Reviewing Learning Tasks through Detecting Specificity in Learning Log Data and Semantic Analysis Based on Information Structure —A Case Study on the Practical Use of Arithmetic Unit Word Problem Posing System: MONSAKUN—

DOI
  • Matsumoto Shimpei
    Faculty of Information and Communications, Hiroshima Institute of Technology
  • Iwai Kengo
    Department of Human Life Studies, Sanyo Women’s College
  • Maeda Kazumasa
    Faculty of Education for Future Generation, International Pacific University
  • Yamamoto Sho
    Faculty of Informatics, Kindai University
  • Hayashi Yusuke
    Graduate School of Advanced Science and Engineering, Hiroshima University
  • Hirashima Tsukasa
    Graduate School of Advanced Science and Engineering, Hiroshima University

Bibliographic Information

Other Title
  • 学習ログデータからの特異性の検出と情報構造に基づく意味的分析による学習課題の再検討 ——単文統合型作問学習支援システムモンサクンの実践データを事例として——

Abstract

<p>MONSAKUN is a software of learning by problem-posing for arithmetic unit word problems. We propose a learning log analysis and visualization method to support reflection activities on the practical use of MONSAKUN. First, we construct a method to convert learning logs into a multidimensional vector and use a clustering algorithm and a visualization method. Then, we apply the proposed method to a large set of log data obtained through practical use in all grades of the same public elementary school. As the analysis results with the proposed method, we concluded the proposed method useful because the proposed method could find some learning tasks that would be inappropriate for the students.</p>

Journal

Keywords

Details 詳細情報について

  • CRID
    1390296666497311488
  • DOI
    10.14926/jsise.40.203
  • ISSN
    21880980
    13414135
  • Text Lang
    ja
  • Data Source
    • JaLC
  • Abstract License Flag
    Disallowed

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