Game-Based Learning & Data Analytics Event Recap

Thu October 3, 2019

spaceship flying through space

Introductory astronomy students explore the universe while learning through playing “At Play in the Cosmos”

On September 18, 2019, Mike Beall and Greg Vaughan from Gear Learning at the Wisconsin Center for Education Research (WCER) presented on game-based learning to kick off this semester’s learning analytics speaker series, co-sponsored by DoIT Academic Technology and the Educational Innovation (EI) Initiative. The presentation focused on the videogame “At Play in the Cosmos” created for an introductory astronomy course for nonscience majors. They have also developed games that teach diverse topics, including empathy and implicit bias, as well as regenerative medicine, opioid safety, electric circuitry and astronomy.

Mike Beall, Director of Gear Learning

Before demoing the game, they provided an overview for how they work with instructors and subject matter experts to design and build learning games, using a backwards design process and focusing on what learners need to be able to do after completing a game.

Afterwards, Mike flew through one of the missions in the game to demonstrate how players assume the role of a search/survey/rescue contractor and take on the exciting challenges the job offers. In addition to helping Mike on the mission by selecting the right tools and answering the game’s questions, event participants considered the types of questions that instructors might have about their learners, and opportunities to collect and use data from this mission.

Greg Vaughan, Chief Technologist for Gear Learning

Greg described the evolution of their data analytics tools and technology, and provided an example of how the data from a learning game would be organized and tracked. He also shared an example of how current data can be reported out in charts, and in a dashboard that displays multiple visualizations.


  • Please check out the slides for more information: Game-based Learning and Data Analytics.
  • The rules of the game should match the rules of the subject matter.
  • Games generate a LOT of data – it’s not feasible to collect and analyze data from commercial games and draw meaningful conclusions. Creating custom games tied to learning objectives allows games to be developed so meaningful data will be captured.
  • Games can be played collaboratively in-class, as an assignment or for extra credit.
  • Games can report actions that player take, to answer questions like:
    • Did a player complete a task?
    • Was the task completed successfully?
    • Is the player showing improvement over time?
  • Dashboards are provided to instructors to help answer those questions.
  • There is no big ‘easy’ button – while instructors want more data (some say they want all of the data), it can be a challenge to determine what data will be meaningful.

The event was part of a series of learning analytics events co-sponsored by the Educational Innovation (EI) Initiative and DoIT Academic Technology. For more information about the university efforts around learning analytics, visit our page here. To stay current on upcoming events and opportunities, join the UW-Madison Learning Analytics team or email and request to be added to the learning analytics group.