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Published (Version of record)CC BY V4.0, Open Access
Published (Version of record)CC BY V4.0, Open
Journal article
Project-work Artificial Intelligence Integration Framework (PAIIF): Developing a CDIO-based framework for educational integration
STEM education, Vol.5(2), pp.310-332
14/03/2025
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Abstract
Artificial intelligence (AI) and generative AI (GenAI) have sparked confusion and concern regarding their impact on education. Beyond the assessment integrity risks that currently draw the most attention, technologies such as ChatGPT, Copilot, and Gemini have also been identified as tools that can support learning. Project work, especially when there is no single correct solution, provides a great opportunity for integration, fostering technology knowledge and higher learning standards. However, no AI-integration framework for project-based work is available, resulting in a limited understanding of how AI integration can occur or be maximized. To address this, a collaborative effort of 16 educators from 9 Australian universities has led to the development of a generic AI implementation framework, built upon the CDIO approach. With a focus on engineering education, this framework can be adapted to other project-based learning contexts, where educators can pick and choose the relevant implementation items as needed. This framework is called the Project-work Artificial Intelligence Integration Framework (PAIIF), and its development and structure are outlined here. Initial implementations have shown the effectiveness of promoting reflection and guidance on where and how AI integration can occur.
Details
- Title
- Project-work Artificial Intelligence Integration Framework (PAIIF): Developing a CDIO-based framework for educational integration
- Creators
- Sasha Nikolic - University of WollongongZach Quince (Author) - University of Southern QueenslandAnna Lidfors Lindqvist - University of Technology SydneyPeter Neal - University of New South WalesSarah Grundy - University of New South WalesMay Lim - University of New South WalesFaham Tahmasebinia - University of SydneyShannon Rios - University of MelbourneJosh Burridge - University of MelbourneKathy Petkoff - Monash UniversityAshfaque Ahmed Chowdhury - Central Queensland UniversityWendy S L Lee - University of New South WalesRita Prestigiacomo - University of New South WalesHamish Fernando - University of SydneyPeter Lok - University of SydneyMark Symes - University of Tasmania
- Publication Details
- STEM education, Vol.5(2), pp.310-332
- Identifiers
- 991013266110302368
- Copyright
- © 2025 the Author(s)
- Academic Unit
- Centre for Teaching and Learning
- Language
- English
- Resource Type
- Journal article