User:MCruz (WMF)/Sandbox/Storytelling toolkit/Knowledge base

Storytelling toolkit

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Evaluation Design Think of the story you will want to tell when, and even of the ending. Imagine as far as you can, and put it in paper! Evaluation starts when planning your next activity or overall program. Think in advance the goals you will measure against, and what metrics could indicate success. Achievable goals. Prepare the report in advance, and update it later. Set up a feedback cycle. Community impact: have a clear target audience in mind. Surveys at different points: plan in advance when you will run surveys about your program. Surveys Your program participants and your partners could be your allies in storytelling. Bring their voices forward with this traditional evaluation tool! Surveys help you know more about the audience you relate to through your activity or program: how old are they? What is their main motivation? What do they think of Wikimedia projects? Did they have fun? Do they feel safe editing? These and other questions can be answered via surveys. This is a complex tool, and program leaders need to consider different aspects when creating a survey. Who should we survey? Defining your survey audience is key. Survey Question Bank. This is a collection of survey questions that you can use to put together your own survey, according to different goals. Framing survey questions: how to approach complex questions in order to get the response you want. Asking the right questions. This learning pattern helps you organize the information you want to find out in your survey. Forms with blank responses can be confusing! Some mistakes to avoid in survey creation. Conducting a semi-structured interview. Timing and tenaciousness: How to ensure high participation rates at post-conference surveys. Reporting How can you relate the current questions in the report structure with the story you want to tell? Are the requested metrics relevant to your context? What other possible metrics could be included? Accumulated experience around standard metrics can help you gather data and think about what matters to you specific context. Calculating global metrics: an overall pattern that looks at standard metrics. Counting featured, quality and valued content in Commons. Evaluating project outcomes.

The Learning Pattern Library has a few collections that can help program leaders evaluate and report programs in a way that is meaningful to the context and beyond. Have experience in these fields? Help expand the knowledge base by writing a Learning Pattern!