TY - JOUR
T1 - Project-work Artificial Intelligence Integration Framework (PAIIF)
T2 - Developing a CDIO-based framework for educational integration
AU - Nikolic, Sasha
AU - Quince, Zach
AU - Lindqvist, Anna Lidfors
AU - Neal, Peter
AU - Grundy, Sarah
AU - Lim, May
AU - Tahmasebinia, Faham
AU - Rios, Shannon
AU - Burridge, Josh
AU - Petkoff, Kathy
AU - Chowdhury, Ashfaque Ahmed
AU - Lee, Wendy S.L.
AU - Prestigiacomo, Rita
AU - Fernando, Hamish
AU - Lok, Peter
AU - Symes, Mark
N1 - Publisher Copyright:
©2025 the Author(s).
PY - 2025
Y1 - 2025
N2 - 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.
AB - 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.
KW - Artificial intelligence (AI)
KW - CDIO
KW - ChatGPT
KW - educational integration
KW - generative AI (GenAI)
KW - project-based learning (PBL)
UR - https://www.scopus.com/pages/publications/105000510369
U2 - 10.3934/steme.2025016
DO - 10.3934/steme.2025016
M3 - Article
AN - SCOPUS:105000510369
SN - 2767-1925
VL - 5
SP - 310
EP - 332
JO - STEM Education
JF - STEM Education
IS - 2
ER -