New Engagement Experiments/PES 1.3.3: Incubator space

Hypothesis: If we develop a new process/track at a Wikimedia hack event to incubate future experiments, it will increase the impact and value of such events in becoming a pipeline for future annual plan projects, whilst fostering more connection and enthusiasm from engineering/design staff and/or volunteers to experiment and engage more with strategic prospects.

Primary success metric - One PES1.3 project is initiated and/or advanced to an OKR from this event.

Status: Completed. Pending report of learnings and recommendations.

Incubator space experiment: Sprinthackular 2024

Aim: Organise an event that supports the “New Engagement Experiments” work in this year’s PES1.3 KR, which aims to encourage staff to work on more small experiments around growing Wikipedia as a knowledge destination for our current consumer and volunteer audiences. This became known as the "Sprinthackular" The Sprinthackular is more targeted than a hackathon, where participants each worked on specific project groups with an explicit goal to make internal prototypes to demo by week’s end.

Goals of the Sprinthackular:

For each group develop an internal prototype to demo by the end of the week in a final showcase
The demo and learnings from the week will help us to determine
- (a) Is this idea worth graduating to experiment?
- (b) If yes, how will we scope the external test to enable actions and future product plans
Working more with colleagues across teams and departments.

Event details

Dates: Aug 12-16 (week after Wikimania 2024 in Katowice)

Location: Remote/Online

Groups/Tracks

There were four different groups, with participants being committed/attached to one project at the start of the event. Each group had a team lead responsible for coordinating ideation, coding and discussion sessions. Below are more details about each group/project track.

Group A. Wikipedia Year in Review (WikiYiR)

Challenge: Year in Review summaries and celebrations have been used successfully by other organizations and products to encourage reflection, participation and engagement. How might we stimulate greater connection with Wikipedia by providing target audiences with insights about their on Wiki community or broader global insights and sister project work?

This work connects to the PES1.3.1 Wikipedia insights hypothesis.

Group B. Android App Trivia Game

Challenge: Daily ‘mini’ games have been used successfully by other organizations and products to encourage learning, participation and engagement. How might a daily play ‘on this day’ trivia game highlight connections across vast areas of knowledge, encourage consumers to visit Wikipedia regularly and facilitate active learning – all leading to longer increased interaction with content on Wikipedia?

Summary for Participants: Participants will engage in creating a multiple choice, daily play, trivia game utilizing ‘On This Day’ content for the Wikipedia Android app. The goal of the game is to encourage increased interaction, sharing and learning for target audiences. A focus should be placed on utilizing existing APIs and data sources.

This work connects to the PES1.3.2 Wikipedia games hypothesis.

Group C. WikiRace Game

Challenge: Daily ‘mini’ games have been used successfully by other organizations and products to encourage learning, participation and engagement (see for example Wordle, LinkedIn, Duolingo). Separately, there are many versions of a Wikipedia linking / race / speedrun game that exist (eg. Wiki linking game, wiki-race, etc). How might we build a first party version of this known Wikipedia game that encourages consumers to visit Wikipedia more regularly? How might this game lead to deepening engagement via visits, donation, account creation, and even contribution (as people learn about how Wikipedia works)?

This work connects to the PES1.3.2 Wikipedia games hypothesis.

Group D. AI-assisted video summaries

Challenge: There are many short “explainer” videos on popular platforms like TikTok and YouTube Shorts that summarize a broad range of knowledge topics into a minute-long video. Just a few examples: The Tiffany Problem (Wikipedia), the Spanish Civil War (Wikipedia), the meaning of the song “Makeba” (Wikipedia). Young people globally spend a great deal of time on and get information from these platforms, and AI tools have made it easy to generate videos like this from existing sources (including Wikipedia – example: What is the history of Mexico City?).

This work connects to early explorations being explored by the Future Audiences team for future experiments.