Phase I CAMEL-CN: Curating a Large-Scale Publicly Available Multimodal Dataset of Student Actions in Illustrative Math to Study Mathematical Misconceptions

This project advances research on mathematics teaching and learning by developing and releasing a large publicly available dataset focused on student reasoning errors in the mathematics domain alongside related instructional classroom context. This resource aims to enable new research and discoveries of how mathematics reasoning errors emerge, evolve, and are resolved over time in authentic learning environments. The project leverages data collected in a free online math platform that includes classwork, homework and assessments across a range of mathematics concepts in Grades 3-12. The platform gives students instant feedback and provides data to teachers to guide instruction. The investigators develop fine-grained annotations of this rich dataset to capture student mathematics problem-solving behaviors, reasoning processes, performance, and instructional contexts for over 500,000 students, enabling longitudinal analyses of learning interactions and outcomes across grade levels. The resulting large-scale, multimodal, multi-year dataset with detailed annotations of student learning interactions and outcomes is expected to enable future discoveries of ways to support mathematics 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. NSF Award ID: 2621434 | Program: 01002526DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Neil Heffernan | Institution: Worcester Polytechnic Institute, WORCESTER, MA | Award Amount: $1,499,998 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2621434 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2621434.html