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

  • Authors:

  • Gwo-Jen Hwang;Fan-Ray Kuo;Peng-Yeng Yin;Kuo-Hsien Chuang

  • Affiliations:

  • Department of Information and Learning Technology, National University of Tainan, 33, Sec. 2, Shulin St., Tainan City 70005, Taiwan;Department of Information and Learning Technology, National University of Tainan, 33, Sec. 2, Shulin St., Tainan City 70005, Taiwan;Department of Information Management, National Chi Nan University, Pu-Li, Nan-Tou County 545, Taiwan;Department of Information Management, National Chi Nan University, Pu-Li, Nan-Tou County 545, Taiwan

  • Venue:
  • Computers & Education
  • Year:
  • 2010

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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.