Growth/Personalized first day/Structured tasks/cs

Tato stránka popisuje práci týmu Growth na projektu strukturovaná editace. Tento projekt souvisí s dalšími projekty týmu Growth: Editačními tipy a Domovskou stránkou. Tato stránka obsahuje nejdůležitější informace, otevřené otázky a rozhodnutí. Více novinek týkající se práce týmu Growth najdete na všeobecné stránce s aktualizacemi. Závažné a větší aktuality budou pak vloženy i sem.

Současný stav

 * 2020-05-01: planning and documenting initial notes

Shrnutí
Tým Growth nasadil Editační tipy v listopadu 2019, což nováčkům ukázalo články, které by mohli editovat, na jejich Domovské stránce. V dubnu 2020 byly tyto články generovány pouze na základě údržbových šablon vložených zkušenými editory, což nováčkům neumožňuje přesně určit, jaké sekce, slova či sekce potřebují jejich pozornost. I přes to ale nadšeně pozorujeme, že nováčci produktivně editují.

Ačkoliv údržbové šablony poskytují nováčkům velké množství různých tipů, kterým by se mohli věnovat, jsou velmi obsáhlé, aby s nimi nováčci snadno uspěli. Na mobilních zařízeních je navíc velmi těžké používat jakýkoli editor - ať už vizuální, nebo wikitextový.

Z tohoto důvodu jsme se rozhodli experimentovat s nápadem strukturované editace. To znamená, že rozebereme každý editory používaný postup na jednotlivé kroky, které jsou pro nováčky snadno uchopitelné. Podle výsledků jazykového týmu a týmu pro Androidovou aplikaci soudíme, že to pomůže nováčkům snadno udělat více editací, a to i na mobilu. Tato strukturovaná editace bude dostupná nováčkům jako součást editačních tipů.

Editování je komplikované
Podle naší předchozí práce soudíme, že první okamžiky nováčka rozhodují o tom, zda na projektu zůstane, či nikoliv. Věříme, že nováčci zůstávají, pokud dokážou rychle něco změnit, a mít tak pozitivní zážitek. Bohužel, editování Wikipedie – téměř jakýkoliv typ příspěvku – je obtížný, což znesnadňuje uspět. Například, pokud chcete přidat do článku jedinou větu, musíte provést zhruba tucet kroků.


 * 1) Nalézt správný článek
 * 2) Zjistit, zda náhodou tato informace již v článku není
 * 3) Vybrat sekci, do které větu přidáte
 * 4) Kliknout na tlačítko Editovat
 * 5) Vložit větu na správné místo
 * 6) Klikněte na tlačítko Citace
 * 7) Vraťte se do zdroje informace, a zkopírujte si odkaz či získejte citační informace
 * 8) Vyplňte a uložte citační formulář
 * 9) Klikněte na tlačítko Zveřejnit změny
 * 10) Vyplnit shrnutí editace
 * 11) Zveřejnit

Nováčci, kteří vidí editor poprvé v životě, neví, jaké tyto kroky jsou, v jakém pořadí by je měli dělat, a jaké tlačítka mají přesně stisknout, aby se to stalo. Jinými slovy, jejich zážitek není strukturován. Nováček se může cítit přetížen, a odejít. Nebo může využít metody pokus-omyl, což často má za následek negativní zpětnou vazbu od dalších, zkušenějších, wikipedistů, což nováčka rovněž může odradit. To je to, o čem je tento projekt: "jak pomoci nováčkům dělat kroky ve správném pořadí?"

Building on knowledge from other teams
Adding structure to editing workflows has been part of the Wikimedia projects for a long time. Some examples include:


 * HotCat: lets users choose categories to add to articles with a few clicks, instead of manually editing the wikitext.
 * Commons Upload Wizard: breaks the process of uploading media to Commons into a series of a simple steps.
 * Citoid: available in the Visual Editor, this breaks down the process of adding a citation into steps that include algorithms to automatically produce the citation text and template.

Most recently, the idea of "structured tasks" has been working well on the Wikipedia Android app and in the Content Translation tool. We're inspired by their work.

With their "suggested edits" project, the Android team broke down the process of adding a title description to a Wikipedia article into one easy step of typing into a text box. They have since done the same with translating title descriptions across languages. In order to do the same tasks without a structured workflow, users would have to go to Wikidata and go through several steps to make those same edits. The team learned that this method works: many Android users make hundreds of these small contributions.

The Language team built the Content Translation tool, which does several things to structure the process of translating an article. It offers a side-by-side interface built for translations, it breaks the translation down into sections, and it automatically applies machine translation algorithms. Though Wikipedians could translate articles before the existence of the tool, the number of manual steps required made it very difficult. This tool is successful, with hundreds of thousands of translations completed. We learned that when translating an article is broken down into steps, with rote parts (e.g. running machine translation) taken care of automatically, more articles get translated.

The Growth team is thinking about applying these same principles to content edits in articles, like adding links, adding images, adding references, and adding sentences.

A structured task sketch
The best way to explain how we're thinking about structured tasks may be through showing a quick sketch. The first structured task we've thought about is "add a link". But the same ideas could apply to structured tasks for "add an image", "add a reference", or even "add a fact".

In the newcomer tasks feature, lots of newcomers complete "add a link" tasks -- in which they add internal blue links in articles that don't have many. This seems like a simple editing task to get started. But we think that many newcomers may not understand how to go through the steps of adding a link and may not know which words to make into links. We're imagining a workflow that walks them through it, step-by-step, with the assistance of an algorithm that can guess which words or phrases might make the best links.

In the sketch below, the newcomer arrives on an article, and is given a suggestion of a word that might make a good link. If they agree that it should be made a link, they are walked through the steps of making the link. This will hopefully teach them to add links on their own in the future -- and perhaps they'll enjoy continuing to receive these algorithmic link suggestions. Regarding the algorithm, the WMF Research team has done some preliminary work that makes us confident that such an algorithm is possible.



In thinking further about this, we sketched a second idea. Instead of being aimed toward teaching the newcomer to add links using the visual editor, this next workflow lets the user quickly confirm or reject recommendations from the algorithm, directly editing the article. While it does not teach them how to add links via the editor, it might help a newcomer edit at high volume, and might be a better fit for a user who is trying to be productive with simple tasks while they are on the go. Or perhaps might be a good fit for users who only are interested in very simple edits, similarly to how the Android app has many editors who only want to write title descriptions.



In thinking about structured tasks, it looks like this might be a big question: should workflows be more aimed toward teaching newcomers to use the traditional tools, or be more aimed toward newcomers being able to do easy edits at higher volume?

Why this idea is prioritized
We think that quickly making productive edits is what leads to newcomer success. Once they've done some edits, the rest of the wiki experience quickly becomes richer. Newcomers can then see their impact, get thanked, ask informed questions to their mentors, create their userpage, etc. Therefore, we want lots of newcomers to make their first edits as soon as possible. We have already seen from the newcomer tasks project that many newcomers are looking for easy tasks to do. But we also have observed these things:


 * Only about 25% of the newcomers who click on a suggestion actually edit it.
 * Only about 25% of those who do a suggested edit do another one.
 * There are a handful of newcomers who really thrive on suggested edits, doing dozens of them every day. This shows the potential for newcomers to accomplish a lot of wiki work.
 * In live user tests, when newcomers are told to copyedit an article or add links to an article, they frequently want to know exactly which sentence or words need their attention. In other words, attempting to edit the full article is too open-ended.

Taking these points along with the experiences described above of the Android and Content Translation teams, we think we could increase the number of newcomers editing and continuing to edit by structuring some of the content editing workflows in Wikipedia.

Opportunities with structured tasks
When we break down editing workflows into steps, we call them "structured tasks". Here are some of the possible benefits we think could come from structured tasks:


 * Make it easy for newcomers to make meaningful contributions.
 * Develop editing workflows that make sense for mobile. Mobile design principles tell us that users should see one step at a time, not a complicated workspace.
 * Let newcomers increase their skills incrementally. They could take on successfully more challenging types of tasks.
 * Let people find an editing experience that fits them. By giving newcomers a feed of structured tasks, they could find the type of tasks that they prefer.
 * Perhaps similar workflows could be opened to experienced editors in the future.

Concerns and downsides to structured tasks
Whenever we add new ways for people to edit Wikipedia, there are many things that can go wrong:


 * By making editing too quick and easy, we may attract vandals, or users who don't apply enough care when editing.
 * Giving newcomers simple workflows may keep them from learning the traditional editing tools, which are essential for doing the most impactful wiki work.
 * Structured tasks may not be good at accounting for differences across languages, idiosyncrasies with wikitext, and could cause other kinds of bugs.
 * Algorithms that surface structured tasks may not be accurate enough, and falsely encourage newcomers to complete edits they shouldn't.