This past winter I had the great pleasure to meet with Kevin McCabe, Professor of Economics and Law at George Mason University. His research has appeared in journals such as the American Economic Review, Science, Economic Theory, Games and Economic Behavior, and many more. He is the Co-Director of the Center for the Study of Neuroeconomics at George Mason and he is in a small group of people who could potentially win the Nobel Prize in Economics for his pioneering work in Neuroeconomics. Beyond being a top notch scholar he is a terrific person. He and his wife Kathleen were great hosts to me on my visit last summer and gave me a detailed explanation of their work with virtual worlds and related outreach. They have some wonderful things going on! Q: Your research has primarily used experimental methods to study economic problems. How did you become interested in using experiments in research? A: In 1985, as an assistant professor at the University of Arizona, I became interested in experiments after attending a seminar by Vernon Smith. I spent a year learning the Plato computer language and working on the design of my first experiment on fiat money as a store of value. After coming back from a fellowship at Washington University in St. Louis, I joined the Economic Science Laboratory to work with Steve Rassenti and Vernon Smith on ‘smart’ markets for Natural Gas and ‘smarter’ auction designs for two-sided call markets. At this point I was pretty much convinced that the scientific method was a great way to study economics and I realized that the combination of theory, experiments, and computational thinking was a perfect fit for me.
Q: Were you doing classroom experiments before you started in your experimental research or was there a moment where you transitioned from experiments for research to experiments for education?
A: A requirement for my fellowship at Washington University, in 1986-87, was to teach a micro class. The class had very smart students, but they had never experienced how markets work. I decided the answer to this lack of experience was to run market experiments which I programmed on my luggable Osborne computer. It was a great way to read the literature and attempt to replicate research in the classroom and I found students enjoyed this learning by doing approach. When I got back to Arizona I taught a monetary course built around the design and testing of monetary institutions. For me the enjoyment was connecting monetary theory to experiments. For the students the enjoyment was asking what will happen as opposed to hearing about what does happen. Since then I’ve used experiments in every class I teach. Q: Other than the Osborne computer what technologies have you used in the past for classroom experiments? A: I’ve used hand run double auctions, public goods, bargaining, and game theory experiments. I moved early on to more sophisticated experiments where I could program the institutional rules and environmental conditions, first on an Osborne computer and later, on laptops. In these experiments the messages were still collected by hand and input into the computer. I also started using networked computers running a simple database in BASIC and then VISUAL BASIC and later using the common shared data format available in FORTRAN. Later, I used the PLATO system, pioneered by Arlington Williams, which was designed to efficiently use the idea of a shared data space. Currently, I program laboratory and web experiments in Python and Virtual World experiments in the Linden Scripting Language. At some point, all my research experiments and results end up in the classroom. I also use Charlie Holt’s Veconlab which implements many experiments by other researchers. Through Veconlab, Holt has helped pioneer the availability of web based parameterized demonstration experiments. Q: When did you start using MobLab and what attracted you to it? A: In spring 2015 I decided to teach a Managerial Economics course for undergraduates. At the time I had just learned about MobLab at a conference and decided to use it in my course. One major attraction was the shift in student access to technology in the classroom. Today every student has a smart phone, tablet, or laptop of some type. MobLab had been designed to work with all of these devices making it an exceptional teaching tool. A second reason I wanted to use MobLab was to introduce a more fluid way of moving back and forth between theory, experiment, and practice. MobLab has short video instructions that allow the instructor to run a demonstration experiment in less than 15 minutes and it provides useful data displays for immediate discussion. Third, Moblab has a survey tool which I use instead of a clicker system to ask in class questions to gauge student comprehension. Q: Now that you have used MobLab a while, what do you like about it as an instructor? What have the student reactions been? A: The value of MobLab is the ease with which experiments can be designed and run on many different devices. MobLab has an instructor interface that makes it relatively simple to manage students and experiments. The data from experiments can be downloaded as a comma separated file with anonymized decisions which can then be made available to students for further analysis. Most students report that they like MobLab experiments in the classroom. MobLab also seems to act as an icebreaker opening more students interest in participating in classroom discussion. I am also very impressed with the continuous improvements and additions made by the MobLab team, their customer support when problems occur, and their willingness to listen to their customers. Q: Do you have a favorite MobLab game to play with students? A: MobLab has many of my favorite experiments making it difficult to choose just one. What I like a lot is the ability to run a sequence of experiments to create a narrative for students. For instance when we talk about how one sided auctions work students first participate in a first price auction followed by a second price auction followed by an English clock auction. They can see how changing the rules of the auction affects bidding behavior. In the next class they are put in common value environments to see how changes in the environment affect bidding behavior. We can then discuss optimal bidding strategies and the importance of expertise in different auctions and auction environments. Q: What advice would you give a new instructor who wants to use games in their classroom? A: My main advice is to use experiments to explore how institutions and culture work to shape incentives and coordinate actions to produce different outcomes. In doing this I would highlight the lessons being learned by the research in economic science. Most of the experiments in MobLab have been replicated many times. Acquaintance with the research literature behind the experiment will prevent the students or the instructor from telling ‘just so’ stories about the data. One feature of MobLab to keep in mind is that classroom experiments are likely to be run without monetary incentives while the research behind the experiment was done with monetary incentives. Without monetary incentives, some experiments in MobLab will not replicate the behavior produced in incentivized experiments. The only way to avoid misinterpretation of the experimental data is to be able to compare what students did without monetary incentives to what subjects did with monetary incentives.