E-Monitoring of Student Engagement Level using Facial Gestures
Student engagement is a key element to ensure effective learning process. In this work, we presented an automatic system for monitoring engagement level from students’ facial gestures. In this way, the tutor can analyse the engagement level of students and improve the teaching method and strategies...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Sukkur IBA University
2023-01-01
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| Series: | Sukkur IBA Journal of Computing and Mathematical Sciences |
| Subjects: | |
| Online Access: | http://journal.iba-suk.edu.pk:8089/SIBAJournals/index.php/sjcms/article/view/983 |
| _version_ | 1797901785235456000 |
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| author | Sohaib Abdullah Ayesha Hakim Abdul Razzaq Nasir Nadeem |
| author_facet | Sohaib Abdullah Ayesha Hakim Abdul Razzaq Nasir Nadeem |
| author_sort | Sohaib Abdullah |
| collection | DOAJ |
| description |
Student engagement is a key element to ensure effective learning process. In this work, we presented an automatic system for monitoring engagement level from students’ facial gestures. In this way, the tutor can analyse the engagement level of students and improve the teaching method and strategies to enhance learning process. There has been extensive research on automated classification of engagement level, but most of these methods rely mainly on expensive eye trackers or physiological sensors in controlled settings. The proposed system monitors and classifies engagement level of student based on YOLO algorithm by determining facial gestures, where students move freely and respond naturally to lectures and surroundings. The proposed model gives a mean average precision (mAP) of 0.65 on a complex dataset where students were allowed to move freely during lecture.
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| first_indexed | 2024-04-10T09:07:24Z |
| format | Article |
| id | doaj.art-1d45bd5bcd884c1988b4258930f717bf |
| institution | Directory Open Access Journal |
| issn | 2520-0755 2522-3003 |
| language | English |
| last_indexed | 2024-04-10T09:07:24Z |
| publishDate | 2023-01-01 |
| publisher | Sukkur IBA University |
| record_format | Article |
| series | Sukkur IBA Journal of Computing and Mathematical Sciences |
| spelling | doaj.art-1d45bd5bcd884c1988b4258930f717bf2023-02-21T05:17:16ZengSukkur IBA UniversitySukkur IBA Journal of Computing and Mathematical Sciences2520-07552522-30032023-01-016210.30537/sjcms.v6i2.983E-Monitoring of Student Engagement Level using Facial Gestures Sohaib Abdullah0Ayesha Hakim1Abdul Razzaq2Nasir Nadeem3MNS-University of Agriculture, MultanMuhammad Nawaz Sharif University of Agriculture, MultanMNS-University of Agriculture, MultanMNS-University of Agriculture, Multan Student engagement is a key element to ensure effective learning process. In this work, we presented an automatic system for monitoring engagement level from students’ facial gestures. In this way, the tutor can analyse the engagement level of students and improve the teaching method and strategies to enhance learning process. There has been extensive research on automated classification of engagement level, but most of these methods rely mainly on expensive eye trackers or physiological sensors in controlled settings. The proposed system monitors and classifies engagement level of student based on YOLO algorithm by determining facial gestures, where students move freely and respond naturally to lectures and surroundings. The proposed model gives a mean average precision (mAP) of 0.65 on a complex dataset where students were allowed to move freely during lecture. http://journal.iba-suk.edu.pk:8089/SIBAJournals/index.php/sjcms/article/view/983face detectionfeature extractionYOLOmAPIoU |
| spellingShingle | Sohaib Abdullah Ayesha Hakim Abdul Razzaq Nasir Nadeem E-Monitoring of Student Engagement Level using Facial Gestures Sukkur IBA Journal of Computing and Mathematical Sciences face detection feature extraction YOLO mAP IoU |
| title | E-Monitoring of Student Engagement Level using Facial Gestures |
| title_full | E-Monitoring of Student Engagement Level using Facial Gestures |
| title_fullStr | E-Monitoring of Student Engagement Level using Facial Gestures |
| title_full_unstemmed | E-Monitoring of Student Engagement Level using Facial Gestures |
| title_short | E-Monitoring of Student Engagement Level using Facial Gestures |
| title_sort | e monitoring of student engagement level using facial gestures |
| topic | face detection feature extraction YOLO mAP IoU |
| url | http://journal.iba-suk.edu.pk:8089/SIBAJournals/index.php/sjcms/article/view/983 |
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