ENLARGING TECHNICAL VOCABULARY IN LIGHT INDUSTRY VOCATIONAL EDUCATION THROUGH AI-BASED TOOLS
DOI:
https://doi.org/10.37547/Keywords:
vocational education, light industry, technical vocabulary acquisition, artificial intelligence in education, CLIL, cognitive load theory, smart pedagogy.Abstract
The digitization of the light industry sector — encompassing textiles, apparel, footwear, and fashion design — demands vocational graduates who possess both technical dexterity and robust professional communication skills. Central to this competence is mastering a highly specialized, interdisciplinary technical vocabulary. Traditional methods like rote memorization and static glossaries fail to provide the contextual relevance and adaptive pacing required by diverse vocational learners. This article explores the systematic integration of Artificial Intelligence (AI) tools — specifically Natural Language Processing (NLP) engines, Large Language Models (LLMs), and adaptive intelligent tutoring systems — to accelerate vocabulary acquisition. Grounded in Content and Language Integrated Learning (CLIL) and Cognitive Load Theory, we examine how AI minimizes extraneous cognitive load by delivering contextualized, gamified micro-learning directly into workshop environments.
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References
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