Using Eye-Tracking Data to Examine Response Processes in Digital Competence Assessment for Validation Purposes

Background: When measuring complex cognitive constructs, it is crucial to correctly design the evaluation items in order to trigger the intended knowledge and skills. Furthermore, assessing the validity of an assessment requires considering not only the content of the evaluation tasks, but also how examinees perform by engaging construct-relevant response processes. Objectives: We used eye-tracking techniques to examine item response processes in the assessment of digital competence. The eye-tracking observations helped to fill an 'explanatory gap' by providing data on the variation in response processes that cannot be captured by other common sources. Method: Specifically, we used eye movement data to validate the inferences made between claimed and observed behavior. This allowed us to interpret how participants processed the information in the items in terms of Area Of Interest (their size, placement, and order). Results and Conclusions: The gaze data provide detailed information about response strategies at the item level, profiling the examinees according to their engagement, response processes and performance/success rate. The presented evidence confirms that the response patterns of the participants who responded well do not represent an alternative to the interpretation of the results that would undermine the assessment criteria. Takeaways: Gaze-based evidence has great potential to provide complementary data about the response processes performed by examinees, thereby contributing to the validity argument.