Holistic Framework for accelerated learning by Adapting & Personalizing lesson plan for children based on emotions
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- Dasaka Amarnath
- International Institute of Information Technology, Hyderabad IIIT - Centre for Cognitive Science
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- Surampudi Bapi Raju
- International Institute of Information Technology, Hyderabad IIIT - Centre for Cognitive Science
説明
<p>Affective education is a formal curriculum designed to help children better understand their feelings and respond to challenging situations, thereby transforming themselves and the world around them. Emotions impact the learning ability at multiple levels (Attention, Memory and decision making etc.). Though they have been advancements in terms of the content (Rich multimedia-based lessons etc.) for effective-learning, proportionate advancements have not taken place in the affective-learning domain – for example "How to adapt the learning based on the current mood and situation?”. Can we mitigate the adverse effects of emotions? This problem of learning is especially compounded for university students where each student has flood of information to absorb & assimilate and is constantly under stress, furthermore, Personalized & Real-time/continual mentoring by the teachers to students is not practical. We have developed a framework and prototype which can be used to adapt the learning-content based on the current mood of the student. We achieve this by capturing the real time gestures & facial expressions (based on universal facial expressions of seven emotions – anger, contempt, disgust, fear, joy, sadness, and surprise) and adapt the content shown to mitigate the negative & amplify the positive impacts of emotion. The Task (Chess Puzzles) given to validate the effectiveness of Methods show significant Improvement on sample size of 80 students.</p>
収録刊行物
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- International Symposium on Affective Science and Engineering
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International Symposium on Affective Science and Engineering ISASE2018 (0), 1-7, 2018
日本感性工学会
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キーワード
詳細情報 詳細情報について
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- CRID
- 1390001288085859328
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- ISSN
- 24335428
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- Crossref
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- 抄録ライセンスフラグ
- 使用不可