Evaluation of Students’ Learning Engagement in Online Classes Based on Multimodal Vision Perspective
The method of evaluating student engagement in online classrooms can provide a timely alert to learners who are distracted, effectively improving classroom learning efficiency. Based on data from online classroom scenarios, a cascaded analysis network model integrating gaze estimation, facial expres...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-12-01
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| Series: | Electronics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-9292/13/1/149 |
| _version_ | 1797358956799066112 |
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| author | Yongfeng Qi Liqiang Zhuang Huili Chen Xiang Han Anye Liang |
| author_facet | Yongfeng Qi Liqiang Zhuang Huili Chen Xiang Han Anye Liang |
| author_sort | Yongfeng Qi |
| collection | DOAJ |
| description | The method of evaluating student engagement in online classrooms can provide a timely alert to learners who are distracted, effectively improving classroom learning efficiency. Based on data from online classroom scenarios, a cascaded analysis network model integrating gaze estimation, facial expression recognition, and action recognition is constructed to recognize student attention and grade engagement levels, thereby assessing the level of student engagement in online classrooms. Comparative experiments with the LRCN model, C3D network model, etc., demonstrate the effectiveness of the cascaded analysis network model in evaluating engagement, with evaluations being more accurate than other models. The method of evaluating student engagement in online classrooms compensates for the shortcomings of single-method evaluation models in detecting student engagement in classrooms. |
| first_indexed | 2024-03-08T15:08:46Z |
| format | Article |
| id | doaj.art-b43827c01d044008aa8314f27095e7b7 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-08T15:08:46Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-b43827c01d044008aa8314f27095e7b72024-01-10T14:54:46ZengMDPI AGElectronics2079-92922023-12-0113114910.3390/electronics13010149Evaluation of Students’ Learning Engagement in Online Classes Based on Multimodal Vision PerspectiveYongfeng Qi0Liqiang Zhuang1Huili Chen2Xiang Han3Anye Liang4College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, ChinaCollege of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, ChinaCollege of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, ChinaCollege of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, ChinaCollege of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, ChinaThe method of evaluating student engagement in online classrooms can provide a timely alert to learners who are distracted, effectively improving classroom learning efficiency. Based on data from online classroom scenarios, a cascaded analysis network model integrating gaze estimation, facial expression recognition, and action recognition is constructed to recognize student attention and grade engagement levels, thereby assessing the level of student engagement in online classrooms. Comparative experiments with the LRCN model, C3D network model, etc., demonstrate the effectiveness of the cascaded analysis network model in evaluating engagement, with evaluations being more accurate than other models. The method of evaluating student engagement in online classrooms compensates for the shortcomings of single-method evaluation models in detecting student engagement in classrooms.https://www.mdpi.com/2079-9292/13/1/149computer visiongaze estimationfacial expression recognitionaction recognitiononline classroomlearning engagement |
| spellingShingle | Yongfeng Qi Liqiang Zhuang Huili Chen Xiang Han Anye Liang Evaluation of Students’ Learning Engagement in Online Classes Based on Multimodal Vision Perspective Electronics computer vision gaze estimation facial expression recognition action recognition online classroom learning engagement |
| title | Evaluation of Students’ Learning Engagement in Online Classes Based on Multimodal Vision Perspective |
| title_full | Evaluation of Students’ Learning Engagement in Online Classes Based on Multimodal Vision Perspective |
| title_fullStr | Evaluation of Students’ Learning Engagement in Online Classes Based on Multimodal Vision Perspective |
| title_full_unstemmed | Evaluation of Students’ Learning Engagement in Online Classes Based on Multimodal Vision Perspective |
| title_short | Evaluation of Students’ Learning Engagement in Online Classes Based on Multimodal Vision Perspective |
| title_sort | evaluation of students learning engagement in online classes based on multimodal vision perspective |
| topic | computer vision gaze estimation facial expression recognition action recognition online classroom learning engagement |
| url | https://www.mdpi.com/2079-9292/13/1/149 |
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