Build Your Own Robot Friend: An Open-Source Learning Module for Accessible and Engaging AI Education
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Abstract (arXiv)
As artificial intelligence (AI) is playing an increasingly important role in our society and global economy, AI education and literacy have become necessary components in college and K-12 education to prepare students for an AI-powered society. However, current AI curricula have not yet been made accessible and engaging enough for students and schools from all socio-economic backgrounds with different educational goals. In this work, we developed an open-source learning module for college and high school students, which allows students to build their own robot companion from the ground up. This open platform can be used to provide hands-on experience and introductory knowledge about various aspects of AI, including robotics, machine learning (ML), software engineering, and mechanical engineering. Because of the social and personal nature of a socially assistive robot companion, this module also puts a special emphasis on human-centered AI, enabling students to develop a better understanding of human-AI interaction and AI ethics through hands-on learning activities. With open-source documentation, assembling manuals and affordable materials, students from different socio-economic backgrounds can personalize their learning experience based on their individual educational goals. To evaluate the student-perceived quality of our module, we conducted a usability testing workshop with 15 college students recruited from a minority-serving institution. Our results indicate that our AI module is effective, easy-to-follow, and engaging, and it increases student interest in studying AI/ML and robotics in the future. We hope that this work will contribute toward accessible and engaging AI education in human-AI interaction for college and high school students.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 3 of its 32 references that are in the map. First posted on arXiv 6 Jan 2024.
Builds on
3 of 32 references.
References · 3
- 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
- 2014Deep Learning Face Attributes in the Wildcited by 3,693
- 2023From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacycited by 143
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Citing papers per year: 2024: 1; 2025: 1; 2026: 1.
3 papers.
- 2025AI Literacy in K-12 and Higher Education in the Wake of Generative AI: An Integrative Reviewcited by 4
- 2024Improving User Experience in Preference-Based Optimization of Reward Functions for Assistive Robotscited by 1
- 2026Improving through Interaction: Searching Behavioral Representation Spaces with CMA-ES-IGcited by 0
- 2026Improving through Interaction: Searching Behavioral Representation Spaces with CMA-ES-IG9 Mar 2026
- 2025AI Literacy in K-12 and Higher Education in the Wake of Generative AI: An Integrative Review27 Feb 2025
- 2024Improving User Experience in Preference-Based Optimization of Reward Functions for Assistive Robots17 Nov 2024