Motivation, stress, and GPA
Keywords:
grade point average, academic motivation, financial stress, postsecondary academic performance, multiple linear regressionAbstract
Objective: This study examined the independent associations of academic motivation and financial stress with postsecondary GPA and tested whether motivation moderates the financial stress-GPA relationship. Methods: Using Education Longitudinal Study of 2002 data, base-year motivation was linked with third-follow-up financial stress and transcript-based GPA. A baseline regression included 6,568 students; an expanded model added socioeconomic status, parental education, sex, race/ethnicity, prior achievement, and the motivation by financial stress interaction. Results: The baseline model was significant, with motivation positively and financial stress negatively associated with GPA. Both associations held in the weighted expanded model (R² = .174) after adjusting for the covariates above, with prior achievement the strongest continuous predictor. Black participants had lower adjusted GPAs than White non-Hispanic participants. Conclusions: Motivation and financial stress were each independently related to GPA. Contrary to the hypothesized buffering effect, the financial stress-GPA relationship was slightly stronger, not weaker, at higher motivation, though the interaction was small and not robust to sensitivity analysis. Significance: These findings suggest motivation and financial stress are independently associated with GPA and may inform student support efforts. Future research should further examine the racial disparities identified here.
Downloads
References
Adams, D. R., Meyers, S. A., & Beidas, R. S. (2016). The relationship between financial strain, perceived stress, psychological symptoms, and academic and social integration in undergraduate students. Journal of American College Health, 64(5), 362–370.
Bouri, E., Gupta, R., Lau, C. K. M., Roubaud, D., & Wang, S. (2018). Bitcoin and global financial stress: A copula-based approach to dependence and causality in the quantiles. The Quarterly Review of Economics and Finance, 69, 297-307. https://doi.org/10.1016/j.qref.2018.04.003
Bozick, R., Lauff, E., & Wirt, J. (2007). Education Longitudinal Study of 2002 (ELS: 2002): A First Look at the Initial Postsecondary Experiences of the High School Sophomore Class of 2002. National Center for Education Statistics.
Britt, S. L., Mendiola, M. R., Schink, G. H., Tibbetts, R. H., & Jones, S. H. (2016). Financial stress, coping strategy, and academic achievement of college students. Journal of Financial Counseling and Planning, 27(2), 172–183.
Broton, K. M., & Goldrick-Rab, S. (2018). Going without: An exploration of food and housing insecurity among undergraduates. Educational Researcher, 47(2), 121–133.
Cook, R. D. (1977). Detection of influential observation in linear regression. Technometrics, 19(1), 15–18.
Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. Springer Science & Business Media.
Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53(1), 109–132.
Fryer, R. G., & Levitt, S. D. (2004). Understanding the Black-White test score gap in the first two years of school. The Review of Economics and Statistics, 86(2), 447–464.
Heckman, S., Lim, H., & Montalto, C. (2014). Factors related to financial stress among college students. Journal of Financial Therapy, 5(1), 19–39.
Hu, E. H., & Morgan, P. L. (2024). Explaining achievement gaps: The role of socioeconomic factors. Thomas B. Fordham Institute.
Ingels, S. J., Pratt, D. J., Alexander, C. P., Jewell, D. M., Lauff, E., Mattox, T. L., & Wilson, D. (2014). Education Longitudinal Study of 2002 (ELS:2002) third follow-up data file documentation (NCES 2014-364). U.S. Department of Education, National Center for Education Statistics.
JMP Statistical Discovery LLC. (2024). JMP® 18 (Version 18.2) [Computer software].
Joo, S. H., Durband, D. B., & Grable, J. E. (2008). The academic impact of financial stress on college students. Journal of College Student Retention: Research, Theory & Practice, 10(3), 287–305.
Koenka, A. C. (2020). Academic motivation theories revisited: An interactive dialog between motivation scholars on recent contributions, underexplored issues, and future directions. Contemporary Educational Psychology, 61, 101831. https://doi.org/10.1016/j.cedpsych.2019.101831
MacKinnon, J. G., & White, H. (1985). Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties. Journal of econometrics, 29(3), 305-325. https://doi.org/10.1016/0304-4076(85)90158-7
O'Brien, R. M. (2007). A caution regarding rules of thumb for variance inflation factors. Quality & Quantity, 41(5), 673–690.
Potter, D., Jayne, D., & Britt, S. (2020). Financial anxiety among college students: The role of generational status. Journal of Financial Counseling and Planning, 31(2), 284–295.
Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of university students' academic performance: A systematic review and meta-analysis. Psychological Bulletin, 138(2), 353–387.
Robbins, S. B., Lauver, K., Le, H., Davis, D., Langley, R., & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological Bulletin, 130(2), 261–288.
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78.
Sirin, S. R. (2005). Socioeconomic status and academic achievement: A meta-analytic review of research. Review of Educational Research, 75(3), 417–453.
U.S. Department of Education, National Center for Education Statistics. (2002). Education Longitudinal Study of 2002 (ELS:2002). National Center for Education Statistics.
Vallerand, R. J., Pelletier, L. G., Blais, M. R., Briere, N. M., Senecal, C., & Vallieres, E. F. (1992). The academic motivation scale: A measure of intrinsic, extrinsic, and amotivation in education. Educational and Psychological Measurement, 52(4), 1003–1017.
Voyer, D., & Voyer, S. D. (2014). Gender differences in scholastic achievement: A meta-analysis. Psychological Bulletin, 140(4), 1174–1204.
White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838.
Wladis, C., Conway, K. M., & Hachey, A. C. (2015). The online STEM classroom—Who succeeds? An exploration of the impact of ethnicity, gender, and non-traditional student characteristics in the community college context. Community College Review, 43(2), 142–164.
Published
How to Cite
Issue
Section
Copyright (c) 2026 International journal of social sciences

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Articles published in the International Journal of Social Sciences (IJSS) are available under Creative Commons Attribution Non-Commercial No Derivatives Licence (CC BY-NC-ND 4.0). Authors retain copyright in their work and grant IJSS right of first publication under CC BY-NC-ND 4.0. Users have the right to read, download, copy, distribute, print, search, or link to the full texts of articles in this journal, and to use them for any other lawful purpose.
Articles published in IJSS can be copied, communicated and shared in their published form for non-commercial purposes provided full attribution is given to the author and the journal. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.

