Student Voice Analytics for Applied Psychology — UK student feedback 2018–2025
Scope. UK NSS open-text comments for Applied Psychology (CAH04-01-02) across academic years 2018–2025.
Volume. ~530 comments; 99.1% successfully categorised to a single primary topic.
Overall mood. Roughly 51.6% Positive, 45.9% Negative, 2.5% Neutral (positive:negative ≈ 1.12:1).
What students are saying
Applied Psychology students talk most about assessment, the teaching itself, and the shape of the curriculum. The most-mentioned topic is Feedback (8.6% share) and it carries a distinctly negative tone (index −33.2), more negative than the sector on the same issue. Closely related categories—Marking criteria (index −49.4) and Assessment methods (−26.8)—reinforce a clear signal: students want transparent criteria, examples of good work, consistent marking, and predictable turnaround.
Set against that, the core teaching experience is a strength. Comments about Teaching Staff are strongly positive (index +43.7, above sector), with students recognising clarity, encouragement and expertise. Delivery of teaching is also positive (+21.5, well above sector), and students speak favourably about the Type and breadth of course content (+25.6) and Module choice/variety (+24.2). Library access is appreciated (+26.6), while general Learning resources are modestly positive.
Operational delivery is mixed. Scheduling/timetabling (−27.1) and Organisation and management of the course (−19.3) attract negative sentiment, and Workload (−34.3) also features in the conversation. Communication about course and teaching is still negative (−27.3) but notably less so than the sector. Remote learning is mildly positive (+5.5) and more positive than the sector benchmark. Placements/fieldwork/trips appear in a smaller share (4.0%) and sit just above neutral on tone (+6.2), though slightly below the sector’s sentiment baseline.
Support narratives are split. Students praise the Availability of teaching staff (+44.0) and Personal Tutor interactions (+22.3), yet general Student support is a net negative (−21.8) and below sector. This pattern suggests that while one-to-one support feels strong, broader support processes and signposting may be harder to navigate.
Finally, external disruption weighs on sentiment: Strike Action (7.4% share, index −62.6) and COVID-19 (−45.8) are both prominent and negative. Student life is only slightly positive (+4.3) and sits well below sector tone for this topic.
Top categories by share:
| Category | Section | Share % | Sector % | Δ pp | Sentiment idx | Δ vs sector |
|---|---|---|---|---|---|---|
| Feedback | Assessment and feedback | 8.6 | 7.3 | 1.3 | −33.2 | −18.1 |
| Teaching Staff | The teaching on my course | 8.2 | 6.7 | 1.4 | +43.7 | +8.1 |
| Type and breadth of course content | Learning opportunities | 8.2 | 6.9 | 1.3 | +25.6 | +3.0 |
| Strike Action | Others | 7.4 | 1.7 | 5.7 | −62.6 | +0.4 |
| Delivery of teaching | The teaching on my course | 7.0 | 5.4 | 1.6 | +21.5 | +12.7 |
| Marking criteria | Assessment and feedback | 4.8 | 3.5 | 1.2 | −49.4 | −3.7 |
| Module choice / variety | Learning opportunities | 4.6 | 4.2 | 0.4 | +24.2 | +6.8 |
| Student support | Academic support | 4.0 | 6.2 | −2.2 | −21.8 | −35.0 |
| Placements/ fieldwork/ trips | Learning opportunities | 4.0 | 3.4 | 0.6 | +6.2 | −5.6 |
| Student life | Learning community | 3.2 | 3.2 | 0.1 | +4.3 | −27.8 |
Most negative categories (share ≥ 2%)
| Category | Section | Share % | Sector % | Δ pp | Sentiment idx | Δ vs sector |
|---|---|---|---|---|---|---|
| Strike Action | Others | 7.4 | 1.7 | 5.7 | −62.6 | +0.4 |
| Marking criteria | Assessment and feedback | 4.8 | 3.5 | 1.2 | −49.4 | −3.7 |
| COVID-19 | Others | 2.3 | 3.3 | −1.1 | −45.8 | −12.9 |
| Workload | Organisation and management | 2.3 | 1.8 | 0.4 | −34.3 | +5.7 |
| Feedback | Assessment and feedback | 8.6 | 7.3 | 1.3 | −33.2 | −18.1 |
| Scheduling/ timetabling | Organisation and management | 2.9 | 2.9 | 0.0 | −27.1 | −10.6 |
| Assessment methods | Assessment and feedback | 2.9 | 3.0 | −0.1 | −26.8 | −3.1 |
Most positive categories (share ≥ 2%)
| Category | Section | Share % | Sector % | Δ pp | Sentiment idx | Δ vs sector |
|---|---|---|---|---|---|---|
| Teaching Staff | The teaching on my course | 8.2 | 6.7 | 1.4 | +43.7 | +8.1 |
| Type and breadth of course content | Learning opportunities | 8.2 | 6.9 | 1.3 | +25.6 | +3.0 |
| Library | Learning resources | 2.1 | 1.8 | 0.3 | +26.6 | −0.1 |
| Career guidance, support | Learning community | 2.3 | 2.4 | −0.1 | +25.2 | −4.9 |
| Module choice / variety | Learning opportunities | 4.6 | 4.2 | 0.4 | +24.2 | +6.8 |
| Personal Tutor | Academic support | 2.1 | 3.2 | −1.1 | +22.3 | +3.6 |
| Delivery of teaching | The teaching on my course | 7.0 | 5.4 | 1.6 | +21.5 | +12.7 |
What this means in practice
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Make assessment clarity non‑negotiable. Publish annotated exemplars, checklist-style rubrics, and clear grade descriptors; set a realistic feedback SLA and communicate when marks are sampled or moderated. This directly targets the pain points in Feedback, Marking criteria and Assessment methods.
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Protect the operational rhythm. Name an owner for timetabling and organisation, keep a single source of truth for course communications, and issue a concise weekly “what changed and why” update. These moves address Scheduling, Organisation and Comms in one go.
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Double down on teaching strengths. Students value the people and the delivery; keep that visible with co-taught sessions, structured signposting in lectures, and simple “what to expect next week” previews. Use those touchpoints to signpost support pathways, closing the gap between highly rated staff access and weaker experiences of general Student support.
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Where placements/fieldwork exist, treat them as designed experiences: confirm site capacity before release, provide pre‑briefs and local orientation, and build in short feedback moments on site.
Data at a glance (2018–2025)
- Top topics by share: Feedback (8.6%), Teaching Staff (8.2%), Type and breadth of course content (8.2%), Strike Action (7.4%), Delivery of teaching (7.0%).
- Assessment & feedback cluster (Feedback, Marking criteria, Assessment methods, Dissertation): ~18.0% of all comments, with predominantly negative tone.
- Delivery & ops cluster (Placements, Scheduling, Organisation & management, Comms, Remote learning): ~14.0% of comments, mixed tone (remote learning above sector; scheduling and organisation below).
- People & growth cluster (Personal Tutor, Student support, Teaching Staff, Availability of staff, Delivery of teaching, Personal development, Student life): ~27.5% of comments, generally positive.
- How to read the numbers. Each comment is assigned one primary topic; share is that topic’s proportion of all comments. Sentiment is calculated per sentence and summarised as an index from −100 (more negative than positive) to +100 (more positive than negative), then averaged at category level. This file includes 1,122 labelled sentences from 1,192 total; 99.1% of comments were classified.
How Student Voice Analytics helps you
Student Voice Analytics turns open-text survey comments into clear, prioritised actions. It tracks topics and sentiment over time, so programme and school teams can see where assessment clarity, operations, and teaching delivery are helping or hindering the student experience.
It supports whole‑institution oversight as well as fine‑grained department and school analysis. The platform produces concise, anonymised summaries and representative comments for partners and programme teams, so you can brief stakeholders without trawling through thousands of responses. Most importantly, it enables like‑for‑like sector comparisons across CAH codes and by demographics (e.g., year of study, domicile, mode of study, campus/site, commuter status). You can segment by site/provider, cohort and year to pinpoint where to intervene, and export-ready outputs (web, deck, dashboard) make it straightforward to share priorities and progress across the institution.
