The ethics of AI assessment: five big issues
Stakeholder conversations surface teacher deskilling and pupils’ wish to be read seriously.
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Stakeholder conversations surface teacher deskilling and pupils’ wish to be read seriously.
The hosts find that tacit knowledge about files, versions and structure often explains beginners’ difficulties.
Two cohorts show operational feasibility, while agreement among model graders does not establish validity.
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.
Protected writing time, with candid design reversals.
Yuk Hui asks what universities lose when knowledge production and economic utility become their defining purposes.
Talbert separates AI assistance with design and practice from delegating grading itself.
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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.