Fab: content-based, collaborative recommendation
Communications of the ACM
Knowledge engineering: principles and methods
Data & Knowledge Engineering - Special jubilee issue: DKE 25
Web-based education for all: a tool for development adaptive courseware
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Design issues for general-purpose adaptive hypermedia systems
Proceedings of the 12th ACM conference on Hypertext and Hypermedia
User Modeling and User-Adapted Interaction
Adaptive Content in an Online Lecture System
AH '00 Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
iWeaver: towards 'learning style'-based e-learning in computer science education
ACE '03 Proceedings of the fifth Australasian conference on Computing education - Volume 20
Personalizing the Interaction in a Web-based Educational Hypermedia System: the case of INSPIRE
User Modeling and User-Adapted Interaction
AHA! The adaptive hypermedia architecture
Proceedings of the fourteenth ACM conference on Hypertext and hypermedia
Ontological user profiling in recommender systems
ACM Transactions on Information Systems (TOIS)
Design and evolution of an undergraduate course on web application development
Proceedings of the 9th annual SIGCSE conference on Innovation and technology in computer science education
Authoring of learning styles in adaptive hypermedia: problems and solutions
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Personalization in distributed e-learning environments
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Automatic identification of user interest for personalized search
Proceedings of the 15th international conference on World Wide Web
Collecting community wisdom: integrating social search & social navigation
Proceedings of the 12th international conference on Intelligent user interfaces
Technology supports for distributed and collaborative learning over the internet
ACM Transactions on Internet Technology (TOIT)
eTeacher: Providing personalized assistance to e-learning students
Computers & Education
Capture, Management, and Utilization of Lifecycle Information for Learning Resources
IEEE Transactions on Learning Technologies
Evaluating Learning Style Personalization in Adaptive Systems: Quantitative Methods and Approaches
IEEE Transactions on Learning Technologies
Learning programming languages through corrective feedback and concept visualisation
ICWL'11 Proceedings of the 10th international conference on Advances in Web-Based Learning
Detecting students' perception style by using games
Computers & Education
Recent development in multimedia e-learning technologies
World Wide Web
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Existing adaptive e-learning methods are supported by student user profiling for capturing student characteristics, and course structuring for organizing learning materials according to topics and levels of difficulties. Adaptive courses are then generated by extracting materials from the course structure to match the criteria specified in the student profiles. In addition, to handle advanced student characteristics, such as learning styles, course material annotation and programming-based decision rules are typically used. However, these additives demand certain programming skills from an instructor to proceed with course construction; they may also require building multiple course structures to handle practical pedagogical needs. In this paper, the authors propose a framework based on the concept space and the concept filters to support adaptive course generation where comprehensive student characteristics are considered. The concept space is a data structure for modeling student and course characteristics, while the concept filters are modifiers to determine how the course should be delivered. Because of the "building block" nature of the concept nodes and the concept filters, the proposed framework is extensible. More importantly, the authors' framework does not require instructors to equip with any programming skills when they construct adaptive e-learning courses.