Web-based education for all: a tool for development adaptive courseware
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Tailoring the interaction with users in electronic shops
UM '99 Proceedings of the seventh international conference on User modeling
User Modeling and User-Adapted Interaction
Developing Adaptive Internet Based Courses with the Authoring System NetCoach
Revised Papers from the nternational Workshops OHS-7, SC-3, and AH-3 on Hypermedia: Openness, Structural Awareness, and Adaptivity
Adaptive feedback generation to support teachers in web-based distance education
User Modeling and User-Adapted Interaction
The Evaluation of an Intelligent Teacher Advisor for Web Distance Environments
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Collaborative student profile to support assistance in CSCL environment
Proceedings of the 2008 Euro American Conference on Telematics and Information Systems
Usability engineering for the adaptive web
The adaptive web
Layered evaluation of interactive adaptive systems: framework and formative methods
User Modeling and User-Adapted Interaction
Web usage mining approach to detect student's collaborative skills
Journal of Web Engineering
Off-line evaluation of recommendation functions
UM'05 Proceedings of the 10th international conference on User Modeling
A decomposition model for the layered evaluation of interactive adaptive systems
UM'05 Proceedings of the 10th international conference on User Modeling
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part I
Evaluating the integration of fuzzy logic into the student model of a web-based learning environment
Expert Systems with Applications: An International Journal
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The evaluation of user modeling systems is an important though often neglected area. Evaluating the inference of user properties can help to identify failures in the user model. In this paper we propose two methods to assess the accuracy of the user model. The assumptions about the user might either be compared to an external test, or might be used to predict the users' behavior. Two studies with five adaptive learning courses demonstrate the usefulness of the approach.