Abstract
CONTEXT
The integration of Generative AI (GenAI) in higher education has become a pivotal area ofdiscussion as institutions strive to balance innovation with academic integrity. While GenAI offerstransformative potential for learning and assessment, its rapid adoption has highlighted challengesof ensuring consistent and ethical use across diverse disciplines. Existing research indicates thatuniversities 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 engineeringcourse outlines. The goal is to understand how the institutional policies on use of GenAI are beingimplemented, 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 coherenceacross institutions and identify the barriers to effective GenAI integration aligned with academicintegrity and education outcomes.
APPROACH OR METHODOLOGY/METHODS
An autoethnographic qualitative survey was conducted with 12 engineering academic staff from tenAustralian higher education institutions, exploring three themes: policy governance, templatestandardisation, and student feedback. Thematic analysis identified patterns, variations andinsights 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, particularlyin terms of governance structures and academic autonomy. Findings highlight inconsistencies inhow GenAI is communicated to students and how academic staff are supported with training, andhow 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 inacademic practices. The study underscores the need for a more standardised and transparentapproach to GenAI integration, particularly in the context of course outlines and assessments.Recommendations include implementing consistently clearer frameworks for GenAI use, providingmore structured support for staff, and aligning institutional policies with pedagogical practices.
The integration of Generative AI (GenAI) in higher education has become a pivotal area ofdiscussion as institutions strive to balance innovation with academic integrity. While GenAI offerstransformative potential for learning and assessment, its rapid adoption has highlighted challengesof ensuring consistent and ethical use across diverse disciplines. Existing research indicates thatuniversities 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 engineeringcourse outlines. The goal is to understand how the institutional policies on use of GenAI are beingimplemented, 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 coherenceacross institutions and identify the barriers to effective GenAI integration aligned with academicintegrity and education outcomes.
APPROACH OR METHODOLOGY/METHODS
An autoethnographic qualitative survey was conducted with 12 engineering academic staff from tenAustralian higher education institutions, exploring three themes: policy governance, templatestandardisation, and student feedback. Thematic analysis identified patterns, variations andinsights 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, particularlyin terms of governance structures and academic autonomy. Findings highlight inconsistencies inhow GenAI is communicated to students and how academic staff are supported with training, andhow 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 inacademic practices. The study underscores the need for a more standardised and transparentapproach to GenAI integration, particularly in the context of course outlines and assessments.Recommendations include implementing consistently clearer frameworks for GenAI use, providingmore structured support for staff, and aligning institutional policies with pedagogical practices.
| Original language | English |
|---|---|
| Title of host publication | 36th Australasian Association for Engineering Education Annual Conference |
| Publisher | Engineers Australia |
| Number of pages | 7 |
| Publication status | Published - 2025 |
| Event | AAEE - Annual Conference of Australasian Association for Engineering Education 2025 - Brisbane, Australia Duration: 7 Dec 2025 → 10 Dec 2025 Conference number: 36th https://aaee2025.org/ (Website/Proceedings) https://aaee2025.org (Website) |
Conference
| Conference | AAEE - Annual Conference of Australasian Association for Engineering Education 2025 |
|---|---|
| Abbreviated title | AAEE2025 |
| Country/Territory | Australia |
| City | Brisbane |
| Period | 7/12/25 → 10/12/25 |
| Internet address |
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Keywords
- Generative AI
- Engineering education
- Academic integrity
- Australian universities
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