Making Human Learning Visible in a World of Invisible Generative AI

An International Perspective

Abstract

The growth of Generative Artificial Intelligence (GenAI) in Higher Education (HE) challenges us to think differently and creatively about learning and assessment in order to prepare graduates for their futures (Dawson, 2023) This presentation will argue that the very strength of GenAI is also its Achilles’ heel. Anyone can access, garner and generate data rapidly, but human beings have never had a greater need for scrutiny and evaluation of this output.  Our graduates will need to have a transparent understanding of how they are learning in terms of the critical choices they make, the information or knowledge they engage with, and where machine learning ends and theirs begins (Okolie et al, 2022). The future of assessment in HE must go beyond simply measuring knowledge acquisition and instead focus on capturing and evidencing students’ capacity for critical thinking.

We will highlight some preliminary findings and early impacts of work underway at the University of Bath (UK) and University of Stellenbosch (South Africa), who are working collaboratively to ensure students develop holistically, excel in critical thinking, and gain the confidence and skills to use GenAI effectively to advance their ideas and learning (Osborne, 2024).

This will be structured in three parts:

Part one (Reviewing): We will outline work during academic year 23/24 by academic staff to review all their assessments against a three-fold categorisation model of permitted GenAI usage. From September 2024, all assessments clearly signal to students the extent to which GenAI is permitted in each assignment.

Part two (Guidance): We will showcase resources that support staff to rethink assessment design that embeds GenAI in ways that are authentic, valid and robust (Upsher et al, 2024). We will also present resources that support students to consider how they might use GenAI ethically, and to develop their AI literacy skills and critical thinking.

Part three (Examples): We will present initial findings from an internal project that is engaging with national and international employers, in-house world-leading AI researchers and our own students that highlight creative approaches to harnessing GenAI as a tool to reinforce and support (rather than replace) human learning.

We conclude by suggesting that HE has always promoted critical thinking and the rigorous investigation and examination of the production of knowledge. We need graduates who can critically engage with their learning, and assessments that capture and evidence this. The only way to do this effectively is to put people at the start, middle and end of our assessment journey.