Peer coaching before writing may reduce AI shortcuts
A guest post describes using ungrading and peer coaching to deepen student thinking and make ChatGPT shortcuts less tempting.
Theory
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Discernment and Disclosure for AI Agents in Education
Marc Watkins argues faculty should question when to use AI agents and disclose their use to students.
Beyond chatbots: AI agents as software, not characters
Furze argues chatbot framing hides corporate responsibility and misdirects education's assessment debates.
Aila trial: less lesson-planning time, but mixed views and declining use
★A randomized trial of teacher planning time helps distinguish time savings from student learning outcomes.
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.
The global conversation on AI in education is shifting. Where does it leave Australian higher education?
Lodge reflects on learning, governance and the limits of chatbot-era reform after Digital Learning Week.
Things to bear in mind when talking about AI
★Specify the technology, setting and experience before treating AI in education as a single object.
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)
★Separate human worth from lists of capabilities that AI cannot replace, adding a perspective on educational purposes.
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
★Examine concrete classroom uses rather than relying on product demonstrations.
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.
Notice, Judge, Redesign: Working Through the AI Productivity Dip
Jisc proposes noticing unproductive interactions, judging what AI can reliably handle, and redesigning workflows. Institutions should allocate learning time; a useful outcome may be recognizing when not to use AI.
Curricular Responses to AI with Deborah Barnett
Coordinating AI competencies across a professional program.
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.
The Overhang
Mollick argues that expertise, breadth, taste and agency help people use AI capabilities. His experiments invite a question: how do learners acquire the knowledge and judgment needed to direct and evaluate increasingly capable tools?
Varying Retrieval Practice to Promote Transfer of Learning
Sumeracki explains Butler et al.’s (2017) experiments contrasting repeated and varied application during retrieval practice. Her account invites asking whether an AI activity makes students retrieve, explain and apply concepts across contexts.
Reading Across Fields and Working with AI: A Course Retrospective — Shishufeng EP29
The second retrospective describes AI-built demonstrations and source navigation, while exposing the limits of keyword retrieval.
Two validity conversations in a time of AI
Dawson separates validating AI assessors from validating assessment when students have AI access.
Don’t Throw Ed Tech Babies Out With the Bathwater
Teacher workload, student thinking, product evidence and family communication are treated separately.
Motivation, Themes and Practice: A Course Retrospective — Shishufeng EP28
Chongqing and participant Mizai revisit how a music course found its themes and used live demonstrations.
AI Implementation in Higher Education in Latin America and the Caribbean
Across 200 higher education institutions in 19 countries, 87% reported AI use in at least one area, while 26% had a formal AI strategy. The report calls for stronger governance and institutional capability.
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.
Moral Instruction Will Not Stop Cheating
Reframing misconduct around incentives and learning.
AI-Aware Online Math Teaching with Jessica Bernards
Rich learning support alongside high-stakes proctoring.
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.
Our Duty of Care in the Age of AI
Course purposes and faculty working conditions belong together.
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.
Finding Sources in the AI Era — Shishufeng EP27
Hanyang and Liushou discuss moving from an unfamiliar topic to a syllabus, search terms and original sources.
AI and Student Agency with Jason Gulya
Student choice within shared course goals.
Three ways alternative grading addresses the EDUCAUSE Horizon report
Talbert argues that changing tasks without changing grading leaves a core incentive problem untouched.
Let’s emphasize human effort and intent in educational materials
Disclosure as a question of educational relationships.
Enduring Methods for an Emerging Medium: The Generative AI Studio
Laura Zarrow describes a studio course using critique and timed design exercises to develop judgment through making.
Reading In An Age Of Thinking Machines
A documented design experiment with open uncertainties.
Generative AI Can Harm Teaching
A recent working paper examines the tension between teacher productivity and student experience.
What if We Accidentally Outsource the Real Work to AI?
Automation can alter the practice behind an artifact.
Analog Is Having a Moment. But Is It Sustainable?
Testing the costs and access limits of analog responses.
The perfect storm: AI, assessment and a sector under pressure
QAA examines the gap between institutional AI policies and students’ day-to-day assessment experience.
What Is Understanding? — Shishufeng EP23
Chongqing uses Hinton’s account of understanding to question what learners lose when AI explanations become too smooth.
Integrating Generative AI Into University Coursework Assessments – a Student Perspective
Medical-science students see value in critiquing AI but resist universal AI integration.
Modality does not equal risk
Online-education practitioners challenge the assumption that physical attendance alone assures learning.
Assuring quality learning in a gen AI-integrated future: adaptive capabilities
TEQSA’s commissioned report connects adaptive capabilities with disciplinary knowledge and learning-process evidence. It proposes process-focused assessment and support for student judgment, agency and self-regulation.
What does assurance of learning actually look like in practice?
UniSQ’s team describes a prototype connecting program outcomes, tasks and assessment security.
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.
Standards-Based Grading Six Years Later
★A six-year course reflection exposes implementation failures and teacher workload, grounding assessment reform in practical constraints.
Freeman revisits a coordinated calculus course of 250–450 students and the compromises required to sustain it.
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.
How An AI Detector Made Me Trust People Less
A personal trial raises questions about labels and trust.
The black box of AI assessment
A vendor’s validity review recognizes that stable scores can still reward the wrong learning.
On AI glasses and wearable AI in assessment
The authors question assessment designs that depend on detecting and excluding wearable assistance.
Mastery Exams
Clark uses known proof tasks and flexible timing to distinguish understanding from spontaneous invention.
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.
What are we going to do about marking now?
Tifflin asks markers to make conceptual grasp, evaluative judgment and transfer visible.
This is an Excellent Paper: The Effects of Prompt Injection on Grading
A Wharton team tests how embedded instructions affect AI grading, finding important differences across models and conditions.
The ethics of AI assessment: five big issues
Stakeholder conversations surface teacher deskilling and pupils’ wish to be read seriously.
Teaching Friends to Use AI — Shishufeng EP9
The hosts find that tacit knowledge about files, versions and structure often explains beginners’ difficulties.
Scalable and Personalized Oral Assessments Using Voice AI
Two cohorts show operational feasibility, while agreement among model graders does not establish validity.
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.
In-Class Writing with James Seitz
Protected writing time, with candid design reversals.
The University Within the Limits of Automated Knowledge
Yuk Hui asks what universities lose when knowledge production and economic utility become their defining purposes.
Six ways to use artificial intelligence tools in alternative grading
Talbert separates AI assistance with design and practice from delegating grading itself.
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.
Listening to My Students at Scale: Exit Tickets, NotebookLM, and the Tightest Feedback Loop I’ve Ever Built
Ipeirotis describes turning exit-ticket responses into targeted follow-up teaching.
Strengthening validity and trust in generalist degrees through program-level approaches to assessment: Possible or pipe dream?
The authors address fragmented evidence in flexible generalist degrees.
A brief update: Why I’m still using AI detection after all, alongside many other strategies
A bounded pro-detection stance with acknowledged costs.
AI feedback customized for student writers: the updated PAIRR prompts
Prompt revision driven by feedback overload.
Is Relying on AI Cognitive “Offloading” or “Outsourcing”?
Outlines illustrate a distinction between external memory support and delegating the thinking itself.
The Conversational Exam: A Scalable Assessment Design for the AI Era
Barba and Stegner report small-group live coding for 58 students, including substantial implementation costs.
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.
Small changes to handle AI
Clark combines flexible practice with selected in-class checks while retaining proof portfolios.
Playing Pretend: Expert Personas Don’t Improve Factual Accuracy
This report tests whether assigning expert identities reliably improves answers to difficult factual questions.
Assessment after Artificial Intelligence: The Research We Should Be Doing
An assessment research agenda asks for precise practices, historical grounding and connected inquiry.
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.
Pitfalls in Evaluating Generative AI — Hung-yi Lee, Lecture 4
This public lesson extends AI literacy to evaluation: metrics, human preferences, model judges and benchmark contamination.
Valid assessment is a plausible argument not an absolute
Steel explains why assessment security alone does not establish a valid learning inference.
Making Progress on Teaching in a World With AI
A skeptical author identifies room for collective experimentation.
Enacting assessment reform in a time of artificial intelligence
TEQSA compares program-wide, unit-level and hybrid approaches to assurance of learning.
Supporting Appropriate Student Use of AI
GeoAI connects AI-use boundaries to disciplinary goals: help with statistical concepts does not mean outsourcing climate-data interpretation. It suggests staged assignments, reflection and checked practice, with privacy and copyright considerations.
GIFT-AI: teaching the game and leveling the field
A 34-student course report centered on feedback comparison.
The wicked problem of AI and assessment
Interviews with 20 educators reveal competing assessment goals and unavoidable trade-offs.
Education isn’t working
The essay distinguishes productive work from the practice needed to become an expert.
Getting the most out of AI feedback
Student-facing strategies, including a failure of flattery.
Generative AI for students
OU distinguishes prohibited, permitted and required use, with disclosure and accessibility guidance.
How ChatGPT Might Inadvertently Improve Student Thinking
Willingham describes conferencing as a way to retain and inspect writing-related thinking.
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.
Alternative grading in a test-forward environment
Talbert examines reassessment backlogs, anxiety and practice in a test-heavy course.
Why banning the banning of AI in assessment is all about increasing trust and agency
Sydney’s designers explain the rationale for open learning tasks alongside secured capability checks.
AI-Integrated Assignments with Kiera Allison, Jamie Jirout, Spyros Simotas, & Jun Wang
Different disciplines, different boundaries and scaffolds.
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.
Talk is cheap: why structural assessment changes are needed for a time of GenAI
The authors distinguish compliance-dependent instructions from changes to assessment structure.
Experience embracing genAI in an engineering computations course: What went wrong and what next
Barba candidly describes a course chatbot and autograder enabling answer-seeking shortcuts.
Peer and AI Review + Reflection (PAIRR): A human-centered approach to formative assessment
A mixed-methods study of experience and judgment.
Do Students Who Rely on ChatGPT “Benefit”?
Wexler challenges interpreting better submitted prose as improved writing ability.
My AI-driven grading changes: A 3x3x3 reflection
A follow-up finds practical relief but persistent test anxiety and narrower assessment.
AI Can’t Do Student Peer Review
Feedback quality is only part of peer response.
Bringing our feedback philosophy to life with AI
A design report explains why unreliable generated questions were replaced with human-written sets.
Exploring two frameworks from The Open University: Critical AI Literacy Skills and Responsible by Design
OU’s designers connect AI literacy with access, bias, environmental and labour questions.
Integrating Artificial Intelligence Into Higher Education Assessment
Williams describes staged AI outlining, peer critique and independent writing in an immunology course.
Prompt Engineering is Complicated and Contingent
Repeated tests illustrate why a successful answer does not establish a reliable prompting technique.
What to do about artificial intelligence now: Examining the real impact on learning
Lodge calls for evidence about learning mechanisms beyond uptake and perceived usefulness.
Reading in the Age of Social Media (and AI)
Reading habits are also an educator’s problem.
AI as Design Accelerator with Ryan Wetzel
Scaffolding collaboration through roles and playtesting.
How AI is changing my grading approach -- for now
Talbert documents an emergency redesign of discrete mathematics assessment and the uncertainty behind it.
ChatGPT in lesson preparation: the 2024 EEF/NFER trial
A 259-teacher trial supports planning-time savings without establishing higher student learning.
Academic Integrity in an LLM World
What should a course credential actually certify?
Using AI to automate written comments
A product trial separates teachers’ evaluative judgment from AI-assisted feedback production.
Teaching with AI in Technical Courses with Jingjing Li
Independent modeling before AI-supported extension.
Trying out Grammarly Authorship Beta
An early account of process evidence and privacy tradeoffs.
The Writing Effect
Writing’s retrieval and elaboration benefits must be balanced against novice cognitive load.
Deceptive Assessment Has No Place in Education
Assessment methods must meet their own integrity standard.
Emotionally Enriched Feedback via Generative AI
A randomised feedback experiment separates improved perceptions from no detected improvement in work quality.
Post-apocalyptic Education
This 2024 essay distinguishes confidence in AI detection from the illusion that completed homework means learning.
Historical foundation: Validity matters more than cheating
The authors place cheating within the broader question of defensible judgments about capability.
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.
No One is Talking About AI’s Impact on Reading
Earlier classic: reading assistance versus reading replacement.
On AI and ‘Meaningful’ Feedback
Earlier classic: ask whether feedback is actually used.
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?
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An index of research, practice, policy and debate on AI in education, across universities, schools and families, with the original source and date for every entry.