This study explores how a pre-service mathematics teacher interprets eye-tracking data to diagnose students’ reasoning when working with histograms. Using a qualitative case study design, the participant engaged with an eye-tracking vignette, featuring a student’s gaze plot, answer, and cued recall explanation. The targeted error was frequency–value confusion, a common systematic error where students treat bar heights as measured values. Findings show that the participant initially relied on assumptions rather than the gaze data itself. Over time, her reasoning shifted to a more reflective analysis, integrating multiple data sources to better understand the student’s thought process. She also identified the limitations of interpreting gaze data in isolation, especially when no clear pattern was evident. This study suggests that the use of eye-tracking data, when scaffolded through structured tasks, can enhance pre-service teachers’ diagnostic skills in the interpretation of statistical graphs.
