Authentic Assessment Through Professional Conversations: An AI friendly assessment method?


  • Daniel Cole



conversations, Authentic learning, Artificial Intelligence, quality, assessment and feedback


Professional Conversations were introduced as an assessment method for the PGCAP at De Montfort University in 2019, allowing students to prepare for the end point assessment of the L7 Academic Professional Apprenticeship (APA). This format evolved to be one of the key successes of the programme, with overwhelmingly positive feedback being received from External Examiners, End-Point Assessors and Students alike. This paper reflects on the steps taken to ensure that both students and assessors were fully prepared to engage in high quality conversations regarding their approach to teaching, learning and CPD. An overview of the approaches to teaching, learning and student support is provided, alongside recommendations on how to assure the quality of the experience and the overall fairness of the outcome awarded. The paper also considers how Professional Conversations could be used more frequently as an assessment method in Higher Education moving forward. The paper concludes with a projection of how assessed conversations could be used to maintain academic integrity in modern higher education (HE), whilst also highlighting key barriers that academics may experience, especially when faced with large student numbers and ever-increasing time constraints.


Bandura, A. (1977). Social Learning Theory. Prentice Hall.

Biggs, J. (2003). Teaching for Quality Learning at University. Open University Press.

Boud, D., & Falchikov, N. (2007). Rethinking Assessment in Higher Education: Learning for the Longer Term. Routledge.

Brand, H.S., & Schoonheim-Klein, M. (2009). Is the OSCE more stressful? Examination anxiety and its consequences in different assessment methods in dental education. European Journal of Dental Education, 13(3), 147-53.

Brown, G., & Knight, P. (1994). Assessing Learners in Higher Education. Routledge.

Dawson, P. (2022) “How to fix the fascinating, challenging, dangerous problem of cheating.” Australian Association for Research in Education.

Herrington, J., & Herrington, A. (2006). Authentic E-Learning in Higher Education: Design Principles for Authentic Learning Environments and Tasks. Routledge.

Kaplan, A., & Haenlein, M. (2019) Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretation, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15-25.

Kogan, J. R., Holmboe, E. S., & Hauer, K. E. (2011). Tools for Direct Observation and Assessment of Clinical Skills in Medical Education: A Systematic Review. Journal of the American Medical Association, 306(3), 309-321.

Merry, K.L., & Weldon, J. (2023) Unboxing the Block: Supporting the staff transition to Block teaching. Educational Developments, the magazine of SEDA. 24(3), 1-5

Pearce, J., & Chiavaroli, N. (2020). Prompting Candidates in Oral Assessment Contexts: A Taxonomy and Guiding Principles. Journal of Medical Education and Curricular Development, 7.

Waring, M., & Evans, C. Facilitating students’ development of assessment and feedback skills through critical engagement with generative artificial intelligence in 'forthcoming, 2024' in C. Evans and M. Waring, Research Handbook on Innovations in Assessment and Feedback in Higher Education: Implications for Teaching and Learning. Elgar Publishing.

Winstone, N.E., R.A. Nash, M.Parker, & J. Rowntree. (2017). Supporting Learners’ Agentic Engagement with Feedback: A Systematic Review and a Taxonomy of Recipience Processes. Educational Psychologist. 52(1), 17–37.