One of the best parts of being in the business of thinking for a living is also one of the most frustrating – thinking is hard. And not only is it hard, it takes time. And not only does it take time, the route is often circuitous. Just when you think you’ve got it, that the idea or project as you have currently articulated it is finally there, you sit back, think again, and realize that you’re not there after all. Many times when I was an undergraduate I had this experience of working on a paper (I was a literature and philosophy major back then, so I wrote a lot of papers!) for weeks; then, the night before it was due, scrapping all but one or two paragraphs usually near the end and writing a whole new paper. I had similar experiences writing by dissertation where I would work and work a piece of it, then read it through and just set it aside as not going into the final text. It’s not the ideas were bad or improperly formed, but that they just weren’t right for that text at that time. Probably a lot of people have had similar experiences.
The work of the lab has many opportunities for thinking and working on an idea, bringing it as far as you’d think it can go and then two days later completely reformulating it. Partially this is because sometimes we have a clear idea of where we want to end up, but not clear paths for getting there. Other times, like Dewey claimed about democracy, we have an idea of what the perfect project or idea is, then at the point that we reach it, we realize that from our new point of view, we actually have a much different sense of what the perfect project or idea would be. Working under these conditions requires both a certain comfort level with ambiguity and a recognition that often the only way to get to something that’s really good, we have to work our way to it, grope our way in some cases.
Beyond living with ambiguity, such thinking requires a certain level of courage and trust: unlike those times when you’re locked up finishing a paper all night, most of the thinking we do on cyberlab exhibits, research, and projects is done out loud – by a group of us. We are floating ideas, trying them out in the group, responding to them, feeling our way to something that makes sense in a place where none of us is THE expert and where all of us at times are simultaneously articulating where we are going while we are trying to go there. It’s that old problem of building the boat while you’re sailing it. And that requires courage to articulate something for the first time and not be afraid that you will get wrong and to not be afraid to keep working it till you really like it. It also requires trust – trust that everyone else is trying to help move the idea along and expand it rather than criticizing or devaluing. Embracing that process can be scary; after all, we like to have a clear path and sense of what the end result will be. But it can also be exhilarating as we push our thinking and our sense of where we are going together.
A nice article on some of our current efforts came out today in Oregon Sea Grant’s publication, Confluence. You can read the story on-line at http://seagrant.oregonstate.edu/confluence/1-3/free-choice-learning.
One of the hardest things to try to describe to Nathan Gilles who wrote the article (and to the folks who reviewed the draft) is the idea that in order for the lab to be useful to the widest variety of learning sciences researchers, the cyber-technologies on which the museum lab are based have to be useful to researchers coming from a wide range of theoretical traditions. In the original interview, I used the term “theory agnostic” in trying to talk about the data collection tools and the behind-the-scenes database. The idea is that the tools stand alone independent of any given learning theory or framework.
Of course, for anyone who has spent time thinking about it, this is a highly problematic idea. Across the social sciences we recognize that our decisions about what data to collect, how to represent it, and even how we go about collecting it are intimately interwoven with our theoretical claims and commitments. In the same way that our language and symbol systems shape our thinking by streamlining our perceptions of the world (see John Lucy’s work at the University of Chicago for the most cogent explanations of these relationships), our theories about learning, about development, about human interaction and identity shape our research questions, our tools for data collection and the kinds of things we even count as data.
Recognizing this, we struggled early on to develop a way to automate data collection that would serve the needs of multiple researchers coming from multiple frameworks and with interests that might or might not align with our own. For example, we needed to develop a data collection and storage framework that would allow a researcher like John Falk to explore visitor motivation and identity as features of individuals while at the same time allowing a researcher like Sigrid Norris to document visitor motivation and identity as emergent properties of mediated discourse: two very different notions of identity and of best ways to collect data about it being served by one lab and database.
The framework we settled on for conceiving of what kind of data we need to collect for all these researchers from different backgrounds is focused on human action (spoken and non-spoken) and shaped by a mediated action approach to understanding human action. Mediated action as an approach basically foregrounds agents acting in the world through the mediation of cognitive and communicative tools. Furthermore, it recognizes that such mediated action always occurs in concrete contexts. While it is true that mediated action approaches are most often associated with sociocultural theories of learning and Cultural Historical Activity Theory in particular, a mediated action approach itself does not make strong theoretical claims about learning. A mediated action framework means we are constantly striving to collect data on individual agents using physical, communicative, and cognitive tools in concrete contexts often with other agents. In storing and parsing data, we strive to maintain the unity of agent, tools, and context. To what extent this strategy turns out to be theory agnostic or learning theory neutral remains to be seen.
Last Friday, Nancy Steinberg, a freelance science writer, and I held a Science Pub Dialogue Event at Rogue Ales across the street from HMSC. We had about 50 folks in the audience, pretty normal for the science pubs sponsored by HMSC. But Nancy and I didn’t want to do a traditional scientist presentation. Instead, following up a project we did earlier this year in Yachats, Oregon, we wanted to create a dialogue between us and the audience around how what we know about free-choice learning can help scientists communicate their work. The audience was probably about 1/3 scientists, 1/3 educators and 1/3 interested folks, and the dialogues worked great. We talked together, the audience talked with us, the audience talked with each other, and the conversations continued for almost an hour after the program officially ended!
The next morning, I left to spend the week of the 15th in Vancouver, British Columbia attending the American Educational Research Association (AERA) Conference and the Vancouver Aquarium. The conference is always useful, but frankly at about 12,000 attendees, too big. This year to make the conference more doable, I primarily attended talks and sessions sponsored by the Informal Learning Environments Special Interest Group. Special interest groups allow you to find a home and strand of presentations within the mass of papers and talks spread out over a quarter of the downtown of the city. As a shameless plug for the Informal Learning Environments group, I’ll point out that the number of slots given to informal education and free-choice learning talks is determined by the number of folks who join the SIG and submit papers each year…
At the conference, I delivered the next in a series of papers outlining the findings from the work Jim Kisiel and I have been doing on family interactions at touch tanks for the last several years. This talk specifically detailed the types of scientific reasoning families are engaging in, unprompted by aquarium staff, arguing that live animal encounters provide a context for scientific reasoning that may be even more productive for families than typical interactive physical science exhibits, where families’ scientific reasoning has been documented before.
After the conference, I got to sit in on a couple of education programs at the Vancouver Aquarium and gave a lunch time talk on the Free-Choice Learning Lab projects that are the subject of this very blog. In the afternoon, I led a 2-hour workshop for staff from the aquarium’s education and interpretive staff on supporting visitor dialogues that can lead to learning. The workshop is a combination of tools we use in the Communicating Ocean Sciences to Informal Audiences class and strategies Heidi Schmoock developed in workshops she’s been running at Cal Polytech in San Luis Obispo. The goal was to introduce the idea of a dialogue or discussion map – a questioning strategy that helps ensure families are talking with educators, rather than being talked at, and that is specifically designed to promote the kinds of conversations that may lead to meaning making and learning.
How do we analyze and study something familiar and taken for granted? How do we take account of the myriad modes of communication and media that are part of practically everything that we do, including learning? One of the biggest challenges we face studying learning (especially in a museum) is documenting meaningful aspects of what people say and do while also taking into account the multiple, nested contexts that help make sense of what we have documented. As a growing number of researchers and theorists worldwide have begun to document, understanding how these multiple modes of communication and representation work to DO everyday (and not so everyday) activities, requires a multimodal approach that often sees any given social interaction as a nexus (a meeting point) of multiple symbol systems and contexts, some of which are more active and salient (foregrounded) at any given moment by participants or by researchers.
This requires researchers to have ways of capturing and making sense of how people use language, gesture, body position, posture and objects as part of communicating with one another – and for learning researchers it means understanding how all of these ways of communicating contribute to or get in the way of thinking and learning. One of the most compelling ways of approaching these problems is through what has come to be called a multimodal discourse analysis (MMDA).
MMDA gives us tools and techniques for looking at human interactions that take into account how these multiple modes of communication are employed and deployed in everyday activities. It also supports our tackling the issue of how context drives meaning of talk and actions and how talk and actions can invoke and change contexts. It does this by acknowledging that the meanings of what people say and do are not prima facie evident, but require the researcher to identify and understand salient contexts within which a particular gesture, phrase, or facial expression makes sense. We are all fairly fluent and deploying and decoding these cues of communication, and researchers often get quite good at reading them from the outside. But how does one teach an exhibit to read them accurately? Which ones need to be recognized and recorded in the database that drives an exhibit or feeds into a researchers queries?
Over the next several months, we’ll be working out answers to these questions and others that will undoubtedly arise as we get going on data collection and analysis. We are fortunate to have some outstanding help in this regard. Dr. Sigrid Norris, Director of the Multimodal Research Centre at the Auckland University of Technology and Editor of the journal Multimodal Communication, is serving as an advisor for the project. We’re also planning to attend the 6th International Conference on Multimodality this August in London to share what we are up to and learn from leaders in MMDA from around the world.
The FCL Lab is the fruit of 7 years of work to imagine creating a center for studying free-choice learning in the Visitors Center at HMSC. Tremendous support from Oregon Sea Grant’s current director, Steve Brandt, and former director, Bob Malouf, as well as sage leadership advice from former Associate Directo, Jay Rasmussen, and current assistant director, Joe Cone, gave us a great early foundation for advancing a research agenda around visitor learning that would be exciting and relevant to university researchers, ocean science educators, and the ISE field at large. We have also had great support for student and faculty research over the years from John Falk and Lynn Dierking heading up the degree programs in FCL through Science and Math Education at OSU and Kerry Carlin-Morgan, the Director of Education at Oregon Coast Aquarium, our next door neighbors and partners in both research and professional development. Funding from NOAA, NSF, Title IIB, and Sea Grant have supported our efforts to integrate research into the visitor experience. This early and ongoing support has made it possible for us to now take the next step to creating experiences that blend research and learning seamlessly and that will allow us to become an open lab space for researchers across the field.
This blog, our website, webinars, and ongoing publications are great ways to find out about and get involved with the amazing group of faculty, students, museum educators, evaluators, developers, designers, and researchers we are working with both in Oregon and nationwide. So, welcome to the FCL Lab. I hope you will become a part of our community!