In this second part of this two-part article, I discuss how WikiProjects, article importance and article quality come together in Wikipedia—and how that conjuncture can help instructors and students with selecting appropriate articles for editing in Wikipedia-based course assignments.
Understanding the Article Assessment Grid
A key WikiProject output is assessment of an article’s quality and importance (see the previous post on the criteria for measuring these). Quality and importance can be plotted on a two-dimensional grid in which each cell represents a particular quality grade and a particular importance level. The cells can then be populated with the number of articles in each of these pairings, using the quality and importance data from the article Talk pages. In Wikipedia, this information is collected—and the cells are populated—with help from a bot (more on which later), allowing for the number of articles of interest to a WikiProject, and their importance and quality, to be updated over time.
The output can be seen by looking at the assessment grid for WikiProject Adoption, fostering, orphan care and displacement (“AFOD”), discussed in the last post. I’ve captured an image of the grid as of 26 February 2017 and hyperlinked it to the actual grid on the AFOD project page, which lets you view the most up-to-date version of the grid.
For now, let’s ignore the bottom part of the grid and focus on the vertical quality axis, starting with “List.” Scanning this line, we see that there are two list-class articles, both of them considered “High” importance. Indeed, these are the only List-class articles for AFOD, as reflected in the “Total” column at far-right, which also shows “2.” Moving up to “Stub,” we can see there are three stub-class articles of high importance, 13 of mid-importance, 31 of low importance, and two that need assessing (“???”), for a total of 49 stub-class articles tracked in this WikiProject. We can keep moving up the quality axis to see the number of articles in the Start-, C-, B-, GA-, and FA-classes and their distribution across importance levels.
Now let’s look focus on the horizontal importance axis, starting with “Top.” We can see that there is one B-class article in this category, three C-class, and seven Start-class articles—for a total of 11 assessed articles in the top-importance category. Moving to the right and following the same procedure, we can see that there are 24 high-importance, 48 mid-importance, and 91 low-importance articles—with the distribution across quality levels as shown in the grid.
This statistical information comes together in two metrics, called WikiWork factors, that serve as a rough guide to the amount of work a given WikiProject entails. These metrics, ω and Ω (the lower- and upper-case versions of the Greek letter omega) are at the bottom of the AFOD assessment grid. The metric ω is the number of steps a WikiProject is from having all articles attain FA status; for example, an A-class article is one step away from that status, while a Stub-class article is six steps away. (List articles aren’t counted.) Multiplying the steps by the number of articles in that class and summing everything yields a ω of 986. The other metric, Ω, is a measure of relative workload: ω divided by the number of articles (again, excluding List articles). It is always a number between zero and six—in this case, 4.91—with lower numbers indicating that less work is needed on average to bring an article to FA status.
Moving from the Assessment Grid to the Article Tables
The astute observer will notice that the numbers in the cells are blue, indicating a link to an active page in Wikipedia. Indeed, clicking on a number in the assessment grid to which this image links takes you to a further page that lists the article titles for the particular quality-importance pairing. (Clicking on the numbers also changes their colour, as it has done for two of the numbers in this image.) For example, clicking on the number “2” in the cell (FA, High) takes you to a table that shows the two articles that are considered “featured” (Wikipedia’s highest quality) and high-importance:
This table shows us that: (i) both articles were rated high-importance on 22 August 2009; (ii) the article “Attachment theory” became a featured article on 30 November 2009; and (iii) the article “Reactive attachment disorder” became a featured article on 18 June 2009. Clicking on the titles under the “Article” heading takes you to the current versions of the articles; clicking on the dates takes you to permanent links to the earlier versions, which, as a pink warning banner declares, “may differ significantly from the current revision.” The letters “t” and “h” are links to the Talk and History pages for the articles; the letter “l” and the heading “Score” relate to the eventual release of the article as part of the offline project, Wikipedia 1.0.
Putting it All Together: Using the Tools to Assign Articles for Editing
From the above, you can see how these tools—the assessment grid and article tables to which they lead—can be used to create a shortlist of existing Wikipedia articles for students to edit. In the AFOD assessment grid, for example, there are 62 articles rated as stub-class or start-class and considered to be top-, high- or mid-importance. This is a likely place to look for candidates for impact and improvement—though even the C- and B-class articles may also be good candidates if the aim is to achieve at least GA status. From this universe of candidates, instructors can generate a list of articles to which students can be reasonably expected to make a meaningful contribution, or from which students can choose their own articles to edit. For example, WikiProject Canadian law, of particular interest to me, has some 300 stub- or start-class articles of mid- to top-importance. The average workload, Ω, is 5.09. There is a lot of work to be done in Wikipedia—and I haven’t even begun to consider the task of writing new articles!
John Kleefeld is an associate professor at the College of Law and a 2017 teaching fellow at the Gwenna Moss Centre for Teaching Effectiveness, where he is coordinating a campus-wide project on integrating Wikipedia assignments into course materials. Portions of this blog series are from an article that he and a former law student wrote about using a Wikipedia assignment for class credit. See J. Kleefeld and K. Rattray, 2016. “Write a Wikipedia Article for Law School Credit—Really?” Journal of Legal Education, 65:3, 597-621.
 That is, 986 ÷ (11 + 22 + 48 + 90 +30) = 4.91.