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Updated: Sep 9, 2025

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教育データに対する可視性グラフ分析: リスクの高いオンライン生徒の予測の可能性とケーススタディ

Hadis Azizi1, Mohammad Sadra Amini1, Sadegh Sulaimany2

  • 1Social and Biological Network Analysis Laboratory (SBNA), Department of Computer Engineering, University of Kurdistan, Sanandaj, Iran.

Scientific reports
|August 31, 2025
PubMed
まとめ

オンライン学習データをグラフに変換して リスクの高い生徒を予測します この教育データマイニングのアプローチは 解釈可能な洞察を提供し ディープラーニングの方法よりも優れています

キーワード:
リスクの高い生徒クリックストリームデータ教育データタイムシリーズ分析視界グラフ視界グラフ解析

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