An Extended and Adaptable Information Model for Learning Objects

  • Authors:

  • Dirk Frosch-Wilke

  • Affiliations:

  • University of Applied Sciences Kiel

  • Venue:
  • ICALT '04 Proceedings of the IEEE International Conference on Advanced Learning Technologies
  • Year:
  • 2004

Quantified Score

Hi-index 0.00

Visualization

Abstract

Learning objects are fundamental elements of a new conceptual model for content creation and course composition in Web-based education. Learning objectsý metadata (LOM) facilitate adaptive selection of learning objects on the Web as well as the instructional development of Web-based courses. Although there are a number of ongoing LOM standard initiatives a lot of problems with LOMs are reported: Reaching from more technical applications (e.g. data integrity deficiencies) to contextualization problems. In this paper we present an information model for learning objects, capable to solve many of these problems. We use proven object-oriented design patterns for modeling the different metadata elements of learning objects and their relationships.