Modelling and Measuring Professional Vision in Medical Education: A Cognitive Process Framework

Physicians routinely operate in environments that require the rapid processing of complex and dynamic visual information to diagnose patient conditions, communicate effectively, and make informed decisions. Despite the central role of visual attention in clinical practice, these processes are rarely conceptualized or systematically measured in medical education research. In other professional domains, such abilities are described as professional vision (PV)—the situated capacity to selectively attend to relevant cues and interpret them considering domain-specific knowledge. Although the term professional vision foregrounds visual attention, we use it here to cover the multimodal clinical perception in which visual cues are typically embedded—predominantly visual, but in many tasks also auditory and verbal—with visual attention as the analytic anchor. This paper introduces a cognitive process model of professional vision for medical education (PV-CP) that specifies the perceptual and cognitive subprocesses underlying how physicians perceive and interpret clinically relevant information. Building on this model, we propose a theory-driven framework for the measurement of professional vision using multimodal indicators. Central to our argument is the assumption that professional vision represents a latent, temporally unfolding construct that cannot be validly captured through single behavioral metrics or outcome measures. Instead, robust measurement requires the coordinated analysis of gaze-based indicators of visual attention and cognitive indicators of reasoning, each reflecting distinct subprocesses of professional vision. By systematically linking families of indicators to specific subprocesses and clarifying their respective inferential strengths and limitations, the PV-CP model advances a process-oriented approach to studying professional vision in medical education. The framework provides a conceptual basis for integrating multimodal data sources and supports more precise interpretations of gaze and reasoning data in expertise research. In doing so, the model contributes to the theoretical refinement of professional vision and offers a structured foundation for future empirical research and the design of learning environments aimed at fostering clinically relevant perceptual–cognitive skills.