2019 Fiscal Year Research-status Report
Automatic detection of level of students' engagement
| Project/Area Number |
18K18168
|
|---|
| Research Institution | Okayama University |
|---|
Principal Investigator |
Yucel Zeynep 岡山大学, 自然科学研究科, 特任助教 (20586250)
|
|---|
| Project Period (FY) |
2018-04-01 – 2021-03-31
|
| Keywords | E-learning / Attention / Engagement / Behavior |
|---|
| Outline of Annual Research Achievements |
We decided to build empirical models for the four behavioral variables derived from facial landmarks. To that end, we used kernel density estimation. In addition, we considered the extremities of engagement level (fully engaged and completely disengaged) as benchmark states. In that respect, we obtained 8 models corresponding to the pair of each of the four behavioral variables and two benchmark states.
We then proposed a probabilistic method for estimating level of engagement. In that respect, each feature value is evaluated in its two corresponding models representing the benchmark states. Making use of the fact that these are complementary, we computed the probability of engagement.
Our results indicate that, the features provide considerable accuracy for distinguishing the two (benchmark) states.
|
| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
We continued to our analysis on experiment data and achieved satisfactory intermediate outcomes, confirming the efficacy of the proposed features in estimation of engagement level.
|
| Strategy for Future Research Activity |
At the current stage, we handle each behavioral feature in an isolated manner. From now we will search for possibilities to incorporate the evidence obtained from each single feature into a single outcome. To that end, we will investigate the independence of features and build joint distributions, if necessary.
|
Research Products
(10 results)
