Decision Maker turned out to be a simple but fun strategy game for 2-4 players. We didn’t make it past the paper prototype because we only had 6 weeks. However, it wouldn’t take much work to publish it as travel game or a digital game. The student designer was faced with difficult lessons to teach, Prospect Theory and decision-making. A scaffolded reading list was essential for getting her up to speed on Prospect Theory. She demonstrated a clear understanding of the topic, developed a good experimental paradigm, created a game mechanic that complimented the lesson, and collected all her data on time. Like many of our student projects, there were errors in data collection that we were lucky to recover from. Nevertheless, the student really proved herself by completing the data analysis, figures, and poster with minimal assistance.

In the game, players made judgments about prospects that were composed of a probability and a value (e.g., 25% chance of winning $400). Players indicated the sure bet (e.g., $110) they would accept in lieu of the prospect. Normally, people behave irrationally when challenged with extreme probabilities or values. They tend to overestimate the utility of prospects with small probabilities and high values. Our game allowed players to practice decision making under these unusual circumstances. We predicted that decision making for extreme prospects would improve with practice.

We averaged the sure bets placed by the subjects and expressed them as proportion relative to the expected utility. If subjects were behaving ideally, the proportion would be close to 1. If they overestimated the utility of the prospect, the proportion would be greater than 1. We compared data between two sessions of game play. There was little difference between these sessions when players were judging probabilities within a “normal” range (6 to 99%). When players first started placing bets on extreme prospects (0.02 to 0.99%), they consistently overestimated the utility of the prospect (Figure 1). However, with practice, they were less likely to overestimate the utility for extreme prospects! Practice had a clear affect on their ability to make accurate decisions (Figure 2). Keep in mind that when subjects were playing the game, they were required to spin a spinner and watch the prospect play out in real time. For extreme probabilities, they might have to get the spinner to land between 0 and 1% several times in a row for the bet to pay off. The physical act of spinning the spinner made the prospect more visceral, which helped students appreciate how unlikely it is to win extreme prospects.

I consider this game a huge success because the student was sufficiently challenged by the material, and she overcame those challenges to produce a fun educational game that had a quantifiable affect on learning outcomes.

Figure 1

Figure 2