A versatile learning context framework for heterogeneous e-Learning applications
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AbstractContextual 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.
English Language Centre
Refereed conference paper
In YT Wu, M Chang, B Li, TW Chan, SC Kong, HCK Lin, HC Chu, M Jan, MH Lee, Y, Dong, KH Tse, TL Wong & P Li (Eds.). Conference Proceedings of the 20th Global Chinese Conference on Computers in Education 2016, p. 684-687. Hong Kong: The Hong Kong Institute of Education, 2016