Applying Cognitive Diagnostic Models to Mechanics Concept Inventories
Vy Le, Jayson M. Nissen, Xiuxiu Tang, Yuxiao Zhang, Amirreza Mehrabi,, Jason W. Morphew, Hua Hua Chang, and Ben Van Dusen

TL;DR
This paper develops and tests a cognitive diagnostic assessment for introductory mechanics, using adaptive models to improve physics education evaluations and support effective teaching strategies.
Contribution
It introduces a novel approach to creating a mechanics cognitive diagnostic using the DINA model and extensive student data, enhancing assessment precision.
Findings
High accuracy in classifying student skills
Good to adequate model fit for student data
Initial item bank useful for future diagnostic development
Abstract
In physics education research, instructors and researchers often use research-based assessments (RBAs) to assess students' skills and knowledge. In this paper, we support the development of a mechanics cognitive diagnostic to test and implement effective and equitable pedagogies for physics instruction. Adaptive assessments using cognitive diagnostic models provide significant advantages over fixed-length RBAs commonly used in physics education research. As part of a broader project to develop a cognitive diagnostic assessment for introductory mechanics within an evidence-centered design framework, we identified and tested student models of four skills that cross content areas in introductory physics: apply vectors, conceptual relationships, algebra, and visualizations. We developed the student models in three steps. First, we based the model on learning objectives from instructors.…
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Taxonomy
TopicsManufacturing Process and Optimization · Design Education and Practice · Engineering Diagnostics and Reliability
