On predicting learning styles in conversational intelligent tutoring systems using fuzzy decision trees
文摘

An enhanced Fuzzy Learning Styles Predictor module is proposed.

Fuzzy decision trees are used to automatically predict individual learning style.

Modelling behaviour of learners during tutorials increases the predictive accuracy.

Transparent set of rules allow clear identification of leaner behaviour.

Better prediction of learning styles leads to improved adaptation.

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