Computer-assisted assessment of student’s work characteristics in sequences of rich elementary geometry tasks

Abstract This study presents an approach that integrates digital formative assessment tasks with cognitive diagnostic modelling to analyze elementary students’ work characteristics. These characteristics refer to the observable strategies and patterns that students use when working on digital geometry tasks that allow multiple correct student-generated examples and constructions, rather than a single predetermined response. The study focuses on triangle altitudes, a concept that is often challenging for learners and teachers. We designed a sequence of curriculum-aligned tasks and administered them to 73 fifth-grade students in the Arab sector of Northern Israel. Student-generated examples were recorded automatically and coded into seven recurring work characteristics that reflect known perceptual and strategic tendencies. The characteristics were placed within a structured skills-by-task matrix and analyzed with a cognitive diagnostic framework (DINA model). The framework evaluates how consistently individual tasks distinguish recurring patterns in students’ constructions. The analysis identified three patterns in the relationships between work characteristics and correctness. It also highlighted tasks that serve as sensitive indicators of students’ conceptual development. The findings suggest that digital task sequences can support systematic identification and analysis of recurring construction patterns that may inform interpretation of students’ developing geometric understanding.