I’m joined today by Mike Perkins to talk about the AI Assessment Scale, following the publication of the latest version of the scale that appeared in the Journal of University Teaching and Learning Practice in September. The AI Assessment Scale has been used by more than 350 institutions globally, has been translated into 30 languages, and is recognised by regulators such as TEQSA (Tertiary Education Quality and Standards Agency) in Australia. Mike Perkins and co-authors Jasper Roe, Leon Furze and Jason MacVaugh have been recognised as guiding lights for educators around the world responding to the widespread availability of Gen AI tools. Mike and I talk about how the team’s thinking has changed on some of the topics related to AI and assessment, their responses to some of the critiques of the original scale, comparisons with other models of AI integration, the international response to the AIAS, and other topics. References Perkins, M., Roe, J., & Furze, L. (2025). Reimagining the Artificial Intelligence Assessment Scale (AIAS): A refined framework for educational assessment. Journal of University Teaching and Learning Practice, 22(7). https://doi.org/10.53761/rrm4y757 Perkins, M., Roe, J., & Furze, L. (2025). How (not) to use the AI Assessment Scale. Journal of Applied Learning and Teaching, 8(2). https://doi.org/10.37074/jalt.2025.8.2.15 Guest bio Assoc. Prof. Dr. Mike Perkins serves as Head of the Centre for Research & Innovation at British University Vietnam (BUV). With a PhD in Management from the University of York, his research journey has evolved from studying performance management in local policing to becoming a leading voice in the integration of Generative AI (GenAI) in higher education. Dr. Perkins is renowned for developing the AI Assessment Scale (AIAS), translated into 30 languages and implemented across more than 350 schools and universities worldwide. His work addresses the critical intersection of technology, academic integrity, and ethical implementation of AI in educational settings. He leads research in the equitable application of GenAI, and provides guidance to educators and policymakers responding to the challenges of the new GenAI landscape. Dr. Perkins' expertise has established him as a sought-after advisor to educational institutions globally, supporting them in ethically integrating Generative AI to enhance student learning while preserving academic integrity. Beyond his work with AI, Dr. Perkins has conducted significant research on broader academic integrity issues, including investigations into diploma mills and student behavior during the COVID-19 pandemic's shift to online learning. His expertise spans performance management, academic integrity, and the strategic integration of emerging technologies in educational settings. Check out the AI Assessment Scale website for the most up to date information and resources on https://aiassessmentscale.com/ Follow Mike on Linkedin: https://www.linkedin.com/in/mgperkins/ Further reading Corbin, T., Dawson, P. and Liu, D. (2025). Talk is cheap: why structural assessment changes are needed for a time of GenAI. Assessment & Evaluation in Higher Education, 1–11. Available at: https://doi.org/10.1080/02602938.2025.2503964 Newton, P. M. and Draper, M. J. (2025) ‘Widespread use of summative online unsupervised remote (SOUR) examinations in UK higher education: ethical and quality assurance implications’, Quality in Higher Education, 31(1), pp. 127–141. doi: https://doi.org/10.1080/13538322.2025.2521174 Perkins, M., Furze, L., Roe, J., & MacVaugh, J. (2024). The Artificial Intelligence Assessment Scale (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment. Journal of University Teaching and Learning Practice, 21(06), Article 06. https://doi.org/10.53761/q3azde36 Timecodes 00:00 Introduction 03:42 Mike’s background in AI and assessment 06:24 Links to EAP 08:12 Differences in the Australian and UK post COVID responses to assessment 12:03 How the thinking behind the new AIAS has changed 15:20 What are we learning with gen AI? 17:44 Examples of AI in teaching and assessment 21:00 Assessment for and of learning 26:57 AIAS and the two-lane approach 29:57 Discursive versus structural changes 36:00 Should training be mandatory? 38:52 Future directions 44:48 What makes a successful writing team?

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