Collaborative Research: Phase I CAMEL-CN: From Errors To Outcomes--Indicators of Procedural and Conceptual Understanding to Improve Student Learning

This project compiles a comprehensive database of student learning and outcome data for mathematical content in Grades 4-10. These data come from projects that implemented successful interventions to support student math learning and include fine-grained data on accuracy and strategy errors over a wide range of math concepts and grade levels. Project outcomes are intended to support new discoveries about student learning and the design and testing of new instructional innovations for teaching mathematics and supporting student long-term success. Research products made available in the Open Science Framework data repository can facilitate data re-use by other researchers. The project leverages previously collected data on student learning of a broad range of foundational mathematical skills, including arithmetic computation, algebraic equation-solving, word problems, and many other skills from over 3,500 students and 700,000 student work samples. The research team aims to (1) develop AI-enabled assessment tools to analyze student handwritten responses to math problems, automatically identify the problem solving strategy, and diagnose errors made in the process; (2) link to learning and motivation outcome data; and (3) develop user-friendly tools designed to support mathematics teachers in real-world classrooms and researchers working to better understand mathematics learning and education. 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. NSF Award ID: 2621343 | Program: 01002526DB NSF RESEARCH & RELATED ACTIVIT,4082PYXXDB NSF TRUST FUND | Principal Investigator: Christina Barbieri | Institution: University of Delaware, NEWARK, DE | Award Amount: $235,384 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2621343 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2621343.html