Developing a Supporting System for Collaborative Learning Utilizing the "Function-Mechanism Hierarchy"

2023 Fiscal Year Final Research Report

• Project/Area Number: 18K13238
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 09070:Educational technology-related
• Research Institution: Shinshu University (2023); Musashino University (2021-2022); Advanced Institute of Industrial Technology (2018-2020)
• Principal Investigator: Ohsaki Ayano 信州大学, 工学部, 特任講師 (50630802)
• Project Period (FY): 2018-04-01 – 2024-03-31
• Keywords: 学習環境デザイン / 協調学習 / データビジュアライゼーション / ラーニングアナリティクス / 量的エスノグラフィー / 学習分析

Outline of Final Research Achievements

Collaborative learning has gained attention as a method to realize active, interactive, and deep learning. However, the design of collaborative learning classrooms often relies heavily on teachers' experience and intuition. To address this issue, this study explored a support method for visualizing the knowledge structure of learning materials in two dimensions: depth and breadth. In addition, it investigated a method for evaluating learning outcomes and processes from the perspective of depth and breadth.
This study confirmed the following three key findings. First, interactive support can effectively assist teachers' thinking processes in the creation of learning materials. Second, analyzing learning outcomes and processes using the two dimensions of depth and breadth of knowledge structure proved useful. Finally, this study indicates the possibility of automated evaluation process using knowledge structure diagrams.

Free Research Field

学習支援システム，ラーニングアナリティクス

Academic Significance and Societal Importance of the Research Achievements

本研究は，従来行われてきた教師の内的な活動としての授業設計検討や評価を可視化し，データに基づいて授業検討を行うことを可能にしたという点で，学術的・社会的な意義をもつ．また，自然言語処理技術の授業設計・評価への適用や質的分析と量的分析の混合アプローチの提案などの成果は，ICT活用が推進されている教育現場における，今後の学習データ分析研究へ貢献すると期待される．