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Facial Emotion Detection in Massive Open Online Courses

  • Mohamed Soltani
  • Hafed Zarzour
  • Mohamed Chaouki Babahenini
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 745)

Abstract

Recently, the Massive Open Online Course (MOOC) has appeared as a new emerging method of online teaching with the advantages of low cost and unlimited participation as well as open access via the web. However, the use of facial emotion detection in MOOCs is still unexplored and challenging. In this paper, we propose a new innovative approach for facial emotion detection in MOOCs, which provides an adaptive learning content based on students’ emotional states and their profiles. Our approach is based on three principles: (i) modeling the learner using the MOOC (ii) using of pedagogical agents during the learning activities (iii) capturing and interpreting the facial emotion of the students. The proposed approach was implemented and tested in a case study on the MOOC.

Keywords

MOOC Massive Open Online Course E-learning Educational technology Technology enhanced learning Emotion detection Facial expression Emotional awareness 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Mohamed Soltani
    • 1
  • Hafed Zarzour
    • 1
  • Mohamed Chaouki Babahenini
    • 2
  1. 1.LIM Research, Department of Computer ScienceUniversity of Souk AhrasSouk AhrasAlgeria
  2. 2.LESIA LaboratoryUniversity of BiskraBiskraAlgeria

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