著者

齋藤 ひとみ 三輪 和久 神崎 奈奈 寺井 仁 小島 一晃 中池 竜一 森田 純哉

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.30, no.3, pp.547-558, 2015-05-01 (Released:2015-05-01)

参考文献数

23

被引用文献数

1

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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.

著者

神崎 奈奈 三輪 和久 寺井 仁 小島 一晃 中池 竜一 森田 純哉 齋藤 ひとみ

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.30, no.3, pp.536-546, 2015-05-01 (Released:2015-05-01)

参考文献数

25

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When people understand an object, they construct a mental model of the object. A mental model is a structural, behavioral, or functional analog representation of a real-world or imaginary situation, event, or process. We conducted a class practice in which newcomers to cognitive science constructed a mental model by implementing and simulating a computational model of cognitive information processing, i.e., a cognitive model. We quantitatively evaluated the learning outcomes of the class. The participants were required to implement a complete cognitive model of subtraction processing. Furthermore, they were required to implement bug models, which are cognitive models with bug rules that cause several types of errors. Pre- and post-tests were performed before and after implementing and using these models, respectively. The results indicate that the class intervention led to the increase of the number of the participants who constructed the correct mental model and promoted more accurate mental simulations. However, the significant effects were confirmed only with participants who correctly completed the bug model, but the effects were limited with those who failed.