ISSN: 2222-6990
Open access
This study presents a comprehensive bibliometric and systematic review of research examining the relationship between Social Cognitive Theory (SCT) and learning mathematics over the past decade. Drawing upon Bandura’s foundational work on sociocognitive mechanisms particularly self-efficacy, observational learning, and reciprocal determinism (Bandura, 1986, 1997) the review investigates how SCT has shaped contemporary mathematics education research. Using the Scopus database (search date: 21 October 2025) and guided by the PRISMA framework (Page et al., 2020), an initial dataset of 552 records was systematically filtered through predefined inclusion and exclusion criteria. Eighteen empirical and theoretical studies were ultimately included for in-depth analysis. The bibliometric results reveal three major trends. First, publication activity increased steadily from 2015 and peaked in 2021, reflecting heightened global interest in sociocognitive dimensions of mathematics learning during and after the COVID-19 pandemic (Bozkurt & Sharma, 2020). Second, influential authors including Robert W. Lent, Matthew J. Miller, Hungbin Sheu, and Yehudit Judy Dori played a central role in advancing SCT and Social Cognitive Career Theory (SCCT), particularly in areas related to mathematics self-efficacy, STEM engagement, and academic persistence (Lent, Brown, & Hackett, 1994; Sheu & Lent, 2013). Third, the most productive institutions and countries led by the United States, Israel, the United Kingdom, Australia, China, and Malaysia serve as global hubs for SCT-based STEM and mathematics education research. Keyword co-occurrence analysis using VOSviewer demonstrates that core constructs such as self-efficacy, students, mathematics, STEM education, career choice, technology, and motivation dominate the conceptual landscape. These clusters highlight the continued relevance of SCT in explaining mathematical learning processes, cognitive regulation, and students’ academic decision-making. The results underscore that SCT remains a robust and widely adopted theoretical framework for understanding how personal beliefs, environmental influences, and learning experiences interact to shape mathematics achievement and STEM career pathways. Overall, this review contributes to the field by mapping the intellectual structure, thematic directions, and global research patterns connecting SCT with mathematics learning. The study also identifies implications for future research, educational practice, and policy development particularly the need to strengthen self-efficacy interventions, integrate SCT with technology enhanced learning environments, and support underrepresented groups in mathematics-related pathways.
Abe, E., Chikoko, V., & Lubinga, S. N. (2021). The link between career outcomes expectancy and career decision-making self-efficacy of STEM students in a South African university.
Abe, E. N., & Chikoko, V. (2020). Exploring the factors that influence the career decision of STEM students at a university in South Africa. International Journal of STEM Education, 7(1), 60.?
?Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, 1986(23-28), 2.?
Bandura, A. (1997). Self-efficacy: The exercise of control. Macmillan.?
Bennett, D., Knight, E., Dockery, A. M., & Bawa, S. (2020). Pedagogies for employability: Understanding the needs of STEM students through a new approach to employability development. Higher Education Pedagogies, 5(1), 340-359.?
Bozkurt, A., & Sharma, R. C. (2020). Emergency remote teaching in a time of global crisis due to CoronaVirus pandemic. Asian journal of distance education, 15(1), i-vi.
?Byars?Winston, A. (2014). Toward a framework for multicultural STEM?focused career interventions. The Career development quarterly, 62(4), 340-357.?
Campbell, T., & Sears, H. (2024). Analyzing elementary students’ access to cognitive-oriented positions in mathematics. International Electronic Journal of Mathematics Education, 19(1), em0769.?
Capone, R. (2022). Blended learning and student-centered active learning environment: A case study with STEM undergraduate students. Canadian Journal of Science, Mathematics and Technology Education, 22(1), 210-236.?
Dori, Y. J., & Belcher, J. (2005). How does technology-enabled active learning affect undergraduate students' understanding of electromagnetism concepts?. The journal of the learning sciences, 14(2), 243-279.?
Ekmekci, A., & Serrano, D. M. (2022). The impact of teacher quality on student motivation, achievement, and persistence in science and mathematics. Education Sciences, 12(10), 649.?
Garrison, D. R., & Vaughan, N. D. (2023). Blended learning in higher education: Framework, principles, and guidelines. John Wiley & Sons.?
Guo, C., Wu, W., Hu, T., & Gao, T. (2025). Unequal access, equal outcomes? Gender differences in the relationship between university-led STEM program factors and undergraduates' career commitment in STEM. International Journal of STEM Education, 12(1), 46.?
?Henrikson, R., & Lumpe, A. (2021). Implementation of a pilot elementary mathematics specialist endorsement program. Education Sciences, 11(3), 93.?
Hidayat, R., Nasir, N., Fadzli, S. A. M., Rusli, N. S., Kamaruzzaman, N. N., Sheng, V. Y. Z., ... & Shukeri, A. S. (2023). Peer tutoring learning strategies in mathematics subjects: Systematic literature review. European Journal of Educational Research, 12(3), 1407-1423.?
Holmes, W. (2022). Artificial intelligence in education. In Encyclopedia of education and information technologies (pp. 88-103). Cham: Springer International Publishing.
Huang, R., Liu, D., Tlili, A., Knyazeva, S., Chang, T. W., Zhang, X., ... & Holotescu, C. (2020). Guidance on open educational practices during school closures: Utilizing OER under COVID-19 pandemic in line with UNESCO OER recommendation. Beijing: Smart Learning Institute of Beijing Normal University, 1-80.?
Jaime, M. F. Z., Cupani, M., & de Mier, M. V. (2015). Evaluation of the performance model of Social Cognitive Theory of Career: contributions of differential learning experiences. Bordón: Revista de pedagogía, 67(4), 153-170.?
Lent, R. W., Brown, S. D., & Hackett, G. (1994). Toward a unifying social cognitive theory of career and academic interest, choice, and performance. Journal of vocational behavior, 45(1), 79-122.?
Lent, R. W., Sheu, H. B., Miller, M. J., Cusick, M. E., Penn, L. T., & Truong, N. N. (2013). Predictors of science, technology, engineering, and mathematics choice options: A meta-analytic path analysis of the social–cognitive choice model by gender and race/ethnicity. Journal of counseling psychology, 65(1), 17.?
Mitsopoulou, A. G., & Pavlatou, E. A. (2021). Factors associated with the development of secondary school students’ interest towards STEM studies. Education Sciences, 11(11), 746.?
Mozahem, N. A., Boulad, F. M., & Ghanem, C. M. (2021). Secondary school students and self-efficacy in mathematics: Gender and age differences. International Journal of School & Educational Psychology, 9(sup1), S142-S152.?
Murtianto, Y. H., Retnowati, E., & Hanham, J. (2025). Reducing cognitive load using social persuasion prompts in mathematics multimedia learning. Mathematics Education Journal, 19(3), 465-488.?
Olaitan, O., & Mavuso, N. (2022). Investigating the challenges faced by female students in STEM courses: case study of a traditional South African University. Perspectives in Education, 40(4), 19-37.?
Ozyazici, G., Wang, Q., & Tillotson, J. W. (2025). Promoting Entrepreneurial Career Development in STEM: Developing and Validating a STEM Entrepreneurial Career Development Measure (SECDM). Journal of Science Education and Technology, 1-15.?
Pajares, F., & Miller, M. D. (1994). Role of self-efficacy and self-concept beliefs in mathematical problem solving: A path analysis. Journal of educational psychology, 86(2), 193.?
Polo-Blanco, I., Suárez-Pinilla, P., Goñi-Cervera, J., Suárez-Pinilla, M., & Payá, B. (2024). Comparison of mathematics problem-solving abilities in autistic and non-autistic children: The influence of cognitive profile. Journal of Autism and Developmental Disorders, 54(1), 353-365.?
Reindl, M., Gniewosz, B., & Dresel, M. (2021). Friends’ influence on the development of academic values in mathematics: are there differences between female and male dyads?. European Journal of Psychology of Education, 36(3), 781-797.?
Santos, P., El Aadmi, K., Calvera-Isabal, M., & Rodríguez, A. (2025). Fostering students’ motivation and self-efficacy in science, technology, engineering, and design through design thinking and making in project-based learning: a gender-perspective study in primary education. International Journal of Technology and Design Education, 1-27.?
Schunk, D. H., & Pajares, F. (2002). The development of academic self-efficacy. In Development of achievement motivation (pp. 15-31). Academic Press.?
Vogelsanger-Holenstein, M., Schukajlow, S., & Bruckmaier, G. (2025). Mathematical modelling and self-efficacy: immediate and long-lasting effects of teaching mathematical modelling with a solution plan. ZDM–Mathematics Education, 57(2), 489-502.?
Yang, Y., & Barth, J. M. (2017). AQ factor analysis approach to understanding female college students’ attitudes toward multiple STEM disciplines. Methodological Innovations, 10(3), 2059799117738704.?
Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemporary educational psychology, 25(1), 82-91.?
Aludhubi, K. H. S. J., Adnan, M. A. bin M., & Chehdimae, H. (2025). Social cognitive theory and its relationship to learning mathematics: A Bibliometric Analysis. International Journal of Academic Research in Business and Social Sciences, 15(12), 147–167.
Copyright: © 2025 The Author(s)
Published by HRMARS (www.hrmars.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode