TESTUDO: A Robotics Kit Evolving into an AI-Driven Companion
DOI:
https://doi.org/10.21240/constr/2025/79.XKeywords:
Robotics, Artificial Intelligence (AI), Education, STEM KitAbstract
Despite Artificial Intelligence (AI)-driven STEM kits being widely available, K-12 students often struggle to access them at reasonable prices. Given the crucial role of hands-on projects in early engineering education, we developed TESTUDO, an affordable, open-source, AI-integrated robotic companion[1]. It is inspired by a tortoise in design and powered by an AI-integrated low-cost microcontroller. It offers a customizable learning experience, making adaptive educational kits accessible to students from all backgrounds. After students build their device, it uses a custom-trained AI model to learn from user interactions, adapting its behavior over time to create a more engaging and personalized experience. Students can then modify and personalize their version of TESTUDO to fit their needs while continuously improving in the iteration process. This modification system relies on open-source programs, designs, and electronic frameworks. The AI model adjusts the tortoise’s development path to align with individual strengths by analyzing user data collected from verbal interactions. This adaptive system enables a dynamic progression, guiding users through tasks based on their performance and engagement levels.References
1. Xin, Q., Wang, X., Ding, A. P., Zhang, Z., Chen, Z., & Guo, Y. (2024). Softy: An interactive kit to revitalize the plush toys of children. In Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction (HRI ‘24) (pp. 1143–1147). Association for Computing Machinery. https://doi.org/10.1145/3610978.3640716
2. Masum, M. H., Rifat, T. S., Tareeq, S. M., & Heickal, H. (2018). A framework for developing graphically programmable low-cost robotics kit for classroom education. In Proceedings of the 10th International Conference on Education Technology and Computers (ICETC ‘18) (pp. 22–26). Association for Computing Machinery. https://doi.org/10.1145/3290511.3290535
3. Weng, T. (2020). Promotion of the graphic control program and building block robot education for disadvantaged students in orphanages. MSIE 2020, April 7–9, 2020, Osaka, Japan. Association for Computing Machinery. https://doi.org/10.1145/3396743.3396789
4. Murai, Y., & Tatsumi, H. (2025). AI-powered walking assistance system for the visually impaired: Estimating navigable areas using pedestrian information and AI cameras. In Proceedings of the 2024 16th International Conference on Education Technology and Computers (ICETC ‘24) (pp. 125–129). Association for Computing Machinery. https://doi.org/10.1145/3702163.3702181
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Copyright (c) 2025 Kaan Tabağ, Mehmet Bener, Emre Dayangaç, Pelin Başyurt, Irmak Üreten, Sedat Yalçın

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