Putting adaptive granularity and rich context into learning objects

  • Authors:
  • Haifeng Man;Qun Jin

  • Affiliations:
  • Graduate School of Human Sciences, Waseda University, Tokorozawa-shi, Japan;Faculty of Human Sciences, Waseda University, Tokorozawa-shi, Japan

  • Venue:
  • ITHET'10 Proceedings of the 9th international conference on Information technology based higher education and training
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

The content granularity and context information are two important factors to the efficiency and reusability of learning objects. The context information is necessary to facilitate the discovery and reuse of learning objects stored in global and/or local repositories. However, traditional learning objects are generally not conceived to incorporate with enough context information. Users have to do some extension of the description item set to fit their special use. In this paper, in order to deal with the issue mentioned above, we firstly introduce a context-rich paradigm, the related service driven tagging strategy, and a context model of learning objects. We further explain how to use the context information to realize the adaptive granularity of the content object. Finally, we show a simple concept model for online authoring systems that support the evolution from resource objects to learning objects.