A structural model of college students’ mathematics performance: the role of psychological, physiological, and psychosocial factors
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Published
Jul 31, 2024
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Bryan L. Susada
Abstract
The study aimed to find the best-fit structural model to describe the mathematics performance of freshmen secondary education students majoring in mathematics concerning psychological, physiological, and psychosocial factors. Psychological factors were measured in terms of self-efficacy and attitudes toward mathematics, while physiological factors were assessed about nutritional status, and wellness and well-being. Psychosocial factors were measured in terms of math anxiety and math interest. A questionnaire was administered to 312 randomly selected mathematics teacher education students who have experienced struggles in their board examination performance. These students came from various higher education institutions in the Davao and the SOCCSKSARGEN (South Cotabato, Cotabato, Sultan Kudarat, Sarangani and General Santos City) regions. The validity and reliability of the questionnaire were established through factor analysis and an internal reliability test, respectively. The findings indicate that students exhibit strong performance in mathematics, possess moderate levels of psychological and psychosocial competencies, and maintain relatively healthy physiological statuses. Additionally, the results reveal a structural model depicting students' mathematics performance with psychological, physiological, and psychosocial factors, which can explain 78% of the data considered in the study. Higher educational institutions may enhance support for students' psychological and psychosocial skills and integrate health and wellness programs to boost their physiological status, given its impact on academic performance. Further research is encouraged to explore additional factors affecting academic success, aiming to develop a more comprehensive understanding of influences on students' performance.
How to Cite
Susada BL. 2024. A structural model of college students’ mathematics performance: the role of psychological, physiological, and psychosocial factors. The Palawan Scientist. 17(1):10–19. https://doi.org/10.69721/TPS.J.2025.17.1.02.
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Keywords
bioecological model of development, ecological system theory, structural equation modeling
References
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Bacsal ED, Ibañez ED and Pentang JT. 2022. Jigsaw strategy: strengthening achievement and interest in mathematics among elementary pre-service teachers. The Palawan Scientist, 14(1): 35-42.
Baker SR. 2004. Intrinsic, extrinsic, and motivational orientations: their role in university adjustment, stress, well-being, and subsequent academic performance. Current Psychology, 23(3): 189-202. https://doi.org/10.1007/s12144-004-1019-9
Bakker A, Cai J and Zenger L. 2021. Future themes of mathematics education research: an international survey before and during the pandemic. Educational Studies in Mathematics, 107(1): 1-24. https://doi.org/10.1007/s10649-021-10049-w
Bandura A. 1997. Self efficacy: The exercise of control. New York: Freemanand Company. 522pp.
Banerjee PA. 2016. A systematic review of factors linked to poor academic performance of disadvantaged students in science and maths in schools. Cogent Education, 3(1): 1-17. https://doi.org/10.1080/2331186X.2016.1178441
Beilock SL, Gunderson EA, Ramirez G and Levine SC. 2010. Female teachers’ math anxiety affects girls’ math achievement. Proceedings of the National Academy of Sciences, 107(5): 1860-1863. https://doi.org/10.1073/pnas.0910967107
Bernardo ABI. 2021. Socioeconomic status moderates the relationship between growth mindset and learning in mathematics and science: evidence from Programme for International Student Achievement 2018 Philippine data. International Journal of School and Educational Psychology, 9(2): 208-222. https://doi.org/10.1080/21683603.2020.1832635
Breslow L, Pritchard DE, DeBoer J, Stump GS, Ho AD and Seaton DT. 2013. Studying learning in the worldwide classroom research into edX's first Massive Open Online Courses. Research and Practice in Assessment, 8(1): 13-25.
Bronfenbrenner U. 1979. The ecology of human development: Experiments by nature and design. Harvard University Press.
Bronfenbrenner U and Ceci SJ. 1994. Nature-nurture reconceptualized in developmental perspective: A bioecological model. Psychological Review, 101(4): 568-586.
CHED (Commission on Higher Education). 2017. Policies, standards and guidelines for bachelor of secondary education. https://ched.gov.ph/wp-content/uploads/2017/11/CMO-No.-75-s.-2017.pdf. Accessed on 21 March 2024
Di Martino P and Zan R. 2011. Attitude towards mathematics: a bridge between beliefs and emotions. ZDM Mathematics Education, 43(4): 471-482. https://doi.org/10.1007/s11858-011-0309-6
Drigas AS and Pappas MA. 2015. On line and other game-based learning for mathematics. International Journal of Online Engineering, 11(4): 62-67. http://dx.doi.org/10.3991/ijoe.v11i4.4742
Florence MD, Asbridge M and Veugelers PJ. 2008. Diet quality and academic performance. Journal of School Health, 78(4): 209-215. https://doi.org/10.1111/j.1746-1561.2008.00288.x
Gabasa MG and Raqueño AR. 2021. Predicting performance of graduates in the licensure examination through path analysis toward curriculum improvement. International Journal of Advance Study and Research Work, 4(1): 11-19.
https://doi.org/10.5281/zenodo.4459829
Ghrouz AK, Noohu MM, Dilshad MM, Warren DS, BaHammam AS and Pandi SRP. 2019. Physical activity and sleep quality in relation to mental health among college students. Sleep and Breathing, 23(1): 627-634. https://doi.org/10.1007/s11325-019-01780-z
Hauge KH and Barwell R. 2017. Post-normal science and mathematics education in uncertain times: educating future citizens for extended peer communities. Futures, 91(1): 25-34. https://doi.org/10.1016/j.futures.2016.11.013
Hill F, Mammarella IC, Devine A, Caviola S, Passolunghi MC and Szűcs D. 2016. Maths anxiety in primary and secondary school students: gender differences, developmental changes and anxiety specificity. Learning and Individual Differences, 48(1): 45-53. https://doi.org/10.1016/j.lindif.2016.02.006
Jett CC. 2019. Mathematical persistence among four African American male graduate students: a critical race analysis of their experiences. Journal for Research in Mathematics Education, 50(3): 31-40. https://doi.org/10.5951/jresematheduc.50.3.0311
Kerr JQ, Hess DJ, Smith CM and Hadfield MG. 2018. Recognizing and reducing barriers to science and math education and science, technology, engineering, and mathematics careers for native Hawaiians and Pacific Islanders. Cell Biology Education Life Sciences Education, 17(4): 1-10. https://doi.org/10.1187/cbe.18-06-0091
Kline RB. 2015. Principles and Practice of Structural Equation Modeling (4th ed.). New York: Guilford Press. 14pp.
Lodico MG, Spaulding DT and Voegtle KH. 2010. Methods in Educational Research: From Theory to Practice. Jossey Bass: A Wiley Imprint, San Francisco, California, USA. 155pp.
Lubans DR, Smith JJ, Morgan PJ, Beauchamp MR, Miller A, Lonsdale C, Parker P and Dally K. 2016. Mediators of psychological well-being in adolescent boys. Journal of Adolescent Health, 58(2): 230-236. https://doi.org/10.1016/j.jadohealth.2015.10.010
Marsigliante S, Gómez ML and Muscella A. 2023. A. Effects on children’s physical and mental well-being of a physical-activity-based school intervention program: a randomized study. International Journal of Environmental Research and Public Health, 20(3): 1-16. https://doi.org/10.3390/ijerph20031927
National Science Foundation. 2013. Mathematics Education. https://www.nsf.gov/funding/pgm_list.jsp?org=DRL&ord=rcnt. Accessed on 01 March 2024.
OECD (Organization for Economic Cooperation and Development). 2016. What is PISA. https://www.oecd.org/pisa/. Accessed on 01 March 2024
Orale RL and Uy MEA. 2018. When the spiral is broken: problem analysis in the implementation of spiral progression approach in teaching mathematics. Journal of Academic Research, 3(3): 14-24.
Pantolla HG, Bunag ES and Padilla CM. 2016. Likelihood estimation of passing the Licensure Examination for Teachers (LET) using multivariate method. Journal of International Scholars Conference-Education/Social Sciences, 1(2): 174-184.
PISA (Programme for International Student Assessment). 2022. PISA results 2022. https://www.oecd.org/publication/pisa-2022-results/ . Accessed on 01 March 2024
PRC (Professional Regulatory Commission). 2022. Licensure Examination for Teachers – Secondary Level of March 2022 result. https://drive.google.com/file/d/15eudAovkSCKUQZyTKp94kMLKSnDPi2-h/view. Accessed on 21 March 2024
Renninger KA and Hidi S. 2011. The power of interest for motivation and engagement. Routledge. 64pp. https://doi.org/10.4324/9781315771045
Robertson T, Benzeval M, Whitley E and Popham F. 2015. The role of material, psychosocial and behavioral factors in mediating the association between socioeconomic position and allostatic load (measured by cardiovascular, metabolic and inflammatory markers). Brain, Behavior, and Immunity, 45(1): 41-49. https://doi.org/10.1016/j.bbi.2014.10.005
Schunk DH. 1995. Self-efficacy and education and instruction. In: Maddux JE (ed). self-Efficacy, adaptation, and adjustment. The Plenum Series in Social/Clinical Psychology. New York, NY: Plenum Press, pp. 281. https://doi.org/10.1007/978-1-4419-6868-5_10
Slaughter JB, Tao Y and Pearson Jr W (eds). 2015. Changing the face of engineering: the African American experience. Johns Hopkins University Press. 165pp.
Susada BL. 2018. A students' preference on mathematics classroom using conjoint analysis. Asian Journal of Multidisciplinary Studies, 1(1): 87-95.
Susada BL and Baquiano MJ. 2015. Social representations of mathematics. Transcendence Research Journal, 1(1): 20-25.
Thomson S, De Bortoli L, Underwood C and Schmid M. 2019. Programme for International Student Achievement 2018: Reporting Australia’s results. Volume I student performance. https://research.acer.edu.au/ozpisa/35/. Accessed on 01 March 2023.
TIMSS (Trends in International Mathematics and Science Study in the United States of America). 2019. TIMSS 2019 U.S. Highlights Web Report. https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2021021. Accessed on 01 March 2023
Waller E. 2014. The price of love: the selected works of Colin Murray Parkes. Routledge Taylor and Francis Group, New York, USA, pp. 90-104. https://doi.org/10.1177/00302228166423
Wang X. 2013. Why students choose STEM majors: motivation, high school learning, and postsecondary context of support. American Educational Research Journal, 50(5): 1081-1121. https://doi.org/10.3102/0002831213488622
Wang Z, Lukowski SL, Hart SA, Lyons IM, Thompson LA, Kovas Y and Petrill SA. 2015. Is math anxiety always bad for math learning? The role of math motivation. Psychological Science, 26(12): 1863-1876. https://doi.org/10.1177/0956797615602471
Zhang J, Zhao N and Kong QP. 2019. The relationship between math anxiety and math performance: a meta-analytic investigation. Frontiers in Psychology, 10(1): 1-17. https://doi.org/10.3389/fpsyg.2019.01613
Zientek LR, Fong CJ and Phelps JM. 2019. Sources of self-efficacy of community college students enrolled in developmental mathematics. Journal of Further and Higher Education, 43(2): 183-200. https://doi.org/10.1080/0309877X.2017.1357071
Zimmerman BJ. 2000. Self-efficacy: an essential motive to learn. Contemporary Educational Psychology, 25(1): 82-91. https://doi.org/10.1006/ceps.1999.1016
Amanonce JCT and Maramag AM. 2020. Licensure examination performance and academic achievement of teacher education graduates. International Journal of Evaluation and Research in Education, 9(3): 510-516. https://doi.org/10.11591/ijere.v9i3.20614
Bacsal ED, Ibañez ED and Pentang JT. 2022. Jigsaw strategy: strengthening achievement and interest in mathematics among elementary pre-service teachers. The Palawan Scientist, 14(1): 35-42.
Baker SR. 2004. Intrinsic, extrinsic, and motivational orientations: their role in university adjustment, stress, well-being, and subsequent academic performance. Current Psychology, 23(3): 189-202. https://doi.org/10.1007/s12144-004-1019-9
Bakker A, Cai J and Zenger L. 2021. Future themes of mathematics education research: an international survey before and during the pandemic. Educational Studies in Mathematics, 107(1): 1-24. https://doi.org/10.1007/s10649-021-10049-w
Bandura A. 1997. Self efficacy: The exercise of control. New York: Freemanand Company. 522pp.
Banerjee PA. 2016. A systematic review of factors linked to poor academic performance of disadvantaged students in science and maths in schools. Cogent Education, 3(1): 1-17. https://doi.org/10.1080/2331186X.2016.1178441
Beilock SL, Gunderson EA, Ramirez G and Levine SC. 2010. Female teachers’ math anxiety affects girls’ math achievement. Proceedings of the National Academy of Sciences, 107(5): 1860-1863. https://doi.org/10.1073/pnas.0910967107
Bernardo ABI. 2021. Socioeconomic status moderates the relationship between growth mindset and learning in mathematics and science: evidence from Programme for International Student Achievement 2018 Philippine data. International Journal of School and Educational Psychology, 9(2): 208-222. https://doi.org/10.1080/21683603.2020.1832635
Breslow L, Pritchard DE, DeBoer J, Stump GS, Ho AD and Seaton DT. 2013. Studying learning in the worldwide classroom research into edX's first Massive Open Online Courses. Research and Practice in Assessment, 8(1): 13-25.
Bronfenbrenner U. 1979. The ecology of human development: Experiments by nature and design. Harvard University Press.
Bronfenbrenner U and Ceci SJ. 1994. Nature-nurture reconceptualized in developmental perspective: A bioecological model. Psychological Review, 101(4): 568-586.
CHED (Commission on Higher Education). 2017. Policies, standards and guidelines for bachelor of secondary education. https://ched.gov.ph/wp-content/uploads/2017/11/CMO-No.-75-s.-2017.pdf. Accessed on 21 March 2024
Di Martino P and Zan R. 2011. Attitude towards mathematics: a bridge between beliefs and emotions. ZDM Mathematics Education, 43(4): 471-482. https://doi.org/10.1007/s11858-011-0309-6
Drigas AS and Pappas MA. 2015. On line and other game-based learning for mathematics. International Journal of Online Engineering, 11(4): 62-67. http://dx.doi.org/10.3991/ijoe.v11i4.4742
Florence MD, Asbridge M and Veugelers PJ. 2008. Diet quality and academic performance. Journal of School Health, 78(4): 209-215. https://doi.org/10.1111/j.1746-1561.2008.00288.x
Gabasa MG and Raqueño AR. 2021. Predicting performance of graduates in the licensure examination through path analysis toward curriculum improvement. International Journal of Advance Study and Research Work, 4(1): 11-19.
https://doi.org/10.5281/zenodo.4459829
Ghrouz AK, Noohu MM, Dilshad MM, Warren DS, BaHammam AS and Pandi SRP. 2019. Physical activity and sleep quality in relation to mental health among college students. Sleep and Breathing, 23(1): 627-634. https://doi.org/10.1007/s11325-019-01780-z
Hauge KH and Barwell R. 2017. Post-normal science and mathematics education in uncertain times: educating future citizens for extended peer communities. Futures, 91(1): 25-34. https://doi.org/10.1016/j.futures.2016.11.013
Hill F, Mammarella IC, Devine A, Caviola S, Passolunghi MC and Szűcs D. 2016. Maths anxiety in primary and secondary school students: gender differences, developmental changes and anxiety specificity. Learning and Individual Differences, 48(1): 45-53. https://doi.org/10.1016/j.lindif.2016.02.006
Jett CC. 2019. Mathematical persistence among four African American male graduate students: a critical race analysis of their experiences. Journal for Research in Mathematics Education, 50(3): 31-40. https://doi.org/10.5951/jresematheduc.50.3.0311
Kerr JQ, Hess DJ, Smith CM and Hadfield MG. 2018. Recognizing and reducing barriers to science and math education and science, technology, engineering, and mathematics careers for native Hawaiians and Pacific Islanders. Cell Biology Education Life Sciences Education, 17(4): 1-10. https://doi.org/10.1187/cbe.18-06-0091
Kline RB. 2015. Principles and Practice of Structural Equation Modeling (4th ed.). New York: Guilford Press. 14pp.
Lodico MG, Spaulding DT and Voegtle KH. 2010. Methods in Educational Research: From Theory to Practice. Jossey Bass: A Wiley Imprint, San Francisco, California, USA. 155pp.
Lubans DR, Smith JJ, Morgan PJ, Beauchamp MR, Miller A, Lonsdale C, Parker P and Dally K. 2016. Mediators of psychological well-being in adolescent boys. Journal of Adolescent Health, 58(2): 230-236. https://doi.org/10.1016/j.jadohealth.2015.10.010
Marsigliante S, Gómez ML and Muscella A. 2023. A. Effects on children’s physical and mental well-being of a physical-activity-based school intervention program: a randomized study. International Journal of Environmental Research and Public Health, 20(3): 1-16. https://doi.org/10.3390/ijerph20031927
National Science Foundation. 2013. Mathematics Education. https://www.nsf.gov/funding/pgm_list.jsp?org=DRL&ord=rcnt. Accessed on 01 March 2024.
OECD (Organization for Economic Cooperation and Development). 2016. What is PISA. https://www.oecd.org/pisa/. Accessed on 01 March 2024
Orale RL and Uy MEA. 2018. When the spiral is broken: problem analysis in the implementation of spiral progression approach in teaching mathematics. Journal of Academic Research, 3(3): 14-24.
Pantolla HG, Bunag ES and Padilla CM. 2016. Likelihood estimation of passing the Licensure Examination for Teachers (LET) using multivariate method. Journal of International Scholars Conference-Education/Social Sciences, 1(2): 174-184.
PISA (Programme for International Student Assessment). 2022. PISA results 2022. https://www.oecd.org/publication/pisa-2022-results/ . Accessed on 01 March 2024
PRC (Professional Regulatory Commission). 2022. Licensure Examination for Teachers – Secondary Level of March 2022 result. https://drive.google.com/file/d/15eudAovkSCKUQZyTKp94kMLKSnDPi2-h/view. Accessed on 21 March 2024
Renninger KA and Hidi S. 2011. The power of interest for motivation and engagement. Routledge. 64pp. https://doi.org/10.4324/9781315771045
Robertson T, Benzeval M, Whitley E and Popham F. 2015. The role of material, psychosocial and behavioral factors in mediating the association between socioeconomic position and allostatic load (measured by cardiovascular, metabolic and inflammatory markers). Brain, Behavior, and Immunity, 45(1): 41-49. https://doi.org/10.1016/j.bbi.2014.10.005
Schunk DH. 1995. Self-efficacy and education and instruction. In: Maddux JE (ed). self-Efficacy, adaptation, and adjustment. The Plenum Series in Social/Clinical Psychology. New York, NY: Plenum Press, pp. 281. https://doi.org/10.1007/978-1-4419-6868-5_10
Slaughter JB, Tao Y and Pearson Jr W (eds). 2015. Changing the face of engineering: the African American experience. Johns Hopkins University Press. 165pp.
Susada BL. 2018. A students' preference on mathematics classroom using conjoint analysis. Asian Journal of Multidisciplinary Studies, 1(1): 87-95.
Susada BL and Baquiano MJ. 2015. Social representations of mathematics. Transcendence Research Journal, 1(1): 20-25.
Thomson S, De Bortoli L, Underwood C and Schmid M. 2019. Programme for International Student Achievement 2018: Reporting Australia’s results. Volume I student performance. https://research.acer.edu.au/ozpisa/35/. Accessed on 01 March 2023.
TIMSS (Trends in International Mathematics and Science Study in the United States of America). 2019. TIMSS 2019 U.S. Highlights Web Report. https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2021021. Accessed on 01 March 2023
Waller E. 2014. The price of love: the selected works of Colin Murray Parkes. Routledge Taylor and Francis Group, New York, USA, pp. 90-104. https://doi.org/10.1177/00302228166423
Wang X. 2013. Why students choose STEM majors: motivation, high school learning, and postsecondary context of support. American Educational Research Journal, 50(5): 1081-1121. https://doi.org/10.3102/0002831213488622
Wang Z, Lukowski SL, Hart SA, Lyons IM, Thompson LA, Kovas Y and Petrill SA. 2015. Is math anxiety always bad for math learning? The role of math motivation. Psychological Science, 26(12): 1863-1876. https://doi.org/10.1177/0956797615602471
Zhang J, Zhao N and Kong QP. 2019. The relationship between math anxiety and math performance: a meta-analytic investigation. Frontiers in Psychology, 10(1): 1-17. https://doi.org/10.3389/fpsyg.2019.01613
Zientek LR, Fong CJ and Phelps JM. 2019. Sources of self-efficacy of community college students enrolled in developmental mathematics. Journal of Further and Higher Education, 43(2): 183-200. https://doi.org/10.1080/0309877X.2017.1357071
Zimmerman BJ. 2000. Self-efficacy: an essential motive to learn. Contemporary Educational Psychology, 25(1): 82-91. https://doi.org/10.1006/ceps.1999.1016
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