Abstract
Rationale
Generative artificial intelligence (AI) is a topical issue. The importance of users being able to recognise the quality of outputs is crucial. Bearman et al. (2024) state that ‘university graduates should be able to effectively deploy the disciplinary knowledge gained within their degrees to distinguish trustworthy insights from the ‘hallucinatory’.’ Ballentine et. al (2024) suggest that generative AI provides an opportunity to move away from assessment that relies on rote learning to the use of critical assessment including authentic scenario-based examples. Such authentic assessment is regarded as an important factor in preparing students for future learning in work and life (Fawns et al., 2024).
As a result of the increased use of generative AI and the emphasis on the graduate competency goals set by QBS, it was identified that engagement with professional practice was crucial to effectively deploying an authentic scenario-based assessment incorporating generative AI.
Innovation in a taxation module
Professional services firms were engaged at key points in the module delivery. The continuous assessment was jointly drafted with a professional practitioner to ensure that it simulated a ‘live’ case in professional practice. The integration of multiple taxes, the use of ChatGPT including the assessment of its accuracy and the need for students to use excel and the Lexis online database were embedded.
Impact
Students confirmed that they are much more informed about a tax career, that the ‘live’ case helped them become work-ready and fostered their professional identity aiding their transition to the labour market.
Generative artificial intelligence (AI) is a topical issue. The importance of users being able to recognise the quality of outputs is crucial. Bearman et al. (2024) state that ‘university graduates should be able to effectively deploy the disciplinary knowledge gained within their degrees to distinguish trustworthy insights from the ‘hallucinatory’.’ Ballentine et. al (2024) suggest that generative AI provides an opportunity to move away from assessment that relies on rote learning to the use of critical assessment including authentic scenario-based examples. Such authentic assessment is regarded as an important factor in preparing students for future learning in work and life (Fawns et al., 2024).
As a result of the increased use of generative AI and the emphasis on the graduate competency goals set by QBS, it was identified that engagement with professional practice was crucial to effectively deploying an authentic scenario-based assessment incorporating generative AI.
Innovation in a taxation module
Professional services firms were engaged at key points in the module delivery. The continuous assessment was jointly drafted with a professional practitioner to ensure that it simulated a ‘live’ case in professional practice. The integration of multiple taxes, the use of ChatGPT including the assessment of its accuracy and the need for students to use excel and the Lexis online database were embedded.
Impact
Students confirmed that they are much more informed about a tax career, that the ‘live’ case helped them become work-ready and fostered their professional identity aiding their transition to the labour market.
| Original language | English |
|---|---|
| Publication status | Published - 23 May 2025 |
| Event | The British Accounting and Finance Association - Accounting Education Special Interest Group Conference - Dublin, Ireland Duration: 21 May 2025 → 23 May 2025 |
Conference
| Conference | The British Accounting and Finance Association - Accounting Education Special Interest Group Conference |
|---|---|
| Country/Territory | Ireland |
| City | Dublin |
| Period | 21/05/2025 → 23/05/2025 |
Bibliographical note
Reference listBallantine, J., Boyce, G and Stoner, G. 2024. ‘A critical review of AI in accounting education: Threat and opportunity’. Critical Perspectives on Accounting, Volume 99, 2024. Available from https://www.sciencedirect.com/science/article/pii/S1045235424000108.
Bearman, J., Dawson, P., Boud, D. and Ajjawi, R. (2024) ‘Developing evaluative judgement for a time of generative artificial intelligence’ Assessment & Evaluation in Higher Education, 49:6, 893-905. Available from https://doi.org/10.1080/02602938.2024.2335321.
Fawns, T., Bearman, M., Dawson, P., Nieminen, J., Ashford-Rowe, K., Willey, K., Jensen, L., Damşa, C. and Press, N. (2024) ‘Authentic assessment: from panacea to criticality’. Assessment & Evaluation in Higher Education. Available from https://doi.org/10.1080/02602938.2024.2404634