AI 기반 영어평가 연구의 국내 동향과 과제: 종합연구 관점에서의 분석
Current trends and future challenges in AI-based English language assessment research: A synthesis study
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Recently, generative artificial intelligence (GAI) systems, such as ChatGPT, is becoming a buzz word in almost every sector of our society. This innovative technology is being widely applied, used, and researched in various contexts of English language education and assessment. The main goals of the current paper are to: (a) investigate the current trends in research and development on AI-based English language assessments by reviewing, and analyzing, recently published research studies in South Korea; and (b) identify a program of research that urgently needs to be conducted to facilitate wide application and effective use of GAI in the field of English language assessment in the South Korean context. Results of analyses show that there were few research studies that attempted to newly develop AI-based, automated English assessment systems or rigorously investigate the reliability and validity of such AI-based assessment systems. Implications of the major findings are also discussed along with some promising avenues of future research.
Abstract
Recently, generative artificial intelligence (GAI) systems, such as ChatGPT, is becoming a buzz word in almost every sector of our society. This innovative technology is being widely applied, used, and researched in various contexts of English language education and assessment. The main goals of the current paper are to: (a) investigate the current trends in research and development on AI-based English language assessments by reviewing, and analyzing, recently published research studies in South Korea; and (b) identify a program of research that urgently needs to be conducted to facilitate wide application and effective use of GAI in the field of English language assessment in the South Korean context. Results of analyses show that there were few research studies that attempted to newly develop AI-based, automated English assessment systems or rigorously investigate the reliability and validity of such AI-based assessment systems. Implications of the major findings are also discussed along with some promising avenues of future research.