Journal article
Evaluating Wikipedia as a self-learning resource for statistics: You know they'll use it
The American Statistician, Vol.73(3), pp.224-231
2019
Abstract
The role of Wikipedia for learning has been debated because it does not conform to the usual standards. Despite this, people use it, due to the ubiquity of Wikipedia entries in the outcomes from popular search engines. It is important for academic disciplines, including statistics, to ensure they are correctly represented in a medium where anyone can assume the role of discipline expert. In this context, we first develop a tool for evaluating Wikipedia articles for topics with a procedural component. Then, using this tool, five Wikipedia articles on basic statistical concepts are critiqued from the point of view of a self-learner: "arithmetic mean", "standard deviation", "standard error", "confidence interval" and "histogram". We find that the articles, in general, are poor, and some articles contain inaccuracies. We propose that Wikipedia be actively discouraged for self-learning (using, for example, a classroom activity) except to give a brief overview; that in more formal learning environments, teachers be explicit about not using Wikipedia as a learning resource for course content; and, because Wikipedia is used regardless of considered advice or the organizational protocols in place, teachers move away from minimal contact with Wikipedia towards more constructive engagement.
Details
- Title
- Evaluating Wikipedia as a self-learning resource for statistics: You know they'll use it
- Authors
- Peter K Dunn (Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and EngineeringMargaret Marshman (Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and EngineeringRobert G McDougall (Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and Engineering
- Publication details
- The American Statistician, Vol.73(3), pp.224-231
- Publisher
- American Statistical Association
- Date published
- 2019
- DOI
- 10.1080/00031305.2017.1392360
- ISSN
- 0003-1305
- Copyright note
- The Author Accepted Version is reproduced with permission from the Journal of Statistical Education. Copyrighted 2015 by the American Statistical Association. All rights reserved
- Organisation Unit
- School of Science and Engineering - Legacy; School of Education - Legacy; School of Education and Tertiary Access; University of the Sunshine Coast, Queensland; School of Health and Sport Sciences - Legacy; School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99451240502621
- Output Type
- Journal article
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- Web Of Science research areas
- Statistics & Probability