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An Analysis of Artificial Intelligence Education Research Trends Based on Topic Modeling

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2024, 29(2), pp.197-209
  • DOI : 10.9708/jksci.2024.29.02.197
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : January 8, 2024
  • Accepted : February 19, 2024
  • Published : February 29, 2024

You-Jung Ko 1

1목원대학교

Accredited

ABSTRACT

This study aimed to analyze recent research trends in Artificial Intelligence (AI) education within South Korea with the overarching objective of exploring the future direction of AI education. For this purpose, an analysis of 697 papers related to AI education published in Research Information Sharing Service (RISS) from 2016 to November 2023 were analyzed using word cloud and Latent Dirichlet Allocation (LDA) topic modeling technique. As a result of the analysis, six major topics were identified: generative AI utilization education, AI ethics education, AI convergence education, teacher perceptions and roles in AI utilization, AI literacy development in university education, and AI-based education and research directions. Based on these findings, I proposed several suggestions, (1) including expanding the use of generative AI in various subjects, (2) establishing ethical guidelines for AI use, (3) evaluating the long-term impact of AI education, (4) enhancing teachers' ability to use AI in higher education, (5) diversifying the curriculum of AI education in universities, (6) analyzing the trend of AI research, and developing an educational platform.

Citation status

* References for papers published after 2023 are currently being built.