AI in Education Podcast

AI in Universities: Why Connection, Not Content, is Now King
This was an exciting episode, because we recorded it on campus at the world's newest university - Adelaide University. It officially started on-campus delivery this week, as it finally opened the doors after merging the University of Adelaide and the University of South Australia. Amid the buzz of students arriving for week 1, Eddie Major and I found some time to sit down and talk about how AI is impacting universities. Eddie is the university's AI Learning and Teaching Coordinator and you may not be surprised to learn that we discussed the AI myths of higher education and what being an "AI-first university" means. 
Eddie debunks the "AI brain rot" myth, explaining that while the technology is disruptive, it is not the end of the university. Instead, we are moving from an era where "Content is King" to one where "Connection is King." We explore:
Upstream AI Use: How students are using tools like NotebookLM to synthesise information before they even start an assignment.
The Soft Skills Surge: Why communication and critical thinking are now more valuable than hard technical skills.
The AI-First University: What it truly means to embed AI literacy across a global curriculum.
References:
We discussed the research from Hiromu Yakura at the Max Planck Institute about the way that ChatGPT was influencing speech. The paper, called "Empirical evidence of Large Language Model's influence on human spoken communication" is available at this link: https://arxiv.org/abs/2409.01754

Research Update: 8 papers on AI in Education you need to know for 2026
 
In this episode, Ray and Dan provide a rapid-fire rundown of the most significant research papers hitting the AI in Education space so far in 2026. After a series of news-heavy episodes, the hosts catch up on the data behind synthetic avatars, grading accuracy, and the psychological biases we hold against AI.
 
Key highlights include:
 
Synthetic Lecturers: Exploring stakeholder perspectives on digital twins and the emotional reaction to the term Deepfake in academia.
 
The Grading Gap: Why ChatGPT tends to be more sycophantic and generous with weak work compared to human instructors.
 
The Disclosure Penalty: New findings from 16 experiments showing why humans devalue creative writing the moment they know AI is involved.
 
Prompting Hacks: The "Groundhog Day" method 😂 Why simply repeating your prompt twice can boost accuracy across 70 different AI systems.
 
Tools for Researchers: Insights into Jasper Roe's research checklist and the "Paper Banana" tool for automating scientific diagrams.
 
Links to all the research papers discussed 
Can synthetic avatars replace lecturers? An exploratory international study of higher education stakeholder perceptions|
https://link.springer.com/article/10.1186/s41239-025-00568-4 


Who grades best? Comparing ChatGPT, peer, and instructor evaluations across varying levels of student project quality
https://www.tandfonline.com/doi/full/10.1080/02602938.2025.2588682?src= 


The Artificial Intelligence Disclosure Penalty: Humans Persistently Devalue AI-Generated Creative Writing
https://doi.org/10.1037/xge0001889 
The older "Transparency Dilemma" paper referenced too:
https://www.sciencedirect.com/science/article/pii/S0749597825000172 


Asking generative artificial intelligence the right questions improves writing performance
https://www.sciencedirect.com/science/article/pii/S2666920X25000141?via%3Dihub 


When AI only asks: how question-driven dialogue shapes prewriting in the classroom
https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2026.1740044/full 


Prompt Repetition Improves Non-Reasoning LLMs
https://arxiv.org/html/2512.14982v1 


How to Use Generative AI in Educational Research
https://www.cambridge.org/core/elements/how-to-use-generative-ai-in-educational-research/916142E735B678F86A59240BFE651F5C  


PaperBanana: Automating Academic Illustration for AI Scientists
https://dwzhu-pku.github.io/PaperBanana/
https://arxiv.org/abs/2601.23265

Is AI an "efficiency engine" or a "cognitive crutch"? In this episode, Dan and Ray explore the OECD's latest warnings regarding "metacognitive laziness" - the risk of students offloading the thinking process entirely to generative tools. As the OECD Digital Education Outlook 2026 suggests, without pedagogical guardrails, we may be sacrificing long-term learning for short-term performance.
 
The discussion shifts to the UK's aggressive new response: the Department of Education's Safety Standards. These rules explicitly ban "sycophantic" or flattering AI designs, stripping away avatars and "personhood" to ensure AI remains a tool rather than a digital companion.
We discuss a NY Times article about AI in schools too, and the global experiments.
We also dive into Deakin University's multidisciplinary inquiry, which provides six essential curriculum recommendations for a world of ubiquitous AI. Finally, we highlight the release of Leon Furze's Teaching AI Ethics, a vital new (and free) resource for teachers navigating these complex waters.
Key References:
OECD: Digital Education Outlook 2026
UK DfE: Generative AI Product Safety Standards for Education (Jan 2026)
UK DfE: Commitment to AI Tutoring for disadvantaged children
NY Times: As Schools Embrace A.I. Tools, Sceptics Raise Concerns
Deakin University's FutureFocus GenAI program
Free E-Book: Teaching AI Ethics by Leon Furze (teachingaiethics.com)

In this special "flipped" episode, the tables are turned on your usual hosts, Dan Bowen and Ray Fleming. Interviewed by Dr. Michael Hallissy from (and for) the teachnet Ireland podcast, Dan and Ray step into the guest seats to share the "AI in Education" podcast origin story - from its 2019 "skunkworks" beginnings at Microsoft to its current status as an independent voice in the global edtech conversation.
The trio dives deep into how the podcast evolved through the 2022 Generative AI explosion, moving from technical "hoodie" discussions about algorithms to essential human skills like empathy and questioning. They reflect on impactful moments, including the complexities of indigenous data rights and why "AI detectors" are a failing tool for schools.
Beyond the backstory, Dan and Ray discuss the widening AI equity gap and their vision for 2026: a focus on "the doers"—the teachers implementing AI in the classroom today. Whether you're a long-time listener or new to the show, this episode offers a rare, personal look at the mission behind the mics.
We think this episode might be especially interesting to all the new listeners who have joined us over the last 6 months, who might have some questions about where and when the podcast started, and Ray and Dan's background! We want to especially thank Michael for asking us great questions, and Pat Brennan for being the technical & scheduling mastermind to make it happen.
Links & References
TeachNet Ireland Podcast: https://teachnet.ie/category/podcasts/
Apple: https://podcasts.apple.com/us/podcast/teachnet-podcasts/id1650615051 
Spotify: https://open.spotify.com/show/4hiz0yCcT7D5qs8J85Fl5K 
Research Paper discussed: "Heads I Win, Tails You Lose"

Welcome to our first episode of 2026. In this heavy-hitting season opener, hosts Dan and Ray are joined by Dr. Mark Bassett, Academic Lead for AI at Charles Sturt University and a "superhero" of AI activism. Mark's an ally in our long standing mantra on the podcast, as we know you've got tired of hearing just Dan and Ray say "AI detectors don't work".
Dr. Bassett breaks down his landmark paper, "Heads We Win, Tails You Lose: AI Detectors in Education" which we describe (hopefully) as the final 'silver nail in the coffin' for detection software. We move past the surface-level "they don't work" argument and dive into the legal, ethical, and systemic risks universities face by relying on "black box" algorithms. Mark compares current AI detection to using a deck of tarot cards to determine a student's future - arguing that these tools have no place in a fair academic integrity process.
We also explore the S.E.C.U.R.E. framework, a tool-agnostic approach to integrating AI into education safely. If you're an educator, student, or leader wondering how to move from suspicion to capability-building, this is the blueprint you've been waiting for.
Links 
The Research Paper: Heads We Win, Tails You Lose: AI Detectors in Education

The Framework: The SECURE Framework for AI Integration

Find Mark Bassett online via his website and LinkedIn

Referenced Study: University of Reading's "Turing Test" paper on AI in Exams