In this episode, we discuss the implications of generative AI on assessment, and on learning and teaching more broadly. This was a wide-ranging conversation that explored some of the detail around how language models work, it’s inability to compare responses to valid models of the world, practical uses for AI in teaching, learning, and assessment, and the risks of having AI being trained on data generated by AI.
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In this episode we talked about whether assessments and teacher-student relationship are even necessary (turns out that they are), whether teaching should be fun (as usual, it depends), whether spending less time on social media is necessary (possibly, but maybe it’s just that our self-control is lacking), and what our best teaching moments in 2018 were.
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In this episode, we had a relatively free-flowing conversation on the issues of classroom-based assessment. We wanted to get into the specifics of the essays, MCQ tests, reflections and other theory-type papers that students write as part of their curricular work. Of course, we recognise that there is no real distinction between “university” and “clinical” assessment in practice but we wanted to specifically discuss the kinds of assessment tasks that lecturers typically set for students in the classroom.
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In this episode, David Nicholls from the Auckland University of Technology talks about their (relatively) new clinical practice assessment form, as well as the process of development and implementation. During the conversation, we move from the instrumental mechanics of how the form works to discussing how the deeper aspects of practice are informed by the social norms of the profession, and how these subtly influence the choices we make about clinical assessment.
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