Meta-analysis of the Subject Matter and Competency Development in Academic Discourse on AI Literacy

Abstract

The purpose of this study is to explore the detailed capabilities, educational issues, and implications of AI literacy through a meta-analysis of the topics of AI literacy in academic discourse and competency development. Based on the results of a meta-analysis of academic discourse on artificial intelligence (AI) literacy between 2018 and 2023, this study explores the specific areas of AI literacy competency and reviews the issues related to AI literacy education. As a result of the analysis, the academic discourse on artificial intelligence literacy was found to be largely divided into four categories: artificial intelligence literacy, data literacy, media literacy, and digital literacy. There was a significant emphasis on the study of artificial intelligence literacy in 2021. Second, AI literacy competency is characterized by proficiency in AI technology, algorithms, data, and machine learning. It encompasses six detailed competencies: AI knowledge, technology, critical thinking, communication, access/utilization, composition/production, and participation. Lastly, when it comes to developing AI literacy competency and addressing education-related issues and tasks, there is a need for an integrated approach that combines technical skills, cultural awareness, introspective abilities, and public debate within the academic community. This includes discussing detailed competencies and segmenting competency subjects. The significance of the study is to determine the path for developing and educating AI literacy competency by examining AI education cases for both students and citizens.