Introduction: Clinical vignette-type multiple choice questions (CV-MCQs) are widely used in assessment and identifying the response process validity (RPV) of questions with low and high integration of knowledge is essential. Answering CV-MCQs of different levels of knowledge application and integration can be understood from a cognitive workload perspective and this can be identified by using eye-tracking. The aim of the pilot study was to identify the cognitive workload and RPV of CV-MCQs of different levels of knowledge application and integration by the use eye-tracking.
Methods: Fourteen fourth-year medical students answered a test with 40 CV-MCQs, which were equally divided into low-level and high-level complexity (knowledge application and integration). Cognitive workload was measured using screen-based eye tracking, with the number of fixations and revisitations for each area of interest.
Results: We found a higher cognitive workload for high-level complexity (M = 121.74) compared with lower-level complexity questions (M = 51.94) and also for participants who answered questions incorrectly (M = 94.31) compared with correctly (M = 79.36).
Conclusion: Eye-tracking has the potential to become a useful and practical approach for helping to identify the RPV of CV-MCQs. This approach can be used for improving the design and development of CV-MCQs, and to provide feedback to inform teaching and learning.[Box: see text].
Keywords: Eye tracking; assessment; cognitive workload; medical education; multiple choice questions.