Effects of Error-Based Simulation as a Counterexample for Correcting MIF Misconception

Lecture Notes in Computer Science 10331 巻 90-101 頁 2017 発行
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タイトル ( eng )
Effects of Error-Based Simulation as a Counterexample for Correcting MIF Misconception
作成者
Shinohara Tomoya
Yamada Atsushi
Horiguchi Tomoya
収録物名
Lecture Notes in Computer Science
10331
開始ページ 90
終了ページ 101
抄録
MIF (Motion Implies a Force) misconception is commonly observed in elementary mechanics learning where students think some force is applied to moving objects. This paper reports a practical use of Error-based Simulation (EBS) for correcting students’ MIF misconceptions in a junior high school and a technical college. EBS is a method to generate a phenomenon by using stu-dents’ erroneous idea (e.g., if a student thinks forward force applied to a skater traveling straight on ice at a constant velocity, EBS shows the skater acceler-ates). Such a phenomenon is supposed to work as a counterexample to students’ misconception. In the practice, students first worked on pre-test of five prob-lems (called ‘learning task’), in each of which they drew all the forces applied to objects in a mechanical situation. They then worked on the same problems on system where EBSs were shown based on their answer. They last worked on post-test of the previous plus four new problems (called ‘transfer task’). As a result, in both schools, the numbers of MIF-answers (the erroneous answers supposed due to MIF misconception) in learning task decreased significantly between pre-test and post-test. Effect sizes of the decrease of MIF-answers were larger than that of other erroneous answers. Additionally, the percentages of MIF-answers to the whole erroneous answers in transfer task were much lower than those in learning task. These results suggest learning with EBS not only has the effect on the resolution of MIF misconception, but also promoted the correction of errors in conceptual level.
著者キーワード
Mechanics
MIF misconception
Error-based Simulation
Counter-example
Practical use
内容記述
'Artificial Intelligence in Education' 18th International Conference, AIED 2017, Wuhan, China, June 28 – July 1, 2017, Proceedings
NDC分類
教育 [ 370 ]
言語
英語
資源タイプ 会議発表論文
出版者
Springer
発行日 2017
権利情報
The final authenticated version is available online at https://doi.org/10.1007/978-3-319-61425-0_8.
This is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。
出版タイプ Author’s Original(十分な品質であるとして、著者から正式な査読に提出される版)
アクセス権 オープンアクセス
収録物識別子
[ISSN] 0302-9743
[ISSN] 1611-3349
[ISBN] 978-3-319-61424-3
[ISBN] 978-3-319-61425-0
[DOI] 10.1007/978-3-319-61425-0_8