Join us to find out about evaluative judgement, AI, and authentic assessment

Wednesday 29 May at 2pm


CRADLE Seminar Series 2024: Seminar #4

In this seminar Professor Margaret Bearman and Dr Joanna Tai explore the impacts of current developments in AI and assessment practices, and its relationship to evaluative judgement and authentic assessment.

  • When: Wednesday 29 May 2024
  • Time: 2pm to 3.30pm (AEST)
  • Where: Deakin Downtown or online
  • Cost: This is a free event

How assessment at university prepares students for the world beyond graduation has been a focus of higher education research for many years, but recent developments such as generative artificial intelligence have shifted these concerns front and centre. This seminar explores two approaches to assessment that emphasise its relevance in a digital world.

We argue that evaluative judgement, the capability to judge the quality of work of self and others, becomes crucial in a time where AI outputs will be commonplace. Assessment practices must therefore support students to develop evaluative judgement in relationship to genAI.

We then to turn to explore authentic assessment – regarded as a panacea to many dilemmas including those relating to AI. However, mimicking existing work and the ‘real’ world becomes an insufficient frame in rapidly developing contexts. Broadening perspectives on authenticity and operationalising it through design practices offer ways forward for assessment to meet current and future needs.

Join us for this compelling and topical presentation at Deakin Downtown or online.


About Margaret Bearman

Professor Margaret Bearman is Professor of Research at CRADLE and her interests span higher and professional education. Margaret is known for her work in assessment design, feedback, education in a digital world, and most recently, artificial intelligence.

About Joanna Tai

Dr Joanna Tai is a Senior Research Fellow at CRADLE. Jo researches student perspectives on learning and assessment from university to the workplace, peer-assisted learning, feedback, assessment literacy, developing capacity for evaluative judgement and research synthesis.








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