Feature

Understand how student experience differs across groups

Analyse student feedback by demographic group so teams can see where experience differs and which evidence supports action.

Student Voice Analytics can analyse open-text comments by supplied demographic fields such as sex, ethnicity, disability, age, study mode, or other institution-approved groupings. The result is a clearer view of where themes and sentiment differ.

Discuss your survey

Discuss the source data, reporting question, outputs and delivery window.

Who this is for

EDI teams, student experience teams, planning teams, and quality leads.

Why it matters

Aggregate comment analysis can hide differences in experience. If some groups report different barriers or stronger sentiment, teams need evidence that is structured enough to act on and careful enough to interpret responsibly.

What teams get

Find differences in the words students use

Compare themes, sentiment, and examples across demographic groups without relying only on headline quantitative gaps.

Support EDI and quality work with evidence

Give teams a stronger basis for discussing inclusive practice, barriers to belonging, and targeted action.

Keep interpretation grounded

Small groups and sensitive fields need careful handling. Outputs can be framed with context, thresholds, and human review.

How it works

Agree which demographic fields can be used for analysis and reporting.
Classify comments and calculate theme and sentiment patterns by group.
Flag differences in volume, tone, and recurring issues.
Prepare summaries and evidence for the appropriate internal audience.

Outputs

Demographic theme and sentiment tables.
Evidence summaries for EDI and quality groups.
Comment examples reviewed before wider circulation.
Pointers to areas needing deeper local investigation.

Governance and evidence quality

Agree the survey, questions, reporting populations and intended audience before analysis.
Keep category definitions, analysis versions and denominators with the output.
Review relevant comments and ambiguous cases alongside the summary.
Agree data handling, access and the level of detail appropriate for each audience.

FAQs

Which demographic fields can be used?

That depends on the data supplied and approved by the institution. Common examples include sex, ethnicity, disability, age, and study mode.

How are small groups handled?

Small groups should be interpreted with care and may need suppression, aggregation, or additional review depending on institutional policy.

Can demographic analysis include verbatim comments?

Yes, but sensitive extracts should be reviewed and redacted before wider sharing.

See the workflow with your team

Discuss the source data, reporting question and outputs your team needs. Explore the worked example before agreeing the scope and delivery window.