Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries
Automatic document metadata extraction using support vector machines
Proceedings of the 3rd ACM/IEEE-CS joint conference on Digital libraries
Convergence of knowledge management and E-learning: the GetSmart experience
Proceedings of the 3rd ACM/IEEE-CS joint conference on Digital libraries
Proceedings of the 3rd ACM/IEEE-CS joint conference on Digital libraries
Element matching in concept maps
Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries
Metaextract: an NLP system to automatically assign metadata
Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries
Digital libraries' support for the user's 'information journey'
Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries
Personalizing the Selection of Digital Library Resources to Support Intentional Learning
ECDL '08 Proceedings of the 12th European conference on Research and Advanced Technology for Digital Libraries
Science teachers' use of online resources and the digital library for Earth system education
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
Pedagogically useful extractive summaries for science education
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Identifying core concepts in educational resources
Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries
Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries
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This paper describes the results of a study designed to validate the use of domain competency models to diagnose student scientific misconceptions and to generate personalized instruction plans using digital libraries. Digital library resources provided the content base for human experts to construct a domain competency model for earthquakes and plate tectonics encoded as a knowledge map. The experts then assessed student essays using comparisons against the constructed domain competency model and prepared personalized instruction plans using the competency model and digital library resources. The results from this study indicate that domain competency models generated from select digital library resources may provide the desired degree of content coverage to support both automated diagnosis and personalized instruction in the context of nationally-recognized science learning goals. These findings serve to inform the design of personalized instruction tools for digital libraries.