{"resourceId":"jisc-he-digital-access-ai-support-2025","versions":[{"version":"external-45807b2217d7a6000864e9fd06f2edd0633c36878617b3080a1f9c593c1d6a81","resource":{"id":"jisc-he-digital-access-ai-support-2025","title":"UK student survey identifies access and AI-support gaps, with important sampling limits","organization":"Jisc","sector":"Higher education student learning and support","geography":"United Kingdom; higher education","publishedAt":"September 2025; exact day unknown","publicationDate":null,"eventDate":null,"sourceName":"Student digital experience insights survey 2024/25: UK higher education survey findings","sourceLabel":"Original sector survey PDF; methods and relevant results inspected","sourceUrl":"https://repository.jisc.ac.uk/10242/1/DEI-2025-student-he-report.pdf","evidenceClass":"public-sector-association","outcomeClass":"cautionary","topics":["knowledge-work","infrastructure","data-security","governance-procurement","accessibility-workforce","operating-model"],"finding":"Student-reported AI use sits alongside gaps in training and basic digital access; the survey does not measure AI learning effectiveness.","sledRelevance":"Interpretation: A transferable checklist for U.S. college support planning, not a U.S. prevalence estimate or evidence that AI caused digital exclusion.","evidence":"15,398 respondents across 30 providers, October 2024–April 2025. Reported AI learning use: 34%; AI training/support: 24%; unsuitable-device difficulties: 37%; wifi difficulties: 60%. Methods note optional questions, unweighted data and changing participating institutions.","architectureImplications":"Interpretation: Evaluate learner devices, bandwidth, authentication and support before expanding a hosted assistant. Supply recoverable sessions and accessible alternatives. The survey cannot choose cloud, on-premises or hybrid hosting; each still depends on usable learner access.","governanceImplications":"Interpretation: Separate account availability, meaningful participation and competence in dashboards. Communicate course-specific permitted use and verify student understanding.","securityPrivacyImplications":"Interpretation: Collect support-needs data proportionately and protect disability disclosures. Explain processing and retention without requiring students to reveal private circumstances to an AI tool.","caveats":"Self-report, not learning or causal evaluation. One institution supplied 5,550 responses. The support-tools accessibility category combines AI with other tools, so it cannot establish AI-specific disability benefit.","streamIds":["student-success"],"roles":{"sales":"Interpretation — Student-success leaders may have licensed AI tools without knowing who can meaningfully access them. Include student services, disability support, library lending, learning technology and procurement. Ask which students encounter device or connectivity problems and whether guidance reaches them before assessment. A bounded engagement could map one course's participation barriers and test a support pathway. The value hypothesis is fewer avoidable access failures, to be measured locally. The UK survey supplies discovery topics rather than a forecast for a U.S. institution. Do not promise learning gains, equate satisfaction with achievement or attribute broad digital barriers to AI alone.","engineering":"Interpretation — Fit an access review to the actual student journey from identity login to course content and help. Prerequisites include supported-device definitions, accessible test cases and a lawful minimal telemetry plan. Test low bandwidth, mobile layouts, keyboard navigation, assistive technology and session recovery. Map outages and authentication failures separately from model-response quality. Protect disability-related support information from unnecessary propagation into assistant prompts. Proposed proof of value: complete representative journeys on agreed devices and document each unresolved barrier with an owner. The survey does not specify a hosting solution or validate a product, and a successful usability check still cannot establish educational effectiveness.","delivery":"Interpretation — Student services should coordinate the intervention with IT, faculty and accessibility staff. Inventory available loan devices, support channels and course guidance; recruit students to test the journey and train frontline staff to route problems. Dependencies include accessible materials, loan capacity and consistent permitted-use messages. Proposed acceptance criteria: every reported critical barrier receives an owner and resolution route, representative journeys pass and students can identify available help. Report unresolved cases and support effort before expanding licenses. These are proposed service gates. Risks include biased feedback, confusing missing responses with satisfied students, and excluding learners who cannot access the survey itself."},"retrievedAt":"2026-09-10T03:02:41Z","enrichedAt":"2026-09-10T03:02:41Z","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Interpretation: Budget accessibility testing and human digital-skills support. Avoid treating tool availability as proof that a student can use it.","procurementImplications":"Interpretation: Include low-bandwidth usability, assistive-technology testing, support obligations, portable records and equitable access costs in evaluation.","operatingModelImplications":"Interpretation: Student services should coordinate access support with learning technology, disability services and faculty; assign one owner for unresolved participation barriers.","updateExplanation":"New in all 151 archive records and candidate-specific search. September 2025 backfill adds student-side access and support constraints; it is not current 2026 usage prevalence.","sourceVerification":{"openedUrl":"https://repository.jisc.ac.uk/10242/1/DEI-2025-student-he-report.pdf","referenceExcerpt":"The data is not weighted to match the national HE student population","promptVersion":"sled-research-v3.1","model":null,"basis":"agent-reported inspection"}}}]}