Date
Publisher
arXiv
K-12 robotics and AI education remains difficult to scale, especially in rural regions lacking sustained technical mentorship. Programs like FIRST provide competition pathways and instructional opportunities, but they do not eliminate the need for local programming and robotics expertise. We introduce AI, Robotics, & Community (ARC), a hubs-based framework where colleges train undergraduate mentors and host workshops for nearby K-12 teams. Mature school programs can become secondary hubs that support additional schools, creating a self-reinforcing education loop where mentorship reach propagates geographically and can even grow super-linearly. We first evaluate ARC through a trial deployment at one university. The trial created three rural robotics teams. On five-point Likert surveys, mean increases in K-12 programming knowledge, resource access, and practice opportunities were 2.00, 2.25, and 1.25 points. Likewise, undergraduate confidence teaching technical concepts, adapting explanations, managing groups, and finding mentoring enjoyable and meaningful increased by 1.29, 1.14, 1.00, and 1.14 points. Additionally, we create a spatial Markov model of ARC's growth and simulate it using the state of Indiana as a testbed. Under moderate conditions, we find that ARC reaches 74% of Indiana's 1,925 public K-12 schools and produces 992 robotics programs after 40 years, compared with 161 projected under natural growth alone. Together, these results show ARC can create and support rural robotics programs, train undergraduate AI and robotics mentors, and potentially scale mentorship across a region.
Study at a glance
- Question: Can a university-centered, hubs-based mentorship framework help establish and scale robotics and AI education across rural K-12 schools?
- Setting and data: Trial deployment at one university forming three rural robotics teams; simulation across 1,925 public K-12 schools in Indiana.
- Method: Pilot deployment evaluation using Likert surveys and a spatial Markov simulation model.
Why it matters
K-12 robotics and AI education remains difficult to scale, especially in rural regions lacking sustained technical mentorship and local programming and robotics expertise.
Key findings
- A simulation under moderate conditions projected the framework would reach 74% of Indiana's 1,925 public K-12 schools and create 992 robotics programs over 40 years, compared to 161 under natural growth.
- In the trial deployment, K-12 participants reported mean increases of 2.00 points in programming knowledge, 2.25 points in resource access, and 1.25 points in practice opportunities on five-point surveys.
- Undergraduate mentors showed average survey rating increases of 1.29 points in technical teaching confidence, 1.14 points in adapting explanations, 1.00 point in group management, and 1.14 points in finding mentoring enjoyable and meaningful.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
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