Conceptualising the AI-Integrated Digital Ecosystem for Link-and-Match in Technical and Vocational Education and Training (TVET): A Scoping Review Protocol

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Original abstract

Technical and vocational education and training (TVET) has long pursued link-and-match: the alignment of vocational learning with labour-market demand. As digitalisation and artificial intelligence (AI) reshape work and learning, a new construct has emerged — the "AI-integrated digital ecosystem", in which interconnected digital systems embed AI capabilities (analytics, matching, personalisation, prediction) to connect vocational education with industry. This construct is, however, defined inconsistently across the literature, and no prior review has consolidated these definitions for the link-and-match context — a conceptual-ambiguity (Type B) gap. This scoping review, conducted per the JBI methodology and reported against PRISMA-ScR, will map and clarify how the construct is conceptualised and operationalised (2015–2026). It uses a Population–Concept–Context (PCC) framework (Population = not applicable; conceptual scoping), searches of Scopus and the Web of Science Core Collection supplemented by backward and forward citation chasing, and a screening and charting workflow assisted by a large language model with the author as sole arbiter and 100% validator. The review provides the shared conceptual foundation required before any reconstruction of a link-and-match model.

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