## 1 Introduction  
Digital competence (DC), commonly referred to as the ability to use digital technologies effectively, safely and responsibly, is a key factor used to avoid social and labor exclusion, as it enables individuals to effectively navigate and utilize technology in various aspects of life [1]. Over the last few years, interest in the assessment of DC has grown significantly, and has been used to accredit the level of DC of individuals. Although several reviews have summarized the progress and shortcomings in this area, some issues are yet to be explored, with a specific focus on instrument validity and reliability, and the identifying of important gaps of sources of evidence to ensure the quality of available tools [2, 3, 4]. These limitations directly impact stakeholders in the following ways: individuals may receive inaccurate assessments of their DC, hindering their employability and social integration; educators struggle to design curricula that accurately reflect students' competencies; and policymakers face challenges in developing informed strategies to enhance digital literacy across populations. Consequently, the inadequacies of current DC assessment tools not only undermine the effectiveness of digital literacy initiatives, but also perpetuate the risks of social exclusion and technological disparity. By addressing these gaps, we can ensure more reliable and valid assessments, thereby supporting individuals in achieving DC and fostering a more inclusive digital society. A key challenge in assessing DC lies in the varied and context-dependent definitions of the construct. While experts have sought to identify essential DCs for all citizens [5], differing definitions [4; 6] complicate the development of consistent assessment methods. The absence of a universally accepted definition of DC results in tools that may assess certain skills but overlook others [7], limiting comparability across studies and settings. Additionally, the context-specific nature of current assessment tools hinders their general applicability, as tools validated in one setting may not be reliable in another [6]. To address this, the European Commission introduced DigComp (Digital Competence Framework for Citizens) [7], which defines DC in terms of the knowledge, skills, and attitudes required to be digitally competent. While DigComp represents progress in standardizing DC, further research is needed to validate its use across diverse contexts and populations, and to address its limitations in capturing the evolving nature of DC. Continued efforts to refine and expand the framework will enable the development of more accurate, adaptable, and comprehensive assessment tools for DC. Another significant issue is that, despite the availability of numerous DC assessment systems using various approaches, most rely on self-assessment, which inadequately measures practical skills and higher-level cognitive abilities [2; 8]. Moreover, as noted by [PERSON] et al., many existing DC frameworks are developed by commercial enterprises [3]. This reliance on proprietary software, such as Microsoft Office or Windows, can shape curricular DCs around specific tools rather than broader competencies. While the introduction of DigComp has enabled more tailored implementations [2; 9], current systems remain largely based on self-reporting, often using multiple-choice questions and Likert scales. This approach minimally assesses practical skills, and individuals often overestimate their competence [10], rendering such assessments unreliable and invalid for accurate competence accreditation. Against this confusing and restricted background, we have identified several lines of action that could be envisaged to address the shortcomings identified. The use of Technology-Enhanced Assessment (TEA) presents both opportunities and challenges in the evaluation of DC.