From the K–12 edition of October 6, 2026
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
Central Washington University College in the High School faculty (Josh Aubol, Steve Stein, Peter Klosterman); published via Washington State Standard and Seattle's Child · K-12 high school teachers / dual-credit programme · Washington State, United States
- Publisher
- Seattle's Child (republishing Washington State Standard)
- Original publication
- 2026-10-05T19:26:06+00:00
- Source retrieved
- 2026-10-07
What happened
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.
Why it matters
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 and measured results
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.
Limitations and uncertainty
Non-random sample from one programme; authors' commentary; correlational findings; republished article whose original appeared in Washington State Standard. Survey conducted May 2026.
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-10-06; this does not change the original publication date. Each role follows the same checklist so takeaways compare across sources.
Sales
Role takeaway
- Customer problem
- 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
- Discovery questions
- 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?
- Value hypothesis
- Clear policy plus subject-specific training may raise teacher confidence and reduce ad hoc responses such as dropping homework.
- Potential engagement
- Semester-long policy-and-PD package for English and math departments with pre/post teacher survey.
- Unsupported claims
- That PD causes teacher confidence
- That confidence improves student learning
- That results generalise beyond this programme
Pre-sales engineering
Role takeaway
- Fit
- Limited; relevant where districts configure teacher-facing AI tools and want subject-specific defaults.
- Architecture and integration
- 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.
- Proof of value
- 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
Role takeaway
- 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.
- Skills and adoption
- English teachers need assignment designs resistant to AI substitution; math teachers need practical uses that free time without replacing practice.
- Governance checkpoints
- policy adoption
- post-PD survey review
- annual review of assessment changes
- Acceptance criteria
- 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
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 relevance to architecture; the main implication is that teacher-facing tools and guidance should differ by discipline.
Governance
Who approves, reviews and stays accountable for outcomes?
Clear written policy on permissible teacher and student AI use is associated with teacher confidence; ambiguity leaves teachers to improvise, including dropping homework.
Security and privacy
What data, permissions and controls need testing?
Limited relevance; the source does not address student data or privacy.
Accessibility and workforce
Who is affected, and what skills or accommodations follow?
Teacher morale and workload are central: many teachers report worsening attitudes toward teaching and are redesigning assessment.
Procurement
What should contracts, pricing and exit terms secure?
Limited; districts buying teacher AI tools should budget for discipline-specific training rather than tool access alone.
Operating model
Which teams own the service once it runs?
Professional development becomes part of AI policy implementation, differentiated by subject.
Publication history
- 2026-10-06K–12 · Issue 304 resources
Stable resource ID: cwu-washington-hs-teacher-ai-survey-20261005