Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

The Educational Value of Artificial Intelligence in Higher Education: A Ten-Year Systematic Literature Review

Version 1 : Received: 31 October 2023 / Approved: 1 November 2023 / Online: 2 November 2023 (00:04:02 CET)

How to cite: Marengo, A.; Pagano, A.; Soomro, K.; Pange, J. The Educational Value of Artificial Intelligence in Higher Education: A Ten-Year Systematic Literature Review. Preprints 2023, 2023110055. https://doi.org/10.20944/preprints202311.0055.v1 Marengo, A.; Pagano, A.; Soomro, K.; Pange, J. The Educational Value of Artificial Intelligence in Higher Education: A Ten-Year Systematic Literature Review. Preprints 2023, 2023110055. https://doi.org/10.20944/preprints202311.0055.v1

Abstract

With the emergence of artificial intelligence (AI), many aspects of our lives, from how we work to how we interact with each other and the world around us is showing dramatic changes. Education is one of the key areas that may be impacted by the rise of AI. Although a large number of studies have been conducted in recent years to shed light on how AI may influence various dimensions of education, a very little work has been carried out to consolidate and synthesis empirical studies on the application of AI in higher education. The present study reviewed empirical studies published between 2013 and 2022 to 1) examine the characteristics of published research in the field, and 2) to present thorough insights on the promises and challenges of this dramatic technology in higher and professional education. This review included 44 empirical studies published as peer-reviewed journal articles. The results indicated that there is rapid increase in the publications focusing on AI in higher education in last a few years. However, a big proportion of these publications are technically theoretical and conceptual proposals for AI intervention. The areas of AI applications in higher education that are supported by evidence based research are presented. Imperative implications are also highlighted for future research and implementation of AI based interventions in higher education.

Keywords

AI; artificial intelligence; higher education; learning; teaching; systematic review

Subject

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

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