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. Copyright © 2016 Global Chinese Society for Computers in Education.
|Title of host publication||Proceedings of the 20th Global Chinese Conference on Computers in Education 2016|
|Editors||Ying-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 Publication||Hong Kong|
|Publisher||The Hong Kong Institute of Education|
|Publication status||Published - 2016|
CitationXie, H., Zou, D., Wong, T.-L., & Wang, F. L. (2016). A versatile learning context framework for heterogeneous e-learning applications. In Y.-T. Wu, M. Chang, B. Li, T.-W. Chan, S. C. Kong, H. C. K. Lin, et al. (Eds.), Conference proceedings of the 20th Global Chinese Conference on Computers in Education 2016 (pp. 684-687). Hong Kong: The Hong Kong Institute of Education.
- Context model
- E-learning systems
- Semantic operations
- Learning context
- Conceptual framework