Courses & Professional Learning

Learn how to use generative AI in your teaching or research. Our courses give you practice with prompts and help you check what the model produces.

Learn how to use generative AI in your teaching or research. Our courses give you practice with prompts and help you check what the model produces.

Courses

New to generative AI? Start with Generative AI for Educators. You can learn at your own pace, starting with no prior AI experience. Practise prompting and checking output as you work on lesson planning and assessment design.

For more practice with source documents, explore the 2025 AI Summer Camp materials. They work through prompting and verification, then move into model differences and research workflows.

Workshops

Our workshop materials introduce language models and develop practical prompting through examples. Contact Brian and Jodie to discuss an AI workshop or professional learning for your school or organisation.

Ballsun-Stanton, B. (2023, June 6). Large Language Models Workshop. OSF. https://doi.org/10.17605/OSF.IO/RD24Y
Read abstract

This two-hour workshop provides a comprehensive introduction to the world of Large Language Models (LLMs), focusing on the recent advancements in Generative AI. Participants will gain insights into the development and functionality of prominent LLMs such as Bing Chat and ChatGPT. The workshop will delve into the concept of LLMs as "calculators for words," highlighting their potential to revolutionize ways of working and learning.

The session will explore the principles of Prompt Engineering and Transactional Prompting, demonstrating how consistent prompts can yield reliable and reproducible results. Participants will also learn about the practical applications of LLMs, including editing and proofreading papers, generating technical documentation, recipe ideation, and more.

The workshop emphasizes the importance of understanding the terms of use and the responsibilities that come with using these powerful AI tools. By the end of the session, participants will be equipped with the knowledge and skills to effectively use LLMs in various contexts, guided by the mantra that a LLM is "Always confident and usually correct."

A recording of one workshop is available on Youtube: https://www.youtube.com/watch?v=c3_P7fVjiK8

Talks & Lectures

Explore what AI changes about teaching and assessment, or how researchers can check and document its use.

Ballsun-Stanton, B. (2026, August 4). AI Multiplies Judgement: Using AI ethically and well in research practice. https://doi.org/10.5281/ZENODO.21781864

Presentation

Read abstract

AI multiplies a researcher's judgement without caring about the sign, so the discipline built around the model matters more than the model. These are the slides from a one-hour lecture to the South Australian Research and Development Institute on using generative AI well in research practice. It opens on workslop, Niederhoffer and colleagues' term for AI output that looks polished while lacking the substance to advance the task (Harvard Business Review, 2025), and asks why capable people send it, since the reason they give is being stretched too thin. From there it sets out the prompting mechanisms that make a model interrogate your thinking rather than flatter it, and closes the first half on a live test of Macquarie's enterprise Copilot, which critiqued a bounded document competently and bluffed on an unbounded question whose sources it never looked at.

The second half works through Macquarie University's 2023 Guidance Note on generative AI in research and the 2025 disclosure and documentation Checklist, covering what each was written to protect, how disclosure scales from a footnote to an appendix, and why AI use is acknowledged rather than cited, since a model cannot be fired and so cannot take the blame. A registered report written under both supplies the worked example, with a use-of-AI declaration spanning roughly 120 sessions of drafting, simulation coding, and citation checking, and with the survey responses sealed from the models on the same terms as from the authors. The lecture ends on what makes the practice ordinary in a team, which is annotated conversations, shared prompts, and leaders going first.

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

Presentation

Read abstract

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. (2025, February 18). Research Use of LLMs: Beyond the chatbot. https://doi.org/10.5281/ZENODO.14885316

Presentation

Read abstract

Slides for the Research Data Alliance event:

Title: AI in Action: How Researchers Leverage AI (Asia/Oceania Friendly Time)

https://www.rd-alliance.org/event/ai-in-action-how-researchers-leverage-ai-europe-americas-friendly-time-2/