Exploring the Relationships Between Motivation and Academic Permormance Among Online and Blended Learners: A Meta-Analytic Review
| Autor: | Andrew Walker, Naomi R. Aguiar, Yu-Chun Kuo |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Online Learning, Vol 28, Iss 4 (2024) |
| Druh dokumentu: | article |
| ISSN: | 2472-5749 2472-5730 |
| DOI: | 10.24059/olj.v28i4.4602 |
| Popis: | In higher education, motivational factors are considered one of “the strongest predictors of academic performance” (Honike et al., 2020, p. 1). A meta-analysis of face-to-face (f2f) courses (Richardson et al., 2012) supports these claims, finding a strong correlation between performance self-efficacy and academic performance (r = 0.59), as well as accounting for 14% of the variation in academic performance using locus of control, performance self-efficacy, and grade goal as predictors. These f2f results are compelling enough that self-efficacy is often used synonymously with online learning in primary research. However, the results of prior f2f meta-analytic reviews have yet to be extended to online and blended learning contexts. We explored student motivation, specifically subscales for attributional style, self-efficacy, achievement goal orientation, self-determination and task value in relation to student academic performance. Informed by 94 outcomes from 52 studies, our results diverge from f2f findings. The highest correlation was mastery avoidance goals (r = 0.22) and academic self-efficacy (r = 0.19) was substantially lower than f2f findings (r = 0.31; r = 0.59) in Richardson et al., (2012). Using a parsimonious model (i.e., delivery mode, learning self-efficacy, and mastery approach goals), students’ average academic performance failed to identify significantly significant predictors. These results call into question the assumption that student motivation is a strong predictor of academic performance in online and blended courses. The lack of strong relationships and the lack of predictive power hold clear implications for researchers, practitioners, and policymakers that assume these relationships are stronger. |
| Databáze: | Directory of Open Access Journals |
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