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A Heuristic Algorithm for planning personalized learning paths for context-aware ubiquitous learning
ARTICLE

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Computers & Education Volume 54, Number 2, ISSN 0360-1315 Publisher: Elsevier Ltd

Abstract

In a context-aware ubiquitous learning environment, learning systems can detect students’ learning behaviors in the real-world with the help of context-aware (sensor) technology; that is, students can be guided to observe or operate real-world objects with personalized support from the digital world. In this study, an optimization problem that models the objectives and criteria for determining personalized context-aware ubiquitous learning paths to maximize the learning efficacy for individual students is formulated by taking the meaningfulness of the learning paths and the number of simultaneous visitors to each learning object into account. Moreover, a Heuristic Algorithm is proposed to find a quality solution. Experimental results from the learning activities conducted in a natural science butterfly-ecology course of an elementary school are also given to depict the benefits of the innovative approach.

Citation

Hwang, G.J., Kuo, F.R., Yin, P.Y. & Chuang, K.H. (2010). A Heuristic Algorithm for planning personalized learning paths for context-aware ubiquitous learning. Computers & Education, 54(2), 404-415. Elsevier Ltd. Retrieved December 6, 2019 from .

This record was imported from Computers & Education on January 30, 2019. Computers & Education is a publication of Elsevier.

Full text is availabe on Science Direct: http://dx.doi.org/10.1016/j.compedu.2009.08.024

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