In this EdTechnical short, Libby and Owen unpack ‘AI agents’ and what they mean for education. Agents are large language models connected to tools and workflows that are allowed to take actions like searching, summarising, and completing multi-step tasks. Recent progress comes from the combination of stronger models and better systems for connecting agents to external tools, enabling more complex and autonomous outputs.

Applying agents to education brings a tension between flexibility and reliability. Agentic systems can be useful for teachers, who operate across varied contexts and need adaptable support. For students, especially in structured learning, too much flexibility can reduce clarity and introduce inconsistency.

This matters because effective learning depends on structure and progression. The value of agents in education depends on how well they are applied to the specific task and learning goal.

Links:

• OpenClaw & Moltbook: The viral story of AI agents building their own Reddit-like social network https://techcrunch.com/2026/01/30/openclaws-ai-assistants-are-now-building-their-own-social-network/
• Claude Research Mode: Anthropic's explainer on deep research https://www.anthropic.com/news/research

Join us on social media:

• BOLD (@BOLD_insights), Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel)
• Listen to all episodes of EdTechnical here: https://bold.expert/ed-technical
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Credits: Sarah Myles for production support; Josie Hills for graphic design; Anabel Altenburg for content production.

At this year's SXSW EDU, Owen joined a panel on what it takes to make voice AI for assessment work in classrooms.

In this live recording of the session, the panelists untangle how voice AI works, and what testing this technology with kindergartners looks like in rural Georgia. They explain why the distinction between capturing what a student said versus what they meant matters enormously for literacy assessment and why questions of privacy, equity and model bias are not afterthoughts but design requirements.

Where does voice AI genuinely open up new possibilities in education, and where is the evidence still thin?

The other panelists were Patti Ura, Director of Learning Technology Research at Digital Promise, Amelia Kelly, VP of Data Science at Curriculum Associates and former CTO of Soapbox Labs, and Kristen Hoff, Head of Measurement at Curriculum Associates.

Links:

• Soapbox Labs, now part of Curriculum Associates
• Digital Promise
• OpenAI Whisper, the open source speech-to-text model

Join us on social media:

• BOLD (@BOLD_insights), Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel)
• Listen to all episodes of EdTechnical here: https://bold.expert/ed-technical
• Subscribe to BOLD’s newsletter: https://bold.expert/newsletter
• Stay up to date with all the latest research on child development and learning: https://bold.expert

Credits: Sarah Myles for production support; Josie Hills for graphic design; Anabel Altenburg for content production.

In this EdTechnical short, Libby and Owen test a conversational plush toy to understand more about AI-powered toys designed for young children. Recent research from Cambridge shows that preschool-aged children can form rapid emotional connections with social robots like these, even when the responses from the robot are inconsistent.

Children’s experiences with AI toys are shaped by voice and real-time interaction. Could highly responsive, frictionless AI systems in toys influence children’s expectations of human relationships?

Libby and Owen discuss the difference between shared, supervised play and extended solo interaction with the toy, which may be less advisable. As the technology continues to improve, the key challenge becomes how these tools are introduced and used in early childhood environments.

Links:

• BBC Article: AI toys for children misread emotions and respond inappropriately, researchers warn
• Cambridge study on AI toys in early childhood
• AI chatbots and the “empathy gap” in children

Join us on social media:

• BOLD (@BOLD_insights), Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel)
• Listen to all episodes of EdTechnical here: https://bold.expert/ed-technical
• Subscribe to BOLD’s newsletter: https://bold.expert/newsletter
• Stay up to date with all the latest research on child development and learning: https://bold.expert

Credits: Sarah Myles for production support; Josie Hills for graphic design; Anabel Altenburg for content production.

In this episode of EdTechnical, Libby and Owen speak with Panos Ipeirotis, Professor at NYU Stern School of Business, about his experiment using AI to run oral exams in university courses. As generative AI makes it easier for students to outsource written assignments, educators are asking whether traditional take-home assessments still measure real understanding.

Panos introduced AI-mediated oral assessments after noticing a mismatch between high-quality written submissions and weak classroom discussion. In the new system, students answer questions from a voice agent that probes their understanding of the material and their own work.

Panos tells Libby and Owen how the exams work, including an AI “council” of language models that evaluates transcripts and produces detailed feedback. What does this approach reveal about the future of assessment? Could AI make oral exams scalable in higher education, and even improve fairness and grading consistency?

Links:

• Panos Ipeirotis – NYU Stern Faculty Profile
• NYU Professor Uses AI-Run Oral Exams to “Fight Fire with Fire”
• Article: The case for oral assessment in the age of AI

Guest Bio

Panos Ipeirotis is a Professor of Information, Operations and Management Sciences at NYU Stern School of Business. His research focuses on data science, AI, and human-AI collaboration. In addition to his academic work, he experiments with practical applications of AI in education, including new models of assessment that combine oral exams with AI-based evaluation.

Join us on social media:

• BOLD (@BOLD_insights), Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel)
• Listen to all episodes of EdTechnical here: https://bold.expert/ed-technical
• Subscribe to BOLD’s newsletter: https://bold.expert/newsletter
• Stay up to date with all the latest research on child development and learning: https://bold.expert

Credits: Sarah Myles for production support; Josie Hills for graphic design; Anabel Altenburg for content production.

In this EdTechnical Short, Libby and Owen explore how AI might reshape teaching through the lens of the “weakest link” theory from economics. They discuss the possibility of full job replacement, partial task automation, and productivity gains for teachers. Automation often shifts the composition of work rather than eliminating roles, as with bank tellers and radiologists.

In schools, planning, grading, diagnosing student understanding, classroom management, and relationship-building are tightly interconnected. Automating one component may reallocate time, but complexity is not neatly reduced.

AI can already perform isolated teaching tasks. What happens to the education system when those tasks are embedded in a deeply relational profession?

Links:

• Michael Kremer (1993), The O-Ring Theory of Economic Development
• David Autor (2015), “Why Are There Still So Many Jobs? The History and Future of Workplace Automation”

Join us on social media:

• BOLD (@BOLD_insights), Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel)
• Listen to all episodes of EdTechnical here: https://bold.expert/ed-technical
• Subscribe to BOLD’s newsletter: https://bold.expert/newsletter
• Stay up to date with all the latest research on child development and learning: https://bold.expert

Credits: Sarah Myles for production support; Josie Hills for graphic design; Anabel Altenburg for content production.

In this episode of EdTechnical, Libby and Owen speak with Kristyn Sommer, a developmental psychologist and child robot interaction researcher.

Together, they explore how young children learn through imitation, why physical presence matters for learning, and what the so-called robot deficit reveals about engagement, psychological safety, and learning outcomes. Kristyn explains where robots can support learning, where they fall short, and why many assumptions about roboteachers are far ahead of the evidence.

They also discuss the practical realities and the ethics of educational robotics, and why robots are more likely to support teachers than replace them anytime soon.

Links:

• Can a robot teach me that? Children’s ability to imitate robots
• Preschool children overimitate robots, but do so less than they overimitate humans
• When is it right for a robot to be wrong? Children trust a robot over a human in a selective trust task

Bio

Kristyn Sommer is a developmental psychologist and child-robot interaction researcher whose work explores how young children learn from and with social robots. She is a postdoctoral research fellow at Griffith University’s School of Applied Psychology, where she investigates how children’s social, emotional and behavioural engagement with robotic teachers affects learning and development. Her research also examines individual differences in how children relate to and trust robots, and how these insights might inform more supportive, evidence-based uses of educational technology. She is also a Jacobs Foundation Research Fellow focused on foundational work in children’s learning with robot companions.

Join us on social media:

• BOLD (@BOLD_insights), Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel)
• Listen to all episodes of EdTechnical here: https://bold.expert/ed-technical
• Subscribe to BOLD’s newsletter: https://bold.expert/newsletter
• Stay up to date with all the latest research on child development and learning: https://bold.expert

Credits: Sarah Myles for production support; Josie Hills for graphic design; Anabel Altenburg for content production.

In this episode of EdTechnical, Libby and Owen sit down with Dan Meyer: math educator, EdTech innovator, and self-proclaimed “token AI sceptic”. Dan’s rare mix of classroom experience and product design insight gives him a unique perspective on how technology intersects with real classrooms. He shares what the classroom teaches him about student engagement, the challenges teachers face, and why motivation is deeply social - which EdTech can overlook.

They dig into how AI can support creativity and connection, why great math teaching starts with inviting and developing, and where “AI guy” might be missing the point. Plus, Dan reveals the AI project he’s excited about and what it means for teachers.

Links:

• TeacherTapp survey on teacher AI use
• EdTechnical’s forecasting competition - deadline 16 December

Bio

Dan Meyer taught secondary maths to students who didn't like secondary maths. He has advocated for better maths instruction on CNN, Good Morning America, Everyday With Rachel Ray, and TED.com. He earned his doctorate from Stanford University in maths education and is the Vice President of Teacher Growth at Amplify where he explores the future of maths, technology, and learning. He has worked with teachers around the world, calls Oakland home, and taught eighth graders there yesterday.

Join us on social media:

• BOLD (@BOLD_insights), Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel)
• Listen to all episodes of EdTechnical here: https://bold.expert/ed-technical
• Subscribe to BOLD’s newsletter: https://bold.expert/newsletter
• Stay up to date with all the latest research on child development and learning: https://bold.expert

Credits: Sarah Myles for production support; Josie Hills for graphic design; Anabel Altenburg for content production.

In this episode of EdTechnical, Libby and Owen look at Alpha School, a model that started as a micro-school in Austin, Texas, and is now expanding. At its core, Alpha condenses academic learning into a morning block where students work largely independently using software, supported by guides rather than traditional teachers. Afternoons are reserved for enrichment and life skills.

Libby and Owen discuss the appeal of this approach , the evidence behind mastery-based learning, and the big questions about scalability and cost. Is this a breakthrough for education or just a well-designed version of ideas we’ve seen before? Join them for a brief dive into Alpha School’s model and what it could signal for future learning models.

Links:

• Alpha School’s white paper
• A parent review of Alpha School
• A Wired article about Alpha School
• EdTechnical’s forecasting competition

Join us on social media:

• BOLD (@BOLD_insights), Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel)
• Listen to all episodes of EdTechnical here: https://bold.expert/ed-technical
• Subscribe to BOLD’s newsletter: https://bold.expert/newsletter
• Stay up to date with all the latest research on child development and learning: https://bold.expert

Credits: Sarah Myles for production support; Josie Hills for graphic design; Anabel Altenburg for content production.