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Factors that influence the teaching use of Wikipedia in higher education

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  • Antoni Meseguer‐Artola
  • Eduard Aibar
  • Josep Lladós
  • Julià Minguillón
  • Maura Lerga

Abstract

A key impact the Internet is having on university teaching involves the new choices being provided because of open educational content. Wikipedia is a clear example of these new options. It is a gigantic open repository of knowledge, and it can also be considered a platform that facilitates collaboration in knowledge creation and dissemination. Our research objective is to understand what the main factors are that influence the teaching uses of Wikipedia among university faculty. Based on a technology acceptance model, and using data from a survey sent to all faculty members of the Universitat Oberta de Catalunya, we analyze the relationships within the internal and external constructs of the model. We found that both the perception of colleagues' opinions about Wikipedia and the perceived quality of the information in Wikipedia play a central role. These two constructs have a significant direct impact on the perceived usefulness of Wikipedia. This perceived usefulness affects, mediated by the behavioral intention of using Wikipedia, the effective use behavior of the encyclopedia. The degree to which an individual considers it is important to participate in open collaborative environments and the Web 2.0 profile of the faculty members also play an important role in our model.

Suggested Citation

  • Antoni Meseguer‐Artola & Eduard Aibar & Josep Lladós & Julià Minguillón & Maura Lerga, 2016. "Factors that influence the teaching use of Wikipedia in higher education," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(5), pages 1224-1232, May.
    • Handle: RePEc:bla:jinfst:v:67:y:2016:i:5:p:1224-1232
    DOI: 10.1002/asi.23488
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    References listed on IDEAS

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    1. Sook Lim, 2009. "How and why do college students use Wikipedia?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(11), pages 2189-2202, November.
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    Cited by:

    1. Rosaria Romano & Francesco Palumbo, 2021. "Partial possibilistic regression path modeling: handling uncertainty in path modeling," Computational Statistics, Springer, vol. 36(1), pages 615-639, March.

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