Long-Term Project-Based Learning with Multi-Skill Integration for Generative AI Curriculum - Xie, Hua; Zhang, Zhiwei (Education Insights, 2026)
Background/Objectives: This study explores the effectiveness of a "multi-skill integrated, long-term project-based learning" (PjBL) approach within a generative artificial intelligence (GenAI) course in vocational colleges. Methods: Grounded in constructivism and authentic learning theory, the study designed an eight-week "AI-assisted short online novel creation" program. This curriculum integrated multiple skills-including AI writing, painting, and data analysis-resulting in the publication of novels on a real-world platform to foster authentic engagement. A quasi-experimental design was employed to compare an experimental group (n = 49) undergoing this long-term integrated instruction against a control group (n = 66) engaged in short-term projects. Results: It indicated that the long-term PjBL approach yielded significantly higher task completion rates (98.0% vs. 78.8%, p < 0.01) and demonstrated superior comprehensive AI literacy compared to the short-term approach. Conclusions: These findings suggest that authentic, long-term complex tasks significantly enhance student efficacy and skill acquisition, providing a valid paradigm for the curriculum design of GenAI courses in vocational education.