Instructors' and Students' Perceptions of AI-Supported Teaching and Learning in Technical-Vocational Education: A Systematic Literature Review

Abstract

The integration of Artificial Intelligence (AI) within Technical-Vocational Education and Training (TVET) is increasingly shaping the educational landscape, presenting both novel pedagogical opportunities and complex challenges. This systematic literature review investigates how instructors and students perceive and experience the implementation of AI-supported teaching and learning approaches in TVET settings. This review addresses the growing need to understand the human dimensions of AI adoption in vocational education, particularly from the perspectives of those directly involved in teaching and learning. As AI technologies become increasingly embedded in educational practices, examining the experiences, perceptions, and concerns of instructors and students is essential for informing effective and responsible implementation strategies. By synthesizing evidence across diverse TVET contexts, this review provides insights into emerging opportunities, challenges, and implications for policy and practice. Following the PRISMA 2020 framework, an initial database search on Lens.org yielded 580 records. After applying rigorous inclusion and exclusion criteria, including filters for publication date, document type, and subject matter, 19 empirical studies were selected for final qualitative synthesis. The findings reveal three overarching themes. First, while instructors exhibit optimism regarding efficiency gains, they express significant concerns about dehumanization, cognitive decline, and threats to academic integrity. Second, students experience enhanced psychological safety through instant feedback, yet face a paradox of being "Engaged but Amotivated" alongside risks of severe technological dependency. Third, AI implementation in TVET is uniquely constrained by the necessity for tactile skill mastery, industry precision, and alignment with local cultural practices. Ultimately, maximizing AI's potential in vocational education requires addressing systemic infrastructure barriers and preserving the hands-on, human-centric core of TVET.