What are students actually saying about Group size SSRs (NSS 2018–2025)?
Students are, on the whole, positive about group sizes and student–staff ratios. Two-thirds of comments are positive, but there are clear pockets where the experience dips — notably among part-time and mature students, and in a few subject areas.
Scope: UK NSS open-text comments for Group size SSRs across academic years 2018–2025.
Volume: ~1,605 comments; 100% assigned to this topic with sentiment.
Overall mood: 66.8% Positive, 29.7% Negative, 3.6% Neutral (positive:negative ≈ 2.3:1). Sentiment index: +29.6.
What students are saying in this category
- The tone is broadly positive: students frequently report manageable class sizes and good access to staff. The overall sentiment index sits at +29.6, reflecting substantially more positive than negative statements.
- Mode matters. Full-time students are positive (index +31.2), while part-time students report a near net-negative experience (−2.4). Apprenticeships are very positive (+44.1) but on a small base (n=5).
- Demographic differences are material. Disabled students are notably positive (+35.9) versus those not disabled (+28.3). Female students report a stronger tone (+34.2) than male students (+20.9). Non‑UK domiciled students are less positive (+16.4) than UK groups.
- Subject patterns vary. Languages and area studies (+46.5), geography/earth/environment (+41.8), and design/creative (+38.1) are strong. Computing is neutral to slightly negative (−0.6), physical sciences is muted (+4.4), and combined/general studies is notably negative (−21.6). Treat small bases with care when interpreting extremes.
Trend & segmentation (2018–2025)
Key segments by tone and volume
| Segment |
N |
Positive % |
Negative % |
Sentiment idx |
| Full-time |
1,492 |
68.1 |
28.4 |
31.2 |
| Part-time |
70 |
40.0 |
57.1 |
-2.4 |
| Apprenticeship |
5 |
80.0 |
20.0 |
44.1 |
| Young (age) |
1,370 |
68.1 |
28.2 |
31.2 |
| Mature (age) |
197 |
58.4 |
39.1 |
19.2 |
| Female |
1,020 |
70.5 |
26.3 |
34.2 |
| Male |
544 |
59.9 |
36.0 |
20.9 |
| Disabled |
282 |
72.3 |
23.0 |
35.9 |
| Not disabled |
1,286 |
65.6 |
31.1 |
28.3 |
| Not UK domiciled |
132 |
55.3 |
40.2 |
16.4 |
By CAH broad area (top 8 by volume)
| CAH area (broad) |
N |
Positive % |
Negative % |
Sentiment idx |
| Unknown CAH area |
493 |
78.9 |
18.9 |
42.3 |
| CAH02 – Subjects allied to medicine |
175 |
67.4 |
28.6 |
29.8 |
| CAH01 – Medicine and dentistry |
113 |
66.4 |
30.1 |
31.1 |
| CAH15 – Social sciences |
111 |
56.8 |
37.8 |
17.0 |
| CAH17 – Business and management |
92 |
55.4 |
39.1 |
18.0 |
| CAH20 – Historical, philosophical and religious studies |
72 |
69.4 |
26.4 |
34.0 |
| CAH03 – Biological and sport sciences |
67 |
62.7 |
37.3 |
17.3 |
| CAH19 – Language and area studies |
59 |
76.3 |
20.3 |
46.5 |
Note: Smaller areas show sharp variation (e.g., Combined/General −21.6; Computing −0.6), but volumes are modest.
What this means in practice
- Protect small-group access in higher‑risk segments
- Set explicit caps for seminars/tutorials on part‑time routes and mature-heavy cohorts; monitor breach rates weekly.
- Pre‑assign reserve facilitators to avoid last‑minute group merges.
- Measure actuals, not just plans
- Capture headcount and staff present per session; publish “planned vs actual” group size summaries by module.
- Escalate when thresholds are exceeded (e.g., >10% over cap for two consecutive weeks).
- Timetable design for SSR stability
- Offer parallel seminar streams with clear capacity; split oversubscribed groups quickly rather than adding seats.
- Prefer more, shorter contact points over fewer, crowded ones where space/staffing allow.
- Targeted support for specific cohorts
- Part-time: ensure equivalent tutorial availability and predictable scheduling.
- Non‑UK domiciled students: set clear expectations about small‑group learning and access routes to staff; signpost early.
- Close the loop visibly
- Provide a simple way for students to flag overcrowding; acknowledge within 48 hours and report fixes by cohort.
How Student Voice Analytics helps you
- Shows how student–staff ratio and group-size comments move over time, with drill‑downs from provider to school/department, programme, and cohort.
- Like‑for‑like comparisons by CAH code and by demographics (age, domicile, mode, site/campus), plus segmentation for apprenticeships and part‑time routes.
- Produces concise, anonymised summaries you can share with programme teams and timetabling/staffing leads; export-ready tables and briefings.
Data at a glance (2018–2025)
- Volume: 1,605 comments; 100% with sentiment.
- Overall mood: 66.8% Positive, 29.7% Negative, 3.6% Neutral; index +29.6 (≈2.3:1 positive:negative).
- Strong segments: Disabled (+35.9), Female (+34.2), Full‑time (+31.2); Languages & area studies (+46.5), Geography/Earth/Environment (+41.8), Design/Creative (+38.1).
- Weaker segments: Part‑time (−2.4), Non‑UK domiciled (+16.4), Combined/General (−21.6), Computing (−0.6). Treat small bases with care.