Applying the Project-work AI Integration Framework (PAIIF)

Early insights from multi-institutional implementation

Abstract

The Project-work Artificial Intelligence Integration Framework (PAIIF) was developed to guide educators in embedding AI tools into project-based learning in engineering education. Grounded in the CDIO model, PAIIF extends the traditional four project stages (Conceive, Design, Implement, Operate) by incorporating four additional sub-stages that emphasise evaluation, communication, and reflection. This paper presents the early application of the PAIIF across six undergraduate and one postgraduate engineering course at five Australian universities during 2024. To evaluate the framework’s effectiveness, a two-phase survey was deployed to capture students’ understanding and usage of GenAI tools before and after the integration. The implementation was tailored to each institution’s policies and curricular context, with instructors selecting relevant stages of the framework based on course learning objectives. This paper offers a snapshot of how GenAI tools were introduced to support ideation, documentation, and evaluation tasks within project work. While full survey results are still being analysed, early observations suggest that PAIIF provided a valuable scaffold for ethical and pedagogically aligned GenAI use. This work contributes initial practical insights for educators seeking to apply structured AI integration in engineering education and lays the foundation for future large-scale evaluations.