By Laini Byfield
Jisc learning analytics code
A practical code of practice that generalizes well to small data programs that monitor participation or outcomes.
What to borrow
Learning analytics governance is one of the few mature domains for ethical monitoring in small populations. The Jisc code of practice is useful whenever you are tracking participation, eligibility, or engagement at the individual level.
Clear, bounded definitions of what the data is for — and what it is not for. Scope creep in small systems is a governance failure, not a technical one.
Participants should know what is collected, how it is used, and who sees it. Jisc treats this as a minimum condition, not a best-practice aspiration.
Explicit data stewardship responsibilities. Who owns the data, who can modify it, and who is accountable when something goes wrong.
When data flags someone negatively, there must be a process for them to respond. Jisc builds this in. Most employer wellness programs do not.
Reference: Jisc, Code of practice for learning analytics.
Governance patterns that travel
Small Data Ethics uses these governance patterns and extends them to incentives and operational pipelines, where error handling and appeals are core design features — not exceptions added after the fact.
A governance framework built for students monitoring their own engagement is a governance framework built for employees monitoring theirs. The data is different. The power dynamic is the same.