Dialogues/informal learning

= All Communities are Learning Communities =

'''Please read the Virtual Event Code of Conduct. We will be recording the event presentations, but not discussions.'''

''The Community Data Science Collective is organizing a series of events called The Science of Community Dialogues with community leaders, organizers, and experts. We are inviting a small number of leaders from across open source communities, online platforms, activist groups, and research organizations to participate.''

This online meeting will take place on September 30th, 2022 9-11 am PDT. The presenters are Regina Cheng (University of Washington) and Dr. Denae Ford (Microsoft Research).

This event is being paid for by a National Science Foundation grant, and will be held at no cost to attendees. A code of conduct will be shared with participants prior to the event. Discussions will be held under Chatham House Rule. Presentations will be recorded, though discussions will not.

If you are interested in attending, register here by Thursday, September 29 at 1pm PT. Participation will be limited to the first 40 registrations in order to have an active conversation.

The topic of this Dialogue is All Communities are Learning Communities. Every community involves the exchange of ideas, welcoming newcomers, and systems to help those newcomers learn how to be an active, successful contributor to the community. In these sessions, described in detail below, we will look at studies on how software developers become valuable members of communities, as well as research on how we teach, learn, and share outside of classrooms and formal education settings, building advanced skills within communities.

Informal Learning Communities
Regina Cheng (University of Washington)

This Dialog session will focus on the topic of online communities as a setting for informal learning. When people think of learning, they often think of formal education, i.e., classrooms and curriculum. When people think of online communities, they often regard them as places where people get together for a common interest. While communities and learning seem to be two separate things, we found evidence that online interest-driven communities can serve as an informal yet effective setting for members to learn and practice advanced skills. We think it would be valuable for community members, leaders, and designers to recognize this potential of online communities and think about the ways to support learning in communities.

To this regard, we will facilitate a conversation that draws from results from several empirical studies. Specifically, the following will be discussed:


 * What are the different things that members learn from online communities?
 * How do members learn in online communities? What are their needs in learning and what are some challenges?
 * How do members form mentoring relationships with each other?
 * How can we support learning in online communities?

Newcomers and Community Leadership
Dr. Denae Ford (Microsoft Research)

Online communities have been a home for software developers to convene and find support from one another -- starting from those early in their programming journey to those familiarly seasoned with a plethora of experiences. One thing that has always kept these communities alive is the social and technical support that members pour into one another. But how do we get there? What does it look like to create a welcoming and productive setting that helps everyone thrive? In this session, we’ll discuss findings from empirical studies that guide us on how to build communities that empower developers to do their best work.

Discussion points we’ll cover include:


 * Inclusive and welcoming learning environments for programmers
 * Supporting newcomers in your community
 * Empowering community leaders to adopt practices that enable learning

Acknowledgements
Thanks to speakers Denae Ford and Regina Cheng! Benjamin Mako Hill had the original idea, and, along with Aaron Shaw, helped direct the high level vision of the event. This event and the research presented in it were supported by multiple awards from the National Science Foundation (DGE-1842165; IIS-2045055; IIS-1908850; IIS-1910202), Northwestern University, the University of Washington, and Purdue University.