期刊名称：Australasian Journal of Educational Technology
印刷版ISSN：1449-3098
电子版ISSN：1449-5554
出版年度：2022
卷号：38
期号：3
页码：22-42
DOI：10.14742/ajet.7526
语种：English
出版社：Australasian Society for Computers in Learning in Tertiary Education
摘要：Artificial intelligence (AI) in higher education has proven to be a useful learning technology; it can help learners achieve positive learning outcomes in the learning environment and can also enable teachers to better understand learners’ learning status and further improve their teaching strategies. This study reviewed the top 50 AI in higher education studies in the Web of Science database from the perspective of highly cited papers and based on a technology-based learning model. The results show that predictions of learners’ learning status (including dropout and retention, student models, and academic achievement) are most frequently discussed in the AI in higher education studies; AI technology is most commonly applied in engineering (including computer courses); AI technologies most often play the role of profiling and prediction in higher education, followed by intelligent tutoring systems and assessment and evaluation. In terms of research issues, the most frequently discussed issues are learning behaviour, accuracy, sensitivity and precision, cognition and affect. Learners’ higher order thinking skills, collaboration or communication, self-efficacy or confidence and skills are less frequently discussed in AI in higher education studies. Accordingly, we propose potential research issues and practitioner notes for AI in higher education as a reference for researchers, educators and decision-makers. Implications for practice or policy: Higher education practitioners and researchers need to be aware of the latest developments in the research and practice of AI in higher education. Teachers need to understand the role they can play in teaching and learning practices through AI technology and how to use it to assist learners. It is important for administrators of educational institutions to understand the challenges teachers face in their teaching practices with AI technology and to develop measures to support them.
关键词：artificial intelligence;higher education;profiling and prediction;intelligent tutoring systems;assessment and evaluation;adaptive systems and personalization
