Towards automatic conceptual personalization tools

ABSTRACT

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.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.1 MODELS AND PRINCIPLES
      H.1.2 User/Machine Systems

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.7 Digital Libraries
          Subjects: User issues

  K. Computing Milieux
  K.3 COMPUTERS AND EDUCATION
      K.3.1 Computer Uses in Education
          Subjects: Computer-assisted instruction (CAI)

General Terms:
Design, Experimentation, Human Factors

Keywords:
competency models, digital libraries, instructional plans, knowledge maps, personalization, student misconceptions