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[marmorata]

[hoangperry]

The documents are likely the problem, counterintuitive as that sounds — because the three you listed are all indirect evidence:

• An acceptance letter proves admission, not current enrollment (you might have deferred or dropped out since).
• A class schedule and syllabus prove courses exist, but often carry neither your name + institution + date in one machine-readable block, which is what the OCR needs.

The automated verifier is tuned for one document class above all: a current-dated enrollment verification / registrar certificate — one page stating you are enrolled now, with your full name, the institution name in text, and an issue date from this term. Most universities generate these on demand (registrar office or student portal). With your names and email already aligned (which you've done), swapping the document class is usually the single change that flips the outcome.

When you submit it: photograph the printed certificate with the device camera, name/institution/date region filling the frame — the server-side compression destroys full-page captures, and "unclear document" rejections are frequently just this.

If a registrar certificate, captured close-up, with your already-matching billing/profile names still gets rejected, you've genuinely exhausted the published requirements — at that point take the application ID to https://support.github.com/contact/education and say exactly that; the ticket queue can see what the automated system actually objected to, which the rejection emails don't fully disclose.