Hong Litian
School of Smart Tourism, Business Administration, Zhejiang Technical Institute of Economics, Hangzhou, 310018, Zhejiang, China.
Sci Rep. 2025 Aug 14;15(1):29898. doi: 10.1038/s41598-025-15202-6.
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.
人工智能在各行业的迅速整合，使得高等职业教育有必要系统地开展人工智能素养培养，以便让学生为人工智能驱动的专业环境做好准备。本研究开发并验证了一种基于能力的综合阶梯式发展路径，该路径专门设计用于提高职业学生的人工智能素养。该研究采用了一种混合方法，将理论框架构建、实证调查和实际实施验证相结合。这个三层路径模型整合了基础认知、技能应用和综合创新层面，以满足多样化的学习需求，同时保持进阶标准。通过对15所院校的2850名学生进行实证调查，该研究识别出了不同的学习者特征和能力缺陷，为个性化发展策略提供了依据。对420名参与者进行的验证实验表明，在所有能力维度上都有显著提升，在六个月的随访中，人工智能素养总体提升了56.0%，持续保持率超过85%。创新的教学方法包括项目驱动学习、体验式方法和混合教学模式，以优化能力发展。综合评估框架提供了强大的评估工具，在平衡形成性和总结性方法的同时，保持与行业标准的一致性。结果表明，与传统教学相比，处于阶梯式路径干预中的学生在认知评估分数上高出34.7%，在技能应用任务上表现优42.3%，在创新能力成果上高出28.9%。本研究有助于从理论上理解基于能力的人工智能教育，同时为提高人工智能时代劳动力的准备程度提供实际实施指导。
