Using games to teach complex concepts

One of Ying “Gina” Tang’s motivations as a researcher is to make learning more fun and effective. Her game-based learning environments are designed to adapt to each student's needs, helping them understand complex concepts while staying engaged. Integrated into these games are artificial intelligence-based pedagogical agents—characters within the game—that interact with each student, track their learning progress and challenges, and provide personalized guidance to enhance their overall learning experience.

Tang, Ph.D., a professor of electrical and computer engineering in the Henry M. Rowan College of Engineering, has designed game-based learning environments that cater to students from middle school through post-university levels.

“I’m hoping to harness technologies like virtual reality (VR), augmented reality (AR) and artificial intelligence (AI) to significantly transform the next generation of education,” Tang said.

SPARC, a multi-person mobile game created for middle grades, helps students learn how to approach and solve problems. The content of the game centers on life and physical science core standards, such as molecules, organisms, their structures, and their role in maintaining a healthy human body. The AI agent in SPARC acts as an in-game learning companion, using large language models to engage in human-like conversation, offering students “learning-by-teaching” opportunities and encouragement.

To create it and to ensure it aligned with curriculum standards, Tang consulted the New Jersey Student Learning Standards for Science and gathered feedback from teachers through a dedicated professional development workshop series during the early design phase.

The AI functionality can also act as an in-game teacher. In Gridlock, another educational game Tang developed for freshman electrical and computer engineering students, players are tasked with repairing a malfunctioning traffic light. 

Within the game, students encounter checkpoint questions and mini games to assess their understanding. If a student has difficulty with a question or puzzle, the system tailors additional instruction or assistance—like extra reading material or an instructional video—based on the student's specific needs.

Tang also collaborates with Rowan’s Machine & Artificial Intelligence Virtual Reality Center on projects for the U.S. Army and the Federal Aviation Administration, applying similar adaptation and personalization techniques to create simulation environments for military personnel.

Her work has been funded by the National Science Foundation, Rowan University/Rutgers-Camden Board of Governors, U.S. Army and the Federal Aviation Administration. 

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