Project Objective
Project GPT+ seeks to develop a web-based application that provides interactive educational storybooks personalized to children’s learning requirements with the help of a fine-tuned GPT model. Young learners will be able to understand complex subjects like biology, chemistry, business, and environmental science through interactive, dynamically generated stories tailored to the topics they input. The platform will also generate quizzes from the story for students to assess their understanding and strengthen their grasp of the material. Ultimately, Project GPT+ aspires to diminish educational inequities by AI to support students in communities with limited access to learning resources.
Team Objective
The goal of the team was to create AI-generated educational storybooks that explain important concepts in business and finance to young school children in a captivating manner. Using language models powered by GPT along with image generation tools, the team created personalized immersive stories, quizzes, and iterative feedback sessions that ensure active participation driven by data. Tasks completed include gathering and organizing training datasets, adjusting hyperparameters of the AI model, creating frontends and interfaces, evaluating engagement on the iliad with AI-driven text analytics and data sciences, developing algorithms which process user data and give relevant recommendations—to ultimately bridge the gaps and disparities in education, equipping learners with technical capabilities alongside social impact.
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About Client
Located in Cebu Province of the Philippines, Apas Camp Lapu-Lapu Elementary School has nearly 2,000 students enrolled. The school faces different barriers concerning the availability of educational materials. These barriers, including a lack of textbooks and other resources, have made it increasingly difficult for students to attain a comprehensive education in our modern society, particularly in an era where technology is prevalent.
Project Lead: Professor Thomas Miller
Data scientist and AI specialist Dr. Thomas W. Miller holds the position of faculty director for the Master of Science in Data Science program at Northwestern University’s School of Professional Studies. He is known for works including Marketing Data Science and Modeling Techniques in Predictive Analytics with Python and R. His areas of interest and expertise include predictive analytics, data bias, artificial intelligence’s implications on societies and politics, and more.
Dr. Miller launched this initiative in hopes of extending the reach of data science education—starting as a graduate-level project with his students and then adapting it to empower younger minds, including high school students, as a way to contribute to the greater good of humanity. As the mentor, he facilitated the development of the curriculum, supported the design and implementation of the program, and lead the seminar and feedback sessions. His span of mentorship duties included quality assurance and guaranteeing the educational value of the project.
Implementation
After completing the project in summer 2025, the final platform was piloted at Apas Campus Lapu-Lapu Elementary School. Our team trained the teachers at this school on how to use the platform and held virtual tutorials and trial sessions to support the different staff members who will be using the platform.
Trial session at the Apas campus
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Currently, the platform is available exclusively to schools and is not open for individual user access.
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For more detail, click → Implementation of Project GPT+
Next Steps
Upon the successful launch at Lapu Lapu Elementary School, we aim to increase its user base by expanding into additional communities and schools. To support this growth, a fundraising campaign will be launched on GoFundMe in fall 2025.
The goal of the campaign is to raise awareness and financial support for schools starting with Lapu Lapu, for technology access, the AI model charges, and further expansion of communities/schools beyond the pilot school.
Program Duration
Feb 2025 - June 2025
Topic Highlights
Introduction to Generative AI & Prompt Engineering
Web Programming for Interactive Quiz Features
Fine-Tuning AI Models to Improve Storybook Quality
Storybook Data Creation for Model Fine-Tuning
Topic Recommendation System for Young Learners
Seminar: Machine Learning to Generative AI
Deliverables
Implementation of Project GPT+