Learning Mathematics from Examples and by Doing: Enhancing Learning Engagement and Self-efficacy

Authors

  • Yarui Zhang
  • Yikun Li
  • Ziyan Chu
  • Jiangjiang Pu
  • Lei Zhang
  • Tianyong Chen

DOI:

https://doi.org/10.56028/aehssr.8.1.58.2023

Keywords:

adaptive production learning methodology; learning from examples and by doing; learning engagement; academic self-efficacy.

Abstract

Purpose: Numerous empirical studies have confirmed that learning from examples and by doing (LFED) can improve learning efficiency; however, its impact on learning motivation is still unclear. Therefore, this study investigated the effects of LFED on students' mathematics learning performance, academic engagement and academic self-efficacy to explore its effect on Learning motivation. Methods: In a cluster randomized controlled trial, 119 seventh-grade students were randomly assigned to either a four-month LFED group (n=59) or a conventional group (n=60). The interventional group was taught by the LFED method, and the other received a traditional teaching method. Both groups were assessed before and after the intervention to measure academic performance in mathematics, learning engagement, and academic self-efficacy. Results: Repeated-measures ANOVA showed a significant group-by-time effect for academic self-efficacy and learning behavior dimension scores; there were no significant group-by-time effects for math academic performance, learning engagement scores, and related dimension scores. Paired-sample t-tests showed no significant change in self-efficacy scores in the LFED group but a significant decrease in self-efficacy and all related dimensions scores in the conventional group. There was no change in cognitive engagement dimension scores in the LFED group but a substantial decrease in the conventional group. Conclusion: As an adaptive learning method originating from artificial intelligence, LFED had an equal impact on math academic performance as traditional teaching methods. However, LFED was feasible and effective in enhancing students’ academic self-efficacy and cognitive learning engagement.

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Published

2023-10-12