Artificial intelligence as a metacognitive coach: supporting planning and reflection in gateway mathematics

The National Science Foundation Division of Undergraduate Education awarded The Ohio State University $364,949 on October 1, 2026, under the STEM Education program (CFDA 47.076) to develop and deploy an AI web interface that serves as a metacognitive coach in gateway mathematics courses.

Over three years through September 30, 2029, the research team will build a tool designed to scaffold pre-exam study planning and post-exam reflection, addressing a central tension between student agency and passive dependency on AI. The project executes a large-scale, cluster-randomized controlled trial to detect shifts in academic performance, course resource use, and study habits among introductory mathematics students. Research will establish evidence-based pedagogical strategies that promote self-regulated learning, mitigate passive dependency, and equip students with AI fluency for the modern workforce. Work is performed in Columbus, Ohio. The award is classified as a Project Grant and is part of NSF's Engaged Student Learning initiative at Level 1. The research aims to strengthen the national STEM workforce by improving student success and persistence in foundational mathematics courses that serve as gateways for science and engineering careers, with findings intended for broad adaptation and implementation across a range of institutions.

Abstract

This project aims to serve the national interest by improving student success and persistence in introductory mathematics courses through the integration of AI-based study planners. Foundational mathematics courses are crucial gateways for students pursuing careers in science and engineering. By providing personalized, interactive support for study planning, the project helps students focus their time and energy directly on the mathematical problem solving rather than the logistical challenges of organizing their schedules and study plans. This approach promises to advance best practices in mathematics education by using emerging technologies to support students and foster independent learning. This level 1 engaged student learning project includes a comprehensive evaluation to ensure the tools developed can be easily adapted and broadly implemented across a wide range of institutions to strengthen the national stem workforce. The overarching goal of this research is to investigate the efficacy of generative AI acting as a metacognitive coach in gateway mathematics courses. A central focus of the project is navigating the tension between student agency and dependency, specifically examining potential substitution effects where students might replace active study strategies with passive AI consumption. Over a three-year period, the research team will develop and deploy an AI web interface designed to scaffold pre-exam study planning and post-exam reflection. This research will establish evidence-based pedagogical strategies that promote self-regulated learning, mitigate passive dependency, and equip students with the AI fluency needed for the modern workforce. Methodologically, the project will execute a large-scale, cluster-randomized controlled trial to detect shifts in academic performance, course resource use, and study habits. The NSF iuse: EDU program supports research and development projects to improve the effectiveness of stem education for all students. Through the engaged student learning track, the program supports the creation, exploration, and implementation of promising practices and tools. 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.- subawards are not planned for this award.