What are students actually saying about Opportunities to work with other students (NSS 2018–2025)?
Students’ views on working with peers are mixed overall: experiences skew slightly negative on balance, but there are clear pockets of strong positivity where collaboration is designed-in and easy to access. Tone varies sharply by age and study mode, suggesting logistics and inclusivity are the main levers.
Scope: UK NSS open-text comments for Opportunities to work with other students across academic years 2018–2025.
Volume: 7,331 comments for this topic (100.0% sentiment coverage); ≈1.9% of all comments in the dataset (385,317 total).
Overall mood: 46.3% Positive, 49.3% Negative, 4.4% Neutral; sentiment index +4.4.
What students are saying in this category
- The balance of comments is close to neutral overall, indicating a split between strong, well-supported peer work and instances where group activity feels hard to organise or sustain.
- Age and mode matter. Younger and full‑time students report notably better experiences (indices +10.2 and +10.4). Mature and part‑time learners skew negative (−9.5 and −12.3), pointing to timetable friction and limited access to peers.
- By sex, men report a more positive tone (+8.8) than women (+1.1). Disabled students sit slightly negative (−0.8) versus those not disabled (+5.6).
- Tone varies widely by subject cluster. Engineering/technology (+26.8) and design/creative (+22.6) are strongly positive; combined/general studies (−16.3), historical/philosophical/religious (−11.6) and law (−11.2) are most negative among larger groups.
Segment differences (selected)
| Segment |
Group |
Comments |
Positive % |
Negative % |
Sentiment idx |
| Overall |
All students |
7,331 |
46.3 |
49.3 |
4.4 |
| Age |
Young |
5,059 |
50.5 |
44.9 |
10.2 |
|
Mature |
2,061 |
35.5 |
60.5 |
-9.5 |
| Mode of study |
Full-time |
5,209 |
50.7 |
44.6 |
10.4 |
|
Part-time |
1,875 |
33.3 |
62.7 |
-12.3 |
| Sex |
Female |
3,985 |
43.7 |
52.3 |
1.1 |
|
Male |
3,121 |
49.4 |
45.7 |
8.8 |
| Disability |
Disabled |
1,230 |
41.6 |
54.3 |
-0.8 |
|
Not disabled |
5,892 |
47.1 |
48.4 |
5.6 |
Notes:
- Two-thirds of comments come from younger students (69.0%); 25.6% are part‑time.
- Very small groups (e.g., “Other sex”, n=8; Apprenticeship, n=24) are not shown above and should be interpreted with caution.
Subject tone spread (CAH1, n≥150; unknown/unspecified excluded)
| Group |
Comments |
Sentiment idx |
| Most positive |
|
|
| (CAH10) Engineering and technology |
650 |
26.8 |
| (CAH25) Design, and creative and performing arts |
347 |
22.6 |
| (CAH02) Subjects allied to medicine |
472 |
10.5 |
| Most negative |
|
|
| (CAH23) Combined and general studies |
319 |
-16.3 |
| (CAH20) Historical, philosophical and religious studies |
220 |
-11.6 |
| (CAH16) Law |
222 |
-11.2 |
What this suggests:
- Where collaboration is built into the course pattern (e.g., studios, labs, projects), tone lifts markedly.
- Generalist or essay-heavy areas risk weaker peer interaction unless deliberately scaffolded.
What this means in practice
- Make collaboration the default, not an optional extra
- Put structured team activity into module timetables (kick‑off, mid‑point, showcase).
- Form groups intentionally (mix skills/backgrounds; balance availability), publish roles, and agree working norms up front.
- Design for time‑poor and off‑pattern learners
- Provide asynchronous routes (discussion boards, shared workspaces, rolling deadlines).
- Offer set “collaboration windows” in evenings/online; publish a simple cross‑cohort matching tool to find partners with compatible schedules.
- Reduce friction and increase accountability
- Create pre‑provisioned digital spaces per group (named channels, folders, templates).
- Use light‑touch peer contribution checks at milestones; include a fair‑minded peer‑assessment component to deter free‑riding.
- Make inclusion visible
- Ensure accessibility (captions, readable docs, hybrid‑ready rooms).
- Offer brief teamwork micro‑skills resources (conflict resolution, delegation, decision‑making) and a clear escalation route.
- Borrow what works
- Ask engineering/creative courses to share patterns (studio hours, crits, project sprints).
- Pilot those patterns in lower‑tone areas with clear outcomes and quick feedback loops.
How Student Voice Analytics helps you
- Shows topic tone and volume over time for this specific category, with drill‑downs by school/department, cohort, campus/site and demographics.
- Benchmarks like‑for‑like across CAH subject groups and student segments (e.g., age, mode, domicile), enabling targeted actions for mature/part‑time learners.
- Produces concise, anonymised briefings for programme teams; exports for boards and quality reviews.
Notes on numbers
- Sentiment index (−100 to +100) is sentence‑weighted; it can diverge from the comment‑level positive/negative split shown above.
- “Unknown” rows are excluded from commentary; very small groups should be treated cautiously.
Data at a glance (2018–2025)
- 7,331 comments on this topic (≈1.9% of all comments); 100.0% sentiment coverage.
- Overall tone near neutral: 46.3% Positive, 49.3% Negative, 4.4% Neutral; index +4.4.
- Biggest gaps: Full‑time vs Part‑time (+22.7 index points), Young vs Mature (+19.7).