The relationship between student learning status and course selection
DOI:
https://doi.org/10.56380/Keywords:
Learning style, Course selection, Study engagement, Academic performance, Factor analysisAbstract
This study analyzed the relationship between student learning status and course selection based on student data. The study confirmed the two-factor structure of student learning success, namely academic engagement and academic performance, using confirmatory factor analysis (CFA) and correlation methods, and explained 73.9% of the total varance. The relusts of the study showed that there was a strong positive correlation between study duration and academic achievement (r=0.77), but the correlation between study duration and GPA was weak (r=0.11). It was also found that the difference in study status between S and D program students was directly related to their initial choice motivation and internal attitude. This indicates the need for higher education institutions to organize course selection counseling services differently based on students’ learning status.
Downloads
References
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. https://doi.org/10.1037/1082-989X.4.3.272
Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31–36. https://doi.org/10.1007/BF02291575
Stevens, J. P. (2009). Applied multivariate statistics for the social sciences (5th ed.). Routledge.
Tinto, V. (1987). Leaving college: Rethinking the causes and cures of student attrition. University of Chicago Press.
Fredi E. Palominos, Seomara K. Palominos, Felisa M. Córdova, Hernán Díaz, Study of the achievement of university students and their relationship with the selection process, Procedia Computer Science, Volume 122, 2017, Pages 985-992, https://doi.org/10.1016/j.procs.2017.11.464
Ivana Ognjanovic, Dragan Gasevic, Shane Dawson, Using institutional data to predict student course selections in higher education, The Internet and Higher Education, Volume 29, 2016, Pages 49-62, ISSN 1096-7516, https://doi.org/10.1016/j.iheduc.2015.12.002.
Karen E. Clayton, Fran C. Blumberg, Jared A. Anthony,Linkages between course status, perceived course value, and students’ preference for traditional versus non-traditional learning environments, Computers & Education, Volume 125, 2018, Pages 175-181, ISSN 0360-1315, https://doi.org/10.1016/j.compedu.2018.06.002
Armstrong, W. B. (2000). THE ASSOCIATION AMONG STUDENT SUCCESS IN COURSES, PLACEMENT TEST SCORES, STUDENT BACKGROUND DATA, AND INSTRUCTOR GRADING PRACTICES. Community College Journal of Research and Practice, 24(8), 681–695. https://doi.org/10.1080/10668920050140837
Babad E, Tayeb A. Experimental analysis of students' course selection. Br J Educ Psychol. 2003 Sep;73(Pt 3):373-93. doi: 10.1348/000709903322275894. PMID: 14672150.
AL-SAREM, Mohammed. Solving Course Selection Problem by a Combination of Correlation Analysis and Analytic Hierarchy Process. International Journal of Electrical and Computer Engineering (IJECE), [S.l.], v. 7, n. 6, p. 3536-3551, dec. 2017. ISSN 2722-2578. doi:http://doi.org/10.11591/ijece.v7i6.pp3536-3551.
Carr, M., & Claxton, G. (2002). Tracking the Development of Learning Dispositions. Assessment in Education: Principles, Policy & Practice, 9(1), 9–37. https://doi.org/10.1080/09695940220119148
Miller, S. (2022). An analysis of the rate of academic clustering and the types of majors chosen by divisions I, II, and III intercollegiate athletes. Journal for the Study of Sports and Athletes in Education, 16(2), 97–113. https://doi.org/10.1080/19357397.2021.1916305
Fenandez-Rio, J., García, S., & Ferriz-Valero, A. (2025). Selecting (or not) physical education as an elective subject: Spanish high school students’ views. Physical Education and Sport Pedagogy, 30(5), 563–575. https://doi.org/10.1080/17408989.2023.2256762
Carrière, R., Trottier, C., Drapeau, V., Goulet, C., Camiré, M., Lemyre, P. N., & Frenette, É. (2023). Experiences of high school stakeholders and student-athletes participating in an ongoing longitudinal life skills training program. Journal of Applied Sport Psychology, 35(2), 178–201. https://doi.org/10.1080/10413200.2021.2015478
Chang, H.-T., Lin, C.-Y., Wang, L.-C., & Tseng, F.-C. (2022). How Students can Effectively Choose the Right Courses: Building a Recommendation System to Assist Students in Choosing Courses Adaptively. Educational Technology & Society, 25(1), 61–74. https://www.jstor.org/stable/48647030
Yao, Z. M., Vongchalitkul, B., Rungrueng, P., So-in, R., & Chen, W.-K. (2023). The Influencing Factors of College Students’ intention in selecting Elective Courses. International Journal of Development Administration Research, 6(1), 16–30. retrieved from https://so02.tci-thaijo.org/index.php/ijdar/article/view/263773
Liu, C., Yang, S. Personalized Learning Ability Classification Using SVM for Enhanced Education in System Modeling and Simulation Courses. Front. Digit. Educ. 1, 295–307 (2024). https://doi.org/10.1007/s44366-024-0035-6
Chang Y-C and Tsai Y-T (2022) The Effect of University Students’ Emotional Intelligence, Learning Motivation and Self-Efficacy on Their Academic Achievement—Online English Courses. Front. Psychol. 13:818929. doi: 10.3389/fpsyg.2022.818929
Babad, E. and Tayeb, A. (2003), Experimental analysis of students' course selection. British Journal of Educational Psychology, 73: 373-393. https://doi.org/10.1348/000709903322275894
T. Morrow, A. R. Hurson and S. S. Sarvestani, "A Multi-stage Approach to Personalized Course Selection and Scheduling," 2017 IEEE International Conference on Information Reuse and Integration (IRI), San Diego, CA, USA, 2017, pp. 253-262, doi: 10.1109/IRI.2017.58.
