Jisc's RAISE reflections question student engagement measures

Updated Sep 29, 2026

Jisc published reflections on student engagement on 25 September 2026, drawing on conversations at RAISE. Its message is to interpret activity data through dialogue with students. For university teams, the practical question is what students can explain that an engagement dashboard leaves unresolved.

What Jisc's student engagement account adds

James Hodgkin, Jisc's Head of analytics, describes discussions at Northumbria University on 9 and 10 September. Delegates raised difficulties accessing information across systems and the need to understand attendance in context.

A delegate put the listening point plainly:

"Data is only powerful if people will listen."

This is a conference account, with no participant count or sampling method reported. It introduces neither a national timetable nor an evaluated intervention.

What this means for institutions

Jisc's separate code of practice for learning analytics recommends consulting student representatives throughout design, rollout and monitoring. It calls for clear explanations of data use and interpretation, and for checking incomplete data and potentially misleading correlations. These provide a basis for reviewing what an engagement measure can support.

Our suggestion is to bring the dashboard owner, survey lead and student representatives together to review an engagement measure. Ask what it records, what it leaves out and which evidence each team can access. For example, a course team reviewing participation could invite students to describe which teaching activities help them learn and what makes participation difficult. Treat those accounts as evidence to investigate, without assuming a cause in advance.

Use the discussion to agree a response that can be checked. Record the issue, the responsible team, the proposed action and when students will hear back. Our guide to student voice and shared decisions explains how feedback, representation and partnership can contribute at different stages. The useful output is a documented decision and follow-up question.

How student feedback analysis connects

For an aggregate course review, we suggest coding open-text feedback around the specific participation question. Possible categories might include access to materials, teaching activities and timetabling, but test them against the comments before adopting them. Keep the survey prompt, respondent group and collection period attached to each set of themes. Do not treat a theme's frequency as the proportion of all students experiencing a problem.

Agree the boundary between this review and individual support work. Jisc's code warns about re-identification when datasets are combined and recommends restricting access to people with a legitimate need. Our student comment governance checklist adds practical questions about redaction, category definitions and traceability. A course-level theme can inform a teaching discussion without being attached to a named student's attendance record.

FAQ

Q: What should a university team do now?

A: Choose an engagement measure already used in a decision. Review its meaning with students, identify missing context and agree how feedback will reach the team able to respond. Check whether the resulting action addresses what students described.

Q: Does this change requirements across the UK?

A: No. The RAISE account is commentary, not a policy announcement. The separate Jisc code addresses UK educational institutions; local teams should distinguish its recommendations from their own institutional rules.

Q: How should student voice influence the interpretation of analytics?

A: Invite students to question what a measure means and discuss the response it prompts. Jisc's code recommends a route to understand, question or correct AI-generated interpretations. Our recommendation is to record disagreement as well as recurring themes when reviewing feedback.

References

[Jisc]: "What are we really measuring when we measure student engagement?" Published: 2026-09-25

[Jisc]: "Code of practice for learning analytics" Published: 2015-06-04; updated: 2026-09-09