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| The Journal of Asia TEFL |
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  Current Issue |
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Go List
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| Volume 21 Number 2, Spring 2024, Pages 270-519 |
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Topic Trends Analysis in Chatbot-Related Studies Using Topic Modeling Techniques: Insights from South Korean English Pedagogy
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Hee-Kyung Lee & Myunghwan Hwang
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This study aimed to investigate the specific topics of scholarly inquiries related to a chatbot within the domain of English pedagogy in South Korea and to track the changes in these topics over time. To achieve this goal, rigorous criteria were established to screen and gather relevant literature, resulting in the selection of 93 scholarly articles. From these articles, titles and abstracts were extracted and analyzed using topic modeling techniques. The findings of this investigation are as follows: first, it was observed that most chatbot-related scholarly articles in Korea predominantly involved students as subjects, and the types of chatbots used reflect sensitivity to current technological trends. Secondly, the topic modeling analysis identified three main topics: "the multifaceted application of chatbots for various purposes (Topic 1)," "understanding the impacts and perceptions of chatbot use (Topic 2)," and "chatbot-centric tasks, the development of task-specific chatbots, and learner-chatbot interactions (Topic 3)." Lastly, the temporal trajectory of these topics revealed a noticeable increase in the proportion of Topic 1, a decrease in Topic 2, and a consistently low frequency of Topic 3. Despite being limited to the context of South Korean English pedagogy, these insights provide several academic implications. Specifically, the findings can help researchers better understand and identify future research areas within and beyond the South Korean English education context.
Keywords: AI chatbots, chatbot-assisted language learning, keyword analysis, topic modeling, trend analysis |
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The Journal of Asia TEFL
