Please use this identifier to cite or link to this item:
Title: A versatile learning context framework for heterogeneous e-Learning applications
Authors: Xie, H
Zou, D
Wang, TL
Wang, FL
Issue Date: 2016
Source: 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
Abstract: 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.
Keywords: Context model
E-learning systems
Semantic operations
Learning context
Conceptual framework
Publisher: Hong Kong Institute of Education
Appears in Collections:Conference Paper

Show full item record

Page view(s)

Last Week
Last month
Citations as of Sep 14, 2020

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.