Welcome to Dataville
Dave Lasala, Creative Director
Rob Schwartzberg, Unity Programmer
Jon Bowen, Unity Programmer & UX Designer
Jiayan “Maggie” Li, Visual Designer
Unity 3D 5.60f3
NYU Steinhardt faculty members Jennifer Hill and Lauren Fellers worked with our team to create a game to support students in the quantitative and statistical reasoning course Statistical Mysteries and How to Solve Them. The goal was to create a game that would increase student engagement in the area of hypothesis testing. The final product, Welcome to Dataville, merges hypothesis-testing scenarios with gamified learning elements. In the game, players are running as candidates for mayor of a small town. Candidates are tested on the attributes of Credibility, Popularity and Competence as they complete hypothesis testing scenarios. The game supports approximately 81 scenarios of varying difficulty levels, with degrees of randomization. It also records anonymous player statistics to help faculty identify areas where students are struggling, as well as help our team improve the game. Notably, students have been pleased with the friendly, colorful aesthetic and the retro sound effects. While the game was originally designed as a learning supplement and study aid, requiring the professor to provide the instruction needed to play the game, Welcome to Dataville is now being evolved into a stand-alone teaching tool.
- 81 scenarios of varying difficulty levels.
- Randomly generated parameters for questions.
- Scaffolded learning experience through contextual help that is reduced as the player progresses through the difficulty levels.
- Sending statistics to professors.
Dave: During beta-testing, the need for onboard teaching in this game (as opposed to separate in-person instruction) became immediately apparent resulting from my desire to rage quit. This resulted in the project timeline being extended to develop a fully onboard teaching component built into the game. The resulting builds have already improved the onboard instruction drastically, and are informing our future models for built in teaching components.
Jon: When developing an interactive teaching tool, context sensitive help is a major benefit. In general the easy solution is designing a tutorial slideshow, but that doesn’t take advantage of the benefits of interactive education. That is why we decided to devise a new, contextual teaching component. This project also makes use of a variety of Amazon cloud services for hosting data, sending statistics to professors, and updating question sets. It was easier than expected to incorporate and knowledge of these capabilities will open up new opportunities when designing future applications.