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

Scope. UK NSS open-text comments for Biology (CAH03-01-02) students across academic years 2018–2025.
Volume. ≈2,910 comments; 98% successfully categorised to a single primary topic.
Overall mood. ≈53.1% Positive, 42.5% Negative, 4.4% Neutral (positive:negative ≈ 1.25:1).

What students are saying

Biology students talk most about Assessment & Feedback. Feedback is the single largest topic (≈8.4% share) and is rated clearly negative overall (index ≈ −23.0), with students asking for clearer, more actionable comments and predictable turnaround. Related assessment topics—Assessment methods (index ≈ −24.1) and Marking criteria (≈ −45.4)—reinforce the same message: clarity of expectations and how to improve is the pressure point. Together with Dissertation, assessment-focused categories account for just under one in five comments (≈18.7%) and lean negative.

Teaching quality and content are sustained strengths. Students are positive about Teaching Staff (≈ +37.0) and Delivery of teaching (≈ +21.6), and they value the Type and breadth of course content (≈ +31.0) and Module choice/variety (≈ +24.8). The availability of teaching staff stands out (≈ +48.7), and the wider student experience is warmly viewed—Student life carries a strong positive tone (≈ +41.0).

Operational delivery is more mixed. Scheduling/timetabling is a notable pain point (≈ −33.5), well below the sector on tone, and Organisation & management of course is mildly negative (≈ −13.8). Remote learning remains slightly negative (≈ −8.7), while Workload is also negative (≈ −30.5) but less so than the sector baseline.

A distinctive feature here is that Placements/fieldwork/trips, while a smaller share than in some disciplines (≈4.5%), are positively received (≈ +30.6) and sit well above the sector’s sentiment for the same topic. Compared with the sector, Biology students discuss assessment, module choice and placements slightly more; generic Learning resources and some facilities topics appear slightly less often.

Top categories by share (discipline vs sector)

Category	Section	Share %	Sector %	Δ pp	Sentiment idx	Δ vs sector
Feedback	Assessment and feedback	8.4	7.3	+1.1	−23.0	−8.0
Type and breadth of course content	Learning opportunities	6.2	6.9	−0.7	+31.0	+8.4
Delivery of teaching	The teaching on my course	6.1	5.4	+0.6	+21.6	+12.9
Teaching Staff	The teaching on my course	5.5	6.7	−1.2	+37.0	+1.5
Student support	Academic support	5.5	6.2	−0.7	+12.3	−0.9
Module choice / variety	Learning opportunities	5.3	4.2	+1.1	+24.8	+7.5
Placements/ fieldwork/ trips	Learning opportunities	4.5	3.4	+1.1	+30.6	+18.8
Assessment methods	Assessment and feedback	4.2	3.0	+1.2	−24.1	−0.4
Personal Tutor	Academic support	3.7	3.2	+0.5	+25.1	+6.4
Marking criteria	Assessment and feedback	3.7	3.5	+0.1	−45.4	+0.3

Most negative categories (share ≥ 2%)

Category	Section	Share %	Sector %	Δ pp	Sentiment idx	Δ vs sector
Marking criteria	Assessment and feedback	3.7	3.5	+0.1	−45.4	+0.3
Scheduling/ timetabling	Organisation and management	2.8	2.9	+0.0	−33.5	−17.0
Workload	Organisation and management	2.0	1.8	+0.2	−30.5	+9.5
COVID-19	Others	3.5	3.3	+0.1	−28.1	+4.8
Assessment methods	Assessment and feedback	4.2	3.0	+1.2	−24.1	−0.4
Feedback	Assessment and feedback	8.4	7.3	+1.1	−23.0	−8.0
Organisation, management of course	Organisation and management	2.8	3.3	−0.5	−13.8	+0.1

Most positive categories (share ≥ 2%)

Category	Section	Share %	Sector %	Δ pp	Sentiment idx	Δ vs sector
Availability of teaching staff	Academic support	2.3	2.1	+0.3	+48.7	+9.4
Student life	Learning community	3.2	3.2	+0.0	+41.0	+8.9
Teaching Staff	The teaching on my course	5.5	6.7	−1.2	+37.0	+1.5
Type and breadth of course content	Learning opportunities	6.2	6.9	−0.7	+31.0	+8.4
Placements/ fieldwork/ trips	Learning opportunities	4.5	3.4	+1.1	+30.6	+18.8
Personal Tutor	Academic support	3.7	3.2	+0.5	+25.1	+6.4
Module choice / variety	Learning opportunities	5.3	4.2	+1.1	+24.8	+7.5

What this means in practice

Make assessment clarity your first lever. Publish annotated exemplars, checklist-style rubrics, and clear marking criteria; set and track realistic feedback SLAs. These actions directly address the most-discussed and most negative topics (Feedback, Assessment methods, Marking criteria).
Stabilise the operational rhythm. Scheduling is a clear drag on sentiment. Name a single owner for the timetable, limit last‑minute changes, and issue a weekly “what changed and why” digest. Keep one source of truth for course communications.
Protect and amplify what works. Teaching Staff, Delivery of teaching, and the Availability of staff are viewed positively—codify the practices behind that (structured sessions, accessible staff hours, visible preparation) and spread them. Keep outward‑facing opportunities (e.g., fieldwork/placements) well‑organised—they are a net positive in this discipline.
Target supportive services where they trail the sector. Careers support is positive but below sector on tone; small improvements in visibility of appointments, tailored advice, and links to modules can move this quickly.

Data at a glance (2018–2025)

Top topics by share: Feedback (≈8.4%), Type & breadth of course content (≈6.2%), Delivery of teaching (≈6.1%), Teaching Staff (≈5.5%), Student support (≈5.5%).
Assessment & feedback grouping (Feedback, Assessment methods, Marking criteria, Dissertation): ≈18.7% of all comments, predominantly negative.
Delivery & ops cluster (Placements, Scheduling, Organisation & management, Course communications, Remote learning): ≈13.9% of comments, mixed to negative, with Scheduling the clear weak spot.
People & growth cluster (Personal Tutor, Student support, Teaching Staff, Availability of staff, Delivery of teaching, Personal development, Student life): ≈27.9% of comments, strongly positive overall.
How to read the numbers. Each comment is assigned one primary topic; share is that topic’s proportion of all comments. Sentiment is summarised as an index from −100 (more negative than positive) to +100 (more positive than negative), 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, across the whole institution and down to faculty, school and programme levels, so teams can see what changed and where.

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), so you can evidence progress against the right peer group. You can segment by site/provider, cohort and year, and produce concise, anonymised summaries for programme teams and external partners. Export‑ready outputs (web, deck, dashboard) make it simple to share priorities and progress.