An integrated decision framework for evaluating and selecting e-learning products


APPLIED SOFT COMPUTING, vol.11, no.3, pp.2990-2998, 2011 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 11 Issue: 3
  • Publication Date: 2011
  • Doi Number: 10.1016/j.asoc.2010.11.023
  • Title of Journal : APPLIED SOFT COMPUTING
  • Page Numbers: pp.2990-2998


A sound decision methodology for evaluating and selecting e-learning products should consider multiple and conflicting criteria and the interactions among them. In this paper, a decision framework which employs quality function deployment (QFD), fuzzy linear regression and optimization is presented for e-learning product selection. First, a methodology for determining the target values for e-learning product characteristics that maximize overall customer satisfaction is presented. The QFD framework is employed to allocate resources and to coordinate skills and functions based on customer needs. Differing from earlier QFD applications, the proposed methodology employs fuzzy regression to determine the parameters of functional relationships between customer needs and e-learning product characteristics, and among e-learning product characteristics themselves. Finally, the e-learning product alternatives are evaluated and ranked with respect to deviations from the target product characteristic values. The potential use of the proposed decision framework is illustrated through an application on e-learning products provided by the universities in Turkey. (C) 2010 Elsevier B. V. All rights reserved.