Innovative AI Systems for Nurturing and Assessing Creativity in K-12 Learning Environments

About This Grant

Creative thinking is fundamental to Science, Technology, Engineering, and Mathematics (STEM) success, yet current methods for assessing and nurturing student creativity are costly, time-intensive, and often inaccessible to under-resourced schools. This project addresses this critical national need by developing artificial intelligence-powered tools to make creativity assessment and mentoring both scalable and broadly accessible in K-12 education. The research team will create and evaluate two interconnected systems that evaluate student creative output and provide real-time guidance during problem-solving activities. By making these tools freely available on the web, the project will enable educators nationwide to systematically monitor and enhance student creativity. As artificial intelligence increasingly becomes part of professional creative work, the products from this work will also prepare students for a transformed future where human-machine collaboration in creative tasks will be commonplace. The project will develop two core artificial intelligence systems. The first, Ocsai Prime, represents a task-agnostic creativity assessment model that uses supervised fine-tuning to evaluate both originality and appropriateness across diverse creative challenges, moving beyond current tools that are limited to specific tasks. The second, Creativity Companion, employs reinforcement learning with human feedback to create an interactive facilitation tool that guides students through creative ideation in real-time. The Companion will be trained using reward modeling based on Ocsai Prime's assessments combined with human feedback to optimize its ability to enhance student creative thinking. Both systems will undergo rigorous evaluation through a randomized controlled trial design in middle school classrooms across three geographically diverse districts, comparing student creativity outcomes, engagement, and learning persistence between artificial intelligence-assisted and control groups. The research will include comprehensive demographic analysis to ensure broad benefits while contributing new knowledge about computational creativity assessment, human-artificial intelligence co-creativity, and educational technology integration in STEM learning environments. This project is funded by the Research on Innovative Technologies for Enhanced Learning (RITEL) program that supports early-stage exploratory research in emerging technologies for teaching and learning. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.