This task will start with @SNowick_WMF and possibly accrue subtasks. @JTannerWMF may add content to this task.
The insight we seek to gain through instrumentation will include:
[] How does the lack of understanding English influences the ability for someone to complete the task
[] We need to explicitly track, which source the image is coming from (Wikidata, Commons, Other Wikis), so that we understand the influence that has on accuracy.
[] We want to understand the success rate of the tutorial
[] We want to know if people like the task. A method to do so is to evaluate if users return to complete it on three distinct dates
[] We want to compare frequency of return to the task (retention) by date across user tenure and language to understand if there was more stickiness for this task by how experienced a user is and if they speak English or not
[] Ensure we can see if someone backgrounds the app
[] Of the people that got the task right, how long did it take them to submit an answer? We want to see this data to categorize if a match is easy or hard
[] We want to see if someone clicked to see more information on a task, this will help us determine the difficulty of a task
[] We want to know how often someone selects certain choices in the pop up dialog in response to No or Not Sure
[] We want to see the user name if they opt-in to showing it
[] We want to know if someone scrolled the article
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Draft schema, based on the above requirements:
* `lang` - Language (or list of languages, if more than one) that the user has configured in the app.
* `pageTitle` - Title of the article that was suggested.
* `imageTitle` - File name of the image that was suggested for the article.
* `suggestionSource` - Source from which this suggestion is being made, e.g. whether the image appears in another language wiki, inside a wikidata item, etc.
* `response` - The response that the user gave for this suggestion. This could be a text field, i.e. literally `yes`, `no`, `unsure`, or a numeric value (0, 1, 2), whichever will be simpler for data analysis.
* `reason` - The justification for the user's response. Since the user may select one or more reasons for their response, this will be a comma-separated list of values that correspond to "reasons" that we will agree on (0 = "Not relevant", 1 = "Low quality", etc)
* `detailsClicked` - Whether the user tapped for more information on the image (true/false).
* `infoClicked` - Whether the user tapped on the "i" icon in the toolbar.
* `scrolled` - Whether the user scrolled the contents of the article that are shown underneath the image suggestion (true/false).
* `timeUntilClick` - Amount of time, in seconds, that the user spent before tapping on the Yes/No/Not sure buttons.
* `timeUntilSubmit` - Amount of time, in seconds, that the user spent before submitting the entire response, including specifying the reasons for selecting No or Not sure.
* `userName` - The wiki username of this user. May be null if the user did not agree to share.
* `teacherMode` - (true/false) Whether this feature is being used by a superuser / omniscient entity.