Effects of a Digital Math Training Intervention on Self-Efficacy: Can Clipart Explainers Support Learners?

In the mathematics domain, learning from worked examples is a best practice method for initial skill acquisition. However, open questions refer to effective digital training interventions in the field. Subject to these questions are the potential effects of self-explanations on self-efficacy, and th...

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Bibliographic Details
Published inInternational Journal of Innovation in Science and Mathematics Education Vol. 30; no. 4
Main Authors Hefter, Markus H., Vom Hofe, Rudolf, Berthold, Kirsten
Format Journal Article
LanguageEnglish
Published Sydney University of Sydney 2022
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ISSN2200-4270
2200-4270
DOI10.30722/IJISME.30.04.003

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Summary:In the mathematics domain, learning from worked examples is a best practice method for initial skill acquisition. However, open questions refer to effective digital training interventions in the field. Subject to these questions are the potential effects of self-explanations on self-efficacy, and the role of clip art explainers currently in vogue (cartoon teachers plus explanations in speech bubbles). We thus developed and field-tested a short-term (approximately 45 minutes) digital training intervention on mathematical proportionality with 113 German secondary school students (Mage: 14.12 years). We applied a quantitative experimental research design to analyse learning processes and outcomes with tests and questionaires. To investigate the potential supportive effects of the clipart explainers, we compared two versions of our intervention: with clip art explainers (clipart condition) and without them (control condition). Our training intervention revealed a significant positive within-subjects effect on the learners’ mathematical self-efficacy related to proportionality tasks. The clipart explainers had a significant negative between-subject effect on the subjective difficulty of the instructional material—with no indications of being detrimental to learning. Finally, we detected self-explanation quality and task engagement to be significant predictors for learning outcomes. Our findings underscore the importance of having learners deeply process the given materials.
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ISSN:2200-4270
2200-4270
DOI:10.30722/IJISME.30.04.003