What UK Sport And Exercise Sciences Students Say: NSS Feedback Analysis (5,096 Comments, 2018–2025)

Key findings

  • 5,096 comments analysed across UK sport and exercise sciences programmes (2018–2025); 57% positive overall
  • Type and breadth of course content is the most-discussed topic (8.1% of comments, sentiment index +33.3)
  • Marking criteria is the biggest pain point (sentiment −38.4, +7.3 vs sector)
  • Personal development is a clear strength (sentiment +64.9)

What students are saying

The Sport and Exercise Sciences narrative centres on the quality and delivery of teaching. Students talk most about the type and breadth of course content (≈8.1% share), with a clearly positive tone (sentiment index ~+33.3) that sits well above sector. Comments about Teaching Staff (≈7.6%) are especially positive (≈+42.4), and Delivery of teaching (≈7.3%) also trends positive and significantly above the sector benchmark, pointing to clear structure, engaging sessions and practical emphasis.

Support and the wider experience also stand out. Student support (≈6.3%) attracts strong praise (≈+35.7, well above sector), as does the Availability of teaching staff (≈+39.5). Students are similarly upbeat about Student life (≈+43.0), General facilities (≈+36.0) and Career guidance/support (≈+38.7).

Assessment & Feedback is more mixed. Feedback (≈7.2%) and Assessment methods (≈4.7%) are discussed often, with mildly negative sentiment overall (≈−8.8 and ≈−12.5 respectively), albeit less negative than sector. Marking criteria (≈3.4%) remains a clear pain point (≈−38.4): uncertainty about expectations and standards drives dissatisfaction, even where the broader teaching experience is strong.

Operational topics are present but smaller by share. Scheduling/timetabling (≈3.1%) leans negative (≈−14.6), and Remote learning (≈3.6%) is slightly negative (≈−7.9). Organisation and management of the course (≈2.9%) is comparatively positive (≈+9.8, significantly above sector). Opportunities to work with other students (≈2.1%) trend negative (≈−14.0) and below sector, suggesting scope to strengthen group work and collaboration structures. Placements/fieldwork/trips appear less frequently than sector (≈2.4% vs 3.4%) and are moderately positive (≈+17.9).

Top categories by share (sport & exercise vs sector):

Category Section Share % Sector % Δ pp Sentiment idx Δ vs sector
Type and breadth of course content Learning opportunities 8.1 6.9 +1.1 +33.3 +10.7
Teaching Staff The teaching on my course 7.6 6.7 +0.9 +42.4 +6.9
Delivery of teaching The teaching on my course 7.3 5.4 +1.8 +23.0 +14.2
Feedback Assessment and feedback 7.2 7.3 −0.2 −8.8 +6.2
Student support Academic support 6.3 6.2 +0.1 +35.7 +22.5
COVID-19 Others 4.7 3.3 +1.3 −26.0 +6.9
Assessment methods Assessment and feedback 4.7 3.0 +1.7 −12.5 +11.2
Remote learning The teaching on my course 3.6 3.5 +0.1 −7.9 +1.1
Marking criteria Assessment and feedback 3.4 3.5 −0.2 −38.4 +7.3
Availability of teaching staff Academic support 3.2 2.1 +1.1 +39.5 +0.2

Most negative categories (share ≥ 2%)

Category Section Share % Sector % Δ pp Sentiment idx Δ vs sector
Marking criteria Assessment and feedback 3.4 3.5 −0.2 −38.4 +7.3
COVID-19 Others 4.7 3.3 +1.3 −26.0 +6.9
Scheduling/timetabling Organisation and management 3.1 2.9 +0.2 −14.6 +1.9
Opportunities to work with other students Learning community 2.1 2.0 +0.1 −14.0 −15.1
Assessment methods Assessment and feedback 4.7 3.0 +1.7 −12.5 +11.2
Feedback Assessment and feedback 7.2 7.3 −0.2 −8.8 +6.2
Remote learning The teaching on my course 3.6 3.5 +0.1 −7.9 +1.1

Most positive categories (share ≥ 2%)

Category Section Share % Sector % Δ pp Sentiment idx Δ vs sector
Personal development Learning community 2.7 2.5 +0.2 +64.9 +5.0
Student life Learning community 3.0 3.2 −0.2 +43.0 +10.9
Teaching Staff The teaching on my course 7.6 6.7 +0.9 +42.4 +6.9
Availability of teaching staff Academic support 3.2 2.1 +1.1 +39.5 +0.2
Career guidance, support Learning community 2.8 2.4 +0.4 +38.7 +8.6
General facilities Learning resources 3.0 1.8 +1.2 +36.0 +12.6
Student support Academic support 6.3 6.2 +0.1 +35.7 +22.5

What this means in practice

  • Make assessment clarity routine. Publish annotated exemplars, task-specific rubrics and plain‑English marking criteria. Agree a realistic feedback turnaround and communicate it upfront. Small moves here will shift sentiment across Feedback, Assessment methods and Marking criteria quickly.

  • Tighten the operational rhythm. Use a single source of truth for timetables and changes; set and honour change‑freeze windows; share a short weekly “what changed and why” update. This reduces friction in Scheduling/timetabling and keeps remote/hybrid elements predictable.

  • Design for collaboration. Where Opportunities to work with other students trend negative, build structured group tasks with clear roles, interim checkpoints and transparent marking. Make collaboration purposeful rather than ad‑hoc.

  • Keep visible support high. Protect office hours, signpost routes to help, and ensure quick acknowledgement even when full answers take longer. This sustains the strong results for Student support and Availability of teaching staff.

Data at a glance (2018–2025)

  • Top topics by share: Type and breadth of course content (≈8.1%), Teaching Staff (≈7.6%), Delivery of teaching (≈7.3%), Feedback (≈7.2%), Student support (≈6.3%). Assessment methods (≈4.7%) and Marking criteria (≈3.4%) also feature heavily.

  • Cluster view:

    • Delivery & ops cluster (placements, scheduling, organisation, comms, remote): ≈13.4% of all comments.
    • People & growth cluster (personal tutor/support, teaching staff, delivery, personal development, student life): ≈32.1% of all comments, with consistently positive tone.
  • 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), then averaged at category level.

How Student Voice Analytics helps you

Student Voice Analytics turns open-text survey comments into precise, trackable priorities. It shows what matters by analysing topics and sentiment over time (2018–2025), at whole‑institution level and down to schools and departments within Sport and Exercise Sciences.

It provides concise, anonymised theme summaries and representative comments for partners and programme teams, and—critically—delivers 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, and export/share outputs (web, decks, dashboards) to keep stakeholders aligned on progress.

How to use this data

This page presents sector-level student feedback analysis for sport and exercise sciences, with sentiment benchmarks and topic breakdowns you can reference directly in institutional documents.

Use this for

  • Annual Programme Review (APR) — reference the top-categories table and sentiment benchmarks to contextualise your programme's results against the discipline.
  • TEF and quality enhancement — cite the sentiment index and sector delta columns as evidence of awareness of student priorities relative to the sector.
  • Professional body revalidation — draw on placement, assessment and support data for evidence of responsiveness to student feedback in your discipline.
  • Staff-Student Liaison Committees (SSLCs) — share the key findings and most-negative categories as discussion starters with student representatives.
  • New programme design — use the topic share and sentiment data to anticipate which aspects of the student experience will need proactive attention.

Common themes in this subject area (on our blog)

Most-read posts in this subject area

Recommended next steps

  1. Look for repeatability: which themes recur across years and modules?
  2. Check whether issues are structural (resources/staffing) or local (one module/team).
  3. Define what “good” looks like for the subject (examples, rubrics, assessment clarity).
  4. Track movement: do actions reduce volume/negativity for key themes next cycle?

Cite this page

Student Voice AI (2025). "Sport And Exercise Sciences student feedback analysis (CAH03-02-01)." Student Voice AI. https://www.studentvoice.ai/cah3/sport-and-exercise-sciences/

Case studies on teaching, course design and feedback in sport sciences

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