## 1 Introduction
The purpose of this exploratory study was to design items suitable for the assessment of DC focused on higher-order thinking skills and gather validation evidence in a custom TEA implementation based on DigComp. In alignment with the United Nations Educational, Scientific and Cultural Organization (UNESCO) [3] and the World Bank [28], we adopted the DigComp framework as our reference model, owing to its significant advantages, as follows: (1) it was developed following an in-depth examination of existing DC frameworks, (2) it underwent a rigorous process of consultation and refinement by specialists in the field of DC, and (3) consequently, it offers a holistic perspective grounded in DC and its related areas. We utilized data from RPS, including ET data, to aid in validating these items and consequently the test itself. We seek to contribute to further the understanding of participants' task-solving behaviors by examining the scan-paths of the participants, which may reveal important information about differences that may not be captured by the final responses, and to explore whether evidence from this analysis can contribute to the validity argument for inferences based on scores. Scan-path and fixation-based measures are well-suited for this study because they provide detailed insights into how participants interact with assessment tasks, offering a nuanced understanding of their cognitive processes and problem-solving strategies. Empirical research has demonstrated that fixation metrics, such as duration and sequence, correlate with information processing and cognitive load, making them valuable for assessing DC [24; 29]. To date, we are not aware of a similar study having been carried out on the design of DC assessments. [PERSON] asserts that validation aims to support an interpretation by rigorously testing for potential errors [30]. A claim is only trustworthy if it has withstood serious attempts to disprove it. This perspective on validity is relevant to studies like this one, which do not offer direct evidence that the cognitive processes involved in test item responses mirror those used in real-world tasks. However, they can help demonstrate their differences [31]. For example, if ET data show that test-takers completed simulation tasks without thoroughly reviewing instructions, it would challenge whether these tasks accurately reflect real-world cognitive processes. While ET data do not directly confirm cognitive processes, they provide valuable inferences [32]. So, we used ET data to validate the inferences made between claimed and observed behavior. We sought to respond to the following research questions:  
1. Is it possible to identify an alternative interpretation of how participants processed the item in terms of areas of interest (AOIs) examined (AOIs are usually defined by researchers to study eye movements within specific limited areas)? 2. Is it possible to identify an alternative interpretation of how participants processed the item in terms of AOIs examined and the order followed for the different AOIs? This paper begins by discussing the background of RP validation. Despite its importance in test validation, RP evidence has been largely underutilized. Given the benefits of RP evidence and the capabilities of TEA, we chose to explore RP data for DC assessment validation, specifically using ET data. Section 3 introduces ET technology and its ability to provide valuable insights into test-takers' performance, emphasizing its potential for assessment validation, particularly in DC evaluation. Section 5 outlines the experimental methodology, focusing on validating alternative interpretations of how participants processed selected items based on AOIs and the order in which they were examined. Metrics and visualization methods from the literature were used to analyze information acquisition and cognitive processing. Section 6 presents the results, followed by the conclusion and a discussion of future directions.