AI in Education Podcast

Tina Austin joins Ray and Dan for a wide-ranging conversation about what AI adoption really looks like in US education beyond the hype, the headlines and the endless frameworks.
Tina is an educator, consultant, policy adviser and the founder of GAInable. She works with schools, colleges and faculty teams on responsible AI adoption. In this episode, she shares how her work evolved from teaching bioethics and AI ethics into supporting educators across the US as they grapple with policy, privacy, assessment, tools, and changing classroom practice.
The conversation explores the fragmented reality of AI in education, why many teachers are feeling "frameworked out", and why Tina believes the best place to start is not with the tool, but with the problem you are trying to solve.
We also dig into Tina's "UnBlooms" framework - a challenge to linear interpretations of Bloom's Taxonomy in the age of generative AI - and discuss critical thinking, student reflection, equity, privacy, and why educators should stay sceptical of easy answers.
A thoughtful episode on using AI well, asking better questions, and meeting learners where they are.
Here's all the links you need:
Tina's new venture, Gainable AI Gainable.ai 
The UnBlooms™ model: A Problem-Centered Framework for Learning Design in the AI Era
https://zenodo.org/records/17298679 
The UnBlooms™ Workbook: How to Design, Teach, and Assess Human Reasoning in the AI Era

Tina's Custom GPT for UnBloom: Unbloom-it


You can contact Tina on email at [email protected]

In this AI News episode, Dan and Ray explore the fast-moving reality of AI in the workplace - and why many of us might not be as prepared as we think.
They unpack a striking story of a KPMG partner fined for using AI to cheat on an AI ethics course, raising questions about assessment, responsibility, and what "cheating" even means in an AI-enabled world.
The conversation then shifts to a growing trend: organisations and universities rolling out AI tools like Copilot at scale, and what this means for equity, productivity, and expectations in the workplace.
Dan and Ray also dive into new research from Anthropic on the future of work, highlighting which roles are most exposed to AI disruption - and why knowledge work may change more than hands-on professions. They explore the idea that the real shift isn't job loss, but job transformation.
Finally, they tackle bold claims from industry leaders that office roles could be automated within 12–18 months, debating what's hype versus reality.
This episode challenges a simple narrative: AI isn't just replacing work - it's redefining what valuable work looks like.
Links to discussions in the podcast:
KPMG partner fined for using artificial intelligence to cheat in AI training test
https://www.theguardian.com/business/2026/feb/16/kpmg-partner-fined-artificial-intelligence-ai-training-test
Aston University is first Midlands University to provide all staff with Microsoft 365 Copilot and Copilot Chat for Students
https://www.aston.ac.uk/latest-news/aston-university-first-midlands-university-provide-all-staff-microsoft-365-copilot-and
NY Times: Who's a Better Writer: A.I. or Humans? Take Our Quiz.
https://www.nytimes.com/interactive/2026/03/09/business/ai-writing-quiz.html 
Anthropic and US Government
https://www.anthropic.com/news/statement-department-of-war
Anthropic future of labour report
https://www.anthropic.com/research/labor-market-impacts
AI Exposure of the Australian & US Job Market
AUS: https://0xtreme.github.io/aus-jobs/ 
US: https://joshkale.github.io/jobs/  
Anthropic Education Report - AI Fluency index
https://www.anthropic.com/research/AI-fluency-index
The end of office workers as we know it?
https://www.msn.com/en-gb/money/other/microsoft-ai-ceo-mustafa-suleyman-issues-18-month-warning-for-office-workers/ar-AA1WvXMi?ocid=entnewsntp&pc=U531&cvid=69957afbd4c747f08d77afaead77499c&ei=56

Professor Stephen Heppell joins Dan and Ray for a wide-ranging conversation about the future of schools, assessment, and learning in the age of AI.
Stephen reflects on more than four decades of innovation in education technology — from early experiments with AI and HyperCard through to today's generative AI systems. Drawing on work around the world, he shares stories from radical learning environments including beach schools, post-hurricane classrooms in the Cayman Islands, and experimental learning spaces designed with students themselves.
A central theme of the episode is the growing gap between how schools currently operate and the skills the modern world demands. Stephen argues that as AI makes knowledge abundant, the most valuable human capabilities will be creativity, ingenuity, collaboration, and ethical judgement - qualities that traditional assessment systems rarely measure well.
The discussion also explores how AI can support teachers rather than replace them, helping with differentiated learning activities, analysis of student understanding, and freeing teachers to focus on the human side of education.
Finally, Stephen challenges educators and policymakers to rethink learning spaces, assessment, and student agency - and to build education systems that prepare learners for a rapidly changing world.
If you want to read about more of Stephen's work, there's plenty more detail on Lindfield Learning Village and lots more on https://www.heppell.net/

In this news-packed episode, hosts Ray and Dan explore Purdue University's bold new requirement for all graduates to demonstrate AI competency; and the strategic partnerships between Harvey.ai (the specialised system for the legal profession) and universities in Sydney, Oxford and Chicago.
The conversation turns to the "first in the world" move by the University of Manchester to provide Microsoft 365 Copilot to 65,000 students and staff - paying homage to the legacy of Alan Turing.
A highlight of the episode is the deep dive into "vibe coding"— the phenomenon of non-programmers using AI to build applications through iterative prompting rather than manual syntax. They also tackle the "AI bubble," the rise of "work slop," and the surprising research showing that Boomers often have a more accurate understanding of how AI works than Millennials.
Links & Resources:
Purdue University adds 'AI working competency' graduation requirement
https://www.purdue.edu/newsroom/2025/Q4/purdue-unveils-comprehensive-ai-strategy-trustees-approve-ai-working-competency-graduation-requirement/ 
University Law Schools introduce AI partnerships
https://www.afr.com/companies/professional-services/sydney-and-uts-law-schools-bow-to-ai-wave-partner-with-harvey-20260119-p5nv49 
University of Manchester announces 'world first' AI rollout with Microsoft
https://www.manchester.ac.uk/about/news/world-first-ai-partnership-between-the-university-of-manchester-and-microsoft-announced/ 
"What we are doing about AI at UWA"
https://www.uwa.edu.au/news/article/2026/february/what-we-are-doing-about-ai-at-uwa 
High school students forced to fight false allegations of AI cheating
https://www.abc.net.au/news/2025-12-22/ai-detectors-incorrectly-brand-high-school-students-ai-cheats/106138394 
New Future of Work Report from Microsoft
https://www.microsoft.com/en-us/research/wp-content/uploads/2025/12/New-Future-Of-Work-Report-2025.pdf 
The Impact of AI on Work in Higher Education
https://www.educause.edu/research/2026/the-impact-of-ai-on-work-in-higher-education 
Americans Have Mixed Views of AI – and an Appetite for Regulation
https://www.searchlightinstitute.org/research/americans-have-mixed-views-of-ai-and-an-appetite-for-regulation/ 
And finally....
From the "Do you ever read T&C's" dept
https://www.linkedin.com/posts/matthewwemyss_i-logged-into-ai-studio-yesterday-and-i-ran-activity-7411400400177729536-hgPL

This week's episode dives into a wave of new research shaping how AI is actually being used in education.
We explore what works (and what doesn't) when it comes to AI-generated feedback, including why blended, "hybrid" feedback may be the most effective approach - and why more feedback doesn't always lead to better outcomes.
The conversation then turns to one of the most important emerging issues: bias in AI systems. From subtle differences in tone to stereotyping based on student characteristics, the research highlights why educators need to be cautious about the data they provide AI tools.
"If you use AI to write feedback, it does not treat every student the same way equally."
We also talk about the growing evidence around AI tutors - where they outperform humans, where they fall short, and what actually drives meaningful learning gains.
Along the way, we tackle major questions around detection, student use, teacher workload, and whether AI can ever replace human connection.
The big takeaway? AI is powerful. And how we design, guide, and use it in education matters more than ever.
Research Papers discussed this week
AI for Feedback
Directive, metacognitive, or a blend of both? A comparison of AI-generated feedback types on student engagement, confidence, and outcomes
https://doi.org/10.1016/j.caeai.2026.100553 
AI assistance in peer feedback provision: Pedagogically sound, but minimally adopted
https://www.sciencedirect.com/science/article/pii/S0360131526000291
Marked Pedagogies: Examining Linguistic Biases in Personalized Automated Writing Feedback
https://arxiv.org/abs/2603.12471


AI and Bias
The Life Cycle of Large Language Models: A Review of Biases in Education
https://bera-journals.onlinelibrary.wiley.com/doi/10.1111/bjet.13505 
AI Tutors
AI tutoring can safely and effectively support students: An exploratory RCT in UK classrooms
https://arxiv.org/abs/2512.23633v1
LearnMate: Enhancing Online Education with LLM-Powered Personalized Learning Plans and Support
https://dl.acm.org/doi/10.1145/3706599.3719857
Effective Personalized AI Tutors via LLM-Guided Reinforcement Learning
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6423358
Unifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI Tutors
https://arxiv.org/abs/2412.09416v1
AI Detection
Trusting AI to detect AI? A systematic evaluation of the reliability and robustness of current AIGC detection tools for student academic work (paywalled)
https://www.sciencedirect.com/science/article/abs/pii/S0360131526000540
Teacher Workload
Shiksha Copilot: Teacher-AI Collaboration for Curating and Customizing Lesson Plans in Low-Resource School
https://arxiv.org/pdf/2507.00456v3 
Student use
The Secret Life of Students project - WonkHE Feb/March 2026
https://wonkhe.com/wp-content/wonkhe-uploads/2026/03/Wonkhe_SLOS2026_Jim_slides.pdf
Is a random human peer better than a highly supportive chatbot in reducing loneliness over time?
https://www.sciencedirect.com/science/article/pii/S0022103126000417?dgcid=rss_sd_all