| Project/Area Number |
18K18168
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 62030:Learning support system-related
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| Research Institution | Okayama University |
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Principal Investigator |
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
|
| Budget Amount *help |
¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2020: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2018: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Keywords | Engagement / Attention / Behavior / E-learning |
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| Outline of Final Research Achievements |
The goal of this study is to automatically recognize the level of engagement of the user of an e-learning system based on video data. If the system can recognize the decrease in level of engagement, it may be possible to support the user appropriately.
In this research, we showed that the level of engagement is reflected in the eye movements. In particular, the frequency of blinking and the duration of blinks are found to be negatively correlated with the level of engagement , and the aspect ratio of the eye and the distance between the eye and the screen are found to be positively correlated with the level of engagement. We modeled the relationship between the level of engagement and eye movements, and proposed a probabilistic method for automatic estimation of the level of engagement. It was shown that as the level of engagement increased, so did the model-based estimate of the probability of engagement.
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| Academic Significance and Societal Importance of the Research Achievements |
学術的有意性：顔のランドマークが集中力レベルの優れた指標であることを示した。また,顔のランドマークを自動的推定のため使用できることも示した。
社会的重要性：最近、特にパンデミックによる 、eラーニングがより多くの人々によって使用されており、提案された方法を用いて、そのユーザーのパフォーマンスを向上させる可能性があると考えられている。
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