발간년도 : [2024]
| 논문정보 |
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| 논문명(한글) |
[Vol.19, No.3] Evaluating ESL Speaking Assessments: A Comparative Analysis Between Traditional and AI-Assisted Methods |
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| 논문투고자 |
John Edward Padilla, Kang-Hee Lee |
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| 논문내용 |
This paper conducts a thorough comparison between traditional assessment methods and AI-powered tools within the context of an ESL school, specifically focusing on evaluating English speaking skills. The aim is to evaluate the precision, usability, and accessibility of a newly proposed AI-assisted assessment method that incorporates technologies from platforms like YouTube and Grammarly, emphasizing that it does not require complex implementation or involve prohibitive costs. Our investigation thoroughly examines the accuracy and reliability of these AI technologies in accurately determining language proficiency among ESL learners. This paper provides detailed insights into both the potential and the limitations of current AI tools for precise evaluation of language skills. Our findings indicate that the AI-powered approach generally yields results that are comparable to those of traditional methods. This underscores the potential of the proposed AI tools to both standardize and streamline the assessment process in educational contexts. By integrating AI tools that are freely accessible, such as those offered by YouTube for video content and Grammarly for text analysis, this method proposes a cost-effective and scalable solution for ESL programs. Such integration is poised to revolutionize assessment practices by significantly enhancing both reliability and accessibility, potentially leading to widespread adoption in educational settings across the globe. |
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