Towards automatic conceptual personalization tools
Faisal Ahmad, Sebastian de la Chica, Kirsten R. Butcher, Tamara Sumner, James Martin · 2007
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.