Individualizing Tutoring with Learning Style Based Feedback

To approximate more closely effective human tutors, intelligent tutoring systems should adapt not only to a student's knowledge but also her learning style. We introduce a pedagogical framework that incorporates the Felder-Silverman learning style model and validated instrument for assessing individual learning style. The framework provides a feedback infrastructure based on the learning style model dimensions (such as visual, verbal, intuitive, sensor, etc.). It has been implemented as part of the DesignFirst-ITS, helping novices learn how to design a class in UML from a problem description. The system has been evaluated with high-school students and results show that learning style based feedback helps students realize higher learning gains.

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