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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Paper Title:	Learners Engagement Analysis for E-Learning Platform
Authors Name:	K.Keerthana , Dr.B.Vanathi , D.Pradeep
Unique Id:	IJSDR2003030
Published In:	Volume 5 Issue 3, March-2020
Abstract:	Adaptive learning is an educational method that utilizes computers as an interactive teaching device. In existing most educational agents do not monitor engagement explicitly, but rather assume engagement and feedback by interaction based on the student’s responses to questionnaires, quiz and tasks. Thus, dynamic learner engagement analysis is a first step towards an automated course feedback tool helpful to the instructor for measuring student engagement. In our system, we propose a hybrid architecture system invoking student facial emotion recognition, eye gaze monitoring, head movements identifications based analyzing dynamic student engagement in classroom and towards a specific course at e-learning platforms. Our proposed architecture uses feature extraction algorithms for facial emotion recognition, Haar Cascade for pupil detection and Local Binary Patterns for recognizing head movements. For a machine learning approach and to provide accurate results we propose a Convolutional Neural Network. Experimental results have been implemented using PyCharm IDE.
Keywords:	video processing, e-learning, emotion recognition, eye tracking, head pose identification
Cite Article:	"Learners Engagement Analysis for E-Learning Platform ", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.5, Issue 3, page no.156 - 161, March-2020, Available :http://www.ijsdr.org/papers/IJSDR2003030.pdf
Downloads:	000337067
Publication Details:	Published Paper ID: IJSDR2003030 Registration ID:191466 Published In: Volume 5 Issue 3, March-2020 DOI (Digital Object Identifier): Page No: 156 - 161 Publisher: IJSDR \| www.ijsdr.org ISSN Number: 2455-2631

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