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NSS open-text research brief · 2026 edition

What Medical Science students said in NSS 2026

Teaching Staff is the most frequently mentioned reportable topic in 2026.

01 · The 2026 answer

What changed from 2025?

The 2026 analysis covers 140 classified comments in Medical Science.

Teaching Staff is the leading reportable topic in this brief. Its mention rate changed by −1.8 percentage points and its sentiment index by +0.5 from 2025.

Teaching Staff

2025 30.4%
2026 28.6%
Share of classified Medical Science comments mentioning this topic.

02 · Findings

Where sentiment differs from the sector

Topics within this subject are shown only when at least 20 comments support the cut.

Above-sector sentiment

  1. Student Support

    n=28 · sentiment +54.0 · +19.5 points vs sector · 20.0% mention rate

  2. Teaching Staff

    n=40 · sentiment +51.0 · +9.1 points vs sector · 28.6% mention rate

  3. Type and Breadth of Course Content

    n=37 · sentiment +31.5 · +5.6 points vs sector · 26.4% mention rate

Below-sector sentiment

  1. Delivery of Teaching

    n=33 · sentiment +4.9 · −18.0 points vs sector · 23.6% mention rate

03 · Comparisons

Topics compared with the sector

Subject and sector figures are calculated on a like-for-like basis using the same deterministic supervised learning approach.

Topic n Mention rate Sentiment Vs sector
Teaching Staff 40 28.6% +51.0 +9.1
Type and Breadth of Course Content 37 26.4% +31.5 +5.6
Delivery of Teaching 33 23.6% +4.9 −18.0
Student Support 28 20.0% +54.0 +19.5
Assessment Methods 26 18.6% −10.5 +6.5
Feedback 24 17.1% −11.6 +0.9

04 · Time series

Current questionnaire period, 2023–2026

The 2023 NSS questionnaire redesign creates a comparability break. We show earlier years separately as context rather than drawing a trend through 2022–2023.

Year Comments
2023 129
2024 125
2025 194
2026 140
Show historical context, 2018–2022

All years were analysed with the same deterministic supervised learning approach, but the survey instrument differs from the current questionnaire.

Year Comments
2018 Not shown: fewer than 20 reportable comments
2019 68
2020 Not shown: fewer than 20 reportable comments
2021 138
2022 101

05 · Action

Three evidence-linked actions

Use the findings to choose a local test, then check the same topic and cohort again rather than treating a sector pattern as a diagnosis of one provider.

  1. 1

    Guarantee usable feed-forward

    Set turnaround standards and require feedback to identify what worked, what needs attention and what the student should do differently next time.

    Evidence: Feedback has a 2026 sentiment index of −11.6 from n=24 comments.

  2. 2

    Make the purpose of assessment explicit

    Map each assessment to its learning purpose, required preparation and place in the programme, then remove avoidable duplication and bunching.

    Evidence: Assessment Methods has a 2026 sentiment index of −10.5 from n=26 comments.

  3. 3

    Spread effective teaching practice

    Use peer review and programme-level discussion to share approaches that students value while addressing avoidable inconsistency between modules.

    Evidence: Teaching Staff has a 2026 sentiment index of +51.0 from n=40 comments.

06 · Method and limits

How to read this evidence

How topics are identified

Deterministic supervised learning models identify topics in each sentence. A comment counts once in every topic it mentions; mention rate is the share of comments included in the analysis for the same population, so topic rates do not sum to 100%.

Sentiment index

The index summarises the balance of positive and negative language from −100 to +100. Scores are averaged within each comment first, so longer comments do not carry more weight.

When results are shown

Pages require at least 100 comments and three reportable topics or subject cuts. Displayed cuts require n≥20; 2026-versus-2025 claims require n≥30 in both years.

Scope

This is authorised aggregate analysis of OfS NSS national undergraduate open-text comments. In 2026, 40,822 of 43,870 source comments were classified (93.1%); mention-rate denominators exclude unclassified comments.

07 · Reuse

Cite this page

Student Voice research team (2026). “Medical Science student feedback: NSS open-text insights, 2026.” Reviewed by Dr Stuart Grey. Student Voice AI. https://www.studentvoice.ai/cah3/medical-sciences-(non-specific)/

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