The ARC (AI, Robotics & Community) framework leverages colleges to train undergraduate mentors and host workshops for nearby K-12 teams, delivering technical guidance to rural schools. When a school program matures it can become a secondary hub, supporting additional schools and creating a self‑reinforcing mentorship network that may grow super‑linearly.
In a university pilot three rural robotics teams were launched. Five‑point Likert surveys showed average gains of 2.00, 2.25 and 1.25 points in K-12 programming knowledge, resource access and practice opportunities. Undergraduate mentors reported increases of 1.29, 1.14, 1.00 and 1.14 points in confidence teaching concepts, adapting explanations, managing groups and finding mentoring enjoyable.
We built a spatial Markov model of ARC growth and simulated it using Indiana as a testbed. The model assumes each hub spawns a new hub in neighboring counties with probability $p$, and the transition matrix $M$ captures the expected change in hub counts. Under moderate assumptions, after 40 years ARC reaches 74% (≈1,425) of Indiana’s 1,925 public K-12 schools, generating 992 robotics programs versus only about 161 programs under natural growth.
These findings demonstrate that ARC can create and sustain robotics programs in rural areas, train undergraduate AI and robotics mentors, and potentially scale mentorship networks across larger regions.
Review