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NSS open-text research brief · 2026 edition

What students said about Contact Time in NSS 2026

Contact Time appears in 1.7% of classified NSS comments in 2026.

01 · The 2026 answer

What changed from 2025?

In 2026, contact time appeared in 1.7% of classified comments (n=678).

The mention rate moved +0.5 percentage points from 2025. The sentiment index changed by −0.9; these are descriptive changes, not estimates of individual student satisfaction.

2025 1.2%
2026 1.7%
Share of classified NSS open-text comments that mention contact time. One comment may mention more than one topic.

02 · Findings

Strengths and pressure points

Subject-area differences within this topic are shown only when at least 20 comments support the cut.

Relative strengths

No positive current-year cut meets the reporting threshold.

Pressure points

  1. (CAH19) language and area studies

    n=48 · sentiment −43.7 · 4.9% mention rate

  2. (CAH15) social sciences

    n=89 · sentiment −35.9 · 2.3% mention rate

  3. (CAH20) historical, philosophical and religious studies

    n=97 · sentiment −35.6 · 6.1% mention rate

03 · Comparisons

Where the 2026 pattern differs

Leading reportable cuts are grouped by dimension and ordered by 2026 comment volume. Each percentage is calculated within the relevant comparison group.

Broad subject areas

Group n Mention rate Sentiment
(CAH20) historical, philosophical and religious studies 97 6.1% −35.6
(CAH15) social sciences 89 2.3% −35.9
(CAH19) language and area studies 48 4.9% −43.7

Detailed subject areas

Group n Mention rate Sentiment
(CAH15-03-01) politics 45 3.5% −43.3
(CAH20-01-01) history 43 6.7% −42.8
(CAH19-01-03) literature in English 35 8.2% −48.0

Age

Group n Mention rate Sentiment
Young 667 1.7% −25.9

Disability

Group n Mention rate Sentiment
Not disabled 530 1.7% −26.8
Disabled 148 1.6% −20.9

Ethnicity

Group n Mention rate Sentiment
White 468 2.3% −25.6
Not UK domiciled 100 1.3% −24.2
Mixed 47 2.3% −25.8

Sex

Group n Mention rate Sentiment
Female 444 1.8% −23.1
Male 232 1.4% −30.0

Mode of study

Group n Mention rate Sentiment
Full-time 676 1.7% −25.5

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 Mention rate Sentiment index
2023 692 1.3% −29.9
2024 808 1.3% −24.6
2025 698 1.2% −24.6
2026 678 1.7% −25.5
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 Mention rate Sentiment index
2018 665 1.4% −26.3
2019 692 1.3% −28.7
2020 688 1.4% −28.9
2021 737 1.0% −33.4
2022 568 0.7% −26.6

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

    Show the value of planned contact

    Explain the role of each contact point, protect essential sessions and make the relationship between taught, guided and independent learning explicit.

    Evidence: 678 reportable comments in 2026, 1.7% of classified comments.

  2. 2

    Start with the clearest variation

    Test the process with (CAH19) language and area studies first, where the 2026 sentiment index is −43.7 from n=48 comments.

    Evidence rule: no displayed cohort or subject cut has fewer than 20 comments.

  3. 3

    Set the next-cycle check now

    Review missed or cancelled contact separately from comments about whether scheduled time is purposeful.

    Compare 2027 with 2026 on a like-for-like basis before describing movement.

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). “Contact Time NSS open-text insights, 2026.” Reviewed by Dr Stuart Grey. Student Voice AI. https://www.studentvoice.ai/category/contact-time/

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