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Descriptive Answer Clustering System for Immediate Feedback
Kazutaka Noro, Haruhiko Takase, Hidehiko Kita, Terumine Hayashi, Naoki Morita
37 - 40
Frontiers in Artificial Intelligence and Applications
Volume 162: Supporting Learning Flow through Integrative Technologies
Abstract

In this paper, we discuss a visualization method of answers of a quiz. Though quizzes (especially descriptive answer style) are effective to identify the level of students' understanding, it is hard for lecturers to catch contents of all answers for effective and immediate feedback. We propose a visualization method based on self-organizing map and k-means method and develop a system that classifies answers and allows lecturers to adjust the results for preferable ones quickly.

$35.00 / €27.50 / £22.00
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