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This content will become publicly available on July 13, 2027

Title: Play, Explore, Reward: Introducing Reinforcement Learning Concepts through Game-Based Learning in Middle School
Reinforcement learning (RL) is increasingly important to AI literacy, yet accessible K-12 tools for introducing RL concepts to students remain scarce. We developed RewardGarden, a game-based learning environment in which middle school students take on the role of a hummingbird collecting nectar under varying reward structures. The browser-based game is complemented by comprehensive educator materials, including a playful narrative introduction to RL, a game tutorial, and a facilitation guide with discussion prompts. In this paper, we describe the design of the learning environment, share insights from a classroom pilot, and provide implementation guidance. To understand implementation and gather feedback, we piloted the game with 92 middle school students across three classrooms. Our experience highlights the promise of game-based approaches for democratizing RL education, while identifying important practical considerations: the value of multi-session designs, the need for balanced reward feedback, and the critical role of scaffolding for complex concepts like exploration-exploitation tradeoffs. We share detailed implementation guidance, the publicly available game, and educator materials to support adoption.  more » « less
Award ID(s):
2148680
PAR ID:
10679499
Author(s) / Creator(s):
; ; ; ; ;
Publisher / Repository:
ACM
Date Published:
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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