From foundational frameworks to future frontiers: critical perspectives of translation competence assessment models and emerging challenges

Translation competence (TC) is a multifaceted construct whose valid assessment remains a central challenge in translator education. In this study, we constructed a decade-bounded corpus of peer-reviewed publications and analyzed it within a qualitative document analysis framework, employing thematic analysis to identify recurring patterns in how TC is conceptualized, operationalized, and evaluated across educational contexts. Using dominant frameworks (notably PACTE and EMT) as analytic reference points, we trace a clear trajectory from single end-product grading toward criteria-referenced, multi-evidence, and process-oriented assessment-designs. The findings indicate that reflective commentaries, portfolios, structured self-assessment, and technology enabled approaches are increasingly used to enhance assessment authenticity and formative value, although implementation remains uneven across contexts. The analysis also foregrounds persistent controversies, including how to balance collaborative learning with individual accountability and how the growing centrality of neural machine translation reshapes both assessable competence and the interpretation of performance. Comparative tables present major competence models, assessment instruments, and reported outcomes. Finally, we delineate recurring gaps, particularly training and industry misalignment and the limited uptake of process evidence and integrate them into a conceptual framework to guide future empirical inquiry and assessment development.