Engaging Minority High School Students in AI-Enhanced Mobile App Design: Cultivating CS Interest and AI Ethics Through Project-Based Learning

This project offers a step‑by‑step framework for building AI‑enhanced mobile apps with block‑based programming tools and Agile methods. It draws on education programs that try to get more people into computer science, and it helps developers create mobile prototypes that are socially relevant and culturally aware. The framework uses MIT App Inventor together with built‑in machine‑learning extensions. With this setup you can run image classifiers, sentiment‑analysis tools, and recommendation engines right on the phone, without needing a server. The development process follows clear Agile sprints, focuses on the user, and includes a specific checklist for AI ethics. This checklist tackles common problems such as algorithmic bias and relying too much

on automated decisions. The work concentrates on real‑world examples, like personalized recommendation systems and mental‑health support interfaces. The result is a detailed guide for making mobile apps that are easy to access, ethically sound, and fully functional. The prototypes show that block‑based environments can make complex machine‑learning ideas easier to understand. They also give beginners a clear path from simple programming to building advanced, AI‑integrated software.

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