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한국교육공학회

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[Vol.25 No.1] Mingyeong JANG, Hyeonwoo LEE (2024) Using topic modeling-based network visualization and generative AI in online discussions, how learners' perception of usability affects their reflection on feedback
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  • 2024-04-30 19:08:11

This study aims to analyze the impact of learners' usability perceptions of topic modelingbased visual feedback and generative AI interpretation on reflection levels in online discussions. To achieve this, we asked 17 students in the Department of Korean language education to conduct an online discussion. Text data generated from online discussions were analyzed using LDA topic modeling to extract five clusters of related words, or topics. These topics were then visualized in a network format, and interpretive feedback was constructed through generative AI. The feedback was presented on a website and rated highly for usability, with learners valuing its information usefulness. Furthermore, an analysis using the nonparametric Mann-Whitney U test based on levels of usability perception revealed that the group with higher perceived usability demonstrated higher levels of reflection. This suggests that well-designed and user-friendly visual feedback can significantly promote deeper reflection and engagement in online discussions. The integration of topic modeling and generative AI can enhance visual feedback in online discussions, reinforcing the efficacy of such feedback in learning. The research highlights the educational significance of these design strategies and clears a path for innovation. 

 

Keywords : Online discussions, Topic modeling, Generative AI, Learner reflection, Feedback usability. 

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내용

이전글 [Vol.24 No.2] Inah KO, Yeon KIM (2023) The Impact of How Often Students Use Mobile Devices on Their Perceptions of the Usefulness and Convenience of the Devices
다음글 [Vol.25 No.1] Dasom KIM Gyeoun JEONG(2024) Predicting Learning Achievements with Indicators of Perceived Affordances Based on Different Levels of Content Complexity in Video-based Learning
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