Mapping Methodological Approaches to Critical Digital Literacy Among TVET Instructors: A Scoping Review

Abstract

Digital competence frameworks for teachers have proliferated, but whether their critical, reflective dimension has been examined among technical and vocational education and training (TVET) instructors remains uncharacterized. This scoping review characterized the methodological approaches, conceptual operationalizations, and evidence gaps in peer-reviewed research on critical digital literacy (CDL) among TVET instructors. Following Joanna Briggs Institute guidance and reported per PRISMA-ScR, Scopus was searched on 3 July 2026 using a Population-Concept-Context strategy, restricted to English-language, peer-reviewed literature from 2013–2026. Eligible sources were charted against a framework combining bibliographic, PCC, and methodological data items. Eighty sources met the eligibility criteria. Results included sources concentrated in Western, Northern, and Southern Europe (30.0%) and Southeast Asia (27.5%, including Indonesia at 22.5%), with smaller shares from East Asia, Eastern Europe/Central Asia, and other regions. Quantitative survey designs accounted for roughly half of charted approaches, while qualitative, configurational, and computational designs were comparatively rare. Nine concept-operationalization categories emerged, with an explicit critical-reflective or ethical dimension reported in only 11.2% of sources. An evidence gap map identified 22 of 54 (40.7%) concept-by-context combinations with no charted source, most notably critical-reflective framing paired with Southeast Asian settings. Research on CDL among TVET instructors relies heavily on a single methodological mode and has not yet reconciled structured competence frameworks with the construct’s critical-reflective dimension, particularly outside Europe. Priority directions include region-specific research on critical-reflective CDL in Southeast Asia, a dedicated CDL-specific instrument, and continued tracking of the emerging artificial-intelligence-related sub-theme.