What UK Students Say About Accommodation: NSS Feedback Analysis (481 Comments, 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.

Key findings

481 comments analysed across UK programmes (2018–2025)
The topic is raised mainly by young and full-time students (≈87.1% young; 94.2% full-time).
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 rem...

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).

How to use this data

This page presents sector-level student feedback analysis for the Accommodation 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.

Recommended next steps

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