26th Australian Institute of Physics Congress and the Australian and New Zealand Conference on Optics and Photonics

Session

AIP PEG: AI in Physics Education

PEG

9 Dec 2026, 16:00

Belinda Hutchinson Building (The University of Sydney )

Conveners

AIP PEG: AI in Physics Education

• Anastasia Lonshakova (The University of Western Australia)

421. Towards evidence-based generative AI use in physics education

Anna Phillips (Monash University School of Physics and Astronomy)

09/12/2026, 16:00

AIP | Physics Education (PEG)

Invited talk

As generative AI tools disrupt education at all levels, physics educators must adapt to a new and rapidly changing landscape. I present a review of current educational practices and literature on the benefits and risks of generative AI use in student learning in physics, mathematics, and coding.

I focus on the impacts of cognitive offloading, the process by which people can reduce the...

194. Teaching students to use AI well

Paul Francis (The Australian National University)

09/12/2026, 16:30

AIP | Physics Education (PEG)

Contributed Oral

AI can be a fantastic aid to learning physics, but it is alas altogether too easy for students to use it to replace their learning, rather than assisting it. We present a series of experiments in trying to train and encourage students to use AI to enhance their learning, spread across several 1st and 2nd year physics and astrophysics classes.

Students are trained in prompting techniques and...

117. Systems and Subjectivity: The Role of Physics Education in Distinguishing Artificial Intelligence from Subjective Experience

Janudi Samarawickrama

09/12/2026, 16:45

AIP | Physics Education (PEG)

Contributed Oral

Physics education is, at its core, an education in systems. It trains students to model the world as structures governed by definite rules, and this systemic mindset is among the most powerful and transferable habits that physics instils. Artificial intelligence, by the OECD definition and in its computational foundations, is precisely such a system, built, trained, and operated through data...

523. Understanding the First-Year Tutor Experience: A Qualitative Review of Student Feedback in Physics

Smrithi Gireesh (University of Sydney)

09/12/2026, 17:00

AIP | Physics Education (PEG)

Contributed Oral

Student evaluations provide valuable insights into the teaching and learning experience that extend well beyond quantitative metrics. With approximately 800 students enrolled each semester in first-year physics units at the School of Physics, University of Sydney, maintaining a high-quality learning experience at scale is an ongoing priority. Within this context, tutors play a pivotal role....

763. PhysEdLLM: Building Interactive Physics Simulation for Education using Large Language Models

Aman Desai (University of Adelaide (AU))

09/12/2026, 17:15

AIP | Physics Education (PEG)

Contributed Oral

We present PhysEduLLM, an LLM agent pipeline that generates interactive web-based physics simulations for educational use. Agents in this package turn a plain-text user request into parameters, and render it using a shared HTML and JavaScript template, and check the result against a given topic's checklist, ensuring physics consistencies before adding quiz-style questions. The package consists...