Artificial Intelligence in Education: a Systematic Literature Review

Zouheir Boussouf, Hanae Amrani, Mouna Zerhouni Khal and Fouad Daidai

Data and Metadata, 2024, vol. 3, 288

Abstract: The article explores the increasing influence of artificial intelligence (AI) in education, addressing contemporary challenges and highlighting its significance in refining teaching methods and enhancing learning efficiency. It is a structured literature review that systematically analyzes existing literature on AI in education, drawing insights from prominent researchers to understand current and future trends. Four key questions guide the analysis: the relationship between education and AI, their interaction, AI's contribution to educational evolution, and research challenges. The study employs a systematic review of literature, focusing on works by eminent scholars such as Lee, Memarian, and Yuan, selected from the Scopus database spanning from 1986 to 2024. It follows a structured approach to gather and analyze data from selected studies. The article progresses by presenting an introduction to the topic, outlining the methodology, and summarizing and analyzing key findings from selected literature. It explores the intrinsic relationship between education and AI, their interaction, and AI's role in evolving the educational process. Major findings underscore the importance of a cautious and ethical approach to integrating AI in education. Despite its potential benefits, challenges and shortcomings in current research are acknowledged, urging for further exploration and consideration of ethical implications

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:dbk:datame:v:3:y:2024:i::p:288:id:1056294dm2024288

DOI: 10.56294/dm2024288

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