The role of affective learner characteristics for learning about abstract algebra: A multiple linear regression analysis
Veith JM, Girnat B, Bitzenbauer P (2022)
Publication Language: English
Publication Type: Journal article, Original article
Publication year: 2022
Journal
Book Volume: 18
Pages Range: em2157
Journal Issue: 10
Open Access Link: https://www.ejmste.com/article/the-role-of-affective-learner-characteristics-for-learning-about-abstract-algebra-a-multiple-linear-12417
Abstract
Recent research has boosted the inclusion of introductory group theory into secondary and
undergraduate mathematics education due to manifold potentials, e.g., with regards to the
promotion of students’ abstract thinking. However, in addition to research on cognitive processes, learners’ affective characteristics have largely remained unexplored in the context of teaching and learning group theory to date. In this paper, we contribute to closing this gap: We report on an empirical study investigating n=143 students’ affective characteristics within a two-weeks course program - the Hildesheim teaching concept. In our study, this concept was used to introduce pre-service primary teachers into group theory. A multiple linear regression analysis reveals that neither mathematics-specific ability self-concept nor subject interest are significant predictors of the achieved conceptual understanding of group theory after the intervention indicating that group theory is not reserved for only the mathematically interested students or students with a high mathematics-specific self-concept.
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Germany (DE)How to cite
APA:
Veith, J.M., Girnat, B., & Bitzenbauer, P. (2022). The role of affective learner characteristics for learning about abstract algebra: A multiple linear regression analysis. Eurasia Journal of Mathematics, Science and Technology Education, 18(10), em2157. https://doi.org/10.29333/ejmste/12417
MLA:
Veith, Joaquin M., Boris Girnat, and Philipp Bitzenbauer. "The role of affective learner characteristics for learning about abstract algebra: A multiple linear regression analysis." Eurasia Journal of Mathematics, Science and Technology Education 18.10 (2022): em2157.
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