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. Currently, most K-12 AI research focuses on introducing fundamental AI concepts using pure virtual platforms like webpages or software. However, robots, as helpful and popular tools in STEM (Science, Technology, Engineering, Math) education, are infrequently used in K-12 AI education, and their role is not sufficiently explored. In this thesis, I introduced educational robots and integrated them with an online platform and an augmented reality interface to help students learn key concepts in reinforcement learning (RL). I chose RL because it is conceptually easy to understand but has received the least attention in previous research on teaching AI to K-12 students. We designed a series of activities in which students can design their own robots and train them with RL to finish a variety of tasks. The activities and platforms were tested with two groups of high school students. Twenty students' engagement and learning results were assessed through qualitative analyses of their behavior and discussions by me and the class instructors. The role of robots and virtual platforms in motivating students and facilitating their learning was also discussed. The result showed that students were able to understand both high-level AI concepts and specific RL terms through our activities. Many students can even construct a deeper understanding of some of the RL concepts than we expected. Also, our approach of combining virtual platforms and physical robots provided students with an interactive and engaging learning experience. The implementation of robots inspired students' curiosity and solution diversity in resolving RL problems, while the integration of virtual platforms helped demystify key concepts of RL and enabled students to construct a deeper understanding of RL by providing them with an intuitive way to collaborate with their robots. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com.bibliotheek.ehb.be/en-US/products/dissertations/individuals.shtml.]