Using planning techniques in intelligent tutoring systems
International Journal of Man-Machine Studies
Integrating user-perceived quality into Web server design
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
ITS '92 Proceedings of the Second International Conference on Intelligent Tutoring Systems
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
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IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
Total-order planning with partially ordered subtasks
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
User models for adaptive hypermedia and adaptive educational systems
The adaptive web
Integrating learning object repositories using a mediator architecture
EC-TEL'06 Proceedings of the First European conference on Technology Enhanced Learning: innovative Approaches for Learning and Knowledge Sharing
Planning for Conditional Learning Routes
MICAI '09 Proceedings of the 8th Mexican International Conference on Artificial Intelligence
International Journal of Advanced Intelligence Paradigms
Planning and execution in a personalised E-learning setting
CAEPIA'11 Proceedings of the 14th international conference on Advances in artificial intelligence: spanish association for artificial intelligence
Expert Systems with Applications: An International Journal
Designer - supporting teachers experience in learning management systems
ICWL'12 Proceedings of the 11th international conference on Advances in Web-Based Learning
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Course generation enables the automatic assembly of course (ware) adapted to the learner's competencies and learning goals. It offers a middle-way between traditional pre-authored ''one-size fits all'' courseware and manual resource look-up. Such an assembly requires pedagogical knowledge, represented, for instance, as expert system rules or planning operators. In this article, we describe the course generation framework Paigos that enables the formalization and application of complex and realistic pedagogical knowledge. Compared to previous course generation approaches, it generates structured courses that are adapted to a variety of learning goals and to the learners' competencies. We describe basic operators and methods for course generation, which are used to formalize seven different types of courses. Furthermore, we present the results of technical evaluations that investigated the performance of the proposed framework. Among others, the results show that Paigos takes less than a second to generate complex courses with an average learning time of about twelve hours. The results also show that large amounts of educational resources are required for an adaptive pedagogically founded course generation.