The AI Assessment Scale (AIAS) in action: A pilot implementation of GenAI-supported assessment

Authors

DOI:

https://doi.org/10.14742/ajet.9434

Keywords:

generative artificial intelligence (GenAI), educational assessment, academic integrity, higher education, Artificial Intelligence Assessment Scale, higher education policy

Abstract

The rapid adoption of generative artificial intelligence (GenAI) technologies in higher education has raised concerns about academic integrity, assessment practices and student learning. Banning or blocking GenAI tools has proven ineffective, and punitive approaches ignore the potential benefits of these technologies. As a result, assessment reform has become a pressing topic in the GenAI era. This paper presents the findings of a pilot study conducted at British University Vietnam exploring the implementation of the Artificial Intelligence Assessment Scale (AIAS), a flexible framework for incorporating GenAI into educational assessments. The AIAS consists of five levels, ranging from “no AI” to “full AI,” enabling educators to design assessments that focus on areas requiring human input and critical thinking. The pilot study results indicate a significant reduction in academic misconduct cases related to GenAI and enhanced student engagement with GenAI technology. The AIAS facilitated a shift in pedagogical practices, with faculty members incorporating GenAI tools into their modules and students producing innovative multimodal submissions. The findings suggest that the AIAS can support the effective integration of GenAI in higher education, promoting academic integrity while leveraging technology’s potential to enhance learning experiences.

 

Implications for practice or policy:

  • Higher education institutions should adopt flexible frameworks like the AIAS to guide ethical integration of GenAI into assessment practices.
  • Educators should design assessments that leverage GenAI capabilities, while supporting critical thinking and human input.
  • Institutional policies related to GenAI should be developed in consultation with stakeholders and regularly updated to keep pace with technological advancements.
  • Policymakers should prioritise research funding into the impacts of GenAI on higher education to inform evidence-based practices.

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Author Biographies

Leon Furze, Deakin University

Leon Furze is a Deakin University PhD Candidate studying the implications of Generative Artificial Intelligence in education. His academic research is focused on how teachers of writing perceive and engage with multimodal GenAI technologies, and on how teaching and assesment methods might be impacted by the technology. Leon is also a consultant and author and works with schools, universities, and organisations on the ethical and practical appications of GenAI. His most recent book is 'Practical AI Strategies', which details the complexities of aspects of GenAI such as bias and intellectual property, and offers advice for educators seeking to use the technology in their day-to-day work.

Dr. Mike Perkins, British University Vietnam

Dr. Mike Perkins is the Head of the Centre for Research & Innovation and a Senior Lecturer in the School of Business at the British University Vietnam, Vietnam.. His current research focuses on performance management, academic integrity, and the impact of Generative AI (GenAI) technologies in academia, particularly concerning HEI policy responses to these advancements. His work on GenAI focuses on the intersection between technology, education, and academic integrity: exploring the efficacy of AI text detectors; media attitudes towards GenAI tools; how AI can be ethically introduced into assessments; policy approaches towards GenAI from both universities and academic publishers, and how these tools can be used in academic research. He is the university lead for the integration of GenAI policies into BUV and has provided training and guidance to Vietnamese educators and policy makers on this topic.

Dr. Jasper Roe, James Cook University Singapore

Jasper Roe is the Head of Department for the Language School at James Cook University Singapore, and a lecturer in sociology and cultural anthropology. Jasper holds a PhD in Social Sciences from University of Valencia and certificates in pedagogy and teaching from the University of London. Jasper’s broad research profile encompasses over 20 peer-reviewed publications in field-leading journals. As a sociolinguist first and foremost, Jasper’s research in the education space has focused on tools used for automated paraphrasing (prior to the advent of GenAI), big-data approaches to linguistic analysis of text, and the investigation of public discourse using microsociology methods. Jasper also holds a keen interest in understanding student and educator perceptions, attitudes, and sentiments towards developments in technology, and his research has now shifted in focus to exploring the ‘human’ factors in the GenAI era of higher education, including perceptions of accuracy, equality, and integrity .

Assoc. Professor Jason MacVaugh, British University Vietnam

Dr Jason MacVaugh is an active researcher and scholar, with publications in several fields including Higher Education Pedagogy and Practice. Two key research themes include academic skills development, and teaching sustainability in the context of Business and Management degree programmes. He is also a holder of an individual National Teaching Fellowship (NTF) award from the UK's Higher Education Academy (now Advance HE). He is currently Dean (Higher Education) at British University Vietnam, Hanoi. 

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Published

2024-10-16

How to Cite

Furze, L., Perkins, M., Roe, J., & MacVaugh, J. (2024). The AI Assessment Scale (AIAS) in action: A pilot implementation of GenAI-supported assessment. Australasian Journal of Educational Technology. https://doi.org/10.14742/ajet.9434

Issue

Early Release Articles

Section

Special Issue 2024 - Advancements in Technology-Enhanced Assessment in Higher Education

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Copyright (c) 2024 Leon Furze, Dr. Mike Perkins, Dr. Jasper Roe, Assoc. Professor Jason MacVaugh

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