This paper presents Project OURALIT, a novel educational intervention system designed to address literacy challenges in resource-constrained public schools in the Philippines. Developed by Mr. John Roy V. Galvez, OURALIT leverages artificial intelligence (AI) to provide personalized learning experiences. The project received the Golden Award at the Pythaverse Educator ThoughtCoCreate 2025 Final Summit, based on its innovative design, practical feasibility, and rigorous evaluation methodology.

1. Introduction

The increasing integration of artificial intelligence (AI) into educational practices presents opportunities for personalized learning and addressing longstanding challenges in diverse contexts. In the Philippines, significant literacy gaps persist, particularly in underserved communities. Project OURALIT was conceived to address this issue through a system that enables individualized instruction at scale.

2. Project OURALIT: System Architecture and Functionality

OURALIT (Our Autonomous Reading Assistant for Literacy Intervention and Transformation) is a modular, AI-driven system designed to:

• Provide Adaptive Personalization: Utilizing Natural Language Processing (NLP) algorithms, the system analyzes student reading levels and dynamically generates customized learning materials.

• Incorporate Localized and Culturally Relevant Content: The system incorporates Filipino and Bicolano languages and cultural references to enhance student engagement and comprehension.

• Enable Real-Time Data Analytics: Teachers have access to comprehensive data dashboards to monitor student progress and identify areas requiring intervention.

• Facilitate Adaptive Learning Pathways: The system continuously adjusts the difficulty level of learning materials based on student performance, ensuring an optimal learning experience.

3. Evaluation Methodology

The evaluation of Project OURALIT at the Educator ThoughtCoCreate (TCC) 2025 Final Summit employed a multi-faceted approach:

• 3.1 AI-Assisted Proposal Scoring: Initial project proposals underwent pre-scoring using AI-based tools to assess relevance, innovation, and feasibility. This automated process served to objectively identify promising projects for further review.

• 3.2 Expert Panel Review: A panel of international experts in education and AI [If space allows, list key judges and their affiliations] conducted in-depth reviews of the shortlisted projects, applying a standardized set of criteria, including: [List the key criteria].

• 3.3 Presentation Assessment: Finalists delivered live presentations, assessed by the judging panel based on clarity, communication effectiveness, and responses to questions.

This rigorous and transparent evaluation process, blending both automated analysis and human expertise, ensured the selection of projects demonstrating both technical merit and practical value.

4. Discussion

The success of Project OURALIT at the TCC 2025 highlights the potential of AI-driven solutions to address complex educational challenges. The project's emphasis on feasibility and cultural relevance, combined with a rigorous evaluation methodology, contributed to its recognition as a promising model for literacy intervention. Further research is warranted to assess the long-term impact of OURALIT on student learning outcomes and its scalability to other contexts.

5. Conclusion

Project OURALIT represents a significant step forward in the application of AI to address the urgent need for improved literacy outcomes. Its success underscores the importance of combining technological innovation with a deep understanding of local contexts and a commitment to rigorous evaluation. The project serves as a valuable model for educators and policymakers seeking to leverage AI to transform education.

Supporting Material:

A full video presentation of Project OURALIT by Mr. John Roy Galvez is available Here.