Background: Students take many tests and exams during their school career, but they usually receive feedback about their test performance based only on an analysis of the item responses. With the increase in digital assessment, other data have become available for analysis as well, such as log data of student actions in online assessment environments. This paper explores how we can use log data to extend performance-related feedback with information related to the applied solution strategy. Methods: First, we performed an exploratory model-based cluster analysis in order to identify the solution strategy of 802 students with a modal age of 14 in a pre-algebra item from the French national assessment "CEDRE." Second, we related the students' solution strategies to their mathematical ability based on the entire assessment. Results: Five distinct groups of students with different in-assessment behavior were identified, of which one group had a significantly lower estimated mathematics ability than the other groups. Conclusion: These findings can provide a basis for more in-depth feedback and further instruction on the level of an individual student and can inform teaching practices at the class level.