Classifying student's attentiveness via spatial-temporal fuzzy logic classification

Chun Ming Tsai, Zong Mu Yeh

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Students' attentiveness in learning activities is a critical component in effective learning. However, there are many factors that may distract learners, resulting in behaviors such as whispering to classmates, glancing away from the lesson, sleeping and even leaving. This study proposes a spatial- and temporal-based fuzzy logic classification to classify student's attentiveness to promote improvement in classroom learning. This method uses spatial and temporal features to define the membership function for input variables in a fuzzy logical classification. This fuzzy classification approach can classify student's attentiveness into five quantified levels. These five levels includes extremely distracted, very distracted, obviously distracted, distracted and attentive. Simulation results indicated that the proposed method is significantly effective for detecting and classifying student's attentiveness.

Original languageEnglish
Pages (from-to)541-553
Number of pages13
JournalInternational Journal of Fuzzy Systems
Volume16
Issue number4
Publication statusPublished - 2014 Dec 1

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Keywords

  • Fuzzy logic classification
  • Intelligent classroom
  • Spatial-temporal features
  • Student's attentiveness

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Artificial Intelligence

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