The American Statistical Association (ASA) DataFest is a celebration of data in which teams of undergraduates work around the clock to find and share meaning in a large, rich, and complex data set. A key feature of ASA DataFest is that it brings together the data science community. Undergraduate students do the work, but they are assisted by roving consultants who are graduate students, faculty, and industry professionals. After two days of intense data wrangling, analysis, and presentation design, each team is allowed a few minutes and no more than two slides to impress a panel of judges. Prizes are given for Best in Show, Best Visualization, and Best Use of External Data.
Elm City Stories is an educational video game designed for middle and high school students. The game was developed for researchers at the Play2Prevent Lab within the Yale School of Medicine. The overall goal for the designers of the game is to prevent negative health outcomes such as HIV, sexually transmitted infections, and substance misuse in young at-risk teens (ages 11-14 years) by increasing their perception of risk and acquiring healthy skills to prevent engaging in risky behavior. A key component to this change is a set of skills that allow teens to predict and understand future consequences of actions.
From a research point of view, one interesting aspect about this game, and games like it, is that researchers usually have to rely on questionnaires to try to predict future behaviors. But people are not always the most reliable reporters of their own beliefs and actions, particularly young people. One promise of using games to understand real-life behavior is that patterns of behavior within a game might predict real-life behavior. For example, perhaps risk-taking in gameplay, or caution, or persistence, reflect behavior in real-life situations. Some examples of low-level cognitive processes that play a role in playing this game are attention, impulsivity, and working memory.
The challenge in this DataFest is to help the researchers who created Elm City Stories to see if their game might be useful in understanding real-life behavior. To do this, they're asking you to try to characterize, measure, observe, and display patterns of play within the game. One goal for future games is to design them so that the games produce real-time data that is useful to psychology researchers.
Data: The primary data set consists of player logs for 166 players. The players were recruited from middle schools in districts throughout the state of Connecticut roughly ten years ago. The log records each "event" that a player performs in the game, as well as the time the action was performed. It also records supplementary information, such as the players' schools, dates of play, etc.
