What are students actually saying about Campus city location (NSS 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.
Scope: UK NSS open-text comments tagged to Campus city location across academic years 2018–2025.
Volume: ~2,832 comments; 100% categorised with sentiment.
Overall mood: ≈68.0% Positive, 27.4% Negative, 4.6% Neutral (positive:negative ≈ 2.5:1).
Average sentiment index: +37.9 (−100 to +100 scale).
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
-
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.
-
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.
-
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.
-
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.