A daily-updated tracker of AI news, product launches and research, tagged by learning principle and by the kind of evidence behind each claim. Every item links to its source.
Get the Friday emailBrowse the trackerPicked automatically by rule: the newest peer-reviewed items first, then the newest preprints and study reports, each touching a learning principle.
Publisher listing: Journal article in Computers & Education, Volume 256 by Chengchen Li, Ye Han, Enhao Feng. Issue: January 2027. Abstract on the publisher page.
Publisher listing: Journal article in Computers & Education by Jered Borup, Charles R. Graham, Leanna Archambault et al. Available online 3 October 2026. Abstract on the publisher page.
Human-AI Interaction is commonly evaluated by what an artificial agent enables during use, yet interaction can also alter the human who acts next. We introduce Residual Human States, a trajectory-based framework for representing the potentially multidimensional human state carried forward after interaction with AI,...
Large language models (LLMs) promise to automate one of higher education's most resource-intensive activities: assessing student writing. Existing evaluations are typically limited to a single model, a single prompt and a single institution.
Large language models can answer the same question in different styles, but users' preferred styles are hidden and vary across users and questions. We study inference-time personalization through online selection from a fixed set of prompts, each representing a persona.
Flags describe what kind of evidence a source cites. They are not quality scores. Full rules
From a peer-reviewed journal feed.
A preprint, or news that reports a study such as a trial, meta-analysis, experiment or survey.
A product launch or announcement whose text cites no study.
News, policy or opinion with no study and no product claim.
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