Preference-based decision making for personalised access to Learning Resources
International Journal of Autonomous and Adaptive Communications Systems
Personalised Instruction E-Learning Model Based On Knowledge Domain
Journal of Integrated Design & Process Science
Comparison of knowledge during the assembly process of learning objects
Journal of Intelligent Information Systems
Recommendation for English multiple-choice cloze questions based on expected test scores
International Journal of Knowledge-based and Intelligent Engineering Systems
A multi-criteria programming model for intelligent tutoring planning
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
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Libraries of learning objects may serve as basis for deriving course offerings that are customized to the needs of different learning communities or even individuals. Several ways of organizing this course composition process are discussed.Course composition needs a clear understanding of the dependencies between the learning objects. Therefore we discuss the metadata for object relationships proposed in different standardization projects and especially those suggested in the Dublin Core Metadata Initiative.Based on these metadata we construct adjacency matrices and graphs. We show how Gozinto-type computations can be used to determine direct and indirect prerequisites for certain learning objects.The metadata may also be used to define integer programming models which can be applied to support the instructor in formulating his specifications for selecting objects or which allow a computer agent to automatically select learning objects. Such decision models could also be helpful for a learner navigating through a library of learning objects. We also sketch a graph-based procedure for manual or automatic sequencing of the learning objects.