AI-assisted audio-learning improves academic achievement through motivation and reading engagement
Artificial intelligence (AI) is transforming education by enabling the creation of innovative learning resources that may cater to diverse learning needs. Students with common forms of neurodiversity, such as ADHD, often face unique challenges in higher education that are not adequately addressed by current educational resources. One potentially helpful resource is audio content, which provides a flexible and accessible supplement to traditional educational materials. While audio content, such as podcasts, is widely popular, its effect on academic achievement remains underexplored. This pre-registered randomized controlled trial investigated the impact of AI-assisted audio-learning modules on academic achievement, with a particular focus on the mediating roles of motivation and reading engagement. Results showed that the audio-learning modules increased student motivation and reading engagement. Importantly, audio-learning driven increases in motivation and reading engagement boosted academic achievement. Furthermore, students with greater ADHD symptom severity particularly benefited from the audio-learning modules, as they played a crucial role in determining course success. Together, this study highlights the potential of AI-assisted audio-learning modules as a valuable tool in digital education environments, catering to diverse learning needs and improving educational outcomes. • AI-assisted audio-learning modules enhance student motivation and reading engagement. • These increases in motivation and reading engagement boosted subsequent academic achievement. • AI-assisted audio-learning modules help mitigate the negative effects of ADHD symptoms on academic achievement. • AI-assisted audio-learning is a valuable tool that supports flexible and diverse learning needs.
Authors
- Anne‐Wil Kramer (ORCID: https://orcid.org/0000-0003-4500-979X)
- Nanda R. Jafarian
Institutions
- University of Amsterdam (NL)
Publication Details
- Journal
- Computers and Education Artificial Intelligence
- Published
- 2024-12-25
- DOI
- https://doi.org/10.1016/j.caeai.2024.100357
- Citations
- 16
- Primary Topic
- Visual and Cognitive Learning Processes
- Type
- article
- Field-Weighted Citation Impact
- 8.12