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http://dx.doi.org/10.15207/JKCS.2022.13.03.011

Error Analysis of Recent Conversational Agent-based Commercialization Education Platform  

Lee, Seungjun (Department of Computer Science and Engineering, Korea University)
Park, Chanjun (Department of Computer Science and Engineering, Korea University)
Seo, Jaehyung (Department of Computer Science and Engineering, Korea University)
Lim, Heuiseok (Department of Computer Science and Engineering, Korea University)
Publication Information
Journal of the Korea Convergence Society / v.13, no.3, 2022 , pp. 11-22 More about this Journal
Abstract
Recently, research and development using various Artificial Intelligence (AI) technologies are being conducted in the field of education. Among the AI in Education (AIEd), conversational agents are not limited by time and space, and can learn more effectively by combining them with various AI technologies such as voice recognition and translation. This paper conducted a trend analysis on platforms that have a large number of users and used conversational agents for English learning among commercialized application. Currently commercialized educational platforms using conversational agent through trend analysis has several limitations and problems. To analyze specific problems and limitations, a comparative experiment was conducted with the latest pre-trained large-capacity dialogue model. Sensibleness and Specificity Average (SSA) human evaluation was conducted to evaluate conversational human-likeness. Based on the experiment, this paper propose the need for trained with large-capacity parameters dialogue models, educational data, and information retrieval functions for effective English conversation learning.
Keywords
Conversation; Agent; Deep Learning; Education Platform; Language Convergence;
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Times Cited By KSCI : 3  (Citation Analysis)
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