Abstract
As artificial intelligence (AI) plays a more prominent role in our everyday lives, it becomes increasingly important to introduce basic AI concepts to K-12 students. To help do this, we combined the physical (LEGO® robotics) and the virtual (web-based GUI) worlds for helping students learn some of the fundamental concepts of reinforcement learning (RL). We chose RL because it is conceptually easy to understand but received the least attention in previous research on teaching AI to K-12 students. Our initial pilot study of 6 high school students in an urban city consisted of three separate activities, run remotely on three consecutive Friday afternoons. Students’ engagement and learning were measured through a qualitative assessment of students’ discussions and their answers to our evaluation questions. Even with only three sessions, students were optimizing learning strategies, and understanding key RL concepts and the value of human inputs in RL training.
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Notes
- 1.
All code and materials available at: https://github.com/ZyZhangT/rlplayground.
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Zhang, Z., Willner-Giwerc, S., Sinapov, J., Cross, J., Rogers, C. (2022). An Interactive Robot Platform for Introducing Reinforcement Learning to K-12 Students. In: Merdan, M., Lepuschitz, W., Koppensteiner, G., Balogh, R., Obdržálek, D. (eds) Robotics in Education. RiE 2021. Advances in Intelligent Systems and Computing, vol 1359. Springer, Cham. https://doi.org/10.1007/978-3-030-82544-7_27
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