Published on: 23/06/2026 · Last updated on: 23/06/2026
Introduction
In this case study Simona Montagnana from our Economics Department outlines how she has adapted one of her behavioural economics assessments for the GenAI age. The assessment has multiple stages designed to ensure that students develop their ability to combine economic theory, empirical interpretation, critical reflection and personal experience, with the responsible use of GenAI.
The assessment has two parts and is organised around four main tasks. In Part A, students are required to firstly, use a GenAI tool to support the development of the initial section of an essay and secondly, to critically evaluate the AI-generated response (Tasks 1 and 2). In Part B, students connect the theoretical concepts explored in Part A to material discussed in class and to a real-world example (Tasks 3 and 4).
Part A: AI-Integrated Theoretical Analysis
The first part of the assessment focuses on students’ ability to engage with the theoretical concepts discussed in the unit, as well as to assess a new concept introduced by an article they are assigned.
Students are presented with two real-world scenarios in the assigned article and are asked to develop an essay using these and an assigned academic reading as a starting point. The reading introduces an alternative theoretical perspective that students should engage with critically in their analysis. Students are expected to:
- Critically evaluate whether the results presented in the article are consistent with the particular theory introduced in the unit (Task 1).
- Use the relevant conceptual approach to explain the differences between the two scenarios (Task 2).
In this part, the use of Generative AI is mandatory. Students are required to use an approved AI tool to support the initial development of their theoretical analysis and to critically evaluate the response provided by the GenAI tool. The AI-generated output must be included as an appendix. The aim is not simply to use AI-generated content, but to encourage students to assess its accuracy, identify potential weaknesses, and reflect on how GenAI can support or mislead students in their economic reasoning.
Part B: Applied and Contextual Analysis
This part of the assessment asks students to apply the theoretical concepts analysed in Part A to both the results of an in-class experiment and real-world contexts. Students are required to:
- Demonstrate their ability to connect academic theory with an in-class experiment (Task 3).
- Identify a recent example from their own country, city, or personal experience where these concepts can be applied (Task 4). (This final element requires them to collect evidence, such as a screenshot, photograph, or other relevant material, and explain how the example relates to the theory.)
In Part B, the use of Generative AI is permitted but not required. Students may use GenAI as an assistive tool, but they remain fully responsible for their work. Part B develops students’ ability to connect theory with empirical observation and personal context, offering them the opportunity to demonstrate clear analytical reasoning and independent judgement.
The role of GenAI in the assessment
A distinctive feature of the assessment is its differentiated approach to the use of Generative AI. For the first part of the assignment, the use of Generative AI is mandatory: students must use an approved tool, Microsoft Copilot, to generate responses to selected theoretical questions. However, they are not simply assessed on the AI-generated content. They must critically evaluate its quality, limitations, accuracy, and usefulness. This encourages students to treat GenAI as an object of analysis rather than as an unquestioned source of answers. To complete this part the GenAI output must be submitted as appendix. Part A is worth 40% of the students’ mark.
For Part B, also worth 40% of the mark, GenAI is permitted but not required. Students may use GenAI as an assistive tool, but they remain responsible for the accuracy, relevance, and logic of their work. Where GenAI is used, students must acknowledge this and provide the relevant AI chat log. In Part B, students are being assessed on their ability to apply theory to an in-class experiment, connect theoretical concepts with empirical results from the class experiment, and identify a relevant real-world or personal example supported by appropriate evidence. Marks are awarded for critical reflection, as per the Faculty Generic Marking Criteria.
Across Part A and Part B, students are expected to present their work clearly, using appropriate academic language, structure, citations, referencing, and acknowledgement of GenAI use, 20% of the mark is allocated to these elements.
Overall, the assessment is designed to help students engage critically with both economic theories and AI-generated material. It supports academic integrity by making GenAI use transparent, while also developing important complementary skills such as judgement, independent research, contextual application, evidence collection, and critical reflection.
This case study illustrates how assessment can move beyond simply preventing GenAI use and instead embed GenAI into the learning process in a structured and educationally meaningful way. The aim is to assess not only theoretical understanding, but also application, independent judgement, evidence-based analysis, and responsible engagement with Generative AI.