A fuzzy model for predicting learning styles using behavioral cues in an conversational intelligent tutoring system

@article{Crockett2013AFM,
  title={A fuzzy model for predicting learning styles using behavioral cues in an conversational intelligent tutoring system},
  author={Keeley A. Crockett and Annabel Latham and David McLean and James O'Shea},
  journal={2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)},
  year={2013},
  pages={1-8}
}
This paper proposes a new model for predicting student learning styles for conversational intelligent tutoring systems (CITS). The learning styles are predicted from behavior cues extracted during conversation obtained during automated CITS tutorials. The heart of the model is a fuzzy rule base determined automatically from existing tutorial data with membership function boundaries optimized by a genetic algorithm. The zero-order Sugeno fuzzy inference model is utilized to predict the Felder… CONTINUE READING

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