TOWARDS AN INTEGRATED PEDAGOGICAL FRAMEWORK OF ASSESSMENT FOR ETHICAL AND CRITICAL ARTIFICIAL INTELLIGENCE LITERACY IN K-12 EDUCATION

The rapid expansion of Artificial Intelligence (AI) in contemporary societies has brought renewed attention to the responsibility of educational systems to prepare learners to engage with AI in a critical, informed and ethically grounded manner. While a growing number of conceptual frameworks define the core dimensions of AI literacy, the assessment of these competences remains a significant gap in both research and educational practice. Current evaluation approaches are largely qualitative, fragmented and predominantly oriented toward technical understanding, thus failing to capture the complex interplay between conceptual knowledge, informed use of AI systems and ethical-critical reasoning highlighted in the literature. Empirical evidence suggests that existing AI literacy initiatives tend to privilege operational and process-oriented knowledge, whereas dimensions such as ethical judgement, learner agency and critical thinking are rarely assessed in a systematic way. Moreover, although AI literacy programs frequently adopt active and collaborative pedagogies, validated competence-based assessment tools aligned with these approaches are still largely absent. To address this gap, this paper proposes a competence-based assessment framework for AI literacy grounded in the AI-related indicators of DigComp 2.2 and DigComp 3.0. The framework integrates knowledge, skills and attitudes and aligns them with the Engage-Investigate-Act structure of Challenge Based Learning, a pedagogical model designed to elicit authentic, performance-based evidence. The resulting assessment grid articulates five competence areas and provides indicators, proficiency levels and examples of authentic evidence. The proposed framework offers teachers and curriculum designers a transparent and pedagogically coherent tool for assessing AI literacy and establishes a foundation for future empirical validation studies.