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Implementation of Competency-Based Assessment in Technical and Vocational Education and Training (TVET): A Systematic Review of Models, Quality Assurance, and Learner Outcomes

Year: 2026
Type: article
Study design: Systematic Review
Abstract: Competency-based assessment (CBA) has become a key approach in Technical and Vocational Education and Training (TVET) systems worldwide, driven by the need to improve workforce readiness, align education with industry needs, and enhance employability outcomes. This study presents a systematic review of literature examining how competency-based assessment is implemented in TVET, with particular focus on assessment models, quality assurance mechanisms, and learner outcomes. A structured review process was followed according to systematic review protocols, and relevant peer-reviewed studies published between 2016 and 2025 were identified from major academic databases, including Scopus, Web of Science, and ERIC. A total of 35 studies were selected and analysed thematically. The findings show that competency-based assessment is commonly carried out through workplace-based, simulation-based, portfolio-based, and performance-based demonstrations, all emphasising the practical application of skills in real or simulated settings. The review further highlights that the effectiveness of CBA largely depends on strong quality assurance mechanisms, such as standardised competency frameworks, assessor competence, moderation procedures, and industry collaboration. Regarding learner outcomes, competency-based assessment helps develop technical skills, employability competencies, workplace readiness, and learner confidence, while also fostering self-directed and lifelong learning. However, challenges like inconsistent assessment practices, limited institutional capacity, and insufficient assessor training remain. The study concludes that strengthening quality assurance systems and improving collaboration between TVET institutions and industry stakeholders are vital for enhancing the effectiveness and credibility of competency-based assessment systems.
Language: English
Subfield: Education
Open Access status: hybrid
OpenAlex ID: W7147170320
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