Supporting Student Learning and Success in Early Undergraduate Mathematics Courses via AI-Enhanced Education

This Level 1 IUSE ESL project from the University of Texas at San Antonio aims to serve the national interest by developing technology to increase student learning and success in early college mathematics courses. This project expands on the existing Adaptive Learning for Interdisciplinary Collaborative Environments (ALICE) platform to develop an AI-assisted adaptive learning platform for students in College Algebra, Precalculus, Calculus I, and Calculus II. These courses remain critical steps on the pathway to nearly all STEM degrees. The project will use detailed student learning outcomes to ensure that the ALICE platform personalizes learning pathways, addresses gaps in understanding, and enables data-informed instructional adjustments. Faculty will use student data from the platform to support both individual students and class-wide teaching practices. The dual goals of this project are to deploy an AI-assisted adaptive learning framework and equip faculty with the skills and knowledge to effectively utilize it. Faculty will participate in professional development, including an 8-week summer workshop, to gain new skills and insights into how to use ALICE and other AI-assisted tools relevant to their pedagogy. The project will conduct three classroom pilots and use the insights gained to iteratively improve project outcomes. Data from student surveys and academic outcomes will be used to study the effectiveness of ALICE on various aspects of the learning experience. Project evaluation will be conducted by an independent evaluator who will track project implementation and progress towards stated goals and deliverables. 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.