Using Evaluation to Shape ITS Design: Results and Experiences with SQL-Tutor
User Modeling and User-Adapted Interaction
An Intelligent SQL Tutor on the Web
International Journal of Artificial Intelligence in Education
Interacting with Inspectable Bayesian Student Models
International Journal of Artificial Intelligence in Education
Adaptive feedback generation to support teachers in web-based distance education
User Modeling and User-Adapted Interaction
Usability engineering for the adaptive web
The adaptive web
Widening the Knowledge Acquisition Bottleneck for Constraint-based Tutors
International Journal of Artificial Intelligence in Education
Evaluating and improving adaptive educational systems with learning curves
User Modeling and User-Adapted Interaction
Fifteen years of constraint-based tutors: what we have achieved and where we are going
User Modeling and User-Adapted Interaction
Exploring quality of constraints for assessment in problem solving environments
ITS'12 Proceedings of the 11th international conference on Intelligent Tutoring Systems
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Intelligent tutoring systems achieve much of their success by adapting to individual students. One potential avenue for personalization is feedback generality. This paper presents two evaluation studies that measure the effects of modifying feedback generality in a web-based Intelligent Tutoring System (ITS) based on the analysis of student models. The object of the experiments was to measure the effectiveness of varying feedback generality, and to determine whether this could be performed en masse or if personalization is needed. In an initial trial with a web-based ITS it appeared that it is feasible to use a mass approach to select appropriate concepts for generalizing feedback. A second study gave conflicting results and showed a relationship between generality and ability, highlighting the need for feedback to be personalized to individual students’ needs.