A Mobile Learning System for Syndromic Surveillance and Diagnosis

  • Authors:
  • Jingyu Zhang;David Levy;Shiping Chen

  • Affiliations:
  • -;-;-

  • Venue:
  • ICALT '10 Proceedings of the 2010 10th IEEE International Conference on Advanced Learning Technologies
  • Year:
  • 2010

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Abstract

As hand-held devices become popular in society, the demand for mobility is extended to teaching and learning purposes. This paper presents the design and implementation of a mobile learning system for syndromic surveillance and diagnosis. This system can assist farmers and veterinary students to study surveillance and diagnosis of farm animal diseases in the field. In this paper, we present a mobile problem-based learning method used for designing the diagnosis learning system. We also describe our solution to the limitation of storage capacity of hand-held devices. We also present how the design is implemented as portable software that can be deployed onto a large range of mobile phones and other hand-held devices.