*THIS TASK IS STILL UNDER CONSTRUCTION*
While we believe that adding images to unillustrated articles is going to be a doable and compelling structured task for newcomers, we have some open questions that can only be answered by putting experiences in front of actual users. Here are two big questions:
- Is our recommendation algorithm accurately surfacing matches that should be added to articles?
- Are newcomers able to confidently confirm the match using the article, image, and image metadata that we can provide?
- Are newcomers able to write good captions using the article, image, and image metadata that we can provide?
- Do newcomers find this task interesting/rewarding/difficult/boring/easy?
To pursue these questions, we want to build a simple tool that surfaces image recommendations and lets users choose whether to add them. This tool would not actually edit Wikipedia, but rather would just simulate the experience of adding images so that we can conduct user tests internally and externally.
One approach would be to build it in two phases:
Phase 1: barebones
Objective: let staff and interested community members quickly experience a series of real image recommendations, giving us all a feel for how strong the algorithm is.
- Draws from a file of image matches and metadata. This exists in T266271.
- Displays the article preview; recommended image; and description, caption, source, and depicts statements for the image.
- User can click a link to open full article in new tab.
- User can click a "Yes", "No", or "Skip" button to advance to the next recommendation.
- Next recommendation is drawn randomly from the file.
Optional ideas, not totally thought-through:
- We include a text field for writing a caption. It could co-exist with the "Yes", "No", "Skip" buttons.
- User can type some identifier (like their name) into a text field during their session. When they click "Yes", "No", or "Skip", this records their name, response for that image, and caption somewhere for us to look at. Then we could see how often users agree on the recommendations, and how often they select "Yes", "No", or "Skip".
Phase 2: user experience
Objective: place real recommendations in a more complete user experience that we can give to live user testers, so that we can get a sense of how users feel about adding images to articles.
One idea is to improve the UI of the Phase 1 tool from above. Another idea might be to hardcode a short series of recommendations (perhaps 15 recommendations) to be served with an Axure prototype. This is all TBD.