Students’ online course activity, together with self-efficacy and test anxiety, predicts mathematics exam results

Getriin Aaviste; Dimitri Löchner; Kariina Laas; Karin Täht

doi:10.31129/LUMAT.14.2.3158

Authors

Getriin Aaviste Institute of Mathematics and Statistics, University of Tartu, Estonia https://orcid.org/0000-0002-5390-3444
Dimitri Löchner Institute of Psychology, University of Tartu, Estonia https://orcid.org/0000-0002-1612-2040
Kariina Laas Institute of Psychology, University of Tartu, Estonia https://orcid.org/0000-0001-6572-2715
Karin Täht Institute of Mathematics and Statistics and Institute of Psychology, University of Tartu, Estonia https://orcid.org/0000-0001-8719-0924

DOI:

https://doi.org/10.31129/LUMAT.14.2.3158

Keywords:

Online Course Activity, Mathematics Achievement, Test Anxiety, Self-efficacy

Abstract

Many students find mathematics to be a challenging subject to learn, leading to anxiety and low self-efficacy. While positive self-beliefs towards mathematics encourage engagement and learning, negative emotions like anxiety restrain it. Voluntary online courses for learning mathematics may provide an opportunity to strengthen mathematical skills in a more flexible and self-paced environment, potentially helping reduce anxiety and increase self-efficacy. The present study investigated the associations among online course activity, test anxiety, and self-efficacy with mathematics performance in high-stakes settings. The analyses focused on 144 final-year high school students who completed the wide national mathematics exam after participating in a voluntary online preparation course. In addition to self-reported data, data regarding online course activity logs and national mathematics exam results from a state registry were extracted. According to our analysis, more frequent online course activity was associated with higher mathematics exam scores. Surprisingly, online course activity was not related to either students' self-efficacy or test anxiety. The regression analysis results suggest that self-efficacy was the strongest predictor of mathematics national examination results, with test anxiety and online course activity also contributing significantly. Although previous research has examined the role of self-beliefs in predicting mathematics exam results, this study offers a fresh perspective by focusing on these relationships in an online educational context, where their dynamics may differ.

References

Alamri, M. M. (2022). Investigating Students’ Adoption of MOOCs during COVID-19 Pandemic: Students’ Academic Self-Efficacy, Learning Engagement, and Learning Persistence. Sustainability, 14(2), 714. https://doi.org/10.3390/su14020714

Arens, A. K., Frenzel, A. C., & Goetz, T. (2022). Self-Concept and Self-Efficacy in Math: Longitudinal Interrelations and Reciprocal Linkages with Achievement. The Journal of Experimental Education, 90(3), 615–633. https://doi.org/10.1080/00220973.2020.1786347

Artino, A. R. (2008). Motivational beliefs and perceptions of instructional quality: Predicting satisfaction with online training*. Journal of Computer Assisted Learning, 24(3), 260–270. https://doi.org/10.1111/j.1365-2729.2007.00258.x

Ashcraft, M. H., & Kirk, E. P. (2001). The relationships among working memory, math anxiety, and performance. Journal of Experimental Psychology: General, 130(2), 224–237. https://doi.org/10.1037/0096-3445.130.2.224

Ashcraft, M. H., & Krause, J. A. (2007). Working memory, math performance, and math anxiety. Psychonomic Bulletin & Review, 14(2), 243–248. https://doi.org/10.3758/BF03194059

Ashcraft, M. H., & Moore, A. M. (2009). Mathematics Anxiety and the Affective Drop in Performance. Journal of Psychoeducational Assessment, 27(3), 197–205. https://doi.org/10.1177/0734282908330580

Ayotola, A., & Adedeji, T. (2009). The relationship between mathematics self-efficacy and achievement in mathematics. Procedia - Social and Behavioral Sciences, 1(1), 953–957. https://doi.org/10.1016/j.sbspro.2009.01.169

Bandura, A. (1986). Social Foundations of Thought and Action. In D. Marks, The Health Psychology Reader (pp. 94–106). SAGE Publications Ltd. https://doi.org/10.4135/9781446221129.n6

Bandura, A. (Ed.). (1995). Self-efficacy in changing societies. Cambridge University Press.

Barroso, C., & Ganley, C. M. (2021). A Meta-Analysis of the Relation Between Math Anxiety and Math Achievement. 35.

Bonafini, F. C., Chae, C., Park, E., & Jablokow, K. W. (2017). How Much Does Student Engagement with Videos and Forums in a MOOC Affect Their Achievement? Online Learning, 21(4). https://doi.org/10.24059/olj.v21i4.1270

Borgonovi, F., & Pokropek, A. (2019). Seeing is believing: Task-exposure specificity and the development of mathematics self-efficacy evaluations. Journal of Educational Psychology, 111(2), 268–283. (2018-20920-001). https://doi.org/10.1037/edu0000280.supp

Brinton, C. G., Buccapatnam, S., Chiang, M., & Poor, H. V. (2015). Mining MOOC Clickstreams: On the Relationship Between Learner Behavior and Performance (arXiv:1503.06489). arXiv. https://doi.org/10.48550/arXiv.1503.06489

Broadbent, J., & Poon, W. L. (2015). Self-regulated learning strategies & academic achievement in online higher education learning environments: A systematic review. The Internet and Higher Education, 27, 1–13. https://doi.org/10.1016/j.iheduc.2015.04.007

Cassady, J. C., & Finch, W. H. (2020). Revealing Nuanced Relationships Among Cognitive Test Anxiety, Motivation, and Self-Regulation Through Curvilinear Analyses. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.01141

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed). L. Erlbaum Associates.

Cook, D. A., & Artino Jr, A. R. (2016). Motivation to learn: An overview of contemporary theories. Medical Education, 50(10), 997–1014. https://doi.org/10.1111/medu.13074

Daker, R. J., Gattas, S. U., Sokolowski, H. M., Green, A. E., & Lyons, I. M. (2021). First-year students’ math anxiety predicts STEM avoidance and underperformance throughout university, independently of math ability. NPJ Science of Learning, 6(1), 17. https://doi.org/10.1038/s41539-021-00095-7

Deci, E. L., & Ryan, R. M. (2000). The ‘What’ and ‘Why’ of Goal Pursuits: Human Needs and the Self-Determination of Behavior. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01

Dowker, A., Sarkar, A., & Looi, C. Y. (2016). Mathematics Anxiety: What Have We Learned in 60 Years? Frontiers in Psychology, 7. https://doi.org/10.3389/fpsyg.2016.00508

Dowker, A., & Sheridan, H. (2022). Relationships Between Mathematics Performance and Attitude to Mathematics: Influences of Gender, Test Anxiety, and Working Memory. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.814992

Evans, B. J., Baker, R. B., & Dee, T. S. (2016). Persistence Patterns in Massive Open Online Courses (MOOCs). The Journal of Higher Education, 87(2), 206–242. https://doi.org/10.1080/00221546.2016.11777400

Figueira, P. V. S. T., Gusmão, T. C. R. S., & Freitas, P. M. de. (2023). Effects of the Math Anxiety of Parents and Teachers on Students. Psico-USF, 28, 1–12. https://doi.org/10.1590/1413-82712023280101

Gonzales, B. B., Iraola-Real, I., Choquehuanca, E. G., Talledo, R. A., & Vargas, Y. I. F. (2019). Self-Efficacy And Its Effect On Anxiety And Performance In Mathematics In Aspiring to Career in Engineering. 2019 International Symposium on Engineering Accreditation and Education (ICACIT), 1–4. https://doi.org/10.1109/ICACIT46824.2019.9130366

Gravemeijer, K., Stephan, M., Julie, C., Lin, F.-L., & Ohtani, M. (2017). What Mathematics Education May Prepare Students for the Society of the Future? International Journal of Science and Mathematics Education, 15(S1), 105–123. https://doi.org/10.1007/s10763-017-9814-6

Greene, J. A., Oswald, C. A., & Pomerantz, J. (2015). Predictors of Retention and Achievement in a Massive Open Online Course. American Educational Research Journal, 52(5), 925–955. https://doi.org/10.3102/0002831215584621

HARNO. (n.d.). Retrieved 17 February 2023, from https://harno.ee/eksamid-testid-ja-uuringud/eksamid-testid-ja-lopudokumendid/riigieksamid#valimine

Heissel, J. A., Adam, E. K., Doleac, J. L., Figlio, D. N., & Meer, J. (2021). Testing, Stress, and Performance: How Students Respond Physiologically to High-Stakes Testing. Education Finance and Policy, 16(2), 183–208. https://doi.org/10.1162/edfp_a_00306

Hembree, R. (1990). The Nature, Effects, and Relief of Mathematics Anxiety. Journal for Research in Mathematics Education, 21(1), 33. https://doi.org/10.2307/749455

Hew, K. F., & Cheung, W. S. (2014). Students’ and instructors’ use of massive open online courses (MOOCs): Motivations and challenges. Educational Research Review, 12, 45–58. https://doi.org/10.1016/j.edurev.2014.05.001

Hiller, S. E., Kitsantas, A., Cheema, J. E., & Poulou, M. (2022). Mathematics anxiety and self-efficacy as predictors of mathematics literacy. International Journal of Mathematical Education in Science and Technology, 53(8), 2133–2151. https://doi.org/10.1080/0020739X.2020.1868589

Hughes, G., & Dobbins, C. (2015). The utilization of data analysis techniques in predicting student performance in massive open online courses (MOOCs). Research and Practice in Technology Enhanced Learning, 10(1), 10. https://doi.org/10.1186/s41039-015-0007-z

Ignacio, N. G., Nieto, L. J. B., & Barona, E. G. (2006). The Affective Domain in Mathematics Learning. International Electronic Journal of Mathematics Education, 1(1), 16–32. https://doi.org/10.29333/iejme/169

Jameson, M. M., Dierenfeld, C., & Ybarra, J. (2022). The Mediating Effects of Specific Types of Self-Efficacy on the Relationship between Math Anxiety and Performance. Education Sciences, 12(11), 789. https://doi.org/10.3390/educsci12110789

Jarvis, D. H. (2015). MOOCs: By Jonathan Haber. MIT Press, Cambridge, MA. 2014, 227 pp. MIT Essential Knowledge Series. ISBN 978-0-262-52691-3 (pbk), ISBN 978-0-262-32297-3 (e-book). International Review of Education, 61(4), 573–575. https://doi.org/10.1007/s11159-015-9499-4

Kadoić, N., & Oreški, D. (2018). Analysis of student behavior and success based on logs in Moodle. 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 0654–0659. https://doi.org/10.23919/MIPRO.2018.8400123

Kaskens, J., Segers, E., Goei, S. L., Van Luit, J. E. H., & Verhoeven, L. (2020). Impact of Children’s math self-concept, math self-efficacy, math anxiety, and teacher competencies on math development. Teaching and Teacher Education, 94, 103096. https://doi.org/10.1016/j.tate.2020.103096

Kazelskis, R., Reeves, C., Kersh, M. E., Bailey, G., Cole, K., Larmon, M., Hall, L., & Holliday, D. C. (2000). Mathematics Anxiety and Test Anxiety: Separate Constructs? The Journal of Experimental Education, 68(2), 137–146. https://doi.org/10.1080/00220970009598499

Kim, C., Park, S. W., & Cozart, J. (2014). Affective and motivational factors of learning in online mathematics courses. British Journal of Educational Technology, 45(1), 171–185. https://doi.org/10.1111/j.1467-8535.2012.01382.x

Liu, E. Z. F., & Lin, C. H. (2010). The survey study of mathematics motivated strategies for learning questionnaire (MMSLQ) for grade 10-12 Taiwanese students. The Turkish Online Journal of Educational Technology, 9(2), 13.

Lu, K., Zhu, J., Pang, F., & Liu, Z. (2024). Understanding college students’ test anxiety in asynchronous online courses: The mediating role of emotional engagement. International Journal of Educational Technology in Higher Education, 21(1), 50. https://doi.org/10.1186/s41239-024-00482-1

Lukowski, S. L., DiTrapani, J., Jeon, M., Wang, Z., J.Schenker, V., Doran, M. M., Hart, S. A., Mazzocco, M. M. M., Willcutt, E. G., A.Thompson, L., & Petrill, S. A. (2019). Multidimensionality in the measurement of math-specific anxiety and its relationship with mathematical performance. Learning and Individual Differences, 70, 228–235. https://doi.org/10.1016/j.lindif.2016.07.007

Miao, J., & Ma, L. (2022). Students’ online interaction, self-regulation, and learning engagement in higher education: The importance of social presence to online learning. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.815220

Phan, T., McNeil, S. G., & Robin, B. R. (2016). Students’ patterns of engagement and course performance in a Massive Open Online Course. Computers & Education, 95, 36–44. https://doi.org/10.1016/j.compedu.2015.11.015

Pintrich, P. R. (2004). A Conceptual Framework for Assessing Motivation and Self-Regulated Learning in College Students. Educational Psychology Review, 16(4), 385–407. https://doi.org/10.1007/s10648-004-0006-x

Pirrone, C., Di Corrado, D., Privitera, A., Castellano, S., & Varrasi, S. (2022). Students’ Mathematics Anxiety at Distance and In-Person Learning Conditions during COVID-19 Pandemic: Are There Any Differences? An Exploratory Study. Education Sciences, 12(6), Article 6. https://doi.org/10.3390/educsci12060379

Puzziferro, M. (2008). Online Technologies Self-Efficacy and Self-Regulated Learning as Predictors of Final Grade and Satisfaction in College-Level Online Courses. American Journal of Distance Education, 22(2), 72–89. https://doi.org/10.1080/08923640802039024

Quintero, M., Hasty, L., Li, T., Song, S., & Wang, Z. (2022). A multidimensional examination of math anxiety and engagement on math achievement. British Journal of Educational Psychology, 92(3), 955–973. https://doi.org/10.1111/bjep.12482

R Core Team. (2024). R: A Language and Environment for Statistical Computing. [Computer software]. R Foundation for Statistical Computing. https://www.R-project.org/

Raman, A., Thannimalai, R., Rathakrishnan, M., & Ismail, S. N. (2022). Investigating the Influence of Intrinsic Motivation on Behavioral Intention and Actual Use of Technology in Moodle Platforms. International Journal of Instruction, 15(1), 1003–1024.

Räsänen, P., Laurillard, D., Käser, T., & von Aster, M. (2019). Perspectives to Technology-Enhanced Learning and Teaching in Mathematical Learning Difficulties. In A. Fritz, V. G. Haase, & P. Räsänen (Eds), International Handbook of Mathematical Learning Difficulties (pp. 733–754). Springer International Publishing. https://doi.org/10.1007/978-3-319-97148-3_42

Revelle, W. (2024). psych: Procedures for Psychological, Psychometric, and Personality Research (Version 2.5.6) [Computer software]. https://cran.r-project.org/web/packages/psych/index.html

Ross, J. A., Scott, G., & Bruce, C. D. (2012). The Gender Confidence Gap in Fractions Knowledge: Gender Differences in Student Belief–Achievement Relationships. School Science and Mathematics, 112(5), 278–288. https://doi.org/10.1111/j.1949-8594.2012.00144.x

Rozgonjuk, D., Kraav, T., Mikkor, K., Orav-Puurand, K., & Täht, K. (2020). Mathematics anxiety among STEM and social sciences students: The roles of mathematics self-efficacy, and deep and surface approach to learning. International Journal of STEM Education, 7(1), 46. https://doi.org/10.1186/s40594-020-00246-z

Rozgonjuk, D., Täht, K., & Vassil, K. (2021). Internet use at and outside of school in relation to low- and high-stakes mathematics test scores across 3 years. International Journal of STEM Education, 8(1), 27. https://doi.org/10.1186/s40594-021-00287-y

Rutherford, T., Liu, A. S., Lam, A. S., & Schenke, K. (2020). Impact on mathematics self-beliefs from a mastery-based mathematics software. Journal of Research on Technology in Education, 52(1), 79–94. https://doi.org/10.1080/15391523.2019.1689210

Şanli, C. (2021). The Relation Between Task Value, Test Anxiety and Academic Self-Efficacy: A Moderation Analysis in High School Geography Course. Participatory Educational Research, 8(1), 265–278. https://doi.org/10.17275/per.21.15.8.1

Saqr, M., López-Pernas, S., Helske, S., & Hrastinski, S. (2023). The longitudinal association between engagement and achievement varies by time, students’ profiles, and achievement state: A full program study. Computers & Education, 199, 104787. https://doi.org/10.1016/j.compedu.2023.104787

Schweinle, A., Meyer, D. K., & Turner, J. C. (2006). Striking the Right Balance: Students’ Motivation and Affect in Elementary Mathematics. The Journal of Educational Research, 99(5), 271–294. https://doi.org/10.3200/JOER.99.5.271-294

Soffer, T., & Cohen, A. (2019). Students’ engagement characteristics predict success and completion of online courses. Journal of Computer Assisted Learning, 35(3), 378–389. https://doi.org/10.1111/jcal.12340

Street, K. E. S., Malmberg, L.-E., & Stylianides, G. J. (2022). Changes in Students’ Self-Efficacy When Learning a New Topic in Mathematics: A Micro-Longitudinal Study. Educational Studies in Mathematics, 111(3), 515–541. https://doi.org/10.1007/s10649-022-10165-1

Sydänmaanlakka, A., Häsä, J., Holm, M. E., & Hannula, M. S. (2024). Mathematics-related achievement emotions – Interaction between learning environment and students’ mathematics performance. Learning and Individual Differences, 113, 102486. https://doi.org/10.1016/j.lindif.2024.102486

von der Embse, N., Barterian, J., & Segool, N. (2013). Test Anxiety Interventions for Children and Adolescents: A Systematic Review of Treatment Studies from 2000–2010. Psychology in the Schools, 50(1), 57–71. https://doi.org/10.1002/pits.21660

von der Embse, N., Jester, D., Roy, D., & Post, J. (2018). Test anxiety effects, predictors, and correlates: A 30-year meta-analytic review. Journal of Affective Disorders, 227, 483–493. https://doi.org/10.1016/j.jad.2017.11.048

Wang, Q., & Mousavi, A. (2023). Which log variables significantly predict academic achievement? A systematic review and meta-analysis. British Journal of Educational Technology, 54(1), 142–191. https://doi.org/10.1111/bjet.13282

Xu, Y. J., Cheng, Q., & Wu, Y. (2026). How self-concept, self-efficacy, and grit contribute to gender differences in middle school mathematics learning in Shanghai: An analysis of global teaching insights data. Asian Journal for Mathematics Education, 5(1), 51–71. https://doi.org/10.1177/27527263251405886

Youn, S., Moll, A. J., & Berg, S. A. (2010). The Role of Intrinsic Goal Orientation, Self-Efficacy, and E-Learning Practice in Engineering Education. 10(1), 16.

Zhuofan, H., Hidayat, R., & Ayub, A. F. M. (2024). The mediating effect of engagement in the relationship between self-efficacy and perceived learning in the online mathematics environment among Chinese students. Discover Sustainability, 5(1), 469. https://doi.org/10.1007/s43621-024-00586-8

Zimmerman, B. J. (2000). Self-Efficacy: An Essential Motive to Learn. Contemporary Educational Psychology, 25(1), 82–91. https://doi.org/10.1006/ceps.1999.1016

Živković, M., Pellizzoni, S., Doz, E., Cuder, A., Mammarella, I., & Passolunghi, M. C. (2023). Math self-efficacy or anxiety? The role of emotional and motivational contribution in math performance. Social Psychology of Education. https://doi.org/10.1007/s11218-023-09760-8