AI for Educators

Are screen time bans protecting children, or taking away tools some need to learn? Discover the accessibility blind spot in the screen time debate and what it means for parents navigating AI in education.

Paddy McGrath, author of The AI Equity Paradox, joins Dan Fitzpatrick to explore how technology can help children communicate, build confidence and express ideas that might otherwise stay hidden.

The conversation begins with a girl who couldn’t speak aloud. An iPad helped her deliver a speech about owls and win a prize. The technology hadn’t made her more intelligent. It had given her a way to show what she already knew.

That story raises a difficult question: when we remove screens from classrooms, whose opportunities do we remove with them?

As parents, we want our children to spend less time staring at screens. We also want them to grow up capable, creative and prepared for a world shaped by artificial intelligence. Paddy and Dan explore how to navigate those decisions, with practical examples from schools and their own families.

IN THIS EPISODE

■ The screen time blind spot: Why blanket restrictions can overlook children who rely on assistive technology to learn and communicate.

■ “Necessary for some, useful for all”: How captions, dictation and other accessibility tools can benefit a much wider range of learners.

■ AI and homework: How to recognize when AI is supporting your child’s thinking and when it is doing the thinking for them.

■ The smartphone dilemma: Navigating friendships, online risks, parental controls and boundaries at home.

■ Children’s creativity: How AI can help bring a child’s original ideas to life, including Dan’s experience turning his son’s drawing into an animated creature.

■ The AI equity paradox: Why two schools with the same access to AI can offer their students very different opportunities.

■ Beyond test scores: Paddy’s argument for paying closer attention to confidence, independence and the barriers a tool helps remove.

■ When your school bans AI: How parents can model responsible use at home and share useful examples with teachers.

If you’re a parent, teacher or school leader trying to make sense of screen time, AI literacy and inclusive education, this conversation offers questions you can take into your next discussion at home or school.

What has technology helped your child do that they previously struggled with? Share your experience in the comments.

Find us at https://theaieducator.io

PADDY MCGRATH

The AI Equity Paradox

https://amzn.eu/d/0bcVoXPA

LinkedIn

https://www.linkedin.com/in/pmcgrathedu/

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OpenAI's always-on AI agents can now work around the clock. Here's what school leaders need to decide before they arrive in your district.

This week's AI in education news: ChatGPT's new "dots" agents, the OpenAI model pulled over safety concerns, Meta's approval-first agent for small businesses, the America.gov AI assistant, the executive order directing federal agencies to say "Super Intelligence", Anthropic's leaked IPO prospectus, and Pope Leo XIV on AI risk. Each story comes with a practical action for principals, teachers and district leaders.

Three actions for this week: build an agent register with an answer, draft, act rule, decide what student data never goes into shared AI workspaces, and put your AI vendors through a short risk and contract check.

More at theaieducator.io

The UN launched a child-protection AI coalition this week, while Stanford's review shows schools have almost no US classroom evidence to go on.

This week's episode covers the UN coalition and the White House access initiative, what NPR and Stanford found about the evidence base for AI in K-12, MIT's "illusion of learning" warning, England's Public First report on young people and AI, and what Massachusetts districts and the Microsoft/AFT privacy standard mean for your school's policies and contracts.

What should schools expect from the companies bringing AI into their classrooms?

Microsoft President Brad Smith joins Dan Fitzpatrick to discuss the new AI Safety and Privacy Standard agreed with the American Federation of Teachers and its New York City affiliate, the UFT.

Their conversation covers enforceable protections, school AI bans, teacher control, independent schools and whether the agreement could extend beyond the United States. Brad also addresses whether stronger safeguards could slow innovation.

Dan then examines the latest PISA findings, the evidence behind Utah’s reported critical thinking gains, AI in special education advocacy and OpenAI’s Learning Lab. The episode closes with three practical actions to help schools check both the protections around their tools and what students are actually learning.

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Follow the podcast for your weekly roundup of AI news and research in education.

The two biggest school districts in America pulled students back from AI this week. In the same 72 hours, the AI labs handed teachers everything for free. Dan walks through the five stories that matter and what each one means for your school on Monday.

NYC's one-year moratorium through eighth grade and the carve-outs nobody reported. LAUSD's district-wide restriction. The Royal Society finding that only 14% of teachers are confident with AI, with principals scoring lower than the teachers they lead. IBM's survey showing 77% of parents want input while 20% understand what's happening. OpenAI's 16-state privacy agreement, and why that matters more than the free access. And the Stanford review and Tennessee trial on what AI tutoring actually does.

Plus three things to do this week: separate your staff and student policies, teach the thing before you police it, and redesign one task.

The Educators' AI Guide 2027: theeducatorsaiguide.com

Back to School AI Summit, 8-9 September: summit.aieducator.tools

You can also watch on YouTube at https://www.youtube.com/@IamTheAIEducator

Our new book is out, so this episode is me walking through what's in it and why we made it.

The Educators' AI Guide 2027 runs to 30 chapters from 28 educators across the world, edited with Heather Brown. I talk through the five issues I set out in the introduction: why the chatbot era is already old news, why we have to start designing for when AI enters the learning rather than whether it does, why assessment has run out of road, what serious AI governance looks like now, and what happens when teachers start building their own software.

Along the way: Larisa Black's blunt test for any assessment, Samantha Armstrong on the difference between a shortcut and a tool, a preschool teacher in Türkiye who got 21 hours a month of documentation down to 90 minutes, Heather's chapter on AI companions, and Stuti Mehta's case for going haule haule.

Get the book at theeducatorsaiguide.com

Women gained seven grade points with Mainstay, making chatbot student performance impossible to ignore in AI college courses.

In this episode:

• Women in an undergraduate Microeconomics course saw their final grades increase by seven percentage points due to course-specific chatbot messages, demonstrating how AI improved grades.
• The Mainstay chatbot improved chatbot student performance by providing timely administrative nudges and support links, rather than generating academic content.
• Research at Georgia State University showed that chatbot student engagement was most effective for the middle 80 percent of students, offering vital scaffolding without necessarily building transferable study habits.
• Implementing AI in higher ed for course support requires significant human design, oversight, and existing infrastructure for it to be effective, as evidenced by the NBER working paper.
• To successfully adopt AI college courses, educators should first audit specific student friction points and measure real outcomes and staff workload, rather than focusing solely on claims of AI improved grades.

Chapters:

• 00:00 — Cold open & welcome
• 00:30 — Women gained seven points with chatbot student performance
• 01:00 — Mainstay chatbot: Nudging, not generating
• 01:45 — The invisible administration and chatbot student engagement
• 02:45 — Strongest effects for the middle 80 percent
• 03:45 — Gender effects and the Microeconomics course
• 04:30 — Performance vs. capability: No transfer of skills
• 05:30 — Implementation details for successful AI college courses
• 06:15 — Research credibility and limitations of the NBER paper
• 07:00 — Advice for leaders: Audit the problem first

How can teachers use AI marking safely?
The study suggests AI is best used for administrative nudges like reminders and connecting students to resources, rather than for academic decision-making or grading content directly.

What specific benefits did the Mainstay chatbot provide in AI college courses?
The Mainstay chatbot improved chatbot student performance by sending personalized text messages for deadlines, missing work alerts, encouragement, and links to tutoring, leading to higher grades and engagement, particularly for women.

Did AI improved grades for all students?
While students assigned to the chatbot were generally more likely to earn an A or B, the most significant gain was observed in women in the Microeconomics course, who earned grades seven points higher; men showed no comparable effect in this study.

Featuring: Dan Fitzpatrick, NBER, Georgia State University, Mainstay, Registry of Efficacy and Effectiveness Studies, National Institute for Student Success, Katharine E. Meyer, Lindsay C. Page, Catherine Mata.

Follow AI in Education with Dan Fitzpatrick for more on AI in education.

Randi Weingarten AI policy pairs an elementary ban with training 100,000 teachers as Los Angeles Unified School District cuts screens.

In this episode:

• Randi Weingarten, president of the American Federation of Teachers, proposes banning student-facing AI in elementary schools to protect young children's foundational thinking skills.
• The American Federation of Teachers plans to train approximately 100,000 teachers in AI this year through the National Academy for AI Instruction, prioritizing adult readiness.
• The episode highlights a critical distinction: AI in elementary schools should be carefully considered, distinguishing between tools that offload cognition and those that remove barriers for students.
• Developing AI skills for students means fostering critical thinking, context evaluation, and fact-checking, rather than just showing them how to type prompts.
• Effective AI in education policy needs to move beyond blanket bans, focusing instead on developmentally informed, tightly controlled applications and teacher involvement from the outset.

Chapters:

• 00:00 — Cold open & welcome
• 00:15 — Randi Weingarten AI policy: Ban for young, train for adults
• 00:45 — The concern: AI and cognitive debt in elementary schools
• 01:15 — Defining 'student-facing AI' and policy nuances
• 01:45 — Beyond bans: AI for accessibility vs. offloading cognition
• 02:15 — Essential AI skills for students in secondary education
• 02:45 — Teacher training as a key part of AI in education policy
• 03:15 — Unions' role in ethical AI deployment and professional development
• 03:45 — Balancing protection and progress in AI policy
• 04:00 — Conclusion: Protected thinking vs. challenged thinking with AI

What is Randi Weingarten's stance on AI in elementary schools?
Randi Weingarten advocates for banning student-facing AI tools in elementary schools to prevent children from offloading foundational thinking skills they need to develop.

How is the American Federation of Teachers addressing AI skills for teachers?
The American Federation of Teachers, led by Randi Weingarten, aims to train approximately 100,000 teachers this year through the National Academy for AI Instruction, using a peer-led model.

What challenges does AI in education policy face regarding student use?
AI in education policy must navigate the tension between preventing cognitive offloading in young learners and leveraging AI for accessibility or developing critical AI skills for older students.

Featuring: Dan Fitzpatrick, Randi Weingarten, American Federation of Teachers, National Press Club, Charter, ChatGPT, Los Angeles Unified School District, National Academy for AI Instruction, AFL-CIO.

Read the original source

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Retention jumped from 67% to 83% in Ayisha Irfan's AI for student thinking pilot at Forging Opportunities for Refugees in America.

In this episode:

• An AI Socratic method increased learning retention from 67% to 83% for students at Forging Opportunities for Refugees in America (FORA) compared to AI summarization.
• Student confidence in using AI tools like Gemini or ChatGPT showed almost no relationship with their actual learning, emphasizing the need for robust AI literacy in schools.
• The real value of AI for student thinking lies in how students respond to questions, retrieve information, and explain concepts, not just in the AI's output.
• For professional development, educators should compare an AI's instant summary with a carefully designed questioning dialogue to understand its impact on delayed learning retention.
• Ensuring AI in refugee education or any diverse context means demanding accessibility as a foundational design element, including language support and suitable reading levels, not an optional setting.

Chapters:

• 00:00 — Cold open & welcome
• 00:15 — FORA pilot: AI for student thinking improves retention to 83%
• 00:45 — Ayisha Irfan's research at Forging Opportunities for Refugees in America
• 01:15 — Gemini's Socratic method vs. ChatGPT's direct answers
• 01:45 — Why productive struggle is key for AI learning retention
• 02:30 — Rethinking AI literacy in schools: beyond confidence and usage
• 03:15 — Addressing equity and accessibility for AI in refugee education
• 03:45 — Essential questions for school leaders on AI engagement and data privacy
• 04:30 — Measuring what matters: delayed learning retention over activity

How can teachers use AI marking safely?
Teachers should prioritize AI tools that prompt students to explain and retrieve information over those that simply summarize, and always ensure robust data governance regarding identifiable student information.

What is the best way to measure AI literacy in schools?
Measuring AI literacy should go beyond self-reported confidence or usage figures; instead, focus on students' ability to reason, explain, and retain information without the AI tool, and how they understand AI's influence on their thinking.

How can AI help students in refugee education?
AI in refugee education can narrow learning gaps if systems provide usable instructions, suitable reading levels, language support, and careful teacher oversight, ensuring accessibility is a foundation, not an afterthought.

Featuring: Dan Fitzpatrick, Gemini, ChatGPT, Forging Opportunities for Refugees in America, FORA, The 74, Augmented Intelligence Advisory, Ayisha Irfan, Google Privacy Policy.

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ChatGPT makes a silent character speak, while AI in literature education shows why Emile Bernard’s Madeleine in the Bois d'Amour defeats pattern matching.

In this episode:

• AI in literature education should focus on critical thinking AI, enabling students to directly confront the limitations of tools like ChatGPT in literary analysis.
• ChatGPT made specific errors when analyzing Carson McCullers' *The Heart is a Lonely Hunter*, including changing a bus to a train and giving dialogue to the silent character, John Singer.
• Southern Gothic AI analysis reveals that AI struggles with the nuanced contradictions and 'grotesque' elements in authors like Flannery O'Connor, highlighting AI limitations in humanities.
• Effective teaching AI literary analysis involves students annotating AI responses for textual support and then revising them, fostering a 'productive struggle' that deepens understanding.
• Rather than simply dismissing AI for lack of 'feelings,' educators should guide students to critique AI interpretations based on textual evidence, coherence, and insight.

Chapters:

• 00:00 — Cold open & welcome
• 00:30 — Exploring AI in literature education with ChatGPT
• 00:52 — ChatGPT’s errors in *The Heart is a Lonely Hunter*
• 01:15 — Why Southern Gothic AI analysis challenges pattern matching
• 01:52 — Critiquing AI interpretations: beyond 'no feelings'
• 02:30 — ChatGPT ignores John Singer’s silence
• 03:00 — Practical teaching AI literary analysis: annotation and revision
• 03:45 — Rethinking assessment: product, process, and live understanding
• 04:15 — Professional development for critical thinking AI
• 04:45 — AI in literature education makes close reading essential

How can teachers use AI in literature education without students misusing it?
Teachers can foster critical thinking AI by allowing students to directly identify AI limitations in literary analysis, such as ChatGPT's errors when analyzing *The Heart is a Lonely Hunter*.

What are the specific AI limitations in humanities subjects, especially literature?
AI's linguistic fluency can create the appearance of understanding without genuine insight, missing nuanced textual details, contradictions, and character specificities, as seen in Southern Gothic AI analysis.

How can teachers develop critical thinking skills using AI tools for literary analysis?
Teachers can have students annotate AI-generated literary analyses, identifying supported claims, areas needing more evidence, and overlooked details, then requiring them to rewrite sections with their own defended interpretations.

Featuring: Dan Fitzpatrick, Emile Bernard, Madeleine in the Bois d'Amour, Carson McCullers, The Heart is a Lonely Hunter, Flannery O'Connor, Spiros Antonapoulos, John Singer, ChatGPT.

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