User Modeling and User-Adapted Interaction
Stereotypes, Student Models and Scrutability
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
KnowledgeTree: a distributed architecture for adaptive e-learning
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
A logical characterization of adaptive educational hypermedia
Hypermedia - Special issue: Adaptive hypermedia in the age of the adaptive web
Personalized e-learning system using Item Response Theory
Computers & Education
Personal Learning Environments
ICALT '06 Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies
Subspace: secure cross-domain communication for web mashups
Proceedings of the 16th international conference on World Wide Web
Visual Mashup of Text and Media Search Results
IV '07 Proceedings of the 11th International Conference Information Visualization
SA-REST and (S)mashups: Adding Semantics to RESTful Services
ICSC '07 Proceedings of the International Conference on Semantic Computing
The Web 2.0 way of learning with technologies
International Journal of Learning Technology
Web 2.0 technology: future interfaces for technology enhanced learning?
UAHCI'07 Proceedings of the 4th international conference on Universal access in human-computer interaction: applications and services
EC-TEL'06 Proceedings of the First European conference on Technology Enhanced Learning: innovative Approaches for Learning and Knowledge Sharing
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Over the last century, many theoretical frameworks and technological solutions for personalized e-learning have emerged. The underlying models, however, are often based on the practice that domain experts develop an adaptation strategy to personalize content or parts of a learning platform, which leads to different problematic aspects decreasing the feasibility or utility of such approaches. After giving a brief overview of the historical development and basic concepts of personalized e-learning, we outline the shortcomings of the traditional `top-down, ex ante' models and present an alternative approach which deals with personal learning environments, web application mashups, learning activities and learner interactions, as well as pattern-based best practice sharing. Furthermore, a prototypic implementation for our `learner-driven, bottom-up' approach to personalized e-learning, namely the `Mash-UP Personal Learning Environment' (MUPPLE), is presented and discussed on the basis of a concrete scenario.