What UK Students Say About COVID-19: NSS Feedback Analysis (12,355 Comments, 2018–2025)
COVID-19 remains a distinctly negative topic in NSS comments. The tone is consistently more critical among younger and full-time students and varies by subject, with some disciplines closer to neutral.
Key findings
- 12,355 comments analysed across UK programmes (2018–2025)
- The overall tone is negative (index −24.0), with more than two-thirds of sentences classed as negative.
- Younger students drive most of the volume (69.4% of comments) and are more negative than mature students (−27.3 vs −16.8).
What are students saying in this category?
- The overall tone is negative (index −24.0), with more than two-thirds of sentences classed as negative.
- Younger students drive most of the volume (69.4% of comments) and are more negative than mature students (−27.3 vs −16.8).
- Full-time students are more negative than part-time (−25.4 vs −19.9). Disabled students are slightly more negative than non-disabled (−25.8 vs −24.0).
- Tone varies by subject. Medicine and dentistry is near neutral (−0.4), while media/journalism (−36.3) and mathematical sciences (−34.2) are among the most negative. Subjects allied to medicine are better than average at −15.9.
Segment snapshot (single-year aggregate)
| Dimension |
Group |
Comments |
Pos % |
Neg % |
Sentiment idx |
| Age |
Young |
8,574 |
26.8 |
70.8 |
−27.3 |
| Age |
Mature |
3,356 |
33.0 |
63.7 |
−16.8 |
| Mode |
Full-time |
9,869 |
28.0 |
69.5 |
−25.4 |
| Mode |
Part-time |
2,036 |
30.7 |
66.0 |
−19.9 |
| Sex |
Female |
7,234 |
29.9 |
67.4 |
−22.6 |
| Sex |
Male |
4,677 |
26.5 |
70.9 |
−27.0 |
| Disability |
Disabled |
2,361 |
27.4 |
69.9 |
−25.8 |
| Disability |
Not disabled |
9,567 |
28.8 |
68.5 |
−24.0 |
| Mode |
Apprenticeship (small base) |
16 |
62.5 |
37.5 |
9.6 |
Subject mix within this topic (examples)
| CAH group |
Comments |
Share % |
Sentiment idx |
| Subjects allied to medicine (CAH02) |
1,539 |
12.5 |
−15.9 |
| Social sciences (CAH15) |
1,095 |
8.9 |
−24.6 |
| Business and management (CAH17) |
760 |
6.2 |
−28.7 |
| Psychology (CAH04) |
755 |
6.1 |
−24.5 |
| Design/creative/performing arts (CAH25) |
667 |
5.4 |
−26.7 |
| Biological and sport sciences (CAH03) |
615 |
5.0 |
−22.3 |
| Medicine and dentistry (CAH01) |
285 |
2.3 |
−0.4 |
| Media, journalism and communications (CAH24) |
138 |
1.1 |
−36.3 |
What this means in practice
- Prioritise disruption-ready delivery
- Keep a simple, pre-agreed playbook for rapid shifts in teaching, assessment and access to resources.
- Maintain a single, up-to-date source of truth for changes; summarise what changed and why.
- Target support where sentiment is lowest
- Younger and full-time cohorts are most negative. Use timely micro-briefings, Q&A sessions and flexible access routes to reduce uncertainty.
- Ensure disability-related adjustments are explicit when arrangements change.
- Lift practice from stronger-performing areas
- Capture what medicine/dentistry and subjects allied to medicine did to keep tone closer to neutral (e.g., continuity of learning and assessment clarity) and adapt it for other disciplines.
- Small but positive apprenticeship feedback suggests value in structured work-integrated rhythms—test which elements scale.
- Make subject-level pain points visible
- For the most negative subjects (e.g., media/journalism, mathematical sciences), run short, time-bound reviews of assessment clarity, workload pacing and access to specialist activities, then publish specific fixes.
How Student Voice Analytics helps you
- Track topic volume and sentiment over time, then drill down from institution to school/department, cohort and site.
- Compare like-for-like across CAH groups and demographics (age, domicile, mode, commuter status), and segment by campus or provider.
- Generate concise, anonymised summaries and export tables/figures for rapid briefing to programme and quality teams.
Data at a glance (2018–2025)
- Volume: 12,355 COVID-19 comments; 100.0% sentiment coverage.
- Overall mood: 28.7% Positive, 68.6% Negative, 2.7% Neutral (index −24.0).
- Cohort contrasts: young −27.3 vs mature −16.8; full-time −25.4 vs part-time −19.9; female −22.6 vs male −27.0; disabled −25.8.
- Subject variation: medicine and dentistry −0.4; subjects allied to medicine −15.9; media/journalism −36.3.