Abstract
As an exemplary representative of AIGC products, ChatGPT has ushered in new possibilities for the field of education. Leveraging its robust text generation and comprehension capabilities, it has had a revolutionary impact on pedagogy, learning experiences, personalized education and other aspects. However, to date, there has been no comprehensive review of AIGC technology’s application in education. In light of this gap, this study employs a systematic literature review and selects 134 relevant publications on AIGC’s educational application from 4 databases: EBSCO, EI Compendex, Scopus, and Web of Science. The study aims to explore the macro development status and future trends in AIGC’s educational application. The following findings emerge: 1) In the AIGC’s educational application field, the United States is the most active country. Theoretical research dominates the research types in this domain; 2) Research on AIGC’s educational application is primarily published in journals and academic conferences in the fields of educational technology and medicine; 3) Research topics primarily focus on five themes: AIGC technology performance assessment, AIGC technology instructional application, AIGC technology enhancing learning outcomes, AIGC technology educational application’s Advantages and Disadvantages analysis, and AIGC technology educational application prospects. 4) Through Grounded Theory, the study delves into the core advantages and potential risks of AIGC’s educational application, deconstructing the scenarios and logic of AIGC’s educational application. 5) Based on a review of existing literature, the study provides valuable future agendas from both theoretical and practical application perspectives. Discussing the future research agenda contributes to clarifying key issues related to the integration of AI and education, promoting more intelligent, effective, and sustainable educational methods and tools, which is of great significance for advancing innovation and development in the field of education.
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The datasets (Coding results) generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
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Chen, X., Hu, Z. & Wang, C. Empowering education development through AIGC: A systematic literature review. Educ Inf Technol 29, 17485–17537 (2024). https://doi.org/10.1007/s10639-024-12549-7
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DOI: https://doi.org/10.1007/s10639-024-12549-7