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Personalizing the Selection of Digital Library Resources to Support Intentional Learning

  • Qianyi Gu
  • Sebastian de la Chica
  • Faisal Ahmad
  • Huda Khan
  • Tamara Sumner
  • James H. Martin
  • Kirsten Butcher
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5173)

Abstract

This paper describes a personalization approach for using online resources in digital libraries to support intentional learning. Personalized resource recommendations are made based on what learners currently know and what they should know within a targeted domain to support their learning process. We use natural language processing and graph based algorithms to automatically select online resources to address students’ specific conceptual learning needs. An evaluation of the graph based algorithm indicates that the majority of recommended resources are highly relevant or relevant for addressing students’ individual knowledge gaps and prior conceptions.

Keywords

Personalization Information Retrieval Intentional Learning Knowledge Map 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Qianyi Gu
    • 1
  • Sebastian de la Chica
    • 1
  • Faisal Ahmad
    • 1
  • Huda Khan
    • 1
  • Tamara Sumner
    • 1
  • James H. Martin
    • 1
  • Kirsten Butcher
    • 2
  1. 1.Department of Computer Science, Institute of Cognitive ScienceUniversity of Colorado at BoulderBoulderUSA
  2. 2.Learning Research and Development CenterUniversity of PittsburghPittsburghUSA

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