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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

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

Automatic detection of students' engagement in online learning settings is a key element to improve the quality of learning and to deliver personalized learning materials to them. Varying levels of engagement exhibited by students in an…

Computer Vision and Pattern Recognition · Computer Science 2021-10-19 Ali Abedi , Shehroz S. Khan

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

With the rise of online and virtual learning, monitoring and enhancing student engagement have become an important aspect of effective education. Traditional methods of assessing a student's involvement might not be applicable directly to…

Machine Learning · Computer Science 2025-10-28 James Thiering , Tarun Sethupat Radha Krishna , Dylan Zelkin , Ashis Kumer Biswas

Common event-triggered state estimation (ETSE) algorithms save communication in networked control systems by predicting agents' behavior, and transmitting updates only when the predictions deviate significantly. The effectiveness in…

Systems and Control · Computer Science 2018-09-28 Friedrich Solowjow , Dominik Baumann , Jochen Garcke , Sebastian Trimpe

We discuss MET, a learning-based algorithm proposed for perceiving a patient's level of engagement during telehealth sessions. We leverage latent vectors corresponding to Affective and Cognitive features frequently used in psychology…

Computer Vision and Pattern Recognition · Computer Science 2023-02-14 Pooja Guhan , Naman Awasthi , and Kathryn McDonald , Kristin Bussell , Dinesh Manocha , Gloria Reeves , Aniket Bera

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

Esports has rapidly emerged as a global phenomenon with an ever-expanding audience via platforms, like YouTube. Due to the inherent complexity nature of the game, it is challenging for newcomers to comprehend what the event entails. The…

Computation and Language · Computer Science 2024-06-14 Thye Shan Ng , Feiqi Cao , Soyeon Caren Han

Multimodal video understanding is crucial for analyzing egocentric videos, where integrating multiple sensory signals significantly enhances action recognition and moment localization. However, practical applications often grapple with…

Computer Vision and Pattern Recognition · Computer Science 2024-04-18 Merey Ramazanova , Alejandro Pardo , Humam Alwassel , Bernard Ghanem

Real-time lower limb movement resistance monitoring is critical for various applications in clinical and sports settings, such as rehabilitation and athletic training. Current methods often face limitations in accuracy, computational…

Signal Processing · Electrical Eng. & Systems 2024-10-29 Buren Batu , Yuanmeng Liu , Tianyi Lyu

Multi-task learning (MTL) is a machine learning technique aiming to improve model performance by leveraging information across many tasks. It has been used extensively on various data modalities, including electronic health record (EHR)…

Machine Learning · Computer Science 2020-07-21 Matthew B. A. McDermott , Bret Nestor , Evan Kim , Wancong Zhang , Anna Goldenberg , Peter Szolovits , Marzyeh Ghassemi

The mental health assessment of middle school students has always been one of the focuses in the field of education. This paper introduces a new ensemble learning network based on BERT, employing the concept of enhancing model performance…

Computation and Language · Computer Science 2024-08-12 Kai Jiang , Honghao Yang , Yuexian Wang , Qianru Chen , Yiming Luo

We propose an approach to Multitask Learning (MTL) to make deep learning models faster and lighter for applications in which multiple tasks need to be solved simultaneously, which is particularly useful in embedded, real-time systems. We…

Computer Vision and Pattern Recognition · Computer Science 2017-11-02 Miquel Martí , Atsuto Maki

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

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

This paper presents our approach for the engagement intensity regression task of EmotiW 2019. The task is to predict the engagement intensity value of a student when he or she is watching an online MOOCs video in various conditions. Based…

Computer Vision and Pattern Recognition · Computer Science 2019-07-09 Kai Wang , Jianfei Yang , Da Guo , Kaipeng Zhang , Xiaojiang Peng , Yu Qiao

Mind-wandering (MW), which usually defined as a lapse of attention, occurs between 20%-40% of the time, has negative effects on our daily life. Therefore, detecting when MW occurs can prevent us from those negative outcomes resulting from…

Signal Processing · Electrical Eng. & Systems 2020-11-30 Yi-Ta Chen , Hsing-Hao Lee , Ching-Yen Shih , Zih-Ling Chen , Win-Ken Beh , Su-Ling Yeh , An-Yeu Wu

Engagement is a key indicator of the quality of learning experience, and one that plays a major role in developing intelligent educational interfaces. Any such interface requires the ability to recognise the level of engagement in order to…

Computer Vision and Pattern Recognition · Computer Science 2019-07-09 Omid Mohamad Nezami , Mark Dras , Len Hamey , Deborah Richards , Stephen Wan , Cecile Paris

Students' engagements reflect their level of involvement in an ongoing learning process which can be estimated through their interactions with a computer-based learning or assessment system. A pre-requirement for stimulating student…

Computers and Society · Computer Science 2024-03-12 R. Maqsood , P. Ceravolo , C. Romero , S. Ventura
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