AI Learning Evidence

Not guidance. A record of published research on AI-assisted learning, and our assessments of it. The limits

Open questions

What the research has not yet answered, why not, and which studies come closest. A question stays open until evidence capable of answering it exists — thin evidence gets a description here, not an unearned verdict.

Q01Open

Does generative AI use during learning impair or improve transfer to unfamiliar problem types?

Most studies do not test transfer at all; the few that do report no significant differences. Absence of transfer testing is not absence of effect.

Closest evidence so far

Q02Open

Does sustained reliance on generative AI erode previously acquired skills?

Longitudinal within-person evidence is absent; existing signals are cross-sectional correlations and scaffold-withdrawal designs.

Closest evidence so far

  • Impact of AI assistance on student agencyRandomized trial · 2024 · Study tier 2 · Secondary different · University direct

    Scaffold withdrawal reduced peer-review quality on the intervention's own metrics (High RoB: circular measurement); pre-LLM system.

Q03Open

Does teacher supervision change what learners retain from AI use, holding the tool constant?

Positive supervised programs exist, but supervision is confounded with structure and materials; no study randomizes supervision itself.

Closest evidence so far

Q04Open

Do findings from university students generalize to secondary students, and vice versa?

Meta-analytic moderator tests find no education-level difference, but over mostly-university samples; paired replications are missing.

Closest evidence so far

Q05Open

Does offering AI tools change participation and engagement, separately from any effect on learning?

One MOOC-scale randomized offer reduced exam participation on average while adopters differed; mechanisms unresolved.

Closest evidence so far