Change Details

=== Background One of the primary objectives of the WMF Product team (particularly Growth and Android), is to grow the contributor population, particularly in small-to-medium sized wikis. So far the focus has been on providing a variety of smaller tasks and also more structured tasks to get newer users to start editing, but there is little experimentation or data available on whether different types of positive feedback (thanks, awards, etc) is able to help sustain editor contributions and increase retention for those users who took the first step in making an edit. === Goal Review the various mechanisms that have been employed to encourage people to contribute content to both on and off-wiki products, and assess their relevance and potential impact—if applied—to the retention of newcomers editing on Wikipedia. * Identify and assess the efficacy of different types of positive reinforcement mechanisms used to encourage sustained user contributions in software. * Provide recommendations for what mechanisms could be used in the context of editor activation and retention for on wiki products. === Hypotheses | Questions 1. Showing users the positive impact of their contributions will encourage them to start contributing to Wikipedia. - What motivates users to start editing in the first place? - How are these motivations translated into retention mechanisms? 2. Users are more likely to continue contributing when recognition and rewards are personalised and come from a real person and. - Are messages of thanks or recognition from real people more effective in motivating contribution over automated sources? - What types of positive feedback or recognition are more likely to encourage sustained contributions? ==== Approach 1. Identify and evaluable different types of positive reinforcement mechanisms used on: (a) Wiki projects (Barnstars, Wikilove, Thanks, etc. and (b) Relevant offwiki products (e.g., Duolingo, Google Contributions, Fitbit, etc) 2. Literature review of research papers on the subject of positive reinforcement mechanisms to extract any actionable advice (this is effective, that is not, etc.) 3. Provide recommendations on ways to apply the knowledge gleaned from approach 1 and 2 in the form of prioritised taxonomy of positive reinforcement mechanisms 4. Create initial design explorations showing how they could be productised in Android and Growth. Note there is a recognized constraint that much of the review will be based on predominantly English-language sites and projects.

=== Background One of the primary objectives of the WMF Product team (particularly Growth and Android), is to grow the contributor population, particularly in small-to-medium sized wikis. So far the focus has been on providing a variety of smaller tasks and also more structured tasks to get newer users to start editing, but there is little experimentation or data available onwiki as to whether different types of positive feedback (thanks, awards, etc) is able to sustain editor contributions and increase retention for those users who took the first step in making an edit. === Goal Review the various mechanisms that have been employed to encourage people to contribute content to both on and off-wiki products, and assess their relevance and potential impact—if applied—to the retention of newcomers editing on Wikipedia. * Identify and assess the efficacy of different types of positive reinforcement mechanisms used to encourage sustained user contributions in software. * Provide recommendations for what mechanisms could be used in the context of editor activation and retention for on wiki products. === Hypotheses | Questions Bestowing users with rewards and recognition that appeal/match to their motivation(s) for editing will encourage their sustained contributions. - Showing users the potential impact of their contributions can instigate their participation. -- What motivates someone to start editing? -- Do specific messages appeal to specific groups more than others? - Providing positive reinforcement about their involvement will encourage users to continue contributing to Wikipedia. -- How might the motivating factors to start editing work for sustaining users interests in continuing to contribute? - Users are more likely to continue contributing when recognition and rewards are personalised and come from a real person. -- Are messages of thanks or recognition from real people more effective in motivating contribution over automated sources? -- What types of positive feedback or recognition are more likely to encourage sustained contributions? ==== Approach 1. Identify and evaluable different types of positive reinforcement mechanisms used on: (a) Wiki projects (Barnstars, Wikilove, Thanks, etc. and (b) Relevant offwiki products (e.g., Duolingo, Google Contributions, Fitbit, etc) 2. Literature review of research papers on the subject of positive reinforcement mechanisms to extract any actionable advice (this is effective, that is not, etc.) 3. Provide recommendations on ways to apply the knowledge gleaned from approach 1 and 2 in the form of prioritised taxonomy of positive reinforcement mechanisms 4. Create initial design explorations showing how they could be productised in Android and Growth. Note there is a recognized constraint that much of the review will be based on predominantly English-language sites and projects.

=== Background One of the primary objectives of the WMF Product team (particularly Growth and Android), is to grow the contributor population, particularly in small-to-medium sized wikis. So far the focus has been on providing a variety of smaller tasks and also more structured tasks to get newer users to start editing, but there is little experimentation or data available onwiki as to whether different types of positive feedback (thanks, awards, etc) is able to help sustain editor contributions and increase retention for those users who took the first step in making an edit. === Goal Review the various mechanisms that have been employed to encourage people to contribute content to both on and off-wiki products, and assess their relevance and potential impact—if applied—to the retention of newcomers editing on Wikipedia. * Identify and assess the efficacy of different types of positive reinforcement mechanisms used to encourage sustained user contributions in software. * Provide recommendations for what mechanisms could be used in the context of editor activation and retention for on wiki products. === Hypotheses | Questions 1. Showing users the positive impact of their contributions will encourage them to start contributing to WikipediaBestowing users with rewards and recognition that appeal/match to their motivation(s) for editing will encourage their sustained contributions. - Showing users the potential impact of their contributions can instigate their participation. -- What motivates userssomeone to start editing in the first place? - How are these motivations translated into retention mechanisms? 2. Users are more likely to continue contributing when recognition and rewards are personalised and come from a real person and-- Do specific messages appeal to specific groups more than others? - Providing positive reinforcement about their involvement will encourage users to continue contributing to Wikipedia. - Are messages of thanks or recognition from real people more effective in motivating-- How might the motivating factors to start editing work for sustaining users interests in contribution over automated sourcesinuing to contribute? - Users are more likely to continue contributing when recognition and rewards are personalised and come from a real person. -- Are messages of thanks or recognition from real people more effective in motivating contribution over automated sources? -- What types of positive feedback or recognition are more likely to encourage sustained contributions? ==== Approach 1. Identify and evaluable different types of positive reinforcement mechanisms used on: (a) Wiki projects (Barnstars, Wikilove, Thanks, etc. and (b) Relevant offwiki products (e.g., Duolingo, Google Contributions, Fitbit, etc) 2. Literature review of research papers on the subject of positive reinforcement mechanisms to extract any actionable advice (this is effective, that is not, etc.) 3. Provide recommendations on ways to apply the knowledge gleaned from approach 1 and 2 in the form of prioritised taxonomy of positive reinforcement mechanisms 4. Create initial design explorations showing how they could be productised in Android and Growth. Note there is a recognized constraint that much of the review will be based on predominantly English-language sites and projects.