What are students actually saying about Library (NSS 2018–2025)?
Students are broadly positive about the library. Two-thirds of comments are positive, with a healthy sentiment index and clear variation by student group and subject.
Scope: UK NSS open-text comments for Library across academic years 2018–2025.
Volume: ~6,731 comments; 100% assigned a sentiment.
Overall mood: 65.0% Positive, 33.1% Negative, 1.8% Neutral (≈1.96:1 positive:negative; sentiment index +30.1).
What students are saying in this category
- Overall tone is positive (+30.1), with low neutrality (1.8%). Most comments come from full-time (80.9%) and younger students (72.8%).
- Differences by demographic are consistent: younger students (index +33.1) are more positive than mature (+24.6); full-time (+32.2) more positive than part-time (+24.1); males (+35.6) more positive than females (+28.1). Students reporting a disability are somewhat less positive (+27.0) than those not reporting a disability (+31.9).
- By ethnicity (as recorded), “Not UK domiciled” stands out as very positive (+51.1). White students are positive overall (+28.2), with stronger tones among Black (+37.3), Mixed (+35.5) and Asian (+30.6) groups.
- Subject patterns vary. Positive outliers include Computing (+47.3; n=181), Subjects allied to medicine (+43.9; n=616) and Engineering (+39.4; n=234). Lower indices appear in Language and area studies (+20.5; n=279) and Combined and general studies (+10.7; n=199). Very small groups can show extreme values.
Segment benchmarks (selected)
| Segment | Comments | Positive % | Negative % | Sentiment idx |
|---|---|---|---|---|
| Overall | 6,731 | 65.0 | 33.1 | 30.1 |
| Age — Young | 4,897 | 66.9 | 31.2 | 33.1 |
| Age — Mature | 1,618 | 60.8 | 37.5 | 24.6 |
| Mode — Full-time | 5,448 | 66.3 | 31.8 | 32.2 |
| Mode — Part-time | 1,026 | 60.6 | 37.5 | 24.1 |
| Sex — Female | 4,044 | 63.4 | 35.0 | 28.1 |
| Sex — Male | 2,466 | 68.6 | 29.0 | 35.6 |
| Disability — Not disabled | 5,263 | 66.0 | 32.2 | 31.9 |
| Disability — Disabled | 1,256 | 62.7 | 35.2 | 27.0 |
| Ethnicity — Not UK domiciled | 487 | 80.9 | 18.5 | 51.1 |
| Ethnicity — White | 4,722 | 62.9 | 35.2 | 28.2 |
| Ethnicity — Asian | 532 | 66.7 | 31.0 | 30.6 |
| Ethnicity — Black | 247 | 70.9 | 26.3 | 37.3 |
Subject patterns (CAH1) — largest groups by volume
| Subject group (CAH1) | Comments | Positive % | Negative % | Sentiment idx |
|---|---|---|---|---|
| Unknown | 1,403 | 63.5 | 34.2 | 29.5 |
| Social sciences | 774 | 64.5 | 34.5 | 28.1 |
| Subjects allied to medicine | 616 | 74.8 | 24.4 | 43.9 |
| Business and management | 538 | 67.7 | 30.5 | 33.6 |
| Historical, philosophical and religious studies | 537 | 61.3 | 36.9 | 25.4 |
| Law | 383 | 63.4 | 33.4 | 29.4 |
| Psychology | 317 | 65.9 | 31.2 | 31.2 |
| Language and area studies | 279 | 56.3 | 41.9 | 20.5 |
| Engineering and technology | 234 | 73.1 | 25.6 | 39.4 |
| Combined and general studies | 199 | 52.8 | 47.2 | 10.7 |
What this means in practice
- Close the experience gap for mature and part-time students. Prioritise access routes that work outside typical hours and reduce friction for time‑poor learners; check whether service touchpoints (help channels, inductions, updates) are equally visible and usable for these groups.
- Target subject areas with lower sentiment. Partner with schools in Language and area studies and Combined/general to review core needs (e.g., resource discoverability, availability, skills support) and set small, measurable fixes.
- Sustain and spread what works. Capture practices from higher‑scoring areas (e.g., Computing, Subjects allied to medicine, Engineering) and replicate where appropriate.
- Improve accessibility for disabled students. Validate the end‑to‑end journey (physical spaces, digital platforms, assistive technologies, staff confidence) and publicise adjustments clearly.
- Keep a simple feedback loop. Publish a short “you said, we did” by segment/subject and track the sentiment index quarterly to evidence change.
How Student Voice Analytics helps you
- Turns all NSS open-text into topic and sentiment metrics for Library, with drill‑downs by school/department (CAH), demographics, and mode/campus/site.
- Surfaces where tone diverges (e.g., mature vs young; part‑time vs full‑time; specific subject groups), with export‑ready summaries for quick briefing.
- Enables like‑for‑like comparisons across CAH codes and demographics, plus segmentation by cohort or site to prioritise actions and monitor impact over time.
Data at a glance (2018–2025)
- Volume: ~6,731 Library comments; 100% with sentiment.
- Overall mood: 65.0% Positive, 33.1% Negative, 1.8% Neutral (index +30.1).
- Composition (share of Library comments): Full-time 80.9%, Part-time 15.2%; Young 72.8%, Mature 24.0%.
Subject specific insights on "library"
