Long-Term Project-Based Learning with Multi-Skill Integration for Generative AI Curriculum

Hua Xie and Zhiwei Zhang

Education Insights, 2026, vol. 3, issue 2, 29-35

Abstract: 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

Keywords: generative AI; project-based learning; multi-skill integration; vocational education; human-computer collaboration (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:axf:eiaaaa:v:3:y:2026:i:2:p:29-35

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