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Estimation of student's engagement based on the posture

Published: 09 September 2019 Publication History

Abstract

It is important for teachers to grasp students' engagement in order to improve the quality of lectures. However, in the e-learning environment, there is no teacher to grasp the students' engagement and it may cause ineffective learning. The purpose of this study is to grasp the students' engagement by using a pressure mat and web camera. We recorded students' postural data, that is upper body pressure distribution and upper body pose, during e-learning lectures. Then we extracted 38 features from upper body pressure distribution and 33 features from upper body pose for every minute, selected proper features and trained classifiers to estimate whether he or she was engaged in the lecture. As a result, the average accuracy was 79.3% for student-dependent estimation. This result shows it is possible to predict the student's engagement automatically.

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Andrea Kleinsmith and Nadia Bianchi-Berthouze. 2007. Recognizing affective dimensions from body posture. In International conference on affective computing and intelligent interaction. Springer, 48--58.
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Cited By

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  • (2024)Implementing and Assessing a Teaching Mode Based on Smart Education in English Literature TeachingInternational Journal of Web-Based Learning and Teaching Technologies10.4018/IJWLTT.33648419:1(1-18)Online publication date: 18-Jan-2024
  • (2024)Dialogue cross-enhanced central engagement attention model for real-time Engagement estimationProceedings of the Thirty-Third International Joint Conference on Artificial Intelligence10.24963/ijcai.2024/353(3187-3195)Online publication date: 3-Aug-2024
  • (2023)DCTM: Dilated Convolutional Transformer Model for Multimodal Engagement Estimation in ConversationProceedings of the 31st ACM International Conference on Multimedia10.1145/3581783.3612857(9521-9525)Online publication date: 26-Oct-2023
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        cover image ACM Conferences
        UbiComp/ISWC '19 Adjunct: Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers
        September 2019
        1234 pages
        ISBN:9781450368698
        DOI:10.1145/3341162
        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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        Publication History

        Published: 09 September 2019

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        Author Tags

        1. e-learning
        2. education
        3. engagement
        4. posture
        5. pressure mat

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        Overall Acceptance Rate 764 of 2,912 submissions, 26%

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        View all
        • (2024)Implementing and Assessing a Teaching Mode Based on Smart Education in English Literature TeachingInternational Journal of Web-Based Learning and Teaching Technologies10.4018/IJWLTT.33648419:1(1-18)Online publication date: 18-Jan-2024
        • (2024)Dialogue cross-enhanced central engagement attention model for real-time Engagement estimationProceedings of the Thirty-Third International Joint Conference on Artificial Intelligence10.24963/ijcai.2024/353(3187-3195)Online publication date: 3-Aug-2024
        • (2023)DCTM: Dilated Convolutional Transformer Model for Multimodal Engagement Estimation in ConversationProceedings of the 31st ACM International Conference on Multimedia10.1145/3581783.3612857(9521-9525)Online publication date: 26-Oct-2023
        • (2023)Multi-modal Affect Detection Using Thermal and Optical Imaging in a Gamified Robotic ExerciseInternational Journal of Social Robotics10.1007/s12369-023-01066-116:5(981-997)Online publication date: 31-Oct-2023
        • (2022)Learning Analytics Based on Wearable Devices: A Systematic Literature Review From 2011 to 2021Journal of Educational Computing Research10.1177/0735633121106478060:6(1514-1557)Online publication date: 12-Feb-2022
        • (2022)Assessing Student Engagement in Classroom Environment Using Computer Vision and Machine Learning Techniques: Case StudyInternational Conference on Innovative Computing and Communications10.1007/978-981-19-2535-1_61(733-747)Online publication date: 23-Sep-2022
        • (2021)A Computer-Vision Based Engagement Evaluation System for More Effective Learning DesignProceedings of the 22nd Annual Conference on Information Technology Education10.1145/3450329.3478312(57-58)Online publication date: 6-Oct-2021
        • (2021)Estimation of Learners’ Engagement Using Face and Body Features by Transfer LearningArtificial Intelligence in HCI10.1007/978-3-030-77772-2_36(541-552)Online publication date: 3-Jul-2021
        • (2020)Estimation of wakefulness in video-based lectures based on multimodal data fusionAdjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers10.1145/3410530.3414386(50-53)Online publication date: 10-Sep-2020

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