In adult online training with spaced attempt–worked‑example cycles and unified adaptive hint‑gating, does making hint-gating criteria transparently rule‑based and previewed to learners (e.g., “you’ll only see a full solution after two unguided attempts on similar items”) reduce illusions of learning and inappropriate hint‑seeking more than an equally strict but opaque gating policy, especially for low‑prior‑knowledge learners who overuse AI hints?

Answer

Making unified adaptive hint‑gating transparent and rule‑based is plausibly somewhat better than using an equally strict but opaque policy at reducing illusions of learning and inappropriate hint‑seeking in this setting—especially for low‑prior‑knowledge learners who tend to overuse AI hints—but expected effects are modest, and good design details matter more than transparency alone.

Likely pattern:

• Low‑prior‑knowledge, heavy hint users: Clear, previewed rules (e.g., “full solutions unlock only after two unguided attempts on similar items”) should reduce impulsive hint‑clicking and make effort requirements more salient, leading to slightly lower illusions of learning and somewhat more genuine retrieval than with opaque lockouts that just feel arbitrary.
• Higher‑knowledge learners: Transparency still helps them plan and may slightly reduce frustration, but the marginal gain in calibration over an opaque policy is probably small because they already self‑regulate better.

However, transparency can backfire or do little if:

• rules are complicated or frequently changing,
• the UI doesn’t reinforce them at the moment of choice (e.g., no reminder like “you’ve used 1 of 2 pre‑solution hints”), or
• learners interpret rules as purely punitive rather than as supports for productive struggle.

So: use simple, previewed rules plus in‑context reminders and neutral, informational framing. Expect small–moderate gains in calibration and reduced hint overuse for novices compared with equally strict but opaque gating, not a dramatic transformation.