What do you know? Connected learning outcomes explored
When I was a kid my dad used to come home from work and greet me by asking, “So what do you know, kiddo?” It was his way of saying hello. But as an seven year-old obsessed with World Book Encyclopedia’s way of sorting knowledge into alphabetized volumes of varying thickness I missed the obvious and instead took up his query at face value: What did I know? Each day I worried over selection of the juicy new fact or strange invention I could share with him over dinner. This was partly a strategy for ensuring that when a conversational break in the adult conversation naturally occurred, that I could slip in, drop my informational nugget, and get out unscathed. As a child of two teachers there was always the danger of the follow-up question, which I tended not to be particularly well prepared to answer—I understood how knowledge could be sorted alphabetically but didn’t quite get how it all fit together. Needless to say, I thought a lot about the outcomes of my own learning, if for no other reason than I felt like my dad’s question deserved a thoughtful answer.
So too, does the question of what participants in the online communities we are studying might know and be able to do. What do participants in Ravelry, StarCraft and LittleBigPlanet mod communities know and what are they able to do by way of their involvement in communities we see as being connected? What, in other words, are the types of learning outcomes a connected learning model might support?
This question is not an easy one to answer, partly because a connected learning model sees learning outcomes as emerging on both individual and collective levels. It is not enough for us to ask what an individual mod maker in the StarCraft community might know and be able to do; we also need to try and understand how expertise and mastery is developing in the community as a whole. It is not just individuals that can learn, we argue; communities do it, too. The individual outcomes of connected learning are inseparable from the collective environments through which these outcomes are produced.
Further, because connected learning, as a model, advocates for experiences that offer low barriers to entry and information, social supports for learning, and diverse opportunities for the development of interest and expertise, it must also advocate for outcomes that are both individual and collective in nature. It is no longer enough to develop metrics and pathways for individual outcomes; we must also find ways to recognize outcomes produced by groups or communities and provide pathways for collective participation. Or so our hypothesis goes.
Consider Ravelry.com, an online site for fiber crafters that Rachel Cody has been studying. Ravelry hosts nearly 25,000 groups of fiber crafters, from a Harry Potter-inspired group that marries fiber crafting with a fictional universe of kid wizards to hardcore pattern-making groups steeped in math. The site offers participants opportunities to showcase individual expertise, through posting, sharing, and achievements. It also offers opportunities, through its group structure, to showcase and celebrate collective outcomes, from civic engagements like hosting a challenge to create knitted baby hats for donation to hospitals to entrepreneurial outcomes like creating a shop at etsy.com to sell group-produced products.
As a community, the members of Ravelry produce knowledge and expertise, projects and products with academic, civic, and peer value. The welcoming nature of the site and the mere existence of the thousands of groups it hosts are mechanisms inviting participation and the development of shared knowledge. Conversely, the environment provides individuals with opportunities to acquire social, economic, and cultural capital, to learn domain-specific content and skills, and develop metacognitive skills and learning dispositions. Unlike models of learning that center solely on individual outcomes and competition for zero-sum resources and rewards, like those seen in most schools, Ravelry exemplifies how connected learning is value-additive, elevating individuals and collectives in an integrated way. High-functioning connected learning environments are characterized not only by engaged learning at an individual level, but by high quality content and standards and collective purpose that is shared by all participants.
Connected learning experiences require connected learning environments that are characterized by high standards for knowledge and expertise, shared norms, and ways of marking contributions and achievement. We are seeing this in our work with sites like Ravelry, as described above, as well as in our study of StarCraft and LittleBigPlanet mod making communities. While we don’t yet have a full picture of the mechanisms by which individual and collective learning outcomes are recognized within connected learning experiences, we are starting to build a framework for what those outcomes might look like, and how they might be supported. That is the topic of a future post, however. Follow up questions are always the hardest to answer.