AI in Criminal Recidivism
The 16-session plan
Research existing machine learning models used for predicting criminal recidivism and summarize their methodologies in a report.
Identify and compile a dataset that includes relevant historical data on criminal cases and recidivism rates for analysis. Additionally, research what cases would benefit from this technology, and who would be impacted.
Preprocess the collected dataset by cleaning and normalizing the data to prepare it for input into a machine learning model.
Select a machine learning algorithm suitable for the prediction task and document the rationale for your choice in a project log.
Frequently asked questions
Who is this project a great fit for?+
BlueRobins projects are designed for curious students in Grades 3-12 who want to build. No prior experience is needed — mentors start wherever your child is and grow the challenge as they grow.
What does a typical session look like?+
Your child meets 1-on-1 with their mentor every week over Google Meet. Programs run 16 sessions of 45 minutes each. Sessions are hands-on from minute one — building, designing, coding, writing, experimenting — with the mentor coaching live, asking great questions, and unlocking the next step.
What will my child build by the end?+
A finished project they're proud of and can show the world. Across 16 sessions, your child turns an ambitious idea into a working app, prototype, research write-up, portfolio, or published artifact. Every student finishes with a completion certificate signed by their mentor.
Why a free trial first?+
So your child can meet their mentor, get a feel for the project, and leave the call excited. The trial is a complimentary 1-on-1 free trial session — no credit card needed. After the trial, you decide if it's the right fit. Most families know within the first 15 minutes.