{"resourceId":"cwu-washington-hs-teacher-ai-survey-20261005","versions":[{"version":"external-174c5a5818e5d70f1f0b6485f147aaabeb98bc2a5080ce8dff8b149cc1766fb6","resource":{"id":"cwu-washington-hs-teacher-ai-survey-20261005","title":"CWU College in the High School survey: 222 Washington math and English teachers split on AI, and clear policies and useful PD track with greater confidence","organization":"Central Washington University College in the High School faculty (Josh Aubol, Steve Stein, Peter Klosterman); published via Washington State Standard and Seattle's Child","sector":"K-12 high school teachers / dual-credit programme","geography":"Washington State, United States","publishedAt":"2026-10-05T19:26:06+00:00","publicationDate":"2026-10-05","eventDate":null,"sourceName":"Seattle's Child (republishing Washington State Standard)","sourceLabel":"Researcher commentary with survey results","sourceUrl":"https://www.seattleschild.com/ai-washington-schools-teachers/","evidenceClass":"independent-research","outcomeClass":"mixed","topics":["accessibility-workforce","governance-procurement","knowledge-work"],"finding":"In a May 2026 survey of 222 Washington high school math and English teachers, 57.0% of English teachers and 37.6% of math teachers said their attitude toward teaching had worsened since AI appeared; 83.7% of English and 54.9% of math teachers reported academic integrity concerns. English teachers were nonetheless more confident teaching responsible AI use (45.5% vs 24.4%) and more likely to require AI experimentation (34.1% vs 14.6%). Teachers with clear institutional AI policies, or useful AI professional development, reported more confidence using AI and teaching students to use it. About one-sixth of responses mentioned moving writing to in-class pen and paper, and some teachers had stopped assigning homework.","sledRelevance":"Adds recent U.S. teacher-level evidence that subject matters and that policy clarity and relevant training go with teacher confidence, as districts nationwide write AI policies this year.","evidence":"Survey of 222 teachers in one university dual-credit programme, reported by its authors in an op-ed. Associations between policy, PD and confidence are correlational; sampling method, response rate and statistical tests are not given.","architectureImplications":"Limited relevance to architecture; the main implication is that teacher-facing tools and guidance should differ by discipline.","governanceImplications":"Clear written policy on permissible teacher and student AI use is associated with teacher confidence; ambiguity leaves teachers to improvise, including dropping homework.","securityPrivacyImplications":"Limited relevance; the source does not address student data or privacy.","caveats":"Non-random sample from one programme; authors' commentary; correlational findings; republished article whose original appeared in Washington State Standard. Survey conducted May 2026.","streamIds":["k12"],"roles":{"sales":"Open with teacher confidence, not tools. In this Washington survey, English teachers were most negative about AI yet most confident teaching responsible use, and teachers with clear policies or useful training felt more capable. That supports a bounded offer to pair a district AI policy with discipline-specific professional development. Keep claims modest: the survey is correlational and from one dual-credit programme, so it cannot show that training causes confidence or better student learning.","engineering":"The technical implications are modest. Discipline differences suggest English teachers need assignment designs and AI-use settings that protect writing, while math teachers may value AI for routine material such as reworking story problems. If a district configures teacher AI tools, set defaults and templates by subject rather than one universal setup. Collect usage and confidence data by department so any professional development effect can be measured rather than assumed.","delivery":"Deliver a district AI policy that states permissible teacher and student use, plus discipline-specific professional development for English and math departments. Address assessment directly, since about one-sixth of responses mention moving writing in class and some teachers dropped homework. Curriculum leaders own subject guidance; professional learning owns training design. Measure teacher confidence and integrity concerns before and after training by subject, and treat targets as proposals."},"roleDetails":{"sales":{"customerProblem":"High school teachers, especially in English, report worsening attitudes and integrity worries about AI, and many lack clear policy or useful training.","stakeholders":["assistant superintendent for teaching and learning","English and math department heads","professional learning director","teachers' association","dual-credit coordinators"],"discoveryQuestions":["Do teachers have a written statement of permitted AI use?","Is your AI training the same for every subject?","How have teachers changed homework or writing assessment?","Do you measure teacher confidence with AI?"],"valueHypothesis":"Clear policy plus subject-specific training may raise teacher confidence and reduce ad hoc responses such as dropping homework.","potentialEngagement":"Semester-long policy-and-PD package for English and math departments with pre/post teacher survey.","unsupportedClaims":["That PD causes teacher confidence","That confidence improves student learning","That results generalise beyond this programme"]},"engineering":{"fit":"Limited; relevant where districts configure teacher-facing AI tools and want subject-specific defaults.","architectureIntegration":"Subject-specific templates and settings in teacher AI tools, with department-level usage reporting.","prerequisites":["teacher AI tool with configurable templates","department tagging of staff accounts","survey instrument"],"constraints":["correlational evidence","single programme sample","no student outcome data"],"security":"Teacher survey and usage data should be aggregated by department to protect individual staff.","proofOfValue":["Compare confidence before and after subject-specific PD","Track department usage of teacher AI tools","Monitor changes in homework and in-class writing practices"]},"delivery":{"work":"Publish clear teacher and student AI-use policy and run discipline-specific professional development for English and math.","dependencies":["board-approved policy","PD time in the calendar","department-head buy-in"],"ownership":"Teaching and learning owns policy guidance and PD; department heads own subject practice.","skillsAdoption":"English teachers need assignment designs resistant to AI substitution; math teachers need practical uses that free time without replacing practice.","governanceCheckpoints":["policy adoption","post-PD survey review","annual review of assessment changes"],"acceptanceCriteria":["Proposed: every teacher can name permitted AI uses for their course","Proposed: measurable rise in confidence after PD","Proposed: departments publish assessment guidance on AI"],"risks":["blanket responses like dropping homework","one-size PD missing subject needs","overstating correlational evidence"]}},"retrievedAt":"2026-10-06T22:06:38-05:00","enrichedAt":"2026-10-06T22:06:38-05:00","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Teacher morale and workload are central: many teachers report worsening attitudes toward teaching and are redesigning assessment.","procurementImplications":"Limited; districts buying teacher AI tools should budget for discipline-specific training rather than tool access alone.","operatingModelImplications":"Professional development becomes part of AI policy implementation, differentiated by subject.","sourceVerification":{"openedUrl":"https://www.seattleschild.com/ai-washington-schools-teachers/","referenceExcerpt":"57.0% of English teachers reported that their overall attitude towards teaching has worsened since AI appeared","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}