Sustainable Education and Digital Transformation
Modeling the role of competence motivation in linking historical mathematical fallibility and student interest in mathematics
Isaac Davor 1 * , Francis Ohene Boateng 1, Stephen Daniels Sarfo 1, Bluemeloph Adoma Kutin 1
More Detail
1 Akenten Appiah Menka University of Skills Training and Entrepreneurial Development, Ghana
* Corresponding Author
Open Access Full Text (PDF)
ARTICLE INFO

Sustainable Education and Digital Transformation, 2027 - Volume 2 Issue 2, Article No: e44674
https://doi.org/10.33902/SEDT.202644674

Article Type: Research Article

Published Online: 27 Sep 2026

Views: 197 | Downloads: 354

ABSTRACT
This study investigates the mediating role of competence motivation in the relationship between exposure to the history of mathematical fallibility and students’ interest in mathematics. A cross-sectional survey design was employed using a quantitative approach. The sample comprised 285 undergraduate students of mathematics education in Ghana. Structural equation modeling and bias-corrected percentile bootstrapping were employed, and the analysis was conducted in AMOS (version 23). The results indicate that historical fallibility has a positive and significant effect on students’ competence, motivation, and interest in mathematics. Competence motivation partially mediated the relationship between the variables. The current study contributes to the existing body of knowledge by filling a gap in the literature. Previous studies have established the relationship between history and interest, but this study isolated fallibility as a motivational variable. The results also indicate that educators should draw on historical accounts of struggles to validate students' errors and foster interest. The findings suggest that integrating narratives of mathematical struggle and historical fallibility into mathematics instruction may contribute to more sustainable forms of mathematics education by promoting long-term student motivation, emotional resilience, and continued engagement with mathematics. The study further implies that humanizing mathematics through historical perspectives can support inclusive and psychologically supportive learning environments within digitally transforming higher education systems.
KEYWORDS
In-text citation: (Davor et al., 2027)
Reference: Davor, I., Ohene Boateng, F., Sarfo, S. D., & Kutin, B. A. (2027). Modeling the role of competence motivation in linking historical mathematical fallibility and student interest in mathematics. Sustainable Education and Digital Transformation, 2(2), e44674. https://doi.org/10.33902/SEDT.202644674
In-text citation: (1), (2), (3), etc.
Reference: Davor I, Ohene Boateng F, Sarfo SD, Kutin BA. Modeling the role of competence motivation in linking historical mathematical fallibility and student interest in mathematics. Sustainable Education and Digital Transformation. 2027;2(2), e44674. https://doi.org/10.33902/SEDT.202644674
In-text citation: (1), (2), (3), etc.
Reference: Davor I, Ohene Boateng F, Sarfo SD, Kutin BA. Modeling the role of competence motivation in linking historical mathematical fallibility and student interest in mathematics. Sustainable Education and Digital Transformation. 2027;2(2):e44674. https://doi.org/10.33902/SEDT.202644674
In-text citation: (Davor et al., 2027)
Reference: Davor, Isaac, Francis Ohene Boateng, Stephen Daniels Sarfo, and Bluemeloph Adoma Kutin. "Modeling the role of competence motivation in linking historical mathematical fallibility and student interest in mathematics". Sustainable Education and Digital Transformation 2027 2 no. 2 (2027): e44674. https://doi.org/10.33902/SEDT.202644674
In-text citation: (Davor et al., 2027)
Reference: Davor, I., Ohene Boateng, F., Sarfo, S. D., and Kutin, B. A. (2027). Modeling the role of competence motivation in linking historical mathematical fallibility and student interest in mathematics. Sustainable Education and Digital Transformation, 2(2), e44674. https://doi.org/10.33902/SEDT.202644674
In-text citation: (Davor et al., 2027)
Reference: Davor, Isaac et al. "Modeling the role of competence motivation in linking historical mathematical fallibility and student interest in mathematics". Sustainable Education and Digital Transformation, vol. 2, no. 2, 2027, e44674. https://doi.org/10.33902/SEDT.202644674
REFERENCES
  • Arthur, Y. D., Appiah, S. K., Amo-Asante, K., & Asare, B. (2022). Modeling student’s interest in mathematics: Role of history of mathematics, peer-assisted learning, and students’ perception. Eurasia Journal of Mathematics, Science and Technology Education, 18(10), em2168. https://doi.org/10.29333/ejmste/12458
  • Asare, B., & Boateng, F. O. (2025). The mediating effect of student motivation on enhancing student math interest through history of mathematics. Contemporary Mathematics and Science Education, 6(2), ep25012. https://doi.org/10.30935/conmaths/16448
  • Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.
  • Blåsjö, V. (2024). Historiography of mathematics from the mathematician’s point of view. In B. Sriraman (Ed.), Handbook of the history and philosophy of mathematical practice (pp. 1127–1148). Springer. https://doi.org/10.1007/978-3-031-40846-5_67
  • Boadu, S. K., & Boateng, F. O. (2024). Enhancing students’ achievement in mathematics education in the 21st century through technology integration, collaborative learning, and student motivation: The mediating role of student interest. Eurasia Journal of Mathematics, Science and Technology Education, 20(11), Article em2534. https://doi.org/10.29333/ejmste/15622
  • Boadu, S. K., & Bonyah, E. (2024). The role of philosophy of mathematics education in mathematics teacher education. Cogent Education, 11(1), Article 2433832. https://doi.org/10.1080/2331186X.2024.2433832
  • Boateng, F. O., Bandoh, S. O., Kwarteng, S., & Lotey, E. K. (2024). Impact of parent interest in mathematics and students’ mathematics interest on student mathematics achievement. Mathematics Education Journal, 8(2), 206–220. https://doi.org/10.22219/mej.v8i2.33182
  • Boateng, F. O., Davor, I., & Manu, C. A. (2026). Innovative teaching methods supported by artificial intelligence and students’ mathematical problem-solving: The mediating role of student engagement. EIKI Journal of Effective Teaching Methods, 4(1), 66–79. https://doi.org/10.59652/7tsj5730
  • Brantlinger, A. (2022). Critical and vocational mathematics: Authentic problems for students from historically marginalized groups. Journal for Research in Mathematics Education, 53(2), 154–172. https://doi.org/10.5951/jresematheduc-2019-0025
  • Bright, A., Welcome, N. B., & Arthur, Y. D. (2024). The effect of using technology in teaching and learning mathematics on student’s mathematics performance: The mediation effect of students’ mathematics interest. Journal of Mathematics and Science Teacher, 4(2), em059. https://doi.org/10.29333/mathsciteacher/14309
  • Carter, J. (2019). Philosophy of mathematical practice—Motivations, themes and prospects. Philosophia Mathematica, 27(1), 1–32. https://doi.org/10.1093/philmat/nkz002
  • Davis, H. A. (2003). Conceptualizing the role and influence of student-teacher relationships on children’s social and cognitive development. Educational Psychologist, 38(4), 207–234. https://doi.org/10.1207/S15326985EP3804_2
  • Davor, I., Asare, C., & Abanamu, A. (2026). Predictors of students’ mathematics problem-solving skills: Feedback, beliefs, learning support, and technology. Sustainable and Pedagogical Technologies, 2(2), Article e43735. https://doi.org/10.33902/SPT.202643735
  • Davor, I., Boateng, F. O., & Akweittey, E. (2026). Modeling the impact of teachers’ digital pedagogical content knowledge (DPACK) on instructional quality and student mathematics achievement. Frontiers in Education, 11, Article 1807792. https://doi.org/10.3389/feduc.2026.1807792
  • Davor, I., Boateng, F. O., & Lotey, E. K. (2025). The mediating role of metacognitive thinking in the relationship between attributional beliefs, academic buoyancy, error-management mindset, and mathematics achievement. European Journal of Mathematics and Science Education, 6(4), 239–253. https://doi.org/10.12973/ejmse.6.4.239
  • Davor, I., Boateng, F. O., Osei-Wusu, F., Osei Bosompem, A., Osei-Tutu, P., & Hamenu, J. (2026). The role of metacognitive awareness as mediator and moderator in the nexus between self-regulated learning and mathematics achievement. Cogent Education, 13(1), Article 2661434. https://doi.org/10.1080/2331186X.2026.2661434
  • Dunn, T. J., Baguley, T., & Brunsden, V. (2014). From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. British Journal of Psychology, 105(3), 399–412. https://doi.org/10.1111/bjop.12046
  • Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53(1), 109–132. https://doi.org/10.1146/annurev.psych.53.100901.135153
  • Felgner, U. (2023). Philosophy of mathematics in antiquity and in modern times (Vol. 62). Springer. https://doi.org/10.1007/978-3-031-27304-9
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
  • Glas, E. (1998). Fallibilism and the use of history in mathematics education. Science & Education, 7(4), 361–379. https://doi.org/10.1023/A:1008695214877
  • Gyasi Alfred, B., Yarhands Dissou, A., & Benjamin Adu, O. (2024). Effects of perceived mathematics connection on mathematics motivation: Mediating role of history of mathematics concepts. International Journal of Mathematics and Mathematics Education, 2(1), 1–14. https://doi.org/10.56855/ijmme.v2i1.898
  • Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
  • Hidi, S., & Renninger, K. A. (2006). The four-phase model of interest development. Educational Psychologist, 41(2), 111–127. https://doi.org/10.1207/s15326985ep4102_4
  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
  • Kalavasis, F., & Moutsios-Rentzos, A. (2023). Re-constructing the image of mathematics through the diversity of the historical journeys of famous mathematicians. In S. Romero Sánchez, A. Serradó Bayés, P. Appelbaum, & G. Aldon (Eds.), The role of the history of mathematics in the teaching/learning process: A CIEAEM sourcebook (pp. 167–187). Springer. https://doi.org/10.1007/978-3-031-29900-1_7
  • Kjeldsen, T. H., & Carter, J. (2014). The role of history and philosophy in university mathematics education. In M. R. Matthews (Ed.), International handbook of research in history, philosophy and science teaching (pp. 837–871). Springer. https://doi.org/10.1007/978-94-007-7654-8_26
  • Marsh, H. W., Guo, J., Dicke, T., Parker, P. D., & Craven, R. G. (2020). Confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM), and set-ESEM: Optimal balance between goodness of fit and parsimony. Multivariate Behavioral Research, 55(1), 102–119. https://doi.org/10.1080/00273171.2019.1602503
  • Raj, K., & Aithal, P. S. (2020). A new concept of circular model of management for achieving sustainable success and growth. International Journal of Management, Technology, and Social Sciences, 1–17. https://doi.org/10.47992/IJMTS.2581.6012.0079
  • Roth, W.-M. (2008). Mathematical cognition and the final report of the National Mathematics Advisory Panel: A critical, cultural-historical activity theoretic analysis. The Mathematics Enthusiast, 5(2–3), 371–386. https://doi.org/10.54870/1551-3440.1116
  • Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54–67. https://doi.org/10.1006/ceps.1999.1020
  • Sterner, P., Pargent, F., Deffner, D., & Goretzko, D. (2024). A causal framework for the comparability of latent variables. Structural Equation Modeling: A Multidisciplinary Journal, 31(5), 747–758. https://doi.org/10.1080/10705511.2024.2339396
  • Wolf, E. J., Harrington, K. M., Clark, S. L., & Miller, M. W. (2013). Sample size requirements for structural equation models. Educational and Psychological Measurement, 73(6), 913–934. https://doi.org/10.1177/0013164413495237
  • Zbiek, R. M., & Conner, A. (2006). Beyond motivation: Exploring mathematical modeling as a context for deepening students’ understandings of curricular mathematics. Educational Studies in Mathematics, 63(1), 89–112. https://doi.org/10.1007/s10649-005-9002-4
LICENSE
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.