Development and validation of a competency-based ladder pathway for AI literacy enhancement among higher vocational students

The rapid integration of artificial intelligence across industries necessitates systematic AI literacy development in higher vocational education to prepare students for AI-driven professional environments. This study develops and validates a comprehensive competency-based ladder development pathway...

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Vydané v:Scientific reports Ročník 15; číslo 1; s. 29898 - 15
Hlavný autor: Hong, Litian
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Nature Publishing Group UK 14.08.2025
Nature Publishing Group
Nature Portfolio
Predmet:
639/705/117
639/705/258
Adaptation
Adult
AI literacy
Algorithms
Artificial Intelligence
Cognition & reasoning
Cognitive style
Collaboration
Competency-based education
Critical thinking
Development strategies
Digital literacy
Educational objectives
Ethics
Female
Higher vocational education
Humanities and Social Sciences
Humans
Innovations
Knowledge
Ladder development pathway
Learning
Literacy
Male
multidisciplinary
Principles
Problem solving
Science
Science (multidisciplinary)
Skills
Student retention
Students
Vocational education
Vocational Education - methods
Workforce development
Young Adult
Competency-based education
Ladder development pathway
Artificial intelligence
Workforce development
Higher vocational education
AI literacy
ISSN:2045-2322, 2045-2322
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Shrnutí:The rapid integration of artificial intelligence across industries necessitates systematic AI literacy development in higher vocational education to prepare students for AI-driven professional environments. This study develops and validates a comprehensive competency-based ladder development pathway specifically designed to enhance AI literacy among vocational students. The research employs a mixed-methods approach combining theoretical framework construction, empirical investigation, and practical implementation validation. The three-tier pathway model integrates foundational cognitive, skills application, and comprehensive innovation layers to address diverse learning needs while maintaining progression standards. Through empirical investigation involving 2850 students across 15 institutions, the study identifies distinct learner profiles and competency deficits, informing personalized development strategies. The validation experiment with 420 participants demonstrates significant improvements across all competency dimensions, with overall AI literacy gains of 56.0% and sustained retention rates exceeding 85% at six-month follow-up. The innovative pedagogical approaches incorporate project-driven learning, experiential methodologies, and hybrid delivery models to optimize competency development. The comprehensive evaluation framework provides robust assessment tools that balance formative and summative approaches while maintaining alignment with industry standards. Results indicate that students in the ladder pathway intervention achieved 34.7% higher cognitive assessment scores, 42.3% superior performance on skills application tasks, and 28.9% better innovation competency outcomes compared to traditional instruction. This research contributes to the theoretical understanding of competency-based AI education while providing practical implementation guidance for enhancing workforce readiness in the artificial intelligence era.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-025-15202-6