From the Student Success edition of October 16, 2026
THE: Bett survey finds 77% of Russell Group undergraduates taught little or nothing about AI, with most AI teaching focused on assignment rules
Bett UK survey reported by Times Higher Education; Russell Group; Universities UK · Higher education AI literacy and graduate readiness · United Kingdom
- Publisher
- Times Higher Education
- Original publication
- Times Higher Education, 15 October 2026
- Source retrieved
- 2026-10-17
What happened
Times Higher Education reports a Bett UK survey of more than 1,000 UK undergraduates. More than three-quarters (77%) at Russell Group universities say they are taught little or nothing about AI, against 64% at post-1992 universities, and 62% of Russell Group respondents say that when AI is taught it is mainly about how far it may inform an assignment. Health and medicine students were the most likely to say AI is not covered at all. Only 34% felt their university had been straight about realistic graduate outcomes, and 78% would have been interested in a shorter technology-personalised degree. The article also notes early results from an ongoing 450-student UCLA study, to be presented at a Cambridge summit, suggesting frequent answer-giving AI use raises short-term performance but weakens independent thinking. The Russell Group said its universities are setting clearer assessment rules and adapting curricula.
Why it matters
Fresh independent evidence that student AI instruction often stops at integrity rules, framing demand for curriculum-embedded AI literacy; transferability to U.S. institutions is limited by UK sector structure.
Evidence and measured results
Survey percentages reported by THE; no sample method, weighting or questionnaire shown. Sector bodies' responses quoted. UCLA findings are preliminary and not inspected.
Limitations and uncertainty
Survey commissioned by an edtech event organiser; methods not disclosed in the article; self-reported perceptions; UK context.
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-10-17; this does not change the original publication date. Each role follows the same checklist so takeaways compare across sources.
Sales
Role takeaway
- Customer problem
- Students report AI instruction focused on what is permitted rather than how to use AI well for study and work.
- Stakeholders
- Provost / PVC education
- Curriculum committees
- Careers service
- Course leads
- Student union
- Discovery questions
- What share of programmes teach AI beyond integrity rules?
- Which disciplines lack coverage?
- Is there a named AI lead per course?
- How would literacy be assessed?
- Value hypothesis
- Interpretation: curriculum mapping plus targeted modules can close a perceived gap students report.
- Potential engagement
- A bounded AI-literacy coverage audit and pilot module set for a few programmes.
- Unsupported claims
- Employability gains
- That Russell Group teaching is objectively worse
- Learning effects of any module
Pre-sales engineering
Role takeaway
- Fit
- Indirect fit; relevant where literacy work needs sanctioned AI access in coursework.
- Architecture and integration
- No system described; interpretation: literacy modules require institutional AI accounts and LMS-embedded exercises.
- Prerequisites
- Sanctioned AI tool access
- LMS integration
- Discipline-specific use cases
- Constraints
- UK sample
- Undisclosed survey method
- Self-reported perceptions
- Security
- Ensure coursework AI use runs through accounts with appropriate data terms rather than personal tools.
- Proof of value
- Pre/post skill assessment in pilot courses
- Coverage map completion
- Student-reported coverage change next year
Delivery
Role takeaway
- Work
- Run a programme-level AI teaching coverage audit and pilot discipline-specific literacy modules.
- Dependencies
- Course teams
- Educational development unit
- Careers service
- IT for tool access
- Ownership
- PVC education or provost office with course leads.
- Skills and adoption
- Course leads need examples beyond integrity rules; health programmes may need tailored content.
- Governance checkpoints
- Coverage audit sign-off
- Module design review
- Annual reporting of coverage
- Acceptance criteria
- Proposed: every programme reports AI teaching beyond assessment rules
- Proposed: named AI lead per course published
- Proposed: measured skill gain in pilot modules
- Risks
- Coverage stays rules-only
- Uneven discipline uptake
- Survey-driven decisions without local data
Implementation considerations
Lighthouse Advisory interpretation across the operating dimensions a public-sector buyer must settle before this evidence becomes a design. Each note answers the question under its heading for this specific source.
Architecture and integration
What must connect, and where does the AI sit in the workflow?
Limited direct architecture relevance; interpretation: literacy programmes that use workplace tools need sanctioned institutional access and course integration.
Governance
Who approves, reviews and stays accountable for outcomes?
Shows rules-first AI teaching; UUK pledged an AI lead for every course, and Bett suggests publishing which courses have one.
Security and privacy
What data, permissions and controls need testing?
Not addressed in the article.
Accessibility and workforce
Who is affected, and what skills or accommodations follow?
Students in vocational and health fields report least AI coverage despite workplace exposure; graduate-readiness concerns are broad.
Procurement
What should contracts, pricing and exit terms secure?
Institutions buying AI tools should pair licences with curriculum time; access alone does not equal instruction.
Operating model
Which teams own the service once it runs?
Curriculum owners and course teams, not only integrity offices, need responsibility for AI teaching.
Publication history
- 2026-10-16Student Success · Issue 396 resources
Stable resource ID: the-bett-survey-russell-group-little-ai-teaching-20261015