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The purpose of this work is to develop an Interactive Diagnostic Assessment System (IDAS) that allows students to interact with “big ideas” in mathematics while monitoring and reporting on progress over time with those ideas. The research presented here specifically focuses on the topic of covariation, within equipartitioning, and how students develop an understanding of the concept based on prior learning experiences. We utilize contemporary approaches for assessment and data collection, such as diagnostics within an item generation environment (IGE) hosted by the Learning Progress Profiles Synchronized for Network Devices (LPPSync) IDAS we have built. The system has been designed around a learning trajectories (LT) approach to diagnostic assessment within formative assessment practices employing technology.
Drew Corley, North Carolina State University
Jere Confrey, North Carolina State University
Kenny Huy Nguyen, North Carolina State University