The effect of learner-generated digital materials on learners’ deep learning approach and self-efficacy

Enas Mohammad Alwafi ()

Journal of Education and e-Learning Research, 2023, vol. 10, issue 3, 415-420

Abstract: This study aimed to explore the effect of learner-generated digital materials on students’ deep learning approach and self-efficacy. A quasi-experimental design that involves a pre-test, a post-test, a control group and an experiment group was used in this study which involved 51 students (25 students participated in the control group and 26 students participated in the experiment group). A questionnaire was used to measure students’ deep learning approach and self-efficacy. The study found that students in the experimental group improved their deep learning approach and self-efficacy more than students in the control group. Learner-generated digital materials can enhance students’ learning experiences. This study contributes new knowledge about the methods by which learner-generated digital material can be used as a learning approach. It also provides insight on how digital tools can be used to support students learning. This study provides recommendations for employing learner-generated digital materials to engage students in the learning experience.

Keywords: Deep learning; Digital materials; Digital tools; Learner-generated materials; Learning approach; Self-efficacy. (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:aoj:jeelre:v:10:y:2023:i:3:p:415-420:id:4755

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