Knowledge, Creativity and Action in Hybrid Learning Communities

The best sociotechnical systems will not only support crowd work, but also will empower individuals to explore, create, and learn. As individuals flock to sociotechnical systems, researchers are still learning how to understand their dynamics.

My work focuses on the processes by which groups of people in online and hybrid communities influence one another’s creative processes and knowledge sharing. I am concerned with how members of technologically-supported communities build understanding and influence one another over time and how technological systems can be built to support individuals collaborating, interacting, and creating. I situate my work within theory from the learning sciences, sociology, and psychology including communities of practice, legitimate peripheral participation, social networks and diffusion of innovation. At different points in my career I’ve focused on communities centered on 1) designing and sharing creative content and 2) engaging data-driven civic action.

Supporting Creativity and Knowledge Acquisition in Learning Communities

My dissertation at the MIT Media Lab, The Sharing of Wonderful Idea: Influence and Interaction in Online Communities of Creators, addressed how to support creativity in two communities, Scratch and the Computer Clubhouse.

Designing socio-technological infrastructure to promote creativity requires supporting individual members, interactions between members, and the group as a whole. Thus, I believe three levels of creativity should be supported: individual, social and collective. People demonstrate individual creativity when members has an idea new to them, even if not to others. Social creativity can be defined as when someone’s product is of value to another member of the community. Value is demonstrated when others in the community adopt or use the idea. Collective creativity is when a group of people contribute to a common creative idea. By investigating creativity at these three levels we can better understand how sociotechnical systems can support both individuals and groups.

Scratch is a visual programming environment for young learners. When Scratch’s online community went live, I studied how its existing users were impacted by the dynamics of the site’s meteoric growth. My eight-month ethnographic investigation of a middle-school Scratch club’s experiences revealed how the members came to understand themselves as Scratchers at three different times: before the site, at site’s initial limited release, and its subsequent rapid growth. Next I analyzed behavioral patterns using web log files community and determined the factors that predict two kinds of influence in the community: social influence and project influence, both key elements of understanding social creativity. These appeared to be two distinct constructs within the community that had implications for how to create a supportive community and how to seed the community with new information.

The Computer Clubhouse Network is composed of 100 after-school learning centers in which underserved youth create with technology. In its online community youth from the physical clubhouses share and discuss their creative work. In my dissertation I 1) described email communication patterns used social network analysis, 2) developed a new social technology designed to diffuse through the community, and 3) then observed how people adopted the innovation by studying the diffusion patterns using social network analysis.

Later as a Research Scientist in the Educational Gaming Environments Group at TERC, I shifted my research to understanding knowledge acquisition. I studied how people share information and built knowledge in digital gaming communities and investigated how knowledge diffused through these communities. In this work my collaborators and I focused on how knowledge sometimes is first implicit –understood but hard to articulate– and only later becomes explicit. Identifying implicit and explicit knowledge helps to design learning analytics both on the individual and social levels.

Data Literacy As a Mechanism for Civic Change

My current research addresses communities that are focused on data-driven civic action.

Our constructions of meaning, whether in the form of formal papers, websites, or social media posts both represent and become our understandings as individuals. Then they allow us to share our ideas and create dialogue with others. This is the iterative work of long societal dialogues, those between writers, critics, and scientists alike. Thus, when we provide people with the tools to create representations of their understandings, we open up possibilities for them to participate in the public dialogue of ideas.

For a civil society to exist, citizens must be able to interpret data effectively, to create and understand data-driven arguments. Many people don’t know how examine data or make a cogent argument with it. Without these abilities, people can treat all data-driven arguments as equivalently right or wrong, regardless of quality.

In my current work I have been developing an approach to engaging communities with data, tools to support the approach, and training on how to use the approach and tools for civic change. I research and design programs in which learners engage in science inquiry within civic-minded communities and through the use of IoT sensors, data analysis tools and telling (non-fiction) stories with data.