Understanding Student Motivation in Learning Biology Among Undergraduate Students

Authors

Capua, Vanesa P.

School of Graduate Studies, Saint Mary’s University, Philippines (Philippines)

Article Information

DOI: 10.47772/IJRISS.2026.100400065

Subject Category: Education

Volume/Issue: 10/4 | Page No: 900-917

Publication Timeline

Submitted: 2026-04-06

Accepted: 2026-04-11

Published: 2026-04-27

Abstract

Motivation is a key driver of students’ engagement and success in learning biology. This study investigated the level of motivation of undergraduate students in learning biology and examined whether significant differences exist when grouped according to sex and course. It also sought to identify the relationship between students’ age and their level of motivation, as well as to determine which profile variable significantly predicts motivation. Quantitative research approach was employed, using descriptive-comparative, correlational, and predictive research designs. Data were collected from 112 voluntary undergraduate students through a validated biology motivation questionnaire. Descriptive statistics were used to analyze students’ level of motivation. Differences by sex and course were examined using an independent samples t-test and one-way ANOVA, respectively. Pearson’s r was utilized to assess the relationship between motivation and age, whereas multiple linear regression was used to identify significant predictors of students’ motivation in learning biology. Results revealed that the undergraduate students were highly motivated to learn biology, regardless of sex and course, as there were no significant differences in motivation levels when grouped by these variables. However, age was found to significantly influence students' motivation, with a direct but weak correlation observed between age and motivation levels. Among the profile variables, age emerged as the most significant predictor of motivation in learning biology. These findings suggest that educators and academic institutions may consider age-related differences when designing instructional strategies and support systems to sustain and improve student motivation in biology learning contexts.

Keywords

Biology, Motivation, Undergraduate, Subscale

Downloads

References

1. Areepattamannil, S., Khurma, O. A., Ali, N., Al Hakmani, R., & Kadbey, H. (2023). Examining the relationship between science motivational beliefs and science achievement in Emirati early adolescents through the lens of self-determination theory. Large-Scale Assessments in Education, 11(1), 25. https://doi.org/10.1186/s40536-023-00175-7 [Google Scholar] [Crossref]

2. Bandhu, M. D., Mohan, M. M., Nittala, N. A. P., Jadhav, P., Bhadauria, A., & Saxena, K. K. (2024). Theories of motivation: A comprehensive analysis of human behavior drivers. Acta Psychologica, 244, 104177. https://doi.org/10.1016/j.actpsy.2024.104177 [Google Scholar] [Crossref]

3. Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215. https://doi.org/10.1037/0033-295X.84.2.191 [Google Scholar] [Crossref]

4. Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52, 1–26. https://doi.org/10.1146/annurev.psych.52.1.1 [Google Scholar] [Crossref]

5. Berg, D. J., & Corpus, J. H. (2013). Enthusiastic students: A study of motivation in two alternatives to mandatory instruction. https://www.semanticscholar.org [Google Scholar] [Crossref]

6. Broussard, S. C., & Garrison, M. E. B. (2004). The relationship between classroom motivation and academic achievement in elementary school-aged children. Family and Consumer Sciences Research Journal, 33(2), 106–120. [Google Scholar] [Crossref]

7. Bunda, T. P., Neviyarni, S., & Nirwana, H. (2024). The role of motivation in influencing student success in learning. Manajia: Journal of Education and Management. https://doi.org/10.58355/manajia.v2i1.29 [Google Scholar] [Crossref]

8. Chen, X., Zimmerman, B. J., & Schunk, D. H. (2022). Motivation and learning in adult education. Learning and Individual Differences, 75, 101–115. [Google Scholar] [Crossref]

9. Cheung, D. (2017). The key factors affecting students’ individual interest in school science lessons. International Journal of Science Education, 40(1), 1–23. https://doi.org/10.1080/09500693.2017.1362711 [Google Scholar] [Crossref]

10. Collie, R., & Martin, A. (2019). Motivation and engagement in learning. Oxford University Press. https://doi.org/10.1093/acrefore/9780190264093.013.891 [Google Scholar] [Crossref]

11. Colomer, J., Serra, T., Canabate, D., & Bubnys, R. (2020). Reflective learning in higher education: Active methodologies for transformative practices. Sustainability, 12(9), 3827. https://doi.org/10.3390/su12093827 [Google Scholar] [Crossref]

12. Cotner, S., Jeno, L. M., Walker, J. D., Jørgensen, C., & Vandvik, V. (2020). Gender gaps in the performance of Norwegian biology students: The roles of test anxiety and science confidence. International Journal of STEM Education, 7, 1–10. [Google Scholar] [Crossref]

13. Deci, E. L., & Ryan, R. M. (2008). Self-determination theory: A macrotheory of human motivation, development, and health. Canadian Psychology, 49, 182–185. https://doi.org/10.1037/A0012801 [Google Scholar] [Crossref]

14. Deci, E. L., Olafsen, A. H., & Ryan, R. M. (2017). Self-determination theory in work organizations: The state of a science. https://doi.org/10.1146/ANNUREV-ORGPSYCH-032516-113108 [Google Scholar] [Crossref]

15. Dou, R., Cian, H., & Espinosa, V. (2021). Undergraduate STEM majors on and off the premed/health track: A STEM identity perspective. CBE—Life Sciences Education, 20, 1–12. https://doi.org/10.1187/cbe.20-12-0281 [Google Scholar] [Crossref]

16. Eckland, N. S., & Berenbaum, H. (2023). Clarity of emotions and goals: Exploring associations with subjective well-being across adulthood. Affective Science, 4, 401–412. https://doi.org/10.1007/s42761-022-00179-6 [Google Scholar] [Crossref]

17. Eccles, J. S., Midgley, C., Wigfield, A., Buchanan, C. M., Reuman, D., Flanagan, C., & Mac Iver, D. (1993). Development during adolescence: The impact of stage-environment fit on young adolescents' experiences in schools and in families. American Psychologist, 48(2), 90–101. https://doi.org/10.1037/0003-066X.48.2.90 [Google Scholar] [Crossref]

18. Ferla, J., Valcke, M., & Schuyten, G. (2010). Judgments of self-perceived academic competence and their differential impact on students’ achievement motivation, learning approach, and academic performance. European Journal of Psychology of Education, 25, 519–536. https://doi.org/10.1007/s10212-010-0030-9 [Google Scholar] [Crossref]

19. Firmansyah, F., Komala, R., & Rusdi, R. (2018). Self-efficacy and motivation: Improving biology learning outcomes of senior high school students. Jurnal Pendidikan Biologi Indonesia. https://doi.org/10.22219/jpbi.v4i3.6878 [Google Scholar] [Crossref]

20. Gibbens, B. B. (2019). Measuring student motivation in an introductory biology class. The American Biology Teacher, 81, 20–26. https://doi.org/10.1525/abt.2019.81.1.20 [Google Scholar] [Crossref]

21. Glynn, S. M., & Koballa, T. R., Jr. (2006). Motivation to learn college science. In J. J. Mintzes & W. H. Leonard (Eds.), Handbook of college science teaching, 25-32. National Science Teachers Association Press. [Google Scholar] [Crossref]

22. Glynn, S. M., Bryan, R. R., Brickman, P., & Armstrong, N. (2015). Intrinsic motivation, self-efficacy, and interest in science. In K. A. Renninger, M. Nieswandt, & S. Hidi (Eds.), Interest in mathematics and science learning, 189–202. American Educational Research Association. [Google Scholar] [Crossref]

23. Goldman, Z. W., Goodboy, A. K., & Weber, K. (2017). College students' psychological needs and intrinsic motivation to learn: An examination of self-determination theory. Communication Quarterly, 65, 167–191. https://doi.org/10.1080/01463373.2016.1215338 [Google Scholar] [Crossref]

24. Gormally, C., & Heil, A. (2022). A vision for university biology education for non-science majors. CBE—Life Sciences Education, 21(4), es5. https://doi.org/10.1187/cbe.21-12-0338 [Google Scholar] [Crossref]

25. Grahaam, M. J., Frederick, J., Byars-Winston, A., Hunter, A.-B., & Handelsman, J. (2013). Increasing persistence of college students in STEM. Science, 341(6153), 1455–1456. https://doi.org/10.1126/science.1240487 [Google Scholar] [Crossref]

26. Guay, F., Chanal, J., Ratelle, C. F., Marsh, H. W., Larose, S., & Boivin, M. (2010). Intrinsic, identified, and controlled types of motivation for school subjects in young elementary school children. British Journal of Educational Psychology, 80(4), 711–735. [Google Scholar] [Crossref]

27. Hadre, P., Crowson, H., Debacker, T., & White, D. (2007). Predicting the academic motivation of rural high school students. Journal of Experimental Education, 75, 247–269. [Google Scholar] [Crossref]

28. Howard, J. L., Bureau, J. S., Guay, F., Chong, J. X. Y., & Ryan, R. M. (2021). Student motivation and associated outcomes: A meta-analysis from self-determination theory. Perspectives on Psychological Science, 16(6), 1300–1323. https://doi.org/10.1177/1745691620966789 [Google Scholar] [Crossref]

29. Hulleman, C. S., & Harackiewicz, J. M. (2020). Promoting interest and performance in high school science classes. Science Education, 104(2), 215–227. [Google Scholar] [Crossref]

30. Hunaepi, H., Suma, I. K., & Subagia, I. W. (2024). Curiosity in science learning: A systematic literature review. International Journal of Essential Competencies in Education, 3(1), 77–105. https://doi.org/10.36312/ijece.v3i1.1918 [Google Scholar] [Crossref]

31. Hunter, A. B. (2019). Why undergraduates leave STEM majors: Changes over the last two decades. In E. Seymour & A. B. Hunter (Eds.), Talking about leaving revisited. Springer. https://doi.org/10.1007/978-3-030-25304-2_3 [Google Scholar] [Crossref]

32. Ishida, K., & Sekiyama, R. (2024). Variables influencing students' learning motivation: Critical literature review. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1445011 [Google Scholar] [Crossref]

33. John, D., Hussin, N., Zaini, M., Ametefe, D., Aliu, A., & Caliskan, A. (2023). Gamification equilibrium: The fulcrum for balanced intrinsic motivation and extrinsic rewards in learning systems. International Journal of Serious Games, 10(3), 83–116. https://doi.org/10.17083/ijsg.v10i3.633 [Google Scholar] [Crossref]

34. Karakolidis, A., Pitsia, V., & Emvalotis, A. (2019). The case of high motivation and low achievement in science: The role of students’ epistemic beliefs. International Journal of Science Education, 41(11), 1457–1474. https://doi.org/10.1080/09500693.2019.1612121 [Google Scholar] [Crossref]

35. Kim, K. J., Hwang, J. Y., & Kwon, B. S. (2016). Differences in medical students' academic interest and performance across career choice motivations. International Journal of Medical Education, 7, 52–55. https://doi.org/10.5116/ijme.56a7.5124 [Google Scholar] [Crossref]

36. Kıran, D., & Sungur, S. (2012). Middle school students’ science self-efficacy and its sources: Examination of gender difference. Journal of Science Education and Technology, 21, 619–630. [Google Scholar] [Crossref]

37. Kışoğlu, M. (2018). An examination of science high school students’ motivation towards learning biology and their attitude towards biology lessons. International Journal of Higher Education, 7, 151–164. https://doi.org/10.5430/ijhe.v7n1p151 [Google Scholar] [Crossref]

38. Koballa, T. R., & Glynn, S. M. (2007). Attitudinal and motivational constructs in science learning. In S. Abell & N. Lederman (Eds.), Handbook of research on science education (pp. 75–102). LEA Publishers. [Google Scholar] [Crossref]

39. Lai, E. R. (2011). Metacognition: A literature review. Pearson Research Report, 24, 1–40. [Google Scholar] [Crossref]

40. Lang & Šorgo, A. (2024). Motivation to learn biology: Adaptation and validation of a science motivation questionnaire with Slovene secondary school students. International Journal of Instruction, 17, 137–156. https://doi.org/10.29333/iji.2024.1738a [Google Scholar] [Crossref]

Metrics

Views & Downloads

Similar Articles