AI in Education Podcast

This week, Ray and Dan end up discussing a fundamental question: what is education actually for in the age of AI?
They explore new EU AI Act transparency requirements and the emerging role of AI watermarking, including what this could mean for the often-unreliable world of AI detection.
The conversation then turns to assessment. With Australian policymakers questioning take-home assessment and universities rethinking assessment for an AI-enabled world, Ray and Dan discuss why the goal isn't simply to make assessment "AI-proof", but to ensure students are still developing knowledge, judgement, creativity and critical thinking.
They also examine major new research into young people's use of generative AI from the Barker Institute and University of Sydney. Across 271 peer-reviewed studies, the evidence suggests AI can improve students' immediate performance and engagement - but better performance doesn't necessarily mean better learning.
Finally, they explore "hybrid reading": how students are using AI to orient themselves, clarify difficult concepts, translate academic language and check their own understanding.
Mentioned in this episode:
Matthew Wemyss' guide to EU AI Act transparency requirements
Information on Claude's watermarking of AI text - and a geeky read about how it does it
New education plugins in ChatGPT Edu
Jason Lodge on AI and assessment
NSW's news on 'take home' assessments
South Australia's Royal Commission into AI
Kelly Ilich on teaching standards in the age of AI
Danny Liu & Adam Bridgeman's "What Should Education Look Like in the Age of AI?"
Barker Institute's research paper "Young People, Learning and Generative AI"
Research from Deakin University's CRADLE team on hybrid reading practices

The Hidden Gender Gap in AI Education, with Juliana Peloche
 
In this episode of the AI in Education Podcast, we welcome Juliana Peloche to explore one of the most important (and often overlooked) conversations in educational AI: the gender gap.
Juliana shares how a Year 5 student's curiosity about AI sparked her own research journey, leading to a PhD and, ultimately, the co-founding of Women in AI Australia. Together, we discuss why representation matters (see Will Artificial Intelligence Get in the Way of Achieving Gender Equality?), the barriers women continue to face in AI (see HBR's Women Are Avoiding AI. Will Their Careers Suffer? and Global Evidence on Gender Gaps and Generative AI Over Time) and what educators, institutions and industry can do to create more inclusive opportunities.
The conversation hears about new research into how female university students are using AI, revealing surprising findings around ethics, trust, academic integrity, and confidence with AI tools. We also explore AI bias, the importance of visible role models, and practical ways schools and universities can encourage more women to lead in the field.


Links and resources:
Women in AI Australia
Learn more about the Women in AI Australia upcoming events
Connect with Juliana Peloche on LinkedIn

Two Free AI Resources Every Teacher Should Download
Lee Barrett joins Ray to unpack the biggest AI in education news and research.
This week, while Dan enjoys the Pacific Northwest, Ray is joined by returning guest Lee Barrett (from CEnet) for a wide-ranging discussion on the latest AI in education news and research.
The episode explores why one of the world's leading law schools is restricting technology in first-year classes while embracing AI later in the course, what Anthropic's new Claude for Teachers initiative could mean for educators, and why headlines about AI "writing" university assignments deserve much closer scrutiny.
The conversation also dives into five new research papers covering AI-assisted teaching, student feedback, assessment reform, learning analytics, and how students are really using AI in higher education.
Along the way, Ray and Lee discuss why assessment - not AI detection - is becoming education's biggest challenge; why productive struggle still matters; and why good teaching remains at the heart of meaningful learning.
This week's free resources
Show Your Work: Assessment in the Age of AI – a practical collection of ideas for designing assessment in an AI-enabled world.
The Science of Learning and Generative AI: A Practical Guide for Secondary Teachers – a research-informed guide from La Trobe University that connects learning science with practical classroom use of AI.

News mentioned
Chicago Law School's first-year technology changes
Anthropic's Claude for Teachers
More than 50% of Australian university assignments used AI - and Turnitin's Learning Integrity Insights Report


AI in Education Research Reports
Generative AI can harm teaching
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7007339 


Artificial intelligence and feedback in university education: effectiveness and student perceptions
https://www.tandfonline.com/doi/full/10.1080/02602938.2026.2697962


Grading in an age of assessment reform: the elephant in the room
https://www.tandfonline.com/doi/full/10.1080/02602938.2026.2694451#d1e187


Interactive learning dashboards: rethinking learning visualisations as engagement tools
https://link.springer.com/article/10.1007/s10639-026-14082-1


Illuminating complex student realities of artificial intelligence through an entangled pedagogy framework
https://link.springer.com/article/10.1007/s10734-026-01730-1 
Just one of the papers from the excellent https://aiinhe.org/ project

How can schools and parents help young people navigate AI while supporting learning, wellbeing and critical thinking? In this episode, Dan and Ray are joined by digital wellbeing researcher Dr Jo Orlando to explore how AI is reshaping education and the lives of young people. They discuss AI literacy, digital wellbeing, equity, social media, and why understanding how students actually use technology is essential. Jo shares practical advice for educators and parents, arguing that the most important tool isn't another policy—it's better conversations. A thoughtful discussion on helping students use AI as a thinking partner, rather than letting AI do the thinking for them.
Jo's website is https://www.joanneorlando.com.au/ for more details on her, her book, and her professional work.
Jo's book, Generation Connected, is available on as both a printed and audiobook

Higher Marks, Lower Learning? AI's Favourite Magic Trick
This week, Ray and Dan unpack a bumper collection of AI in education news and research, all pointing to one critical question: Is AI helping students learn…or just helping them score higher?
The episode begins with a striking case from Brown University, where a take-home exam averaged 96%, only for the same cohort to average 48% in a supervised final. From there, Ray and Dan explore what the latest research says about AI-assisted assessment, automated marking, AI tutors, critical thinking, and the growing importance of student agency.
They also discuss:
New evidence on AI marking compared with human examiners
Research showing how guided AI tutoring can improve maths learning
Why critical thinking is the biggest predictor of successful AI use
The risks of "never-skilling" when students rely too heavily on AI
AI detectors: what they can (and can't) reliably tell us
New Australian data on AI's impact on employment
The latest Digital Education Council survey of university students
Online safety and the growing challenge of AI-assisted image abuse
As always, the episode is packed with practical insights, research summaries, and plenty of discussion about what all this means for educators, schools and universities.
Links - News
Voice got an upgrade
https://openai.com/index/introducing-gpt-live/
Inside Higher Ed article: Brown Professor Suspects Majority of His Class Used AI to Cheat
https://www.insidehighered.com/news/faculty/learning-assessment/2026/07/08/brown-professor-suspects-most-his-class-used-ai-cheat
Digital Education Council AI in Higher Education Global Survey
https://www.digitaleducationcouncil.com/resource-library-items/ai-in-higher-education-global-survey-2026
One in 25 teens affected by AI-assisted online abuse, study finds. Read Lee Barrett's opinion: https://www.linkedin.com/posts/lee-barrett-a7624923b_boys-major-victims-of-ai-assisted-online-share-7480417534723244033-OjWU/
AI and employment in Australia - report from Department of Education and Workplace Relations
https://www.dewr.gov.au/download/17666/ai-and-employment-australia/43205/ai-and-employment-australia/pdf
 
Links - Research
AI in University Assessment: Evaluating the Opportunities and Risks of Automated Marking
https://www.emotional-cognition.psychol.cam.ac.uk/sites/default/files/OpRaise%20Report_DIGITAL.pdf
LLM Performance on a Real, Double-Marked GCSE Benchmark
https://arxiv.org/abs/2606.24973
Teaching with Gemini: Measuring the impact of Guided Learning on student mathematics progress in Sierra Leone
https://deepmind.google/blog/measuring-the-impact-of-learning-with-ai-in-sierra-leone-and-beyond/
https://storage.googleapis.com/deepmind-media/LearnLM/learnLM_sierraleone_may26.pdf
Access is Not Enough: Human Support Improves Engagement with AI Tutoring
https://nssa.stanford.edu/studies/access-not-enough-human-support-improves-engagement-ai-tutoring
The Generative AI Learning Penalty: Evidence from Chinese Secondary Education
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6868618
The agency gap: perceived human AI agency, reflection and generative AI learning across UK and China based higher education contexts
https://www.tandfonline.com/doi/full/10.1080/03075079.2026.2686986
How Do Autonomy, Critical Thinking, and Artificial Intelligence Value Perception Affect University Student Self-regulated Learning?
https://link.springer.com/article/10.1007/s11528-026-01203-3
The cognitive impact of ChatGPT in higher education: A systematic review of critical and creative thinking outcomes
https://www.sciencedirect.com/science/article/pii/S2666920X26000330
AI-induced never-skilling in medical education
https://doi.org/10.1038/s41591-026-04438-y (Paywalled)
Who wrote this? Evaluating the reliability of AI detection tools in higher education
https://link.springer.com/article/10.1007/s40979-026-00226-w 
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