Fostering teachers’ interpretations of formative assessment results using clustered heatmaps

Teachers can use formative assessment results to inform their instruction to each student’s current level of understanding. In practice, this is a complex task. Thus, we investigated in two preregistered online experiments whether clustered heatmaps can support teachers in reading and interpreting assessment results accurately and efficiently for adaptive teaching according to their students’ strengths and weaknesses. N = 202 pre-service and N = 262 in-service teachers for primary and secondary education interpreted formative assessment results from the subjects German and mathematics. The findings indicate that clustered heatmaps are sufficiently intuitive and can improve the accuracy and efficiency with which teachers group students according to their strengths and weaknesses. Novice teachers, in particular, appear to benefit from the algorithm-based visual cues provided by clustered heatmaps. If future research corroborates this evidence, clustered heatmaps could be implemented in dashboards to promote beneficial teacher-technology interactions with the aim of enhancing student learning.