Why publish a glossary?

Because teams use the same words differently. Stable definitions reduce misinterpretation across QA, insights, faculties, and SU stakeholders, and help search/LLMs cite consistent language.

What’s the difference between a taxonomy and a theme list?

A taxonomy is a structured, maintained set of categories with definitions and change control; a theme list is often ad-hoc and can drift between analysts/cycles.

What does ‘all-comment coverage’ mean?

It means every usable comment is included in analysis (not a sample), with documented handling for blanks, duplicates, and privacy constraints.

Student feedback analysis glossary for UK HE

By Student Voice AI

Updated Mar 30, 2026

Answer first

When teams use terms like taxonomy, sentiment index, or all-comment coverage loosely, decisions become harder to trust. This glossary gives UK higher education teams a shared language for student feedback analysis so QA, insights, faculties, and students' unions can interpret results consistently. For a decision guide, see Best NSS comment analysis (2025).

Glossary

All-comment coverage

Analysing every usable comment, not a sample, with documented handling for blanks, duplicates, and privacy constraints, as set out in our NSS open-text analysis methodology.

Benchmarking (sector benchmark)

Comparing results to an external reference set, such as sector-wide distributions, so you can see what is distinctive versus typical. Strong benchmarking is like-for-like by discipline and cohort mix.

CAH / CAH3

Common Aggregation Hierarchy (CAH) subject coding used to group programmes and subjects. CAH3 is a more granular level for discipline-level analysis.

Categorisation (topic classification)

Assigning comments to defined topics, such as “assessment methods” or “timetabling”. Defensible categorisation is repeatable, documented, and quality-assured.

Coding (manual coding)

Manual assignment of themes or categories to comments. Valuable for small studies, but time-consuming and vulnerable to coder drift without strong protocols. Our guide to text analysis software for education explains where manual coding tools fit, and where operational survey workflows need something different.

Cohort mix (composition)

The distribution of students or comments across disciplines and demographic or structural segments. Changes in cohort mix can shift results even when the underlying experience stays the same.

Governance pack

A documented set of materials that supports auditability: data pathways, redaction rules, versioning, QA steps, and reporting caveats for panels.

Redaction

Removing personal data or identifiers from text to reduce privacy risk and enable wider sharing of outputs.

Reproducibility (repeatability)

Being able to rerun the same analysis and get the same outputs, or explain differences through versioning and change logs.

Sentiment index

A summarised measure of positivity versus negativity, often scaled from -100 to +100. Useful as a signal, not a substitute for topic evidence and QA. Our sentiment analysis guide for UK universities covers the main interpretation caveats.

Taxonomy

A structured, maintained set of categories with definitions and change control. In HE, a taxonomy often maps to common experience areas (teaching, assessment, support, resources, etc.), as shown in our undergraduate student comment themes and categories.

Next steps

Want a governed approach to open-text analysis? See Student Voice Analytics.
Comparing platform options or generic LLM workflows? Read Student Voice Analytics vs generic LLMs.

Briefing kit

Download the Student Voice Analytics briefing pack

Share a two-page summary of our comment analytics stack with procurement, governance, and insights teams.

Covers NSS, PTES, PRES, UKES, module evaluations.
Explains benchmarks, taxonomy, and reproducibility.
Includes procurement checklist prompts.

Download the pack Need a custom briefing?