User Modeling and User-Adapted Interaction
Personalizing the Interaction in a Web-based Educational Hypermedia System: the case of INSPIRE
User Modeling and User-Adapted Interaction
Expert Systems with Applications: An International Journal
Towards automatic conceptual personalization tools
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Intelligent web-based learning system with personalized learning path guidance
Computers & Education
Pedagogically useful extractive summaries for science education
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Reasoning about the seasons: middle school students' use of evidence in explanations
ICLS '10 Proceedings of the 9th International Conference of the Learning Sciences - Volume 2
Smap: to generate the personalized learning paths for different learning style learners
Edutainment'10 Proceedings of the Entertainment for education, and 5th international conference on E-learning and games
Computational Linguistics
Learning path generation by domain ontology transformation
AI*IA'05 Proceedings of the 9th conference on Advances in Artificial Intelligence
Creating and delivering adaptive courses with AHA!
EC-TEL'06 Proceedings of the First European conference on Technology Enhanced Learning: innovative Approaches for Learning and Knowledge Sharing
Algorithms for robust knowledge extraction in learning environments
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part II
Identifying core concepts in educational resources
Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries
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A key challenge facing educational technology researchers is how to provide structure and guidance when learners use unstructured and open tools such as digital libraries for their own learning. This work attempts to use computational methods to identify that structure in a domain independent way and support learners as they navigate and interpret the information they find. This article highlights a computational methodology for generating a pedagogical sequence through core learning goals extracted from a collection of resources which in this case, are resources from the Digital Library for Earth System Education (DLESE). This article describes how we use the technique of multi-document summarization to extract the core learning goals from the digital library resources and how we create a supervised classifier that performs a pair-wise classification of the core learning goals; the judgments from these classifications are used to automatically generate pedagogical sequences. Results show that we can extract good core learning goals and make pair-wise classifications that are up to 76% similar to the pair-wise classifications generated from pedagogical sequences created by two science education experts. Thus we can dynamically generate pedagogically meaningful learning paths through digital library resources.