Logistic Regression in Analyzing the Determinants of University Students' Mathematics Performance
Abstract
Mathematics provides an effective way of building mental discipline, encourages logical reasoning, and plays a crucial role in understanding the contents of other subjects. Mathematics performance is affected by several factors including grade, social economic status, background and many more. The aim of this study is to investigate the factors which are related to students’ mathematics performance and to identify the significant factors which affect the students’ mathematics performance of MAT133 course. This study was conducted in UiTM Negeri Sembilan, Kuala Pilah campus. 480 students were selected from various programs who had registered Pre-Calculus course (MAT133). This study employed Logistic regression analysis to test the relationship between predictor variables and the dichotomous outcome variable which is categorized as low or high achiever in MAT 133 course. About 55.7% of the students are high achiever who achieved higher than 70% marks in MAT133. The research findings reveal that students’ intake on July (OR = 2.941), male students (OR = 0.315), students who scored A+, A and A- in Modern Mathematics in SPM exam (OR = 0.340), students who had B+ and B- in Additional Mathematics in SPM (OR = 0.512) and assessment marks for MAT133 were found to have a significantly higher possibility to be high-achiever in MAT133. Acquiring strong mathematical background is a priority as a fundamental preparation for students to learn mathematics in higher institution.
References
analysis of course dropping behaviors among community college students,” Res. High. Educ.,
vol. 60, no. 2, pp. 184–202, 2019.
[2] A. N. Shuhaimi, M. H. Ismail, N. Sahar, N. H. A. Jabar, N. F. Yaakob, and N. F. M. Razi,
“Exploring the Relationship between Level of Cognitive Ability in Mathematics within Two
Different Schools in Tapah,” Math. Sci. Informatics J., vol. 1, no. 2, pp. 43–50, 2020.
[3] L. C. Mann and M. Walshaw, “Mathematics anxiety in secondary school female students:
issues, influences and implications,” New Zeal. J. Educ. Stud., vol. 54, no. 1, pp. 101–120,
2019.
[4] O. Kasimu and M. Imoro, “Students’ Attitudes Towards Mathematics: The Case of Private and
Public Junior High Schools in The East Mamprusi District, Ghana,” IOSR J. Res. Method
Educ., vol. 7, no. 5, pp. 38–43, 2017.
[5] A. J. Kersey, K. D. Csumitta, and J. F. Cantlon, “Gender similarities in the brain during
mathematics development,” npj Sci. Learn., vol. 4, no. 1, pp. 1–7, 2019.
[6] S. Rodriguez, B. Regueiro, I. Piñeiro, I. Estévez, and A. Valle, “Gender differences in
mathematics motivation: Differential effects on performance in primary education,” Front.
Psychol., vol. 10, p. 3050, 2020.
[7] C. R. Fisher, C. D. Thompson, and R. H. Brookes, “Gender differences in the Australian
undergraduate STEM student experience: a systematic review,” High. Educ. Res. \& Dev., vol.
39, no. 6, pp. 1155–1168, 2020.
[8] G. C. Leder, “Do girls count in mathematics?,” in Educating Girls, Routledge, 2017, pp. 84–
97.
[9] A. M. and L. Mejía-Rodríguez, H. Luyten, and M. R. M. Meelissen, “Gender differences in
mathematics self-concept across the world: An exploration of student and parent data of
TIMSS 2015,” Int. J. Sci. Math. Educ., vol. 19, no. 6, pp. 1229–1250, 2021.
[10] K. O. Asante, “Secondary Students Attitudes towards Mathematics,” Ife Psychol., vol. 20(1),
no. March, pp. 121–133, 2012.
[11] U. Das and K. Singhal, “Gender Differences in Mathematics Performance: Evidence from
Rural India,” in IARIW-ICIER Conference New Delhi, India, 2017, doi:
http://dx.doi.org/10.2139/ssrn.2991511.
[12] H. Suwono, R. Fachrunnisa, C. Yuenyong, and L. Hapsari, “Indonesian students’ attitude and
interest in stem: An outlook on the gender stereotypes in the STEM field,” in Journal of Physics:
Conference Series, 2019, vol. 1340, no. 1, p. 12079.
[13] J. A. Prieto-Saborit, D. Méndez-Alonso, J. A. Cecchini, A. Fernández-Viciana, and J. R.
Bahamonde-Nava, “Cooperative Learning for a More Sustainable Education: Gender Equity
in the Learning of Maths,” Sustainability, vol. 13, no. 15, p. 8220, 2021.
[14] F. H. Bezzina, “Investigating Gender Differences in Mathematics Performance and in Selfregulated
Learning: An empirical Study from Malta,” Equal. Divers. Incl. An Int. J., vol. 29, no.
7, pp. 669–693, 2010, doi: 10.1108/02610151011074407.
[15] T. H. Eng, V. L. Li, and N. H. Julaihi, “A Case Study of ’ High-Failure Rate ’ Mathematics
Courses and its ’ Contributing Factors on UiTM Sarawak Diploma Students,” in Conference
on Scientific and Social Research, 2009, no. July 2008, pp. 1–11.
[16] N. A. Ahmad, S. A. Hassan, A. R. Ahmad, C. Lay Nee, and N. H. Othman, “The Trend of
Academic Achievement among Malaysian Boys and Girls: Where are the Boys?,” Glob. J.
Bus. Soc. Sci. Rev., vol. 5, no. 1, pp. 1–8, 2017.
[17] G. Stoet and D. C. Geary, “The gender-equality paradox in science, technology, engineering,
and mathematics education,” Psychol. Sci., vol. 29, no. 4, pp. 581–593, 2018.
[18] T. H. Eng, V. L. Li, and N. H. Julaihi, “The relationships between students’ underachievement
in Mathematics courses and influencing factors,” Procedia - Soc. Behav. Sci., vol. 8, no. 5, pp.
134–141, 2010, doi: 10.1016/j.sbspro.2010.12.019.
[19] J. Murray, “The Factors that Influence Mathematics Achievement at the Berbice Campus,” Int.
J. Bus. Soc. Sci., vol. 4, no. 10, pp. 150–164, 2013.
[20] P. Blatchford and R. Webster, “Classroom contexts for learning at primary and secondary
school: Class size, groupings, interactions and special educational needs,” Br. Educ. Res. J.,
vol. 44, no. 4, pp. 681–703, 2018.
[21] H. B. M. Tahir, S. N. B. S. Wahid, and Z. B. Abu, “Factors affecting UiTM Pahang students’
achievement in learning mathematics,” in CSSR 2010 - 2010 International Conference on
Science and Social Research, 2010, no. Cssr, pp. 591–595, doi:
10.1109/CSSR.2010.5773850.