The Practice
The emergence of generative AI presents complex challenges for academic integrity and assessment design. Within Principles of Quantitative Social Science, AI was incorporated into both teaching and assessment not as a technical requirement but as an opportunity for critical and ethical reflection. The central aim was to foster digital reflexivity, encouraging students to think explicitly about how and why they engage (or choose not to engage) with AI in their learning.
The summative assessment is a portfolio of quantitative analysis tasks. The first question in the portfolio invites reflexive engagement with AI:
“Reflect on your decision to use or not to use AI and how this shaped your learning journey in QRM.”
Students were encouraged, but not required, to use AI tools. They were asked to reflect on their decisions and to consider the implications of AI for authorship, responsibility, and methodological understanding. Blackboard guidance outlined acceptable and unacceptable uses (for example, troubleshooting syntax errors was acceptable; generating full analyses or text outputs was not).
To scaffold this reflection, a Collaborative Learning Lab session was devoted to AI and academic integrity. These full-cohort sessions are designed to be creative and interactive. I began with a short story: someone discovers that the person they’ve been flirting with has been using AI to write their messages, prompting them to question what was real. Students then discussed:
- Was it clever use of technology or dishonest?
- Would you feel deceived or impressed?
- Where’s the line between human or AI authorship?
This first story and discussion point provided a disarming path into what could be considered a loaded topic. I then introduced University study skills materials on AI, highlighted academic integrity values, and directed students to the Blackboard page clarifying acceptable and unacceptable AI use on this unit (even this delineation I now feel uncomfortable with, but some clarity was required).
Next, I read a second story: a student uses AI to help interpret their statistical results and polish their portfolio, then wonders whether this reliance has crossed the line between legitimate support and dishonesty. Drawing on the earlier discussion and the institutional guidance introduced in between, students debated again where, and why, a boundary might have been crossed.
This approach positioned AI as a something to be examined, interpreted, and problematised rather than as a threat to be eliminated. It encouraged transparency, dialogue, and critical engagement with emerging technologies.
The Impact
Students’ reflective responses to the set question in the portfolio demonstrated sophisticated engagement with questions of ethics, authorship, and learning. Some used AI to troubleshoot syntax code, others for support in structuring written results, while others explicitly rejected it. Many articulated a deeper understanding of what it means to learn a new skill and how AI mediates their learning process.
This reflective use of AI transformed it from a potential integrity risk into an instrument for critical thinking and self-awareness. It helped normalise open discussion of AI use, reducing the secrecy and anxiety that often surround it.
These reflections also provided insight into students’ digital literacies and their moral reasoning. Engagement with AI varied widely: some students enjoyed the novelty and the sanctioned freedom to explore, others expressed caution about grey areas, and a few resisted its use altogether to the point of seeming offended at the suggestion of using AI. This variety provided welcome nuance to the stereotype that “all students are using AI” and highlighted AI-literacy as another axis of diversity within the cohort.
Next Steps
Future activity will expand this approach through peer-led dialogue on AI use and ethics. In collaboration with students, we will design a school position on AI to provide clarity for both staff and students about our shared values and expectations.
This case study demonstrates that embedding AI in assessment in a flexible, reflective way does not compromise academic integrity but offers a tangible means for students to practise honesty, builds trust between staff and students, and acknowledges diversity in students willingness to use AI.
Contact:
Dr Jennifer Whillans
jennifer.whillans@bristol.ac.uk
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