| Title: |
Modeling the Incubation Effect Among Students Playing an Educational Game for Physics |
| Source: |
DOI: 10.1007/978-3-319-61425-0_31 |
| Author(s): |
May Marie P. Talandron, Ma. Mercedes T. Rodrigo, and Joseph E. Beck |
| Online Reference: |
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| Abstract: |
We attempted to model the Incubation Effect, a phenomenon in
which a momentary break helps the generation of a solution to a problem,
among students playing Physics Playground. We performed a logistic regression
analysis to predict the outcome of the incubation using a genetic algorithm for
feature selection. Out of 14 candidate features, those that significantly predicted
the outcome were total badges earned prior to post-incubation, the problem’s
level of difficulty, total attempts made prior to post-incubation, and time interval
of post-incubation. We found evidence that incubation in the earlier part of the
game is more beneficial than breaks at the later part where students may already
be mentally exhausted. |
| File: |
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| Relevant Principles (APA): |
原理3 学生的认知发展和学习并不受限于固有的发展阶段
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| Notes (Theories): |
问题解决失败后的休息能引起孵化效应，即休息一段时间后能自发的不需要努力的使得知识获得联系从而领悟了问题解决的方法。但现在影响孵化效应的变量还不清楚。 研究得出，学生解决问题的能力，孵化前获得的徽章总数来表示，问题的难度是孵化与孵化成功正相关，孵化或游戏后期的休息，以及孵化后的尝试与孵化成功之间负相关。 |
| Notes (Technologies): |
逻辑回归回归算法，利用遗传算法选取特征建立了孵化效应的模型，准确率77% |
| Notes (Applications): |
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| Notes (Impacts): |
该研究能给智能导学系统的休息的设计提供一定理论基础 |
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