What are students actually saying about Accommodation (NSS 2018–2025)?
Students who comment on accommodation are predominantly critical. Around two-thirds of sentences are negative, and the overall sentiment index sits in firmly negative territory.
Scope: UK NSS open-text comments tagged to Accommodation across academic years 2018–2025.
Volume: 481 comments; 100.0% with sentiment analysis coverage.
Overall mood: 27.4% Positive, 67.2% Negative, 5.4% Neutral (positive:negative ≈ 0.41:1; sentiment index −23.2).
What are students saying in this category?
- The topic is raised mainly by young and full-time students (≈87.1% young; 94.2% full-time). Their tone is notably negative (full-time index −25.0; young −24.1), whereas mature students are less negative (−12.8). A small part-time group is net positive (+27.2; n=20).
- There is no major difference by sex (Female −24.1; Male −21.6). Disabled students are slightly less negative than non-disabled (−18.6 vs −24.1), but both remain critical overall.
- By ethnicity, negativity is broad-based. Not UK-domiciled students are more negative (−28.5) than White (−23.1) and Asian (−20.1) groups, while the Black group is comparatively less negative (−16.9). Smaller groups show more volatility.
- Subject mix matters. Among larger cohorts, Psychology (−33.2) and Medicine & Dentistry (−33.7) are most negative, while Law (−10.6) and Business & Management (−19.4) are less negative. This suggests different expectations or experiences of the accommodation offer across disciplines.
Segment snapshot (2018–2025)
| Segment |
Group |
n |
Pos % |
Neg % |
Sentiment idx |
| Age |
Young |
419 |
27.2 |
67.5 |
−24.1 |
| Age |
Mature |
54 |
31.5 |
61.1 |
−12.8 |
| Mode |
Full-time |
453 |
26.5 |
68.2 |
−25.0 |
| Mode |
Part-time |
20 |
55.0 |
35.0 |
27.2 |
| Disability |
Not disabled |
360 |
26.4 |
67.8 |
−24.1 |
| Disability |
Disabled |
113 |
31.9 |
63.7 |
−18.6 |
| Sex |
Female |
269 |
27.5 |
66.5 |
−24.1 |
| Sex |
Male |
199 |
27.6 |
67.8 |
−21.6 |
Subject variation (CAH groups with 20+ comments)
| Subject group (CAH1) |
n |
Sentiment idx |
| Social sciences (CAH15) |
54 |
−24.9 |
| Business and management (CAH17) |
31 |
−19.4 |
| Historical, philosophical and religious studies (CAH20) |
30 |
−22.7 |
| Psychology (CAH04) |
28 |
−33.2 |
| Engineering and technology (CAH10) |
28 |
−22.0 |
| Law (CAH16) |
28 |
−10.6 |
| Medicine and dentistry (CAH01) |
25 |
−33.7 |
| Computing (CAH11) |
24 |
−27.3 |
Notes: Sentiment index ranges from −100 to +100. Smaller subject groups (e.g., Design/Creative Arts with n=14 at −49.8) can show extreme values and should be interpreted with caution.
What this means in practice
- Focus on the largest and most negative cohorts: target improvements for full-time and young students, especially around arrival and the first term (clear guidance, rapid issue resolution, proactive welfare checks).
- Set clear service standards: publish and track SLAs for accommodation enquiries and repairs (e.g., acknowledgement within 24 hours; first-fix windows), and provide a single, up-to-date channel for status updates.
- Strengthen support for international students: pre-arrival briefings covering contracts, rights, safety, costs, local services, and a 24/7 contact route for urgent issues.
- Close the loop visibly: offer short “issue resolved” summaries to residents and end-of-month dashboards by site, showing open vs closed cases and turnaround times.
- Learn from brighter spots: run short interviews with part-time and less-negative cohorts (e.g., Law, Business) to identify practices worth scaling (communication tone, clarity of information, site management routines).
How Student Voice Analytics helps you
- See accommodation sentiment over time and by segment (age, mode, disability, ethnicity), with drill-down from institution to school/department and site/campus where available.
- Compare like-for-like against relevant peer groups by CAH code and demographics, and track whether targeted actions for specific cohorts (e.g., full-time/young; international) move the needle.
- Produce concise, anonymised summaries for estates, residence managers and student services; export tables and charts for quick briefings.
FAQs
- How is the “sentiment index” calculated?
It is 100 × (P(Positive) − P(Negative)) at sentence level, averaged within the category (range −100 to +100).
- What does “n” represent in the tables?
The count of comments in this category from that segment across 2018–2025.
Data at a glance (2018–2025)
- Volume: 481 comments; 100.0% with sentiment coverage.
- Overall mood: 27.4% Positive, 67.2% Negative, 5.4% Neutral; sentiment index −23.2.
- Concentration: ~87.1% young and 94.2% full-time. Part-time is net positive (+27.2; n=20).
- Subject differences: most negative in Medicine & Dentistry (−33.7) and Psychology (−33.2); less negative in Law (−10.6).