Yao Tong
Papers
1
Total Citations
78
H-Index
1
About
Yao Tong is a leading researcher at the intersection of artificial intelligence and education, with a particular focus on how game-based learning (GBL) can transform AI literacy. Their most-cited work, a 2022 systematic literature review on GBL in AI education (78 citations), has become a foundational reference for educators and technologists seeking to make complex AI concepts accessible through interactive, game-driven pedagogies. This review not only synthesizes empirical studies but also charts a clear roadmap for future research, highlighting how playful engagement can demystify machine learning, robotics, and algorithmic thinking for learners of all ages. Beyond this landmark paper, Tong’s broader contributions include designing and evaluating novel AI curricula that integrate gamification, as well as exploring ethical and equity issues in AI education. Their work has been instrumental in bridging the gap between technical AI development and classroom practice, influencing both academic discourse and real-world instructional design. With a growing citation impact and a reputation for rigorous, forward-looking scholarship, Yao Tong is helping to shape how the next generation learns about—and with—artificial intelligence.
Research Focus
Key Achievements
Top Papers
- 1