Reducing attrition among biology undergraduates requires a holistic understanding of students’ academic, motivational, and socioemotional experiences. Guided by Bandura’s model of triadic reciprocity, this study employed an unsupervised K-medoids clustering algorithm to examine patterns of personal, behavioral, and environmental influences among biology students who persisted in the major and those who switched out within one semester of declaring the major at a large Minority-Serving Institution in the United States. The analysis incorporated multidimensional data capturing personal influences (science identity, mathematics motivation, self-efficacy, and grit), behavioral influences (help-seeking behaviors and career goals), and environmental influences (mathematics anxiety and academic stress). Several models incorporating these three domains identified more students at risk of switching than models using traditional academic admissions indicators alone. Findings highlight the value of integrating student-reported experiences with institutional data to inform early, targeted interventions that support persistence in biology.
The present study examines action orientation and achievement goal orientations as psychological resources for students’ subjective expectations of academic success in computer science degree programs in higher education. Drawing on a positive psychology perspective, volitional self-regulation processes are conceptualized as key personal resources that support motivation, persistence, and academic success in demanding study contexts. We utilize the theory of volitional action control and achievement goal theory, focusing on two volitional domains—prospective action orientation (maintenance and implementation of intentions) and action orientation following failure (adaptive emotional processing of setbacks)—as well as mastery and performance goal orientations. These characteristics are understood as developable strengths that may be particularly relevant in competitive and gender-segregated STEM environments. Empirically, the study is based on a survey of first-year computer science students at two German universities (N = 174). Separate binary logistic regression analyses for female and male students examined associations between volitional resources and two subjective indicators of academic success: study satisfaction and the subjectively perceived likelihood of degree completion. Gender was conceptualized as an analytical differentiation perspective rather than a causal predictor. The findings reveal distinct patterns across gender groups, indicating that volitional self-regulation processes relate differently to students’ subjective academic success evaluations for female and male students. Overall, the study contributes to positive psychology–informed higher education research by highlighting the relevance of gender-sensitive, strength-based approaches in STEM degree programs.
STEM education has emerged as a rapidly expanding academic field in the twenty-first century. As scholarly publications have proliferated, the field has evolved from an acronym initially used primarily as a descriptive label into a distinct area of scholarship with its own academic identity. In this editorial, we first provide an overview of the journal's development and performance over the years. We then extend the discussion to examine the evolving identity of STEM education through the contributions of diverse publication outlets and explore the field's development across multiple dimensions, including research advancement, scholarly communication, and journal development.
This study investigated the effects of AR-supported geometry learning integrated with the 5E instructional model on primary school students’ geometric thinking skills, academic achievement, and mathematics anxiety. Conducted with 62 students (31 in the experimental group and 31 in the control group), the study employed an embedded mixed-methods design. The findings revealed that students who participated in the AR-supported 5E geometry learning intervention demonstrated significantly greater improvement in geometric thinking skills and higher academic achievement than those in the control group. The intervention appeared to facilitate students’ understanding of abstract geometric concepts by providing interactive and visual representations. Although mathematics anxiety decreased over time in both groups, the reduction was not significantly greater in the experimental group. Qualitative findings complemented the quantitative results by showing that students found the learning process enjoyable and motivating, which enhanced their engagement and active participation. Students also reported that the activities improved their visualization of geometric objects and supported conceptual understanding. Overall, the findings suggest that integrating AR-supported geometry learning with the 5E instructional model can enhance students’ geometric thinking skills and academic achievement while providing an engaging learning experience. The implications of these findings for primary school geometry instruction are discussed.
In the last thirty years, student engagement has received attention as a critical contributor to students’ school success. Given the positive links between engagement and academic outcomes, it is critical to understand antecedents of student engagement. Guided by Situated Expectancy-Value Theory (SEVT), this study examined how competence-related beliefs, task values (attainment, intrinsic, and utility values), and cost perceptions (task effort, outside effort, loss of valued alternatives, and emotional cost) were associated with five dimensions of engagement — behavioral, cognitive, emotional, social, and agentic—over two time points in undergraduate introductory math and science courses. Path analyses with motivation constructs at time one predicting engagement dimensions at time two (N = 247) revealed that while competence-related beliefs were primarily associated with cognitive and emotional engagement, task values were significantly associated with behavioral, cognitive, emotional, social, and agentic engagement. Notably, when evaluated independently, different facets of cost exhibited both positive and negative associations with various engagement dimensions. The findings underscore the complex relationships between motivational constructs and engagement dimensions in STEM education. The study highlights the need for tailored motivational strategies to enhance student engagement in introductory math and science courses.
Engineering problems have long been integral to classroom instruction, serving as essential tools for educational development. However, the generation of these problems has remained constant over the years. The advent of Generative Artificial Intelligence (Gen-AI) offers a new opportunity to enhance problem generation in engineering. In this paper, we introduce an innovative approach that leverages the unique capabilities of Gen-AI to redefine how mechanical engineering problems are generated. Using a mixed-method research design, we explore students’ performance, preferences, mental workload, and emotional responses across various problem sources from the manufacturing domain in mechanical engineering, specifically traditional textbook-based problems and Gen-AI-generated problems. The findings of this research reveal significant impacts of Gen-AI-generated problems on student output towards the problems. Preliminary insights from this research contribute to advancing engineering pedagogy by demonstrating Gen-AI’s potential to transform traditional problem generation methods and enrich students’ learning experiences.
Undergraduate participation in university-led research continues to grow, offering significant educational benefits. However, access to research opportunities often remains part of the hidden curriculum, with limited guidance on how to join a lab. Our study supports this observation and introduces an intervention designed to help incoming undergraduates leverage both their assets and institutional resources to engage in research. We analyzed institutional data on undergraduate research enrollment, identified common barriers students face, and assessed their progress toward joining research labs. Our findings show that most STEM (Science, Technology, Engineering, and Mathematics) undergraduates expect research to play a significant role in their careers and intend to participate; however, many lack clarity on how to initiate their research endeavors. Participation disparities were evident: PEER (Persons Excluded because of their Ethnicity and Race) students were less likely to engage in their first year, and first-generation students were less likely to participate in later years. The intervention designed to improve these disparities was well received, with over 50
This classroom-based experimental study investigated how learner choice and concept map format influence undergraduate students’ conceptual learning in an introductory chemistry course. While prior research has examined the effects of instructional choice on motivation and learning, little is known about how choice interacts with cognitively demanding tasks such as concept mapping in STEM settings. Grounded in Generative Learning Theory, Self-Determination Theory, and the ICAP Framework, we employed a 2 (choice vs. no-choice) × 3 (concept map format: translation, fill-in-the-blank, correction) factorial design, with perceived competence as a covariate. A total of 529 students completed concept map activities, followed by retention and transfer assessments. Results revealed significant main effects of both choice and concept map format on retention: students who selected their preferred activity achieved higher scores, and map translation format produced the strongest outcomes. For transfer, only concept map format yielded a significant effect, with map translation associated with the highest adjusted means, while choice alone did not influence transfer. These findings suggest that autonomy-supportive instructional design enhances retention when paired with cognitively demanding tasks, yet scaffolding may be necessary to extend benefits to knowledge transfer. Implications for the design of STEM instruction highlight the importance of aligning autonomy with competence-supportive, generative learning activities to foster deeper conceptual understanding.
The ability to work in a team is cited as a key outcome for many undergraduate Science, Technology, Engineering, and Mathematics (STEM) programs, both as a method for improving learning and as a highly desired trait for employers. Despite a growing focus on teamwork, our ability to design appropriate teamwork curriculum is limited by our poor understanding of what students arriving at university know about teamwork, what teamwork skills they consider themselves to possess, and their attitudes towards teamwork. We delivered a mixed-methods survey to first-year STEM undergraduate students (n = 205) to benchmark knowledge, skills and attitudes towards teamwork among students from different demographics. We observed strong internal consistency and measurement invariance across demographic groups, enabling comparisons by gender, race/ethnicity, first-generation status, Pell grant eligibility, and academic major. Students overwhelmingly self-reported as highly skilled at teamwork and as having positive attitudes. We observed very limited evidence for differences in self-reported knowledge, skills, or attitudes towards teamwork among demographic groups, including when we explicitly compared among intersectional identities. Given prior evidence of inequitable teamwork experiences reported by students from underrepresented identities, our findings point to potential limitations of current self-reporting instruments and support the development of more specific teamwork items that better inform curriculum choices.
Though much research has revealed the importance of competence-related and task value beliefs on career decision-making in science, technology, engineering, and math (STEM), it is not yet clear what motivational factors are most salient on adolescents’ minds as they consider pursuing STEM careers, particularly among those from historically marginalized gender and racial/ethnic groups. This qualitative study examined the salient motivational benefits and challenges of STEM careers perceived by Black and Hispanic high school girls and boys (n = 391), with attention to students’ intersecting gender and racial/ethnic group membership. By coding over 150 open-ended survey responses, we found that the most salient benefits students reported perceiving for STEM careers were related to task value beliefs, particularly utility value followed by attainment and intrinsic value. The most salient motivational challenges included high perceptions of cost and low competence-related beliefs in STEM. Findings also highlighted the importance of socializers in shaping students’ STEM career motivation. Gender and racial/ethnic group differences emerged, such that girls more often reported intrinsic value-related benefits than did boys. Additionally, relative to other groups, Hispanic girls more often and Black boys less often reported competence-related concerns. Insights for designing culturally responsive educational interventions and programming aimed at broadening STEM career participation are discussed.
The development of educational research has been accompanied by substantial growth in both publication output and the number of journals over recent decades. To better understand these changes, this study examines the evolution of journal inclusion and impact within the "Education Educational Research" category of Clarivate's Social Sciences Citation Index (SSCI). The analysis reveals a distinct trajectory in the field's development, characterized not only by expansion but also by shifting patterns of scholarly influence. In particular, the findings highlight the increasing visibility and impact of multidisciplinary and interdisciplinary research, especially in STEM education. These trends suggest a reorientation of high-impact educational scholarship toward areas aligned with technological innovation and global research priorities. The study concludes by discussing key implications and directions for future research.
This study examines patterns of teaching and research productivity among STEM faculty at a large public research university. Using eight indicators of research productivity and eight indicators of teaching productivity, we conducted a cluster analysis that identified three distinct productivity profiles among Research-Focused Faculty (RF), Teaching-Focused Faculty (TF), and Lecturers. These clusters reflect high, moderate, and low research productivity combined with varied levels of teaching activity. We then evaluated how faculty type, rank, gender, and discipline relate to membership in these clusters. The findings show that research and teaching productivity are not strongly correlated and that productivity patterns are shaped by faculty type and disciplinary context. RF in the high research cluster tended to have lighter lower division teaching responsibilities and stronger engagement in undergraduate research mentorship, while TF and Lecturers were more heavily concentrated in clusters with high teaching obligations. Gender was not a significant predictor of cluster membership once faculty type, rank, and discipline were included in the model, though this result should be interpreted with caution because important forms of academic labor were not captured in the available metrics. The study highlights the need for evaluation systems that recognize the varied contributions faculty make to teaching and research and provides a framework for understanding how institutional structures and disciplinary norms shape faculty productivity.
Student engagement in math and science courses decreases starting in middle school and continues throughout high school. This lack of engagement results in students taking only the required math and science coursework and not advanced coursework that would help prepare them for future careers in science, technology, engineering, and mathematics fields. Integrated STEM (Science, Technology, Engineering, Mathematics) learning activities may be used to promote student engagement and learning. This experimental design study was conducted with students in grades 3–5 in one mid-sized rural school district in the upper mid-west. Student engagement was analyzed using a pre/post-survey. Modeling analysis measured the extent to which lesson type, integrated STEM lesson or traditional non-integrated lesson, predicted student engagement. Additionally, we examined the extent to which engagement mediates the relationship between lesson type and student learning. Findings from this study indicate that integrated STEM learning activities increased student engagement, which may lead to students taking additional math and science courses in high school and pursuing a future in a high-demand STEM career.
Science interest is critical in creating a scientifically literate public. However, students’ science interest begins to wane early in their education and this study shares findings from an innovative intervention that aims to mitigate the decline in science interest. The intervention provides students with hands-on science experiences and the program effects are measured using a holistic set of measures that operationalize science interest, including students’ attitudes towards science, Epistemological Understanding of Science (EUS), perceptions of scientists (Draw-A-Scientist Test; DAST), and science identity. The measures indicated the program had the largest positive effect on students’ science attitudes, an affective measure of interest, and EUS, a cognitive measure of interest. With respect to gender, girls’ EUS scores were higher overall. Further, the program had the largest effect on 2nd graders’ science interest, suggesting that early elementary is a critical time for intervention.
Timely completion of Science, Technology, Engineering, and Mathematics (STEM) doctor of philosophy (PhD) programs has become a growing concern due to its implications for academic productivity, resource allocation, and workforce development. Consequently, researchers have investigated supervision quality, student motivation, academic culture, and regional challenges to doctoral progression. However, research examining how gender-related factors affect thesis completion experiences, particularly in STEM disciplines, remains limited. This study analyzed institutional data from 148 students (66.2
The “leaky pipeline” is the oft-used metaphor to characterize the loss of STEM students in the progression from high school through college and into the labor force. This view of STEM education—which posits a unidirectional flow out of STEM fields—is both pervasive and influential in K-12, higher education, and workforce development policy. But there has been limited empirical support for this claim that “leaving STEM” is unidirectional and reduces the size of the STEM cohort. This study analyzes two cohorts in nationally representative, longitudinal surveys of four-year college students to examine freshman-to-bachelor’s degree pathways. We find that although a third of STEM-intending freshmen leave STEM fields and graduate in non-STEM majors, the size of the STEM graduating class is larger than the freshmen STEM class in the two cohorts of bachelor’s degree graduates. STEM graduates in both cohorts are comprised of large shares of students who did not initially declare a STEM major: just under 20
Recruiting and retaining science, technology, engineering, and mathematics (STEM) college students is essential given the rising demand for professionals in these fields. Motivational climates in STEM labs, specifically caring and task-involving environments, may positively impact students’ college experiences. This study investigated whether perceptions of the motivational climate in biology labs impacted factors including students’ eagerness to attend lab, excitement for their major, preparation for future courses, belief in instructor support, and peer relationships. A total of 894 students completed end-of-semester surveys measuring their perceptions of their biology lab motivational climate and learner-related motivational outcomes. Analysis of variance (ANOVA) were used to compare caring versus non-caring and task-involving versus non-task-involving lab climates at individual and group levels. Most students reported moderately high caring and high task-involving climates and neutral adaptive learning responses. Individually, students perceiving both a caring and task-involving climate scored significantly higher across all outcomes. When grouped by section, outcome variables showed higher trends and some significant differences for the caring and task-involving groups. Findings highlight that perceptions of a caring, task-involving lab climate may enhance students’ learning experiences, potentially improving retention and graduation rates. Instructors play a pivotal role in fostering such climates, which can enhance STEM educational outcomes.
Mathematics anxiety can be debilitating. In this study, we tested the veracity of a structural equation model with self-regulation and mathematics self-efficacy on the dependent variable mathematics anxiety. Consideration was also given to the interaction effect of gender and enrolled in an entry-level STEM math course. These variables are relevant given gender differences in mathematics anxiety and perceived capabilities in STEM math courses. Findings from our study affirm the importance of self-efficacy and self-regulatory processes and may inform future strategies for reducing math anxiety. The inclusion of gender in this model might inform differentiated strategies for mitigating mathematics success.
Artificial intelligence (AI) has emerged as a prominent research focus in higher education. Despite increased interest, significant gaps remain in theory and knowledge, particularly regarding emerging factors such as self-efficacy (SE) and perceived trust (PT), and these gaps are especially pronounced among demographics like Gen Z. This study examines the adoption of AI technology among Gen Z university students, focusing on the influence of SE and PT. It also explores how gender, course major, and experience may moderate AI adoption. A total of 349 students were sampled, and the study employed an extended UTAUT, structural equation modelling, and multigroup analysis. This study has provided an improved and tested theoretical framework to enhance understanding of AI adoption in the field, with an R² value of 0.751. Behavioural Intention (BI) is influenced by SE, PT, and Perceived Expectancy (PE), with a diminishing role of Social Influence (SI), suggesting a more individualistic viewpoint among Gen Z, besides emphasising efficacy and trust in technology. Experience influences all the predictive factors, but its impact diminishes as experience increases, while gender has no impact on the adoption of AI. Additionally, the course major also influences the predictive effect. The findings imply that for the successful adoption of AI among Gen Z university students, universities, policymakers, and Big Tech should minimise the burden on efficacy and foster elements of trust, such as data security and privacy. However, the findings may also reflect Gen Z’s intention to adopt technology beyond the academic sphere.
Effective teamwork is crucial for the academic and professional success of STEM students. However, structured, theory-based frameworks to enhance teamwork skills remain limited. This study applies the Theory of Planned Behavior (TPB) to design and evaluate interventions that enhance attitudinal and motivational factors to facilitate the application of teamwork skills among engineering students. Forty-four students in two engineering courses participated in pre- and post-intervention self-assessments using an adapted TeamQ survey and qualitative feedback. Interventions targeted attitudes toward, subjective norms, and perceived behavioral control of teamwork in course projects. Quantitative results showed significant improvements in behavioral indicators of teamwork, including participation, communication, task management, and conflict resolution. Qualitative analysis using Latent Dirichlet Allocation, Non-negative Matrix Factorization, and sentiment analysis indicated increased focus on leadership, accountability, and positive perceptions, with a notable decline in negative sentiments, reflecting shifts in students’ expressed attitudes. Findings provide preliminary support for TPB-based interventions to foster teamwork skills and a structured framework for integrating such training into curricula. The study highlights the importance of addressing both technical and psychological factors to promote successful collaboration in engineering education, with potential implications for broader STEM contexts.
