The Future of Education

What should education and assessment value when AI can produce a fluent answer?

How is AI shaping teaching and the future of the university? We examine what education should value when AI can produce a fluent answer, and how assessment can still show what a student understands.

Assessment and the purpose of university

Our manifesto for universities argues for education that rewards process and judgement, with room for students to try an approach and learn when it fails. It draws on an experimental AI-integrated unit at Macquarie University and proposes principles for universities to consider. Read the manifesto.

We also turn those questions into assessment practice. Our published guidance permits careful AI use while making students responsible for checking the work. A keynote develops the same approach in class: ask students to explain a prompt that worked or failed, then assess how they review and improve their process. Read the assessment guidance or view the keynote.

A finished answer reveals less about learning when a tool can produce it. Making students’ reasoning and revision visible can help educators see what students understand, while opening a wider question about what university education should protect and build.

Publications and materials

Ballsun-Stanton, B. (2025, September 25). How Teaching Must Become Process-Oriented instead of Knowledge-Oriented. https://doi.org/10.5281/ZENODO.17171573

Presentation

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Keynote for "eTeach-Jahrestagung” | 2025 Sep 25

Slides in German and English, plus  prompt logs of Claude use for development

Resources used:

https://osf.io/preprints/edarxiv/6mke5_v3

https://doi.org/10.1080/1360080X.2025.2509187

https://doi.org/10.1007/s44204-025-00247-1

https://zenodo.org/communities/iacap-aisb-25-teachingai/

https://osf.io/rd24y/

https://denubis.github.io/KI-Summercamp-2025/basic/

https://dataverse.ada.edu.au/dataset.xhtml?persistentId=doi:10.26193/CDCZA7

Ballsun-Stanton, B., & Khalid, M. (2025, June 16). The Emperor’s New Clothes: A Manifesto for Universities in an AI-Haunted World. https://doi.org/10.5281/ZENODO.15671962

Paper

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Universities face an existential crisis revealed, but not caused, by artificial intelligence. Using Lakatos' Philosophy of Science, we argue higher education has become a degenerating research programme, maintaining formal structures while abandoning educational substance. Drawing on evidence from an experimental AI-integrated unit at Macquarie University, we pose three interlocking questions: What constitutes content-increasing education when AI handles information transfer? How can universities reconnect education to meaningful world-making? What academic practices enable transformative rather than transactional learning? Student transformations documented in our unit suggest design principles for post-transactional universities that embrace productive failure, reward process mastery, and develop new capabilities beyond credentialism.

Head, A., & Ballsun-Stanton, B. (2024, April 4). Use of Generative Artificial Intelligence in Undergraduate Assessment. Macquarie University. https://doi.org/10.5281/ZENODO.10916388

Preprint

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This is a policy currently in use in an earlier form in the Faculty of Arts, Macquarie University, Sydney Australia. It is use-agnostic and sets parameters for risks, communication of risks, and possible benefits in a bid to both set guardrails and educate students. Some modification will be needed for use outside of Legal education. We are serious about the recommendation about models.

Here is the document in HTML form:

Use of Artificial Intelligence

The use of Artificial Intelligence is not prohibited. The use of Large Language Models (LLMs) such as OpenAI's ChatGPT GPT-4 (paid), Perplexity.ai (free/paid), Microsoft Copilot in creative mode (free), or Claude 3 Opus (paid) when working on this assessment is permitted. These tools can complement your efforts on assessments and can assist with planning, research, and editing, but they must be used intentionally and with utmost care. Intentional and careful use of these tools may assist the quality of your final submission, but poor or reckless use of the tools can quite easily negatively impact the quality of your submission. You are fully responsible for any issues or errors arising from their use. If you are considering actively engaging with LLMs to assist in completing this assessment, then please read the following very carefully.

Acknowledgement

It is essential to acknowledge any tool used, both the model used and the way that you used it. (See below for my acknowledgement.)

CRITICAL: Confabulations, hallucinations, and fictitious sources

It is your responsibility to use Generative AI tools ethically and appropriately. Any fictitious sources contained in your submitted paper will result in a failure of the assessment, regardless of whether they originated from your own research, Generative AI, or a random webpage. This is not an academic integrity issue, but a matter of ensuring the accuracy and reliability of your work.

Remember, LLMs always sound confident but are not always correct (and depending on how the LLM is used may be very wrong). Proper prompting is essential for improving the quality of the results (see below for resources on prompting).

Embedded models

Microsoft Word and Google Docs have built-in text autocomplete features powered by LLMs. Use this "autocomplete" feature at your own risk, as it may result in bland and generic writing.

Vague responses

Poor prompting may lead to American-centric or vague responses that do not address the specifics of Australian law. When using these models, it is your responsibility to thoroughly check all outputs to ensure they are relevant and accurate. Reliance on an LLM output without thorough oversight is strongly advised against.

Copyright concerns

As future lawyers, it is your responsibility to obey the law. Do not upload copyrighted material, including unit materials (slides, articles, question text) or anything with a clear copyright, to these international systems without an appropriate license (e.g., CC-BY). Always read and comply with the terms of use of any research services you use.

Appropriate and ethical use

Read the terms of service of the LLM tools you use. Some, like OpenAI (https://openai.com/policies/sharing-publication-policy), have specific acknowledgement requirements for your work.

While powerful, these tools may not always increase productivity or research speed (https://www.hbs.edu/faculty/Pages/item.aspx?num=64700). Use them judiciously.

A trap

Do not treat LLMs as search engines. Even those with web search capabilities (e.g., perplexity.ai, ChatGPT GPT+ subscription, Microsoft Copilot) may not search effectively. Ensure that all factual information you want the models to work with is well-contained within your prompts.

Recommendations

We strongly advise against using ChatGPT's free version, as it may lead to unsatisfactory results and is prone to confabulations. Use tools running GPT-4 or equivalent, such as Microsoft Copilot in creative mode (free with a throwaway account, not your MQ account). Avoid upsells from the LLMs and choose "creative mode" for GPT-4; "balanced mode" uses GPT 3.5.

Here are recommended sources to help you use these powerful but potentially dangerous tools:

A short bibliography on prompting for those who are interested.

https://www.oneusefulthing.org/p/a-guide-to-prompting-ai-for-what

https://www.oneusefulthing.org/p/captains-log-the-irreducible-weirdness

https://simonwillison.net/2023/Apr/2/calculator-for-words/

Acknowledgement

Claude 3 Opus was used to edit this text on AI usage to remove many of the Americanisms introduced by my colleague.