Assessing historical literacy using the Common European Framework of Reference (CEFR): developing macrodescriptors through AI-assisted coding

Recent research on disciplinary literacy in CLIL and multilingual education highlights the need for theoretically grounded and pedagogically interpretable frameworks to guide teachers in task design and assessment. Cognitive Discourse Functions (CDFs) have been proposed as a key construct to describe how learners use language to construct disciplinary knowledge (Hüttner et al., 2025). Within the COST Action CLILNetLE, Lorenzo et al. (2024) developed CEFR-based disciplinary literacy descriptors across seven CDFs (Categorise, Define, Describe, Evaluate, Explain, Explore, and Report) for B1 and B2 levels in History, subsequently validated in further studies (Cabrera-Zlotnick et al., in press). While these descriptors provide a fine-grained representation of functional progression, their multi-layered for mat may limit direct pedagogical usability in multilingual classrooms. Building on previous studies, this study aims to synthesise the seven function-based descriptors into unified global profiles for B1 and B2. Data were analysed using MAXQDA, in which the original descriptors were condensed through summary-based coding into two synthetic macro descriptors for the discipline of History that integrate the seven CDFs into holistic, level-specific profiles. Overall, the study demonstrates how research-based frameworks can be adapted and tested to create practical, teacher-friendly tools that connect disciplinary literacy research with classroom practice in CLIL and multilingual education.