Using Gaze Behavior to Analyze Self-Regulated Learning in Nursing Students

Abstract

Developing clinical judgment is a critical outcome of nursing education and depends on students’ ability to regulate their cognition and attention during complex patient-care scenarios (Betts et al., 2019). This study leverages gaze analysis to examine nursing students’ use of clinical judgment during simulation training across participant-defined events mapped onto stages of the nursing process (assessment, planning, intervention, reassessment). A central objective was to test how gaze statistics, fixation distributions across regions of interest (ROIs), and sequences of ROIs can characterize self-regulatory processes across nursing process stages. Eye-tracking data were collected from nursing students during adult (2023) and pediatric (2024) simulation rotations in individual and team-based settings. The Segment Anything Model 2 algorithm was used to detect participant fixations on defined ROIs. Fixation metrics were analyzed in conjunction with scanpath trend analysis, a method for aggregating and comparing gaze sequences to identify common attentional patterns across events. Results revealed systematic changes in gaze organization across stages, progressing from broad, distributed cycles during assessment to tighter, task-focused loops during planning and intervention, followed by minimal evidence of reflection during reassessment. Team simulations showed rapid, distributed gaze patterns linked to shared regulation; individual simulations showed slower, focused patterns tied to autonomous control and greater cognitive load. Together, these findings highlight the potential of gaze metrics to identify self-regulatory patterns linked to clinical judgment development. Future work should integrate gaze data with behavioral and performance measures to more precisely evaluate the depth of self-regulated learning and its relationship to clinical performance quality.