Curriculum Sequencing in a Web-Based Tutor
ITS '98 Proceedings of the 4th International Conference on Intelligent Tutoring Systems
Adaptive course generation through learning styles representation
Universal Access in the Information Society
Adaptive Learning with the LS-Plan System: A Field Evaluation
IEEE Transactions on Learning Technologies
LS-LAB: A Framework for Comparing Curriculum Sequencing Algorithms
ISDA '09 Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
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Curriculum Sequencing is one of the most interesting challenges in learning environments, such as Intelligent Tutoring Systems and e-learning The goal is to automatically produce personalized sequences of didactic materials or activities, on the basis of each individual student's model In this paper we present the extension of the LS-Lab framework, supporting an automated and flexible comparison of the outputs coming from a variety of Curriculum Sequencing algorithms over the same student models The main aim of LS-Lab is to provide researchers or teachers with a ready-to-use and possibly extensible environment, supporting a reasonably low-cost experimentation of several sequencing algorithms The system accepts a student model as input, together with the selection of the algorithms to be used and a given learning material; then the algorithms are applied, the resulting courses are shown to the user, and some metrics computed over the selected characteristics are presented, for the user's appraisal.