 /df of ~2.49. An X 2 /df value close to 2 or less indicates a good model fit.
In summary, the fit indices suggest an acceptable overall model fit. Figure 1 presents the model generated, while Table 6 shows the reclassification of the items for the development of the final version of the measurement instrument.
Figure 1 . Results of the confirmatory factor analysis after item reclassification. Source: Own elaboration using SPSS Amos.
Table 6 . Reclassified reagents.
Finally, to measure the reliability of the instrument, the internal consistency of the instrument was estimated through the calculation of Cronbach's Alpha coefficient, obtaining a measurement precision of 0.966. According to the scale established for this measurement, the result is considered excellent.
The final version of the instrument allows measuring the level of financial literacy of women entrepreneurs in terms of attitudes, knowledge, behaviors and decision making aligned to the sub-competencies of complex thinking according to the results of the confirmatory factor analysis as shown in Figure 1 , given the need to promote female entrepreneurship not only as a form of self-support but also as a source of employment generation and economic growth ( UNESCO, 2017 , 2020 ; INEGI, 2020 ; UN Women, 2021 ) through financial inclusion initiatives that offer an increase in financial literacy levels allowing women entrepreneurs to face and weather the ups and downs of the economy ( Raccanello and Guzmán, 2014 ; Ali et al., 2018 ; Oggero et al., 2020 ; García-Mata, 2021a ) but also help them to enable complex reasoning competencies needed in a constantly evolving business environment ( Bay and Catasús, 2014 ; Dzwigol et al., 2020 ; Vanegas et al., 2020 ; Ramos et al., 2021 ). Knowing the level of financial literacy aligned to complex thinking competencies through the designed instrument allows the design and generation of effective financial literacy programs.
Content validity through expert judgment, as shown in Table 2 , allowed establishing the relevance of the items designed ( Escurra, 1988 ; Padilla García and Benítez, 2014 ; Sireci and Padilla, 2014 ; Matsumoto-Royo et al., 2021 ), while the exploratory and confirmatory factor analysis established the construct validity and its high relationship with the dimension assigned to them, as well as the reliability and internal consistency of the data validated by calculating Cronbach's Alpha ( García and Caro, 2009 ; González and Pazmiño, 2015 ; García-González et al., 2020 ). The information collected through the instrument can be used in financial literacy programs with emphasis on complex thinking sub-competencies for financial decision making in business.
The analyses carried out show that the instrument designed is a valid and reliable measure of financial literacy aligned with complex thinking competencies in Mexican women entrepreneurs. In conclusion, this study has generated an innovative instrument that can be used to measure the mastery not only of attitudes, knowledge, behaviors and financial decision-making of women entrepreneurs in Mexico, but also their interrelation with the sub-competencies of complex thinking that are necessary in the daily practice of entrepreneurship in the country.
A possible limitation of this study is related to the participants, since it was applied to women with some initiative to support entrepreneurship and who also have access to the internet through a mobile device, which leaves out those with lower socioeconomic status and/or limited use of electronic devices or digital media or who do not belong to any network to promote entrepreneurship. The validation of this instrument through its application to a population sample that includes women entrepreneurs who do not have the support of business development initiatives and in areas with limited access to internet or mobile devices is recommended to cover this limitation. Another future line of research is the design of longitudinal research to measure the effects over time of a personalized financial literacy initiative and its impact not only on the lengthening of the life of the business but also on its growth and performance levels, on the other hand, the possibility of studying in depth the impact of the empowerment in complex thinking skills for the empowerment of female entrepreneurship is generated.
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethical approval was not required for the study involving human participants in accordance with the local legislation and institutional requirements. Written informed consent to participate in this study was not required from the participants in accordance with the national legislation and the institutional requirements.
KB-C: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Validation, Writing – original draft, Writing – review & editing. MR-M: Funding acquisition, Methodology, Supervision, Writing – review & editing. AE-R: Writing – review & editing. MM-B: Writing – review & editing.
The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. The authors acknowledge the financial support of Tecnologico de Monterrey through the “Challenge-Based Research Funding Program 2022”. Project ID # I005 - IFE001 - C2-T3 - T also academic support from Writing Lab, Institute for the Future of Education.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.
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Keywords: financial literacy, complex thinking, measurement instrument, higher education, educational innovation
Citation: Bayly-Castaneda K, Ramírez-Montoya MS, Erdély-Ruiz A and Montoya-Bayardo MA (2024) Financial literacy to develop complex thinking skills: quantitative measurement in Mexican women entrepreneurs. Front. Educ. 9:1331866. doi: 10.3389/feduc.2024.1331866
Received: 01 November 2023; Accepted: 29 May 2024; Published: 03 July 2024.
Reviewed by:
Copyright © 2024 Bayly-Castaneda, Ramírez-Montoya, Erdély-Ruiz and Montoya-Bayardo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: María Soledad Ramírez-Montoya, solramirez@tec.mx
† ORCID: Karla Bayly-Castaneda orcid.org/0000-0002-4170-6072 María Soledad Ramírez-Montoya orcid.org/0000-0002-1274-706X Arturo Erdély-Ruiz orcid.org/0000-0003-1653-8342 Miguel Angel Montoya-Bayardo orcid.org/0000-0002-5545-6334
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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Need help please, I made 5 proposals for the past weeks but all got rejected dahil either not STEM related or just not feasible at all according to our research teacher. I seriously need your help guys, lutang na lutang na isip ko kakaisip ng research topic and worse, haggang Friday nalang since computan na ng grades for 1st quarter :((
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Here are 10 practical research topics for STEM students: Developing an affordable and sustainable water purification system for rural communities. Designing a low-cost, energy-efficient home heating and cooling system. Investigating strategies for reducing food waste in the supply chain and households.
Quantitative research involves gathering numerical data to answer specific questions, and it's a fundamental part of STEM fields. To help you get started on your research journey, we've compiled a list of 200 quantitative research title for stem students. These titles span various STEM disciplines, from biology to computer science.
Chemistry. Let's get started with some quantitative research topics for stem students in chemistry: 1. Studying the properties of superconductors at different temperatures. 2. Analyzing the efficiency of various catalysts in chemical reactions. 3. Investigating the synthesis of novel polymers with unique properties. 4.
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Embark on a captivating journey through the cosmos of knowledge with our curated guide on Quantitative Research Topics for STEM Students. Explore innovative ideas in science, technology, engineering, and mathematics, designed to ignite curiosity and shape the future. Unleash the power of quantitative research and dive into uncharted territories ...
101 Quantitative Research Topics for STEM Students Biology Research Topics. Effect of Temperature on Enzyme Activity: Investigate how different temperatures affect the efficiency of enzymes in biological reactions. The Impact of Pollution on Aquatic Ecosystems: Analyze the correlation between pollution levels and the health of aquatic ecosystems. Genetic Variability in Human Populations: Study ...
There are several science research topics for STEM students. Below are some possible quantitative research topics for STEM students. A study of protease inhibitor and how it operates. A study of how men's exercise impacts DNA traits passed to children. A study of the future of commercial space flight.
environmental science. These research endeavors contribute to theoretical frameworks and practical applications, technological innovations, and evidence-based decision-making. Here is a list of 200 quantitative research topics for STEM students. Keep in mind that. these topics cover a broad range of disciplines within STEM The impact of ...
Here are the key characteristics of quantitative research topics for STEM Students: Measurable Data: Quantitative topics examine things that can be measured and quantified with numbers, allowing statistical analysis of the data. Statistical Analysis: Quantitative topics use mathematical statistics to analyze numerical data and spot patterns ...
With the rapid increase in the number of scholarly publications on STEM education in recent years, reviews of the status and trends in STEM education research internationally support the development of the field. For this review, we conducted a systematic analysis of 798 articles in STEM education published between 2000 and the end of 2018 in 36 journals to get an overview about developments ...
An example of quantitative research topics for 12 th -grade students will come in handy if you want to score a good grade. Here are some of the best ones: The link between global warming and climate change. What is the greenhouse gas impact on biodiversity and the atmosphere.
Discover engaging Quantitative Research Topics for STEM Students - Explore the world of science, tech, engineering, and math with simplified, fascinating ideas.
199+ Engaging Quantitative Research Topics for STEM Students. March 20, 2024 by Rupam. Discover engaging quantitative research topics for STEM students, spanning energy solutions, medical advancements, and cutting-edge technology. Explore hands-on ideas to sharpen skills and make a tangible impact on the future. Hey STEM buddy!
Scholar Launch has compiled a list of 11 compelling research ideas tailored for STEM students: . Topic 1: Artificial Intelligence (AI) AI stands at the forefront of technological innovation. Students can engage in research on AI applications in various sectors and the ethical implications of AI. This field is suitable for students with ...
Here are 8 key points on how to do experimental research effectively. 1. Clear Research Focus. Begin by defining a clear and focused research question. A well-defined question provides a purpose and direction for your experiment, guiding your choices in variables and methodology. 2.
Quantitative research involves collecting and analyzing numerical data to identify patterns, trends, and relationships among variables. This method is widely used in social sciences, psychology, economics, and other fields where researchers aim to understand human behavior and phenomena through statistical analysis.
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 ...
Trending Topic Research File. Science, Technology Engineering, and Mathematics (STEM) is one of the most talked about topics in education, emphasizing research, problem solving, critical thinking, and creativity. The following compendium of open-access articles are inclusive of all substantive AERA journal content regarding STEM published since ...
Here are the top quantitative research topics for STEM students in the Philippines in 2024. 1. Impact of Climate Change on Farming. Analyze how changing weather affects the growth of crops like rice and corn in different parts of the Philippines. Use numbers to find ways and suggest ways farmers can adapt. 2.
Worldwide, STEM education, which integrates the disciplines of science, technology, engineering, and math, is gaining popularity in K-12 settings due to its capacity to enhance 21st-century skills such as adaptability, problem-solving, and creative thinking (National Research Council [NRC], 2015).In STEM lessons, students are frequently guided by the engineering design process, which involves ...
Combination of Statistics and Biology? It will be easier if you already have specific parameters e.g. Correlational Analysis on the Efficiency of [METHOD] Teaching for Grade 12 Students in 2nd Semestral [STEM SUBJ] Final Grade Reports. In this way, possible topics for your research will come naturally and will be more appropriate depending on ...
We were having trouble picking out our quantitative research topics that must be related to stem. Some of our old title proposals were rejected because it was hard to quantify and required a diploma to do. We would like to do research that is a bit unique and doable for us students. Here are some of the title drafts we've thought of:
Currently I have these topics but my teacher suggested that we won't use "Academic Performance" because its too common. -stress levels of grade 12 students in online education -level of preparedness in making research of grade 12 students -The Effects of Online Learning on Senior High School Grade-12 STEM Student's Academic Performance ...
The optional math bootcamp ahead of the program ensures all students have the opportunity to be fully prepared to succeed. Core courses. For the first half of the program, you'll take core courses in microeconomics, macroeconomics, and data science and econometrics, taught by leading economists with an extensive research record on these topics.
This article is part of the Research Topic Building the Future of Education Together: Innovation, Complexity, Sustainability, Interdisciplinary Research and Open Science View all 14 articles Financial literacy to develop complex thinking skills: quantitative measurement in Mexican women entrepreneurs
Since you are a STEM student (like me but Im already College), most experimental quanti researches I've read so far are alternatives of this and that (eg. Alternative for Cell Staining)... so take time to go to library and read existing research. Need help please, I made 5 proposals for the past weeks but all got rejected dahil either not STEM ...
A study co-authored by a researcher at Tulane University's A. B. Freeman School of Business has uncovered important insights into how individual investors' risk preferences influence their online trading behaviors and performance.. Yang Pan, assistant professor of management science, analyzed data from over 7,000 investor accounts at a major Chinese brokerage firm over a 44-month period from ...