Enhancing Online Education Through Machine Learning: A Comprehensive Review And Future Directions

  • Mamani Bandyopadhyay
  • Bablu Pramanik
Keywords: Facial Expression Recognition, Deep Learning, Education, Random Forest Classifier, Online Education


Online  learning  environments  are  gaining  popularity  as  an  alternative  to  traditional learning environments during times of global pandemic. The traditional classroom setting has given way  to  online learning  in recent educational developments.  To  employ it  as a classifier in online education, the goal of this work is to construct a real-time face emotion detection system  that  recognizes and categorizes  emotions of a  human. It uses  machine learning to identify, forecast, and analyse a learner's facial expressions, and it further maps those expressions to a learning affect that categorizes the emotions of those who are seen on camera. Academic feelings can have a significant impact on learning outcomes. Students typically  show  their  emotions  through their  facial  expressions,  voice,  and  behavior.  A spontaneous facial expression database is created in light of the inference algorithm's lack of training samples. It consists of two subsets: a video clip database and a picture database, and it includes the typical emotional facial expressions. The database contains 1,274 video clips and 30,184 photos from 82 pupils. The parameters for student facial detection can be used to gauge each learner's rate of concentration. The performances of the SVM and RF classifier in facial expression for the image are presented. The results of testing this with the RF algorithm and a 90.14% accuracy rate produced extremely good results. 

Author Biographies

Mamani Bandyopadhyay

Department of Computer Science and Engineering, Brainware University

Bablu Pramanik

Department of Computer Science and Engineering, Brainware University


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How to Cite
Mamani Bandyopadhyay, & Bablu Pramanik. (1). Enhancing Online Education Through Machine Learning: A Comprehensive Review And Future Directions. Revista Electronica De Veterinaria, 25(1S), 155-164. Retrieved from https://veterinaria.org/index.php/REDVET/article/view/580