Bibliometric Analysis of Human-Centered AI in Education: Trends, Challenges, and Opportunities
Abstract
The addition of Human-Centered Artificial Intelligence (HCAI) in education presents equal opportunities and challenges, yet there is a lack of comprehensive understanding of how these technologies are being researched and implemented. This study conducts a bibliometric analysis to explore the trends, challenges, and opportunities associated with Human-Centered AI (HCAI) in education, focusing on research articles published in 2021. 233 articles were systematically selected from prominent academic databases, including IEEE Xplore, MDPI, Elsevier, ACM, and ARXIV. The selected articles were rigorously analyzed using VOSviewer and a bibliometric tool that facilitated the examination of co-authorship patterns and keyword trends within the dataset. The analysis revealed the diverse and interdisciplinary system of HCAI research, with significant contributions from leading academic publishers and a wide array of thematic focus areas and AI ethics, as well as student-centered learning and the integration of AI into educational systems. The findings indicate a growing collaborative effort among researchers across the globe, with certain authors and institutions emerging as key contributors to the field. These challenges highlight the critical gaps in current research, suggesting that future studies delve deeper into the long-term implications of HCAI in education and develop strategies to address the identified barriers. This research contributes to the constant dissertations on HCAI by providing a detailed summary of the present national research and contribution and the potential future directions for scholars and practitioners in this field.
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References
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