{"resourceId":"stanford-k12-evidence-base-review-2026","versions":[{"version":"external-87fb4d6fc132f21c65fa34fe7b4d5413fd987cdaba06a98dc47e9064031a0481","resource":{"id":"stanford-k12-evidence-base-review-2026","title":"Stanford evidence review separates assisted performance from independent learning","organization":"SCALE Initiative, Stanford University","sector":"K–12 education","geography":"U.S.-oriented review drawing on international and some postsecondary studies; local K12 transfer requires validation","publishedAt":"2026; exact publication day unverified","publicationDate":null,"eventDate":null,"sourceName":"The Evidence Base on AI in K-12: A 2026 Review","sourceLabel":"University research synthesis","sourceUrl":"https://scale.stanford.edu/sites/default/files/The%20Evidence%20Base%20on%20AI%20in%20K-12%20Report.pdf","evidenceClass":"academic-research","outcomeClass":"mixed","topics":["knowledge-work","governance-procurement","accessibility-workforce","operating-model"],"finding":"The review reports mixed independent-learning results despite gains during AI-assisted tasks, alongside promising educator-support findings.","sledRelevance":"Interpretation: Newly archived background for fall 2026 district evaluation decisions, not September 12 breaking news. Adds the review's specific methodology and constraints to existing tutoring and implementation coverage.","evidence":"Authors report 20 causal papers selected from an 818-paper repository using AI screening and human review. Evidence spans different comparisons, samples and durations; this edition does not treat it as a pooled effect estimate.","architectureImplications":"Interpretation: Keep student-facing assistance, teacher copilots and independent assessment as distinct workflows. The synthesis supplies no local compute sizing or cloud/on-premises/hybrid comparison; developer productivity and autonomous agents have limited applicability.","governanceImplications":"Interpretation: Approve outcome definitions and a comparison before procurement; require renewed evidence for material workflow changes.","securityPrivacyImplications":"Interpretation: Assess transcript access, retention and supplier reuse separately; learning findings do not certify privacy or safety.","caveats":"Repository is largely preprints and uses restricted keywords. Report states an October 2025 snapshot but cites later-dated work; exact cutoff coverage remains unresolved. It excludes pre-LLM tutoring by definition. Google.org is among disclosed funders. Included original trials were not all reopened, so no individual effect sizes are republished here.","streamIds":["k12"],"roles":{"sales":"Interpretation: District assessment, curriculum and procurement leaders need to know whether a proposed assistant improves independent competence. Ask whether evidence measures work completed with assistance or later performance without it, and whether the learners resemble local students. Offer a bounded evidence-to-pilot plan for one instructional use. The value hypothesis is a defensible continuation decision. Do not equate a university review with product endorsement, or quote aggregate return on investment from studies with different baselines and durations.","engineering":"Interpretation: Instrument assisted sessions separately from independent assessments. Prerequisites include approved curriculum, a comparison workflow, accessible assessment tasks and model-version records. Keep evaluation exports separate from operational student records, minimize identifiers and verify deletion with the vendor. Hosting topology must follow district requirements; this report does not establish a preferred one. Proposed validation compares pre-specified unassisted and delayed tasks against ordinary instruction, reporting missing data and review effort. A usage dashboard alone is insufficient.","delivery":"Interpretation: The assessment director should own the evaluation plan, supported by teachers, privacy staff and an accessibility specialist. Secure assessment time and permissions, train staff to administer unassisted tasks consistently, and communicate alternatives to families. Proposed acceptance requires completed baseline and follow-up reporting, disclosed attrition, and a recorded decision against locally agreed learning and workload criteria before expansion. Risks include changes to the model during evaluation, selective reporting, unsupported transfer from older students and inadequate follow-up participation."},"retrievedAt":"2026-09-13T03:01:40Z","enrichedAt":"2026-09-13T03:03:16Z","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Interpretation: Include accommodated and multilingual tasks in evaluation and account for educator review time.","procurementImplications":"Interpretation: Request evidence for the configured service, grade and assessment outcome rather than generic AI claims.","operatingModelImplications":"Interpretation: Give assessment and curriculum owners authority over scale-up, with IT responsible for version and access controls.","updateExplanation":"New canonical URL: absent from all 247 full-library records retrieved at offsets 0, 100 and 200. Related K12 coverage was reviewed. This is additional review evidence, not a substantive update to an archived original trial; overlapping studies are not counted as independent replications.","sourceVerification":{"openedUrl":"https://scale.stanford.edu/sites/default/files/The%20Evidence%20Base%20on%20AI%20in%20K-12%20Report.pdf","referenceExcerpt":"effects are mixed.","promptVersion":"sled-research-v3.1","model":null,"basis":"agent-reported inspection"}}}]}