Outcomes of FLC project – Revising my cluster course to reflect “open production”

This FLC sparked my interest in the idea of “open production” in science – a way of performing work that hews more closely to the ideals of how science “ought” to work and to some extent a remedy for the pressures at most academic institutions to engage in practices that degrade scientific quality.


Course redesign – Open production

I proposed for my FLC project that I would incorporate some of these ideas into the redesign of my cluster course that I was undertaking already to reshape it into a new partnership with Rita Chesterton as “Designing for Science – Designing for Market.” The course is centrally about how to do good, effective design. For a product that you might want to market, that means starting with your potential audience first and working with them to understand their needs and iteratively involving them in the design process rather than inventing a product and only then asking, “I wonder who I could sell this to?” For science, that can mean, among other things, setting up social pressures for yourself that will help ensure that you are designing and testing with rigorous, statistically robust processes.

As often happens when I experiment with a course, I guessed correctly only some of my students’ responses. It turned out to be unexpectedly easy for my students to generate the reasons why open production would be useful in science. I used The Invisible Gorilla to introduce the idea that humans tend to think that we perceive, remember, and attend to a lot more than we really do, and our intuitions about these things tend to color the way we interact with other people. By framing the conversation with these concepts already in mind, my students were readily able to speculate accurately about the biases (most unintentional) that can affect scientists and suggest ways in which open production might counteract these problems.

So the motivation for the concept required much less time and energy than I had anticipated. However, because we did not progress to the main team project until later in the semester than I had originally planned, I have had fewer opportunities to have the students practice the application of these ideas.

But yesterday in class, each of the 3 teams of students, who are all working on different applications of Brain-Computer Interfaces, made concrete predictions of the outcomes of their project work in the remaining 4 weeks of the semester. We will be able to return to those predictions and compare them against the reality of what happens. I do not usually ask my students to make predictions this specific, so it will be interesting to see how this turns out.

Team science – outcomes and conference reporting

This course, and a previous version of the cluster taught with Brett Fadem, is particularly special to me because it has given me a chance to experiment with ways of helping undergraduates learn how to work effectively and efficiently in teams. Assigning students to work in a team is not the same as teaching them to work in a team. Without teaching, students inevitably come out of team projects with the exact same skills they walked in with – or worse, because they might be practicing (i.e., learning, reinforcing) ineffective methods that make long-term team work even more miserable for all of them.

The low-level skills that I teach as part of this effort – mostly falling into what is often called “emotional intelligence” – are skills that I also suspect would make one more willing to embrace the idea of open production in science. At the heart of this is the recognition that our own perceptions are fallible – and not only fallible; the whole point of perception is to reduce incoming sensory information into something much simpler that is heavily influenced by our past experience and our current needs and goals. People with different experiences and goals bring fundamentally different perceptions to a team. And because our perceptions are sensibly, directly shaped by our prior experience and goals, we have a tendency to see – in a completely literal sense – what we have learned to see or need to see.

The reality of how perception works means that we need to make extra effort to communicate with each other exactly what it is that we perceive. It also means that we need to make extra effort to follow practices that will automatically lower the potential effects of our biases when designing and carrying out scientific experiments. Our differences in perception strengthen the ability of teams if they are expressed; left unexpressed, they tend to lead to miscommunication, frustration, and unproductive arguments over who is “right.” Our differences in perception can strengthen the reach of our science if acknowledged; left unacknowledged, they lead to false confidence in one’s own results, they reduce the types of questions that get asked, and they tend to shape science and engineering to suit the most privileged members of society.

I presented or co-presented aspects of our classroom approach to teaching undergraduates these skills in two conferences this spring, both attended primarily by engineers and innovators who are interested in pedagogy:

At the IEEE ISEC conference at Princeton University on March 10, I presented, “Escape room-like puzzles to teach undergraduate students effective and efficient group process skills,” with a short paper accompanying this work-in-progress presentation. At the VentureWell OPEN 2018 conference in Austin on March 22-24, I co-presented with Rita Chesterton, “When neuroscience and entrepreneurship combine forces – Two classes, one lab, unlimited potential.”

At the VentureWell conference in particular, we had a lot of productive conversations with others who have been gamifying course materials, or experimenting with ways of teaching group process skills, or using other innovative approaches – but all of whom were looking for new and better ways not only of teaching science and engineering but were also finding better ways of doing science and engineering. I found the experience inspiring, and it felt like these conference conversations helped close the circle on the experiments I set up as part of this FLC project.

This whole Faculty Learning Community has turned out to be a usefully thought-provoking experience and enjoyable exchange with other members of the group.

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