A versatile learning context framework for heterogeneous e-learning applications

Haoran XIE, Di ZOU, Tak-Lam WONG, Fu Lee WANG

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Research


Contextual data of learners play a vital role in various e-learning applications in recent years, as learning contexts not only provide learners with context-aware services but also enhance effectiveness. However, various e-learning systems adopt different contextual models (i.e., application-dependent contextual model), and consequently data sharing and system integration are challenging. In this article, we propose a unified learning context framework to support heterogeneous e-learning applications. This context framework, being versatile and flexible to various e-learning applications, can address the shortcoming of application-dependent models. Within the framework, we define a set of contextual operations to manipulate and customize the learning context data. The proposed context framework can support various context-aware e-learning applications. Through the case studies, we also verify that the proposed framework is very flexible and powerful in different scales.
Original languageEnglish
Title of host publicationConference Proceedings of the 20th Global Chinese Conference on Computers in Education 2016
EditorsYing-Tien WU, Maiga CHANG, Baoping LI, Tak-Wai CHAN, Siu Cheung KONG, Hao Chiang Koong LIN, Hui-Chun CHU, Mingfong JAN, Min-Hsien LEE, Yan DONG, Ka Ho TSE, Tak Lam WONG, Ping LI
Place of PublicationHong Kong
Number of pages4
Publication statusPublished - 2016
Externally publishedYes


  • context model
  • e-learning systems
  • semantic operations
  • learning context
  • conceptual framework


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