Project-work Artificial Intelligence Integration Framework (PAIIF): Developing a CDIO-based framework for educational integration

Sasha Nikolic; Zach Quince; Anna Lidfors Lindqvist; Peter Neal; Sarah Grundy; May Lim; Faham Tahmasebinia; Shannon Rios; Josh Burridge; Kathy Petkoff; Ashfaque Ahmed Chowdhury; Wendy S.L. Lee; Rita Prestigiacomo; Hamish Fernando; Peter Lok; Mark Symes; Sasha Nikolic; Zach Quince; Anna Lidfors Lindqvist; Peter Neal; Sarah Grundy; May Lim; Faham Tahmasebinia; Shannon Rios; Josh Burridge; Kathy Petkoff; Ashfaque Ahmed Chowdhury; Wendy S.L. Lee; Rita Prestigiacomo; Hamish Fernando; Peter Lok; Mark Symes

doi:10.3934/steme.2025016

STEM Education

2025, Volume 5, Issue 2: 310-332. doi: 10.3934/steme.2025016

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Research article

Project-work Artificial Intelligence Integration Framework (PAIIF): Developing a CDIO-based framework for educational integration

1.
Faculty of Engineering & Information Sciences, University of Wollongong, Wollongong, Australia
2.
School of Engineering, University of Southern Queensland, Springfield, Australia
3.
Faculty of Engineering & Information Technology, University of Technology Sydney, Sydney, Australia
4.
Faculty of Engineering, University of New South Wales, Sydney, Australia
5.
Faculty of Engineering, University of Sydney, Sydney, Australia
6.
Faculty of Engineering and IT, University of Melbourne, Melbourne, Australia
7.
Engineering Office of the Dean, Monash University, Monash, Australia
8.
School of Engineering and Technology, Central Queensland University, Gladstone, Australia
9.
Centre for Maritime Engineering and Hydrodynamics, University of Tasmania, Hobart, Australia

Academic Editor: Med Amine Laribi

Received: 08 October 2024 Revised: 06 February 2025 Accepted: 17 February 2025 Published: 14 March 2025

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.
- Artificial intelligence (AI),
- CDIO,
- ChatGPT,
- educational integration,
- generative AI (GenAI),
- project-based learning (PBL)
Citation: Sasha Nikolic, Zach Quince, Anna Lidfors Lindqvist, Peter Neal, Sarah Grundy, May Lim, Faham Tahmasebinia, Shannon Rios, Josh Burridge, Kathy Petkoff, Ashfaque Ahmed Chowdhury, Wendy S.L. Lee, Rita Prestigiacomo, Hamish Fernando, Peter Lok, Mark Symes. Project-work Artificial Intelligence Integration Framework (PAIIF): Developing a CDIO-based framework for educational integration[J]. STEM Education, 2025, 5(2): 310-332. doi: 10.3934/steme.2025016

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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.

References

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Author's biography Dr Sasha Nikolic is a Senior Lecturer at the University of Wollongong with a PhD in Engineering Education. He has worked in academia and industry. Dr. Nikolic has received multiple teaching and learning awards, including Australian Awards for University Teaching in 2012 and 2019, and AAEE awards in 2019 and 2023. He served in multiple governance roles with IEEE, and is an Associate Editor of the European Journal of Engineering Education. He currently serves as President for both the Australasian Association of Engineering Education and the Australasian Artificial Intelligence in Engineering Education Centre, where he leads multi-institutional initiatives on Generative AI; Dr Zachery Quince is a senior lecturer in Teaching and Learning at Southern Cross University. His expertise includes biomedical engineering curriculum development, professional engineering skills development, and ethical GenAI use in higher education. He has led the development of digital technology integration and GenAI. His research focuses on graduate employability and industry aligned skills. A recipient of multiple teaching awards, he has secured grants for projects on GenAI in education and professional skill development; Dr Anna Lidfors Lindqvist is a Lecturer in the School of Mechanical and Mechatronic Engineering at the University of Technology Sydney (UTS), Australia. She specialises in applied mechanical design projects and engineering education. Her research in engineering education focuses on innovative assessment methods, studio learning, formative assessment, and feedback literacy to enhance student learning and professional skill development. She actively collaborates with industry and academia to bridge the gap between education and engineering practice. She is a member of the Australasian Association for Engineering Education (AAEE) Early Career Academy; Dr Peter Neal is a Senior Lecturer in Process Engineering (Education Focused) with the UNSW School of Chemical Engineering in Sydney, Australia. He specialises in Engineering Education focusing on inquiry- and project-based learning, as well as overseeing curriculum design and quality. His research interests include engineering education and engineering economics & risk analysis. He is Vice-President of the Australasian Artificial Intelligence in Engineering Education Centre and a member of the Australasian Association for Engineering Education; Dr Sarah Grundy is a Senior Lecturer in Chemical Engineering (Education Focused) at The University of New South Wales. She specialises in advanced materials, process engineering and design. Her research interests also include engineering education with a current focus on generative artificial intelligence, project-based learning and work-integrated learning. She is a member of The Australasian Artificial Intelligence in Engineering Education Centre (AAIEEC) leadership team and Senior Fellowship Higher Education Academy (SFHEA); Dr May Lim is a Nexus Fellow and Senior Lecturer in Chemical Engineering at The University of New South Wales. Her contributions to education are multifaceted and include the development of procedures, resources, and toolkits aimed at creating assessments that are not only valid and reliable but also feasible and scalable. Additionally, Dr. Lim is an active member of various working and advisory groups, where she contributes her expertise to areas such as innovation, e-Portfolio, artificial intelligence and feedback practices; Dr Faham Tahmasebinia is a Senior Lecturer in Civil Design and Construction Management at the University of Sydney, Australia. His expertise lies in civil design, structural engineering, and engineering education. His research focuses on applying numerical methods in civil engineering, integrating digital twins and Building Information Modelling (BIM) in civil construction engineering, and using artificial intelligence in civil engineering education. He is an active member of the Australasian Association for Engineering Education (AAEE), and a graduate member of the Institution of Civil Engineers (ICE) and the Institution of Structural Engineers (IStructE); Dr Shannon Rios is a Senior Lecturer of Engineering and Computing Education with the University of Melbourne. He specialises in expert teaching practice and teacher training. His engineering education research interests include; differentiated education, teamwork, and academic development. Dr Rios is the recipient of the 2024 iChemE Hanson Medal and the winner of the 2024 University of Melbourne Patricia Grimshaw award for Mentor Excellence; Mr Josh Burridge is a Lecturer in Engineering and Computing Education, specializing in software development and HCI. He has a Bachelor of Technology from RMIT University and a Master of Information Technology from The University of Sydney. He has leveraged software and HCI towards the development of new technologically-enabled laboratories in engineering education, and his PhD thesis titled "The Design and Evaluation of Laboratories in Engineering Education: The Purpose-First Approach" is under examination; Ms Kathy Petkoff is a Lecturer in Mechanical and Aerospace Engineering at Monash University. She specializes in teaching engineering design. Her research interests focus on how engineers will use Generative AI and how universities will support the adoption of this technology. She is a member of the Australasian Association for Engineering Education (AAEE); Dr Ashfaque Ahmed Chowdhury is a passionate and experienced educator and researcher with over 20 years of academic and industry experience. He serves as a Senior Lecturer and Discipline Leader at the School of Engineering and Technology at CQUniversity in Australia. Dr. Chowdhury is a leading researcher in the fields of applied energy and fuel technologies. He holds both a PhD and a Master of Engineering Degree by Research, specializing in Energy Technology and Thermodynamics. His research focuses on the numerical, theoretical, and experimental aspects of sustainable and resilient energy technologies, including bioenergy and renewable hydrogen. He is a fellow of the Higher Education Academy (FHEA); Dr Wendy Lee is a Lecturer and Nexus Fellow in the School of Electrical Engineering and Telecommunications at the University of New South Wales, Australia. She specialises in engineering education and terahertz technology. Her research interests include innovative teaching methods, hands-on learning, and the integration of electrical, mechanical, and computer science engineering to enhance student collaboration and problem-solving skills. She is a member of IEEE, AAEE, and the Terahertz Innovation Group at UNSW. Her work focuses on modernising engineering education to provide first-year students with a dynamic and industry-relevant learning experience; Dr Rita Prestigiacomo is a Lecturer (Nexus Fellow) at the Graduate School of Biomedical Engineering, where she previously worked as an academic developer and a post-doctoral fellow. With a PhD in Education from the University of Sydney, she brings a rich background in teaching. Dr. Prestigiacomo areas of expertise include curriculum development, reflective teaching and learning practices, student engagement, group work and co-design work, all underpinned by a practical approach bridging theory and practice; Dr. Hamish Fernando is a lecturer in the School of Biomedical Engineering at the University of Sydney, Australia. His research interests include body composition, metabolic syndrome and AI in Education. He is a member of the Australasian Artificial Intelligence in Engineering Education Centre (AAIEEC) of the Australasian Association of Engineering Education (AAEE); Dr Peter Lok is an Educational Designer at the Faculty of Engineering, University of Sydney. His research interests focus on AI-enhanced engineering education, the influence of Third Space Professionals, and the use of ethnographic methods to examine dynamics in engineering teaching and learning. He also explores the impact of play on educational practices. A Senior Fellow of the Higher Education Academy, Dr. Lok leverages his experiences as a higher education educator and design engineer in medical device startups to foster innovative and inclusive educational communities; Dr Mark Symes is a senior lecturer at The Australian Maritime College. He has over 35 years of industry experience and has been involved in higher education over the last 14 years with various work-integrated and peer assessment programs. He is currently leading the development of a higher education apprenticeship program that combines a trade and associate degree qualification. His primary research is the development and application of improved techniques used in the assessment of Graduate attributes in problem-based learning (PBL). He is a member of the Australasian Association for Engineering Education (AAEE) and is a committee member of the Industry Skills Council of Australia

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