Conference paper
Use of Generative AI in the Australian Engineering Curriculum – the academics' perspective
Proceedings of the 36th Australasian Association For Engineering Education Annual Conference, pp.1-7
Australasian Association for Engineering Education (AAEE) Annual Conference, 36th (Brisbane, Australia, 07-Dec-2025–10-Dec-2025)
Australasian Association For Engineering Education
2025
Abstract
CONTEXT
The integration of Generative AI (GenAI) in higher education has become a pivotal area of discussion as institutions strive to balance innovation with academic integrity. While GenAI offers transformative potential for learning and assessment, its rapid adoption has highlighted challenges of ensuring consistent and ethical use across diverse disciplines. Existing research indicates that universities have struggled with the implementation of clear policies regarding GenAI.
PURPOSE OR GOAL
This study investigates academic perspectives of how GenAI is being addressed in engineering course outlines. The goal is to understand how the institutional policies on use of GenAI are being implemented, the consistency of messaging to students across the curriculum, and the students’ feedback academics are getting. Specifically, this paper seeks to assess the degree of coherence across institutions and identify the barriers to effective GenAI integration aligned with academic integrity and education outcomes.
APPROACH OR METHODOLOGY/METHODS
An autoethnographic qualitative survey was conducted with 12 engineering academic staff from ten Australian higher education institutions, exploring three themes: policy governance, template standardisation, and student feedback. Thematic analysis identified patterns, variations and insights in how GenAI is framed within course outlines and assessment tasks.
ACTUAL OR ANTICIPATED OUTCOMES
The study reveals significant variation in how GenAI is implemented across institutions, particularly in terms of governance structures and academic autonomy. Findings highlight inconsistencies in how GenAI is communicated to students and how academic staff are supported with training, and how they perceive their roles in enforcing GenAI guidelines.
CONCLUSIONS/RECOMMENDATIONS/SUMMARY
The findings suggest that while GenAI is widely adopted across Australian engineering institutions, the absence of consistent and clear policies has led to confusion among students and variability in academic practices. The study underscores the need for a more standardised and transparent approach to GenAI integration, particularly in the context of course outlines and assessments. Recommendations include implementing consistently clearer frameworks for GenAI use, providing more structured support for staff, and aligning institutional policies with pedagogical practices.
Details
- Title
- Use of Generative AI in the Australian Engineering Curriculum – the academics' perspective
- Authors
- Euan Lindsay (Corresponding Author) - Aalborg UniversityAneesha Bakharia - The University of QueenslandJulie Jupp - University of Technology SydneyZachery Quince - Southern Cross UniversityWinn Wing-Yiu Chow - The University of MelbourneStella Peng - The University of MelbourneSusan Zhang - La Trobe UniversityRezwanul Haque - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringKathy Petkoff - Monash UniversitySasha Nikolic - University of WollongongAnna Lidfors Lindqvist - University of Technology SydneyMohamed Atef Ali Madni - Polytechnic Institute AustraliaElisa Martinez-Marroquin - University of Canberra
- Publication details
- Proceedings of the 36th Australasian Association For Engineering Education Annual Conference, pp.1-7
- Conference details
- Australasian Association for Engineering Education (AAEE) Annual Conference, 36th (Brisbane, Australia, 07-Dec-2025–10-Dec-2025)
- Publisher
- Australasian Association For Engineering Education
- Date published
- 2025
- Copyright note
- Copyright © 2025 Euan Lindsay, Aneesha Bakharia, Julie Jupp, Zachery Quince, Winn Wing-Yiu Chow, Stella Peng, Susan Zhang, Rezwanul Haque, Kathy Petkoff, Sasha Nikolic, Anna Lidfors Lindqvist, Mohamed Atef Ali Madni, Elisa Martinez-Marroquin: The authors assign to the Australasian Association for Engineering Education (AAEE) and educational non-profit institutions a non-exclusive licence to use this document for personal use and in courses of instruction provided that the article is used in full and this copyright statement is reproduced. The authors also grant a non-exclusive licence to AAEE to publish this document in full on the World Wide Web (prime sites and mirrors), on Memory Sticks, and in printed form within the AAEE 2025 proceedings. Any other usage is prohibited without the express permission of the authors.
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991188344702621
- Output Type
- Conference paper
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