理論に基づく実験結果の解釈の支援

• 齋藤 ひとみ

  愛知教育大学教育学部

• 三輪 和久

  名古屋大学大学院情報科学研究科

• 神崎 奈奈

  名古屋女子大学短期大学部

• 寺井 仁

  名古屋大学大学院情報科学研究科 JST CREST

• 小島 一晃

  帝京大学ラーニングテクノロジー開発室

• 中池 竜一

  京都大学大学院教育学研究科

• 森田 純哉

  名古屋大学未来社会創造機構

書誌事項

タイトル別名

• Supporting Theory-based Data Interpretation through Model Construction
• 認知科学の授業実践におけるモデル構築の効果に関する検討
• Investigation of Practice in Cognitive Science Class

抄録

Data interpretation based on theory is one of most important skills in scientific discovery learning, but to achieve this process is difficult for learners. In this study, we propose that model construction and execution could support data interpretation based on theory. We used the web-based production system ``DoCoPro'' as an environment for model construction and execution, and we designed and evaluated class practice in cognitive science domain to confirm our ideas. Fifty-three undergraduate students attended the course in Practice 1 in 2012. During class, students constructed a computational model on the process of semantic memory and conducted simulations using their model from which we evaluated any changes in learner interpretation of experimental data from pretest to posttest. The results of comparing pretest with posttest showed that the number of theory-based interpretations increase from pretest to posttest. However, we could not confirm the relationship between students' interpretations and their mental models acquired through learning activities and whether the students could transfer their understanding of theory to other different experimental data. Therefore, we conducted Practice 2 in 2013, in which 39 undergraduate students attended the course. Instruction in Practice 2 was same as in Practice 1. We improved pretest and posttest to assess students' mental model of theory and whether they transfer their understanding to another experiment. Comparing the pretest and posttest results showed that students acquired more sophisticated mental models from pretest to posttest, and they could apply their understanding of theory to their interpretations of near transfer experimental data. The results also indicated that students who shifted their interpretations from non theory-based to theory-based acquired more superior mental models on theory. Finally, we discuss applicability of our findings to scientific education.

収録刊行物

• 人工知能学会論文誌

  人工知能学会論文誌 30 (3), 547-558, 2015

  一般社団法人 人工知能学会

キーワード

• model construction
• cognitive model
• class practice
• theory-based data interpretation
• scientific discovery

詳細情報

• CRID: 1390282680084108928
• NII論文ID: 130005068490
• DOI: 10.1527/tjsai.30.547
• ISSN: 13468030
• ISSN: 13460714
• 本文言語コード: ja
• データソース種別:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• 抄録ライセンスフラグ: 使用不可