Student Voice Analytics for Nursing — UK student feedback 2018–2025

Scope. UK NSS open-text comments for Nursing (CAH02-04-01) students across academic years 2018–2025.
Volume. ≈2,101 comments; 97.3% successfully categorised to a single primary topic.
Overall mood. Roughly 51.4% Positive, 45.6% Negative, 3.0% Neutral (positive:negative ≈ 1.13:1).

What students are saying

Nursing students anchor much of their experience in the realities of practice. Comments about placements, fieldwork and trips dominate—around one in six comments (≈17.0% share). The tone is mixed but leans negative (sentiment index ≈ −7.6), sitting well below the sector benchmark for the same topic.

Alongside placements, students devote substantial attention to the delivery mechanics of their programmes. Taken together—remote learning, course organisation/management, course communications and timetabling—this “delivery & ops” set plus placements accounts for ≈35.1% of all comments. Within it, the most negative tone appears around communication about the course (−46.3) and overall organisation/management (−20.9). Timetabling (−13.1) and remote learning (−4.9) also skew negative, albeit closer to sector on tone.

Set against those frictions, people-centred support is a clear strength. References to Student support (index ≈ +28.2) and Personal Tutor (+38.3) are strongly positive and above sector. Students are generally positive about Teaching Staff (+21.6) and Delivery of teaching (+25.3), especially where structure and expectations are clear. Comments about Personal development are particularly strong (+61.5). The Library stands out with very high positivity (+68.3), far above sector on tone.

In Assessment & Feedback, the picture is typical of the wider sector but with local emphases. “Feedback” appears in ≈3.1% of comments and is mildly negative (−6.9), whereas “Marking criteria” is a smaller but more negative theme (−42.6). The thread tying these topics together is clarity—what good looks like, how it’s judged, and how feedback drives improvement.

Finally, some topics appear less frequently here than in the sector. Students talk relatively less about module choice/variety (0.8% vs 4.2% sector) and general learning resources (1.0% vs 3.8%), suggesting day‑to‑day delivery and practice exposure dominate the lived experience.

Top categories by share (Nursing vs sector):

Category	Section	Share %	Sector %	Δ pp	Sentiment idx	Δ vs sector
Placements/ fieldwork/ trips	Learning opportunities	17.0	3.4	13.6	−7.6	−19.4
Student support	Academic support	8.1	6.2	1.9	+28.2	+15.0
Remote learning	The teaching on my course	6.6	3.5	3.1	−4.9	+4.1
Type & breadth of course content	Learning opportunities	5.7	6.9	−1.2	+24.9	+2.4
Teaching Staff	The teaching on my course	5.0	6.7	−1.7	+21.6	−14.0
Personal development	Learning community	4.9	2.5	2.4	+61.5	+1.7
COVID-19	Others	4.9	3.3	1.5	−29.4	+3.6
Organisation & management	Organisation and management	4.8	3.3	1.4	−20.9	−7.0
Personal Tutor	Academic support	4.7	3.2	1.6	+38.3	+19.6
Communication about course	Organisation and management	4.3	1.7	2.6	−46.3	−10.5

Most negative categories (share ≥ 2%)

Category	Section	Share %	Sector %	Δ pp	Sentiment idx	Δ vs sector
Communication about course and teaching	Organisation and management	4.3	1.7	2.6	−46.3	−10.5
Workload	Organisation and management	2.8	1.8	1.0	−42.7	−2.7
Marking criteria	Assessment and feedback	2.7	3.5	−0.9	−42.6	+3.1
COVID-19	Others	4.9	3.3	1.5	−29.4	+3.6
Organisation, management of course	Organisation and management	4.8	3.3	1.4	−20.9	−7.0
Scheduling/ timetabling	Organisation and management	2.4	2.9	−0.4	−13.1	+3.4
Placements/ fieldwork/ trips	Learning opportunities	17.0	3.4	13.6	−7.6	−19.4

Shares are the proportion of all Nursing comments whose primary topic is the category. Sentiment index ranges from −100 (more negative than positive) to +100 (more positive than negative).

Most positive categories (share ≥ 2%)

Category	Section	Share %	Sector %	Δ pp	Sentiment idx	Δ vs sector
Library	Learning resources	2.0	1.8	0.2	+68.3	+41.6
Personal development	Learning community	4.9	2.5	2.4	+61.5	+1.7
Personal Tutor	Academic support	4.7	3.2	1.6	+38.3	+19.6
Student life	Learning community	2.2	3.2	−1.0	+33.7	+1.6
Availability of teaching staff	Academic support	2.5	2.1	0.4	+29.0	−10.3
Student support	Academic support	8.1	6.2	1.9	+28.2	+15.0
Delivery of teaching	The teaching on my course	3.7	5.4	−1.7	+25.3	+16.5

What this means in practice

Treat placements as a designed service. Confirm capacity early, make changes visible and timely, and set simple, reliable feedback expectations during practice exposure. Raising predictability around placements tends to lift sentiment across adjacent delivery topics too.
Tighten the operational rhythm. Name ownership for timetabling and programme organisation, maintain a single source of truth for course communications, and publish brief weekly updates on “what changed and why.” These small disciplines reduce noise and improve trust.
Make assessment clarity the default. Provide clear marking criteria, annotated exemplars and realistic turnaround commitments. When students understand what “good” looks like and how feedback connects to improvement, sentiment improves quickly.
Build on people and resources strengths. Leverage Personal Tutors and Student support as visible points of contact, and signpost the Library actively—both are strong, confidence‑building assets for students.

Data at a glance (2018–2025)

Top topics by share: Placements (≈17.0%), Student support (≈8.1%), Remote learning (≈6.6%), Type & breadth of course content (≈5.7%), Teaching Staff (≈5.0%), Personal development (≈4.9%).
Delivery & ops cluster (placements, communications, organisation/management, timetabling, remote learning): ≈35.1% of all comments; tone leans negative, with communications and organisation the most critical.
People & growth cluster (personal tutor, student support, teaching staff, availability of staff, delivery of teaching, personal development, student life): ≈31.1% of comments; tone strongly positive, led by Personal development and Library.
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 to +100, then averaged at category level.

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 for every discipline, with views for the whole institution and fine‑grained analysis at faculty, school and programme levels. It produces concise, anonymised theme summaries and representative comments so you can brief programme teams and external partners without trawling thousands of responses.

Crucially, it supports like-for-like sector comparisons across CAH codes and demographics (e.g., year of study, domicile, mode of study, campus/site, commuter status). You can segment by site/provider, cohort and year to target interventions where they will move sentiment most. Export‑ready outputs (web, decks, dashboards) make it straightforward to share priorities and progress across the institution.