Beyond chatbots: AI agents as software, not characters
Furze argues chatbot framing hides corporate responsibility and misdirects education's assessment debates.
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Public readings arranged by original publication date. People and institutions use explicit mappings; article sources remain in their details.
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Aila trial: less lesson-planning time, but mixed views and declining use
An English primary-school randomized trial found roughly 24% less planning time with Aila, about 49 minutes weekly, without inferior assessed resources. Use declined during the ten-week trial, and teacher views were mixed.
Things to bear in mind when talking about AI
Selwyn calls for precise, contextual discussion of AI and warns against treating a power user’s experience as universal expertise. Constructive critique should ask what alternative forms of AI and educational practice people want.
Must Children Keep Acquiring More Abilities in the AI Era? (translated title)
Educator Zhang Shuling questions defining children’s worth through an ever-expanding list of abilities AI cannot yet perform. Useful capacities matter, but do not exhaust the purpose of education.
Six Important Findings from the AI in Action Learning Tour
Meyer highlights observations about teacher roles, curriculum fit, actionable suggestions and multilingual access, alongside disengaging uses. He asks how people actually use AI before treating capabilities as educational outcomes.
Teacher AI Competency Frameworks: UNESCO IITE’s comparative report
The UNESCO IITE–Shanghai Open University project compares 36 teacher AI competency frameworks, examining competencies, implementation and assessment across policy, curriculum and teaching practice.
What Should We Teach Children When AI Can Do So Much? (translated title)
Liu reports on a program at Kaohsiung Girls’ Senior High School in Taiwan emphasizing problem selection, collaboration, AI-supported making and explaining concepts to other learners.
Don’t Throw Ed Tech Babies Out With the Bathwater
Teacher workload, student thinking, product evidence and family communication are treated separately.
The algorithm in the room: AI and the future of education
This UNESCO collection brings together 26 think pieces on agency, young people’s development, pedagogy, expression, public governance and educational futures. It broadens discussion beyond tool capabilities.
What if transferable skills don’t exist?
A deliberately strong argument locates reasoning and problem-solving in domain knowledge.
How Should AI Be Used in Schools?
Examples of planning and writing ask which cognitive tasks can appropriately be delegated.
Is This a Good Use of the Technology? Is It a Good Use of Your Brain?
Furze proposes two contextual questions: is this a good use of the technology, and of the learner’s own thinking? He examines accessibility, outsourcing and assessment, questioning whether fixed categories capture individual needs.
Students should only use AI for things they already know how to do well.
The proposed restriction concerns independent general-purpose AI use, not all instructional software.
How Alpha School Teaches Writing
The critique asks whether interest-driven writing loses opportunities to consolidate curriculum knowledge.
Generative AI Can Harm Teaching
A recent working paper examines the tension between teacher productivity and student experience.
An AI marking case study: from four hours to twenty minutes
A classroom case exposes teacher reading, student trust and ambiguous AI feedback.
Just an Exam — Shishufeng EP22
Hanyang and Chongqing use university choices to question the idea that one decision fixes an entire life path.
Why personalising education based on student interests doesn’t work
Performance-based adaptation is distinguished from rewriting every topic around a learner’s interests.
Is AI feedback true but useless?
A large redrafting project makes uptake of feedback visible while leaving learning unresolved.
Choosing to Stay Human
Mollick considers how convenient AI defaults can bypass the effort through which people develop valued abilities.
The black box of AI assessment
A vendor’s validity review recognizes that stable scores can still reward the wrong learning.
China’s AI+Education Action Plan: curriculum, teacher development and governance
The five-department action plan connects AI literacy, university curricula, teacher development, applications and safeguards, with goals for 2030. These are policy directions, not completed implementation or demonstrated learning effects.
The ethics of AI assessment: five big issues
Stakeholder conversations surface teacher deskilling and pupils’ wish to be read seriously.
Understanding the Evidence Base on AI in K-12 Education
A Stanford review identified 20 higher-quality causal studies within over 800 K12 AI papers available by October 2025. Assisted performance and unaided learning diverge; long-term, equity and wellbeing evidence remains limited.
Education in the AI Era Should Foster Independent Thought and Lived Growth
Li Zhengtao argues that educational purposes should shape technology, protecting students’ own thinking and lived learning.
Is Relying on AI Cognitive “Offloading” or “Outsourcing”?
Outlines illustrate a distinction between external memory support and delegating the thinking itself.
Alison Gopnik on Childhood Learning, AI as a Cultural Technology, and Rethinking Nature vs. Nurture
Gopnik connects exploration, apprenticeship and AI literacy in an interview that preserves disagreement about machine reasoning.
Can LLMs be personal tutors?
Question quality, accuracy, alternatives and persistence matter beyond fluent explanations.
AI tutoring can safely and effectively support students: An exploratory RCT in UK classrooms
An exploratory 165-student trial retains message-by-message human supervision and uncertain transfer estimates.
AI is uncannily good at judging writing
A large vendor report concerns judging agreement, not student learning.
Education isn’t working
The essay distinguishes productive work from the practice needed to become an expert.
Against “Brain Damage”
Mollick challenges sensational interpretations of AI studies and examines learning, idea generation and writing practices.
Generative AI without guardrails can harm learning: Evidence from high school mathematics
A mathematics RCT directly separates assisted performance from subsequent unaided assessment.
From Chalkboards to Chatbots: Evaluating the Impact of Generative AI on Learning Outcomes in Nigeria
A teacher-supported six-week programme improved paper-test outcomes, with important attrition and design caveats.
Do Students Who Rely on ChatGPT “Benefit”?
Wexler challenges interpreting better submitted prose as improved writing ability.
Bringing our feedback philosophy to life with AI
A design report explains why unreliable generated questions were replaced with human-written sets.
ChatGPT in lesson preparation: the 2024 EEF/NFER trial
A 259-teacher trial supports planning-time savings without establishing higher student learning.
Using AI to automate written comments
A product trial separates teachers’ evaluative judgment from AI-assisted feedback production.
The Writing Effect
Writing’s retrieval and elaboration benefits must be balanced against novice cognitive load.
Post-apocalyptic Education
This 2024 essay distinguishes confidence in AI detection from the illusion that completed homework means learning.
AI competency framework for teachers
UNESCO outlines 15 teacher competencies across five dimensions and three progression levels, supporting teacher development and assessment design while foregrounding ethics, human agency and pedagogy.
Historical reference: AI-Generated Summaries Are a Problem—for Authors and Society as a Whole
An author’s inspection of generated book companions reveals losses beyond factual accuracy.
Andy Matuschak — The reason most learning tools fail
Matuschak distinguishes forgetting from never understanding, and discusses questioning, memory and fading scaffolds. The interview offers a lens for AI tools: do they help learners notice confusion and act, or mainly ease consumption?