Guest Post

Guest Post, Zac McGee: Utilizing Prediction Markets for Increased Classroom Engagement

I am excited to introduce a guest post by Zac McGee, assistant professor of government. Stay tuned for a follow-up podcast on this wonderful work. If you are interested in writing a guest post for the blog, please find more information about CITA’s scholarship of teaching grant here.

Utilizing Prediction Markets for Increased Classroom Engagement

Zac McGee

Leading up to the 2020 election nearly $150 million flowed through the United States’ largest election prediction market. Americans bet real dollars and cents on the outcomes of everything from who would win the Alabama Senate election to what the margin of control would be in Congress (down to the exact number of seats each party might hold!). While gambling certainly has pernicious effects, scholars started to notice that the markets actually predicted the real-world outcomes better than even the most sophisticated forecasting models in some cases. The broader scholarly consensus today is that markets, forecasts, and polls all aggregate different information, but the reality of spending your own money to predict a political event means you might second-guess betting on a scandal-ridden candidate just because they are a member of your favored political party.

Dr. Precious Hall and I, at St. Lawrence University (SLU), recognized this logic as an opportunity to pursue one of the most important learning goals of the Government Department. That is, students should be encouraged to take an active interest in political life, to engage with difference, and to develop the habits of intellectual curiosity, self-reflection, and open-mindedness that are the hallmarks of lifelong learning. We agreed that this semester we would integrate a private elections prediction market in our courses here at SLU. And while we didn’t ask the students to spend any real money on the market, we did provide material and academic incentives to encourage them to do well in the market.

Here’s how it worked in practice. At the start of the third week of the semester students were randomly assigned one race rated as a “toss up” by the Cook Political Report. Four times throughout the semester students were asked to present information about their assigned race to the class and update the race’s information on the prediction market’s webpage. They researched various aspects of each candidate in their race collecting information ranging from how much money was being raised and spent, to what their advertising looked like, and, of course, which issues they were discussing, among other things.

At any time between week 3 and Election Day students were permitted to use their virtual currency (of which each student starts with 100,000) to place bets on which candidate they thought was going to win a given election. After Election Day, the market “paid out” virtual currency to each student based on whether or not they bet on the correct candidate and how much each candidate’s “stock” was worth. The students who had the largest realized profit won the prizes.

Precious and I sought to engage our students actively, regularly, and with notable depth in the United States 2022 midterm elections. We also conducted an IRB-approved survey to assess the extent to which participation in this market led to increased political efficacy, knowledge, and engagement. While our results remain to be analyzed, we will be presenting our research at multiple conferences in 2023.

None of this would have been possible without the guidance from other scholars in this area who helped put us on the right path. In particular, we seek to thank Dr. Patrick Buckley at the University of Limerick (UL), who has himself published many times on the benefits of using prediction markets in college courses. Notably, Dr. Buckley is not a political scientist and is instead a faculty member in the Kemmy Business School at UL. This underscores the interdisciplinary nature of implementing a prediction market in college classes. Paddy, most importantly, helped us find the platform for our prediction market. We settled on Prediki and were incredibly fortunate to have worked with them throughout this semester. Not only were they helpful on the technical support and logistical side of pulling this project off, but they also gave us a significant discount. They believed in our project and our roles at a nonprofit educational institution conducting an experiment with implications for democracy. Their values aligned with ours and their support was swift and consistent. We certainly recommend them for anyone else considering implementing a market in their class.

At the end of the day, whether or not we find experimental results, Precious and I feel deeply that our students, and ourselves, were exposed to significantly more contemporary political information about the election than we otherwise would have been. We felt the student excitement around doing something new, innovative, and outside of the box. If you are interested in adopting a prediction market for your class, please feel free to reach out to me. I would be more than happy to chat and provide whatever guidance I can.