Ethical Decision-Making Framework and AI | UQ Assessment Ideas Factory

Students will prepare a 2,500 word written essay in two parts that develops an individual ethical decision-making framework for mental health practice and critically reflects on the use of this framework in conjunction with generative artificial intelligence (AI). The task is designed to deepen students’ understanding of ethical theory, professional values, and real-world decision-making processes, while also encouraging critical evaluation of the emerging role of AI in mental health practice.

PART 1: Ethical Framework Development
Students will conduct a literature review drawing on ethical theory, professional codes, regulatory expectations, and relevant mental health ethics literature. Using this evidence base, students will develop and justify a personalised ethical decision-making framework tailored to their professional identity and therapeutic context. The framework should be original, theoretically supported, and structured as a practical step-by-step model for guiding future ethical decisions in mental health practice.

PART 2: Applied Reflection & AI Analysis
Students will apply their ethical framework to a hypothetical ethical dilemma provided in the course and will input their framework into a generative AI tool to explore how AI interprets, applies, or distorts their model. Students will then critically analyse the strengths, limitations, and ethical risks associated with AI-mediated decision making, including potential issues around bias, confidentiality, professional judgement, clinical nuance, and client safety. Students will conclude this section with a reflective statement articulating their professional position on whether, when, and how AI could be ethically incorporated into mental health practice.

Appendix Requirement:
All AI prompts and AI-generated outputs must be submitted in an appendix (not included in the word count). Students must clearly distinguish their own ideas, interpretation, and reasoning within the essay from any AI-generated material. Failure to include prompts/output may result in academic penalty.

Advantages

Course staff were really impressed by students works and reflections on this emerging topic. Some of the reflections were very nuanced, highlighting strengths and weaknesses of using AI, within the context of the current mental health landscape. After the course, tutors provided positive feedback on the assessment design, especially because it’s currently the only assessment piece within the Master of Mental Health program that prompts students to critically reflect on AI use in mental health practice.

Students noted they appreciate the opportunity to have space to critically reflect on AI use in mental health practice. One student said she "loved the assessment" for ethics - so overall really positive feedback. Some students also developed very strong positions regarding AI use; citing wider ethical concerns or clear positions based on the assessment activity.

Challenges

The main challenge with this assessment piece was the implementation. This assessment was an evolution from a previous assessment design where students were asked to create an Ethical Decision-Making Framework and apply it to a real ethical dilemma they had experienced in practice. As a result of the change, tutors were a little confused by this new integration of AI and required some tutors to orient themselves to AI in order to best support students. Additional meetings were provided to support staff in this process. Despite this initial setback, there seemed to be no issues. I also provided very specific instructions on Blackboard and didn't have any questions from students.

I will implement this assessment again in Semester 1 2027 with minimal changes to the assessment design. I will likely review and refine the resources and the rubrics, and I’m interested in designing a formative activity in the weeks preceding so students can get feedback on their emerging ideas for the assignment.

Learning outcomes

L02 Analyse the regulatory and professional structures governing mental health practice in Australia, including emerging ethical challenges related to digital and AI-mediated practice.
L03 Analyse and apply ethical principles to dilemmas and challenges in mental health practice.

PLEASE NOTE: The academic integrity information displayed on this page is currently under review. Some examples and descriptions were developed before the widespread availability of generative AI tools and may not reflect current approaches to assessment security. When adapting an assessment idea, staff should consider how the design supports authorship, verifies student achievement of learning outcomes, and mitigates inappropriate use of AI and other forms of academic misconduct.

Details

CLASS SIZE: 20-40, 40-60
YEAR LEVEL: Post-graduate
ASSESSMENT SECURITY: Open
SUPERVISION STATUS: Not supervised
SUBMISSION MEDIUM: Text
ASSESSMENT DELIVERY MODE: Digital task
AUTHENTICITY CONTEXT: Reflective / Professional identity
GRADUATE ATTRIBUTES: Accomplished scholars, Courageous thinkers, Connected citizens, Influential communicators, Respectful leaders
CONDITIONS: AI Required

Health, Medicine and Behavioural Sciences Ethical Decision-Making Framework and AI

Advantages

Challenges

Learning outcomes

Details