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The Privacy Ledger - protect and govern student data

Institutional Review Boards and Student Data

A plain-language guide to institutional review boards and student data: the record, the purpose, the authority and the safeguard.

Privacy check
Record
research dataset in research data and secondary use
Data
Institutional Review Boards and Student Data
Safeguard
consent or a lawful exception, plus de-identification checked for small cohorts
First check
Check that the recipient is bound to use the data only as agreed.

The short answer

Put merely, institutional review boards and student information is regarding control over a research dataset that belongs, in a practical sense, to a student and is held in trust by a college. The college might use it for the objective it was collected for, share it where the law or a valid permission permits, and must protect it everywhere else. Everything in this guide is a way of making that sentence workable at a desk, stage by stage.

Design-stage review catches problems when they are still cheap to fix, and late review catches them when they are expensive to undo.

Security baselines for new platforms ought to be set before launch, because retrofitting safeguards following adoption rarely restores the information already disclosed.

Health and safety exemptions are for genuine emergencies, judged on the facts at the time, and they do not create a standing permission to disclose broadly.

Retaining a personal copy of a file file helps a student track what an university holds, and institutions ought not to obstruct that habit.

What this covers

Alumni platforms hold giving, employment and contact information, and former students should be able to correct and limit that information.

Students who are additionally employees have files in both capacities, and the capacity in which a file was created matters to its treatment.

Single sign-on creates an identity record of its own, including authentication events that can reveal patterns of student activity.

LGBTQ students can be harmed by directory disclosures that reveal identity or associations, and opt-out processes should be easy to find and use.

Career services retain employment and internship information, and disclosing that information with employers needs consent analysis even when the disclosing feels useful.

Audit and evaluation disclosures must be limited to the audit or evaluation objective, and the receiver must be bound to that objective.

How to work through it

Retain applicant records on a stated schedule, and delete them when that schedule expires, rather than keeping them indefinitely.

Identify the authorization before the data moves, not after, because retrospective authorization is usually no authorization at all.

Monitor student record systems for anomalous access, and investigate anomalies, since uninvestigated anomalies teach staff that nobody watches.

Check consent for specificity, freedom and revocability, and do not rely on a blanket consent that was never explained.

Assess AI tools with the same gate, plus a particular review of training information use, prompt storage and output handling.

Contain return of records in vendor contracts, in an usable format, because a file returned in an unusable form is not truly returned.

Document exemptions to policy with an identified approver and an expiry, because permanent exemptions are just undeclared policy alters.

Locate each copy before deciding, including the vendor copy, the backup copy and the copy in the shared drive.

A worked illustration

The contract in that illustration names the information, limits use to the college's objectives, bans advertising use, and sets removal ninety days after the contract ends.

Consider a learning app for younger students that tracks behaviour across sessions and shares aggregates with a third party, without a privacy review.

Consider a researcher who asks for identifiable student files and is offered a de-identified extract instead, with a documented agreement for the study.

Consider a registrar asked by a parent for a student's grades following the student has turned eighteen and is no longer a dependent for the relevant purpose.

In that illustration the audit finding becomes a remediation task with an owner and a date, and the subprocessor's copy is deleted on a verified timetable.

Where guides go wrong

Permitting tracking in learning applications for younger students to go unreviewed is a mistake, since behavioural information accumulates silently over a school year.

Screening younger users by collecting more information than the screening requires is an error, since the safeguarding then becomes the problem.

This guide does not substitute for an university's own policies or counsel, and a conflict between the two should be resolved in favour of the university's own advice.

Including a diagnosis in an accommodation letter, when a lecturer solely needs to know the accommodation, is an error that discloses more than the purpose needs.

Excluding students from confidentiality oversight is a mistake, because students notice problems that staff have normalised.

Sources and evidence on the record

  • Family Educational Rights and Privacy Act regulations, 34 CFR Part 99, text on eCFR.
  • US Department of Education, Student Privacy Policy Office, studentprivacy.ed.gov - FERPA guidance, FAQs and model notices.
  • US Department of Education, ed.gov - guidance, Dear Colleague letters and enforcement information.

Evidence basis: 34 CFR Part 99 research provisions and review board practice Applies when: When a college holds, uses or discloses a research dataset in the context of research data and secondary use

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