透過您的圖書館登入
IP:18.216.96.204
  • 期刊
  • OpenAccess

An Enhanced LTSA Model Providing Contextual Knowledge for Intelligent e-Learning Systems

並列摘要


Learning objects along with their sequencing are being studied to support efficient e-learning systems. They could solve the problem of costly reproduction of learning materials for e-learning systems. The problem arising here is related to the size and complexity of methods used to achieve the appropriate composition of learning objects in order to generate courses with pedagogic efficiency and value. We concentrate our attention on the adaptive and intelligent composition of learning objects. It is the main theme of instructional design, a major concern of which is the representation and organization of subject contents to facilitate the learning process. We believe that modeling the structure of subject contents, i.e., contextual knowledge, in an e-learning system can help an instructional designer to design and implement an adaptive and intelligent sequence of learning. A metadata-based ontology is introduced for this purpose and added to the IEEE LTSA model. Further, UML is used to design of an ontology-based educational contents model based on IMS specifications. In this way, the proposed solution provides a complete solution for the design and development of efficient e-learning systems.

被引用紀錄


郭盈顯(2012)。藉由3D遊戲為基礎的情境式學習提升專注力之學習成效分析--以英語教學為例〔碩士論文,崑山科技大學〕。華藝線上圖書館。https://doi.org/10.6828/KSU.2012.00094

延伸閱讀