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In education and intervention programs, user engagement has been identified as a major factor in successful program completion. Automatic measurement of user engagement provides helpful information for instructors to meet program objectives…

Computer Vision and Pattern Recognition · Computer Science 2022-11-08 Ali Abedi , Shehroz Khan

Understanding student behavior in the classroom is essential to improve both pedagogical quality and student engagement. Existing methods for predicting student engagement typically require substantial annotated data to model the diversity…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Ahmed Abdelkawy , Ahmed Elsayed , Asem Ali , Aly Farag , Thomas Tretter , Michael McIntyre

Considering learner engagement has a mutual benefit for both learners and instructors. Instructors can help learners increase their attention, involvement, motivation, and interest. On the other hand, instructors can improve their…

Computer Vision and Pattern Recognition · Computer Science 2024-05-08 Somayeh Malekshahi , Javad M. Kheyridoost , Omid Fatemi

Engagement, which links to attentional, emotional, and cognitive dimensions, plays an important role in learning. In online and video-based learning environments, learners often need to regulate their own interactions with instructional…

Human-Computer Interaction · Computer Science 2026-05-05 Zikang Leng , Edan Eyal , Yingtian Shi , Jiaman He , Yaqi Liu , Thomas Plötz

Student engagement plays a crucial role in the successful delivery of educational programs. Automated engagement measurement helps instructors monitor student participation, identify disengagement, and adapt their teaching strategies to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Sadaf Safa , Ali Abedi , Shehroz S. Khan

With the increase of distance learning, in general, and e-learning, in particular, having a system capable of determining the engagement of students is of primordial importance, and one of the biggest challenges, both for teachers,…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Prabin Sharma , Shubham Joshi , Subash Gautam , Sneha Maharjan , Salik Ram Khanal , Manuel Cabral Reis , João Barroso , Vítor Manuel de Jesus Filipe

In this paper, we propose a novel technique for measuring behavioral engagement through students' actions recognition. The proposed approach recognizes student actions then predicts the student behavioral engagement level. For student…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Ahmed Abdelkawy , Aly Farag , Islam Alkabbany , Asem Ali , Chris Foreman , Thomas Tretter , Nicholas Hindy

Engagement in virtual learning is crucial for a variety of factors including student satisfaction, performance, and compliance with learning programs, but measuring it is a challenging task. There is therefore considerable interest in…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Ali Abedi , Shehroz S. Khan

Student engagement is an important factor in meeting the goals of virtual learning programs. Automatic measurement of student engagement provides helpful information for instructors to meet learning program objectives and individualize…

Computer Vision and Pattern Recognition · Computer Science 2023-02-07 Ali Abedi , Shehroz S. Khan

In this paper, we introduce a new dataset for student engagement detection and localization. Digital revolution has transformed the traditional teaching procedure and a result analysis of the student engagement in an e-learning environment…

Computer Vision and Pattern Recognition · Computer Science 2018-06-28 Amanjot Kaur , Aamir Mustafa , Love Mehta , Abhinav Dhall

Student engagement is a key construct for learning and teaching. While most of the literature explored the student engagement analysis on computer-based settings, this paper extends that focus to classroom instruction. To best examine…

Computer Vision and Pattern Recognition · Computer Science 2024-10-28 Ömer Sümer , Patricia Goldberg , Sidney D'Mello , Peter Gerjets , Ulrich Trautwein , Enkelejda Kasneci

Engagement detection in online learning environments is vital for improving student outcomes and personalizing instruction. We present ViBED-Net (Video-Based Engagement Detection Network), a novel deep learning framework designed to assess…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Prateek Gothwal , Deeptimaan Banerjee , Ashis Kumer Biswas

We propose a multimodal approach for detection of students' behavioral engagement states (i.e., On-Task vs. Off-Task), based on three unobtrusive modalities: Appearance, Context-Performance, and Mouse. Final behavioral engagement states are…

Human-Computer Interaction · Computer Science 2019-01-18 Nese Alyuz , Eda Okur , Utku Genc , Sinem Aslan , Cagri Tanriover , Asli Arslan Esme

In recent times, online education and the usage of video-conferencing platforms have experienced massive growth. Due to the limited scope of a virtual classroom, it may become difficult for instructors to analyze learners' attention and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Sharva Gogawale , Madhura Deshpande , Parteek Kumar , Irad Ben-Gal

Engagement is an essential indicator of the Quality-of-Learning Experience (QoLE) and plays a major role in developing intelligent educational interfaces. The number of people learning through Massively Open Online Courses (MOOCs) and other…

Computer Vision and Pattern Recognition · Computer Science 2022-04-14 Sarthak Batra , Hewei Wang , Avishek Nag , Philippe Brodeur , Marianne Checkley , Annette Klinkert , Soumyabrata Dev

This study presents high-throughput, real-time multi-agent affective computing framework designed to enhance classroom learning through emotional state monitoring. As large classroom sizes and limited teacher student interaction…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Hai Nguyen , Hieu Dao , Hung Nguyen , Nam Vu , Cong Tran

To investigate the detection of students' behavioral engagement (On-Task vs. Off-Task), we propose a two-phase approach in this study. In Phase 1, contextual logs (URLs) are utilized to assess active usage of the content platform. If there…

Computers and Society · Computer Science 2019-01-21 Eda Okur , Nese Alyuz , Sinem Aslan , Utku Genc , Cagri Tanriover , Asli Arslan Esme

Asynchronous video learning, including massive open online courses (MOOCs), offers flexibility but often lacks students' affective engagement. This study examines how teachers' verbal and nonverbal vocal emotive expressions influence…

Human-Computer Interaction · Computer Science 2026-05-19 Hung-Yue Suen , Yu-Sheng Su

The increasing adoption of smart classroom technologies in higher education has mainly focused on automating attendance, with limited attention given to students' emotional and cognitive engagement during lectures. This limits instructors'…

Artificial Intelligence · Computer Science 2026-01-14 Keith Ainebyona , Ann Move Oguti , Joseph Walusimbi , Ritah Kobusingye

The COVID-19 pandemic and the internet's availability have recently boosted online learning. However, monitoring engagement in online learning is a difficult task for teachers. In this context, timely automatic student engagement…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Sandeep Mandia , Kuldeep Singh , Rajendra Mitharwal , Faisel Mushtaq , Dimpal Janu
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