A conceptual model of personalized virtual learning environments

  • Authors:

  • Dongming Xu;Huaiqing Wang;Minhong Wang

  • Affiliations:

  • BIS, UQ Business School, The University of Queensland, St Lucia, Qld 4072, Australia and Department of Information Systems, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China;Department of Information Systems, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China;Department of Information Systems, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2005

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Abstract

The Virtual Learning Environment (VLE) is one of the fastest growing areas in educational technology research and development. In order to achieve learning effectiveness, ideal VLEs should be able to identify learning needs and customize solutions, with or without an instructor to supplement instruction. They are called Personalized VLEs (PVLEs). In order to achieve PVLEs success, comprehensive conceptual models corresponding to PVLEs are essential. Such conceptual modeling development is important because it facilitates early detection and correction of system development errors. Therefore, in order to capture the PVLEs knowledge explicitly, this paper focuses on the development of conceptual models for PVLEs, including models of knowledge primitives in terms of learner, curriculum, and situational models, models of VLEs in general pedagogical bases, and particularly, the definition of the ontology of PVLEs on the constructivist pedagogical principle. Based on those comprehensive conceptual models, a prototyped multiagent-based PVLE has been implemented. A field experiment was conducted to investigate the learning achievements by comparing personalized and non-personalized systems. The result indicates that the PVLE we developed under our comprehensive ontology successfully provides significant learning achievements. These comprehensive models also provide a solid knowledge representation framework for PVLEs development practice, guiding the analysis, design, and development of PVLEs.