What UK Students Say About Campus, City and Location: NSS Feedback Analysis (2,832 Comments, 2018–2025)

Students are broadly positive about the campus city/location experience. Tone is strongly favourable overall, but less so for part-time and mature cohorts, and lower for some subject areas.

Average sentiment index: +37.9 (−100 to +100 scale).

Key findings

  • 2,832 comments analysed across UK programmes (2018–2025)
  • Location is a net positive across the dataset: two-thirds of comments are upbeat; full-time students are particularly positive.
  • Part-time students are notably more negative on this topic (index −2.5), and mature students are positive but less so than younger students (+18.4 vs +41.9).

What students are saying in this category

  • Location is a net positive across the dataset: two-thirds of comments are upbeat; full-time students are particularly positive.
  • Part-time students are notably more negative on this topic (index −2.5), and mature students are positive but less so than younger students (+18.4 vs +41.9).
  • Ethnicity differences are visible: Not UK domiciled students are very positive (+49.5), while Black students are less positive (+17.6).
  • By subject area (CAH1), sentiment varies: historical/philosophical/religious studies and law are highly positive; subjects allied to medicine and psychology are lower.

Segments at a glance (2018–2025)

Key cohorts

Segment Comments Positive % Negative % Sentiment idx
All students 2,832 68.0 27.4 37.9
Full-time 2,576 70.0 25.5 40.9
Part-time 180 38.3 56.1 -2.5
Young 2,327 70.6 24.8 41.9
Mature 450 53.8 41.6 18.4

Subject area (CAH1) — segments with ≥85 comments

Subject area (CAH1) Comments Sentiment idx Positive % Negative %
(CAH20) historical, philosophical and religious studies 121 53.8 75.2 18.2
(CAH16) law 129 45.9 72.9 20.2
(CAH01) medicine and dentistry 96 44.3 68.8 26.0
(CAH19) language and area studies 85 42.7 70.6 28.2
(CAH03) biological and sport sciences 125 42.6 71.2 20.8
(CAH10) engineering and technology 144 41.3 69.4 27.1
(CAH15) social sciences 310 39.9 70.0 27.4
(CAH11) computing 129 37.6 69.8 24.8
(CAH17) business and management 267 36.7 67.4 25.5
(CAH04) psychology 119 29.1 63.0 33.6
(CAH02) subjects allied to medicine 226 19.1 55.8 42.0

Notes:

  • Disability status shows no overall gap on this topic (index +38.0 for both disabled and not disabled).
  • Small-N subgroups (e.g., apprenticeship, “other sex”) should be interpreted cautiously.

What this means in practice

  1. Focus on part-time and mature experiences

    • Run a quick location-access audit for evening/weekend patterns (transport links, parking, lighting, entrance routes, wayfinding).
    • Provide concise “commuter essentials” pages in course handbooks and induction (last-bus times, late-opening spaces, nearest secure study areas).
    • Monitor this segment’s sentiment quarterly to check if changes shift tone.
  2. Reduce variation between subject areas

    • Pair lower-scoring areas (e.g., subjects allied to medicine, psychology) with higher-scoring peers (e.g., law, historical studies) to share what works locally (maps, placements/clinic adjacency, city partnerships).
    • Create a standard “city orientation pack” each school can localise: 10-minute walk maps, safe routes, cost/time comparisons for travel modes.
  3. Close ethnicity gaps

    • Convene diverse student panels to review location touchpoints (routes, transport hubs, safety, belonging in city spaces) and prioritise fixes.
    • Make reporting/feedback channels easy to find and act on issues promptly; publish “you said, we did” for location topics.
  4. Keep strengths visible

    • Where sentiment is already high, capture the enabling practices (clear local information, convenient facilities, community links) and scale them.

How Student Voice Analytics helps you

  • Track this category’s topic and sentiment over time and by segment (mode, age, ethnicity, subject area, site/campus).
  • Drill from provider level to schools/departments; export concise, anonymised summaries for quick briefings.
  • Like-for-like comparisons across CAH codes and demographics; segment by cohort or campus to target local improvements.
  • Share export-ready tables and charts with programme and professional services teams.

How to use this data

This page presents sector-level student feedback analysis for the Campus, City and Location category (Others), with demographic and subject-area benchmarks you can reference directly in institutional documents.

Use this for

  • Annual Programme Review (APR) — reference the segment benchmarks to contextualise your programme's feedback patterns against the sector.
  • TEF and quality enhancement — cite the demographic breakdowns and subject-area sentiment as evidence of awareness of differential student experience.
  • Equality, diversity and inclusion (EDI) — use the ethnicity, disability and age segment data to evidence where feedback experience differs by student group.
  • Staff-Student Liaison Committees (SSLCs) — share the key findings and subject-area table as discussion starters with student representatives.
  • Action planning — use the "What this means in practice" recommendations as a starting point for targeted interventions.

Common subject areas linked to this theme (on our blog)

Most-read posts in this category

Recommended next steps

  1. Quantify: how often does this theme appear (and where)?
  2. Segment: by discipline (CAH/HECoS), level, mode, and cohort where appropriate.
  3. Benchmark: compare like-for-like to avoid cohort-mix artefacts.
  4. Act: define 1–3 changes, then track whether the theme shifts next cycle.

Cite this page

Student Voice AI (2025). "Campus, City and Location: NSS student feedback analysis (2018–2025)." Student Voice AI. https://www.studentvoice.ai/category/campus-city-location/

Subject specific insights on "campus city location"

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