What are students actually saying about Scheduling timetabling (NSS 2018–2025)?
Students most often describe timetable instability and short‑notice changes. The tone is strongly negative overall, concentrated among full‑time and younger students, while part‑time students report markedly better experiences. Fastest wins: lock schedules earlier, run clash‑detection across modules, publish a single source of truth with a change log, and protect minimum notice periods.
Scope: UK NSS open‑text comments tagged to Scheduling timetabling across academic years 2018–2025.
Volume: ~10,686 comments (~2.8% of all comments in our dataset); 100% with sentiment.
Overall mood: ≈34.4% Positive, 60.3% Negative, 5.3% Neutral (positive:negative ≈ 0.6:1; sentiment index −12.2).
What students are saying in this category
The balance of comments is negative, suggesting frequent disruption, clashes or late communication around timetables. Both women and men report a similar tone (index −12.2 for each), indicating the issue is systemic rather than gender‑specific.
Mode and life stage matter. Full‑time students contribute nearly two‑thirds of these comments and are strongly negative (index −30.5; 19% positive vs 75% negative). Part‑time students are a clear outlier in the other direction (index +25.3), implying that clearer patterns and fewer clashes in part‑time routes may be protective. Younger students are notably negative (index −25.7), while mature students are mildly positive (index +8.3).
There is subject variation. Particularly negative tones appear in veterinary sciences (−46.8) and medicine & dentistry (−33.5). More positive pockets include combined & general studies (+24.8) and psychology (+13.6). Across ethnic groups the tone leans negative, from −9.1 (White) to −29.4 (Not UK domiciled). Small segments (e.g., apprenticeships, very small subject areas) can be volatile and should be interpreted with care.
Segments at a glance (share and tone)
Mode of study
| Mode | Share % | n | Pos % | Neg % | Sentiment idx |
|---|---|---|---|---|---|
| Full‑time | 64.5 | 6894 | 19.0 | 75.3 | −30.5 |
| Part‑time | 31.7 | 3391 | 65.1 | 30.3 | +25.3 |
| Apprenticeship | 0.4 | 41 | 9.8 | 85.4 | −39.7 |
Age
| Age group | Share % | n | Pos % | Neg % | Sentiment idx |
|---|---|---|---|---|---|
| Young | 58.4 | 6243 | 23.0 | 71.2 | −25.7 |
| Mature | 38.4 | 4101 | 51.0 | 44.3 | +8.3 |
Notes: Sentiment index ranges from −100 to +100. Rows with “Unknown/Unspecified” are omitted for clarity.
What this means in practice
- Set a timetable “freeze window” and a visible change log
- Publish earlier; give a minimum notice period for any change.
- Summarise weekly “what changed and why” in one channel that students actually use.
- Run clash‑detection before publishing
- Check across modules, rooms, staff, cohorts and assessment deadlines.
- Stress‑test full‑time patterns specifically (the most negative group).
- Protect high‑risk groups from disruption
- For full‑time and younger students, prioritise fixed days/blocks to reduce commute and childcare conflicts.
- When changes are unavoidable, offer an immediate mitigation (recording, alternative slot, remote access) with clear instructions.
- Standardise how changes are communicated
- One source of truth; timestamps on updates; no parallel/conflicting messages.
- Include room details, delivery mode, and links in the same place every time.
- Track operations with simple KPIs
- Schedule changes per 100 students; median notice period; same‑day cancellation rate; clash rate before/after publication; time‑to‑fix.
- Lift and spread what works in part‑time routes (+25.3) into full‑time timetables where feasible.
How Student Voice Analytics helps you
- Surfaces timetable‑related comments and sentiment over time, with drill‑downs from provider to school/department and programme.
- Like‑for‑like comparisons by subject clusters (CAH), demographics, mode, campus/site and cohort.
- Compact, anonymised summaries ready for programme and timetabling teams, with export/share options for boards and quality committees.
Data at a glance (2018–2025)
- Volume: 10,686 comments (100% with sentiment); ≈2.8% of all comments.
- Overall tone: 34.4% Positive, 60.3% Negative (index −12.2; ≈0.6:1 positive:negative).
- Notable contrasts: Full‑time (−30.5) vs Part‑time (+25.3); Young (−25.7) vs Mature (+8.3). Subject pockets range from veterinary (−46.8) and medicine/dentistry (−33.5) to combined & general (+24.8) and psychology (+13.6).
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