Student Voice Analytics for Medical Sciences — UK student feedback 2018–2025

Scope. UK NSS open-text comments for Medical Sciences (CAH01-01-01) students across academic years 2018–2025.
Volume. ~590 comments; 99% successfully categorised to a single primary topic.
Overall mood. Roughly 49.1% Positive, 46.4% Negative, 4.5% Neutral (positive:negative ≈ 1.06:1).

What students are saying

The Medical Sciences conversation is led by course design and assessment. Feedback is the single biggest topic (≈9.1% share) and is strongly negative (sentiment index −31.6), notably below the sector benchmark for the same topic. Marking criteria also draws a concentrated, very negative tone (−56.4). In contrast, Assessment methods (4.6% share) is less negative than sector, suggesting method choice itself is not the core problem—clarity, fairness and usefulness of feedback are.

Learning opportunities feature prominently and positively. Type and breadth of course content (8.7%) is well-regarded (index +21.8), and Module choice/variety (7.2%) is also positive. Where class size is mentioned (Group size/SSRs, 2.1%), tone is very strong (+58.0).

People and delivery remain consistent strengths. Teaching Staff (6.7%) is highly positive (+42.1, above sector), Delivery of teaching (5.1%) is net positive, and Student support (4.5%) is clearly appreciated (+23.4). Smaller but notable positives include Personal Tutor (+40.6) and Availability of teaching staff (+51.7).

The main friction is operational. Organisation and management of the course (5.5%) is deeply negative (−43.7), as are Scheduling/timetabling (−53.8) and Communication about course and teaching (−39.9). Student voice sentiment (2.6% share, −39.7) indicates many students do not feel their input leads to change. Collectively, this “delivery & ops” cluster accounts for roughly one-seventh of all comments and sits well below sector on tone.

Other notes. Placements/fieldwork/trips are barely mentioned (0.7%) and are positive when they appear. Remote learning is slightly positive (+4.9) and markedly better than sector. Career guidance/support attracts attention (4.3%) but is less positive than the sector average, and Library sentiment is also softer than sector.

Top categories by share (discipline vs sector)

Most negative categories (share ≥ 2%)

Shares are the proportion of all Medical Sciences 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%)

What this means in practice

Start with assessment clarity. Publish annotated exemplars, checklist-style rubrics, and concise marking briefs that show “what good looks like.” Calibrate marking across modules and set a realistic feedback SLA, then report on turnaround performance openly. These steps address the core drivers behind negative Feedback and Marking criteria sentiment.

Stabilise the operational rhythm. Name an owner for scheduling and course organisation, implement a timetable “freeze” window, and issue a weekly change log to a single source of truth. Bundle key updates (what changed and why) and hold a short, regular Q&A slot. This directly targets Organisation & management, Scheduling, and course Comms.

Close the loop on student voice. Publish “You said, we did” updates each term and give visibility to decisions that cannot be implemented (with reasons). Invite a small rotating panel of students to preview changes before roll‑out to strengthen perceived responsiveness.

Protect the positives. Maintain visibility of teaching availability and the supportive culture that underpins strong Teaching Staff, Student support and Personal Tutor sentiment. For careers, integrate short, practical guidance points within modules and signpost next steps clearly.

Data at a glance (2018–2025)

• Top topics by share: Feedback (≈9.1%), Type & breadth of course content (≈8.7%), Module choice/variety (≈7.2%), Teaching Staff (≈6.7%), Organisation & management of course (≈5.5%).
• Delivery & ops cluster (placements, scheduling, organisation, course comms, remote learning): ≈14.1% of comments, with notably negative tone driven by Scheduling (−53.8), Organisation & management (−43.7) and Comms (−39.9).
• People & growth cluster (personal tutor, student support, teaching staff, delivery of teaching, personal development, student life): ≈23.7% of comments, generally positive (e.g., Teaching Staff +42.1; Student support +23.4).
• Relative to sector attention: above-sector focus on Module choice/variety (+3.0 pp), Organisation & management (+2.1 pp), Feedback (+1.8 pp), and Career guidance (+1.9 pp). Under‑discussed vs sector: Placements (−2.7 pp), Personal Tutor (−1.5 pp), Learning resources (−2.2 pp).
• How to read the numbers. Each comment is assigned one primary topic; share is that topic’s proportion of all comments. Sentiment is scored per sentence and summarised as an index from −100 (more negative) to +100 (more positive), then averaged at category level.

How Student Voice Analytics helps you

Student Voice Analytics turns open-text survey data into clear, prioritised actions. It tracks topics and sentiment over time so you can see which issues are rising or falling across the whole institution as well as within specific departments and schools.

You can evidence impact with like-for-like sector comparisons across CAH codes and by demographics (e.g., year of study, domicile, mode of study, campus/site, commuter status). Segment results by site/provider, cohort and year to target interventions precisely. The platform also generates concise, anonymised summaries and representative comments for partners and programme teams, and provides export-ready outputs (web, slides, dashboard) to share priorities and progress quickly.