Trainer-teacher-learners, as I noted while facetiously promoting a game called Speed PowerPointing a few years ago, have a magnificent ability to transform challenges into learning innovations. That ability was on display again yesterday when new and returning members of the #lrnchat community engaged in our weekly (Thursdays, 8:30 pm ET/5:30 pm PT) tweet chat and, in the process, seemed to create a new format we might call “Macho Tweet Chatting.”
#lrnchat participants, as the community blog explains, “are people interested in the topic of learning from one another and who want to discuss how to help other people learn in formal, informal, social and mobile ways.” The weekly chats (originally 90 minutes, now 60 minutes) have a well-established format: begin with brief introductions; warm up by responding to a question about what we learned that day (or that week if we somehow went all day without learning something); respond to six inter-related questions on a pre-announced theme; and conclude by posting wrap-up tweets during which we re-introduce ourselves and are encouraged to engage in shameless acts of self-promotion (which usually help us learn what our colleagues are currently doing/promoting/producing). When the virtual smoke clears from those hour-long sessions, we find that we’ve taken approximately eight or nine minutes to respond to and build upon colleagues’ comments about each of those six questions.
But that wasn’t what we encountered when we joined a session on the topic of Persistence in Learning yesterday. The community organizers, with little explanation until we were well into the session, had decided to create lightning rounds by tossing 10 rather than six questions (in addition to the usual introductions, wrap-up, and what-did-you-learn questions) into the mix. It was only when someone asked why the chat seemed to be moving much more quickly than usual that we learned what was behind the innovation: those preparing the questions about persistence had difficulty in winnowing down the number of proposed questions, so they changed the format rather than eliminate thought-provoking content that would foster our learning process yesterday.
The usual format fosters numerous initial responses, some retweeting of those responses so that others not engaged in the live session have a glimpse of what our discussions produce, and a variety of playful offshoots as individual community members engage one-on-one before another question from the community moderators more or less draws us all back together into a somewhat cohesive online conversation. The increased number of questions within an unexpanded period of time simply upped the ante: we had to respond much more quickly than usual; we struggled to engage in the retweeting that is such a fundamental element of expanding the community into the larger communities in which each of us individually interacts; and the playful one-on-one side-conversations were even more frenetic than usual.
It was clear that this was the sort of learning opportunity that would require some after-class effort to fully appreciate what we experienced—and learned—via the lightning-round format. Immediately creating an initial stand-alone transcript via Storify rather than waiting for community moderators to post it on the blog later this week made it obvious to me that many of the tweets were shorter than usual. (I suspect that the 140-character ceiling on tweets was higher than many of us could reach given the time limits we faced in composing each tweet.) Skimming that transcript so soon after the session ended also made me realize how much more content I had missed than I normally do—and made me appreciate how helpful it was to have created a useful learning object in the form of a Storify document—rereading content provided plenty of valuable opportunities to continue benefiting from the wisdom of this particular crowd by luxuriating over some of the observations; laughing at some of the funnier exchanges; and relishing the sense of support upon which a community like #lrnchat is built and sustained.
A post-session reading also produced some insights that may not have been intended by those posting comments. When we see someone post “eyes glazing over” in response to a question about when it is better to surrender rather than persevere, for example, we can also retroactively read the comment as a reflection of the idea that some of us may have felt our eyes glazing over because of the fire-hose flood of information coming our way. When we see even one of our most agile, literate, and pithy colleagues acknowledge that “it’s hard to catch up on this fast-moving #lrnchat,” we’re reminded that in connected learning environments and connectivist massive open online courses (MOOCs), the best lesson learned is that it’s not actually necessary to “keep up”—learning is often about what we can and choose to absorb rather than being about what someone else wants us to absorb. And if we’re empathetic enough to carry our own frustration over not keeping up into an appreciation for the frustration overwhelmed learners feel, we’ve absorbed an important lesson through the experiential learning #lrnchat so frequently fosters. And when we re-read my own tongue-in-cheek suggestion that #lrnchat may need to adopt The Flash and Quicksilver as our mascots, we might also take the suggestion as a reminder that training-teaching-learning at times seems to require superpower-level skills.
What remains most encouraging and most important is that, at the end of the day (and the Macho Tweet Chat), those who stayed with it acknowledged how invigorating and—in the most positive of senses—challenging the session was. We came. We chatted. We laughed. We learned. And, in the best of all worlds, we experienced an exercise (and form of exercise) we may be able to share with some of our most advanced learners so all of us continue learning together.