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Employing automatic content recognition for teaching methodology analysis in classroom videos

Author

Listed:
  • Muhammad Aasim Rafique
  • Faheem Khaskheli
  • Malik Tahir Hassan
  • Sheraz Naseer
  • Moongu Jeon

Abstract

A teacher plays a pivotal role in grooming a society and paves way for its social and economic developments. Teaching is a dynamic role and demands continuous adaptation. A teacher adopts teaching techniques suitable for a certain discipline and a situation. A thorough, detailed, and impartial observation of a teacher is a desideratum for adaptation of an effective teaching methodology and it is a laborious exercise. An automatic strategy for analyzing a teacher’s teaching methodology in a classroom environment is suggested in this work. The proposed strategy recognizes a teacher’s actions in videos while he is delivering lectures. In this study, 3D CNN and Conv2DLSTM with time-distributed layers are used for experimentation. A range of actions are recognized for a complete classroom session during experimentation and the reported results are considered effective for analysis of a teacher’s teaching technique.

Suggested Citation

  • Muhammad Aasim Rafique & Faheem Khaskheli & Malik Tahir Hassan & Sheraz Naseer & Moongu Jeon, 2022. "Employing automatic content recognition for teaching methodology analysis in classroom videos," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-20, February.
    • Handle: RePEc:plo:pone00:0263448
    DOI: 10.1371/journal.pone.0263448
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