The Current Status of Empirical Research on Deep Learning within the Educational Domain
Deep learning, as an efficient and proactive mode of learning, has garnered extensive attention in the educational domain. This paper systematically reviews the connotations and empirical research status of deep learning, aiming to provide references and insights for subsequent studies. Initially, the connotations of deep learning are thoroughly explored from aspects such as conceptual definition, characteristic analysis, and its correlation with cognitive theories, thereby clarifying its pivotal role in education. Subsequently, the themes, methods, contexts, and outcomes of empirical research on deep learning are meticulously analyzed, revealing the current research hotspots and trends, and pointing out the deficiencies and limitations in the existing studies. Finally, a critical review of the existing literature is conducted, and directions for future research are proposed. The research findings indicate that deep learning significantly enhances academic performance, knowledge comprehension, learning experience, and the development of thinking and capabilities. However, further in-depth and extended research is still required, especially in terms of the comprehensiveness of research themes, the richness of research methods, and the diversity of research contexts.
Authors
- Wentao Li (ORCID: https://orcid.org/0000-0001-8980-0909)
Institutions
- Jiangxi Agricultural University (CN)
Publication Details
- Journal
- International Journal of Education and Humanities
- Published
- 2025-01-23
- DOI
- https://doi.org/10.54097/g94w0n14
- Citations
- 1
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 1.69