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 language | English |
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Pages (from-to) | 541-553 |
Number of pages | 13 |
Journal | International Journal of Fuzzy Systems |
Volume | 16 |
Issue number | 4 |
Publication status | Published - 2014 Dec 1 |
Externally published | Yes |
Keywords
- Fuzzy logic classification
- Intelligent classroom
- Spatial-temporal features
- Student's attentiveness
ASJC Scopus subject areas
- Theoretical Computer Science
- Software
- Computational Theory and Mathematics
- Artificial Intelligence