An Approach for Learner Categorization Based on Emotions in Intelligent Adaptive E-Learning Environment


  • Myneni Madhu Bala Institute of Aeronautical Engineering, Hyderabad, India
  • Haritha Akkineni P.V.P Siddhartha Institute of Technology, Vijayawada, India
  • Chennupalli Srinivasulu Institute of Aeronautical Engineering, Hyderabad, India



Convolution Neural Network, E learning system, Face emotion recognition


The pandemic across the globe has constrained the change from a conventional face to face to e-learning platforms. The most challenging task during online learning is to be aware and support the emotional side of students. In existing environments, the emotion of the listener consideration is lagging. This can be provided by capturing the emotions of the listener through facial expressions. In general, the most common facial expressions are happy, sad, anger, fear, disgust, neutral and surprise. This knowledge can be used to classify different listeners. Hence in this article, we proposed a novel approach to identify an emotion based learner category in the development of Intelligent Adaptive E-Learning Environment by using Convolution Neural Network. The major work is composed of emotion detection model and learner categorization. The emotion detection model is trained by using a standard FER2013 dataset and it is extended with live streams of learners. The results of emotion detection model are extended to categorize the learners by fusing emotions and comprehend as Active, Evaluative, Passive and Non-Listener. The proposed model is trained using 100 epochs and achieved an accuracy of 94.44% in the training phase. This knowledge helps to interpret learner’s participation in e-learning environment.


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Author Biographies

Myneni Madhu Bala, Institute of Aeronautical Engineering, Hyderabad, India

Myneni Madhu Bala is currently working as a professor and Dean of computational studies at Institute of Aeronautical Engineering, Hyderabad. She received her Ph.D in Computer Science and Engineering from JNTUH. She has Twenty one years of academic and research experience Her research interests are Data Science frameworks, Image Mining, Text mining, Machine learning, Artificial Intelligence, Deep Learning and Data Analytics. She has published about 57 articles in reputed Journals indexed in SCOPUS, SCI etc. She has published 2 patents. She has received grants from AICTE for organizing Short Term Training Programs and Faculty Development Programs. She is a reviewer for Elsevier, Springer and more indexed journals. She acted as sessionchair, organising member, and advisory member for various International Conferences. She delivered various invited talks on Data Modelling, Data Science and Analytics. She is a Life member of professional bodies like CSI and ISTE, Sr. Member for IEEE, WIE & International association IAENG, ICST, SDIWC.

Haritha Akkineni, P.V.P Siddhartha Institute of Technology, Vijayawada, India

Haritha Akkineni is currently an associate professor in Information Technology at PVP Siddhartha Institute of Technology, Vijayawada. She received her Ph.D in Computer Science and Engineering. She is working in the area of Opinion Mining and Data Sciences. She has twelve years of academic and research experience Her research interests are Data Science, Image Mining, Artificial Intelligence, Data Analytics, Deep Learning and Machine Learning. She has published about 35 papers in reputed Journals like SCOPUS UGC etc. She has published 2 patents. She has received grants from AICTE for organizing Short Term Training Programs. She is a reviewer for SCOPUS indexed journals. She authored a book on Opinion Mining. She acted as Workshop/tutorial chair for various International Conferences. She delivered various invited talks.

Chennupalli Srinivasulu, Institute of Aeronautical Engineering, Hyderabad, India

Chennupalli Srinivasulu is working as Professor of CSE at Institute of Aeronautical Engineering (IARE). He has 24 Years of experience in Teaching and Industry. His Area of Interest is Parallel Computing, Soft Computing, Software Engineering etc. He has published more than 38 Publications in reputed International Journals.


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How to Cite

Bala, M. M. ., Akkineni, H. ., & Srinivasulu, . C. . (2022). An Approach for Learner Categorization Based on Emotions in Intelligent Adaptive E-Learning Environment. Journal of Mobile Multimedia, 18(06), 1709–1732.