From the K–12 edition of October 20, 2026
Evanston Township High School lets students use AI only with teacher authorization and a written disclosure, after two years of drafting and a June ransomware attack
Evanston Township High School District 202 (reported by The Daily Northwestern) · K-12 high school student AI use policy, academic integrity and teacher professional development · Evanston, Illinois, United States
- Publisher
- The Daily Northwestern
- Original publication
- October 20, 2026 (The Daily Northwestern)
- Source retrieved
- 2026-10-21
What happened
Following a new Illinois policy on AI in K-12 schools, ETHS updated its guidelines for 2026-27: students may use AI for coursework only if the teacher authorizes it and the student attaches a disclosure statement; unauthorized or undisclosed use is treated as plagiarism or academic dishonesty, with penalties up to failing the course. Staff said the guidelines took two years to finalize and rolled out while the school remains in 'triage mode' after a June cyberattack. A teacher PD session, 'Protecting Learning in the Age of AI,' is planned for late October. ETHS is a Google for Education Reference District with access to Gemini's Guided Learning mode; staff encourage teachers to use Google Docs revision history to see how student writing changed. The instructional technology director framed AI as a free alternative to paid tutoring.
Why it matters
A concrete high school policy that pairs teacher authorization with student disclosure and process evidence, under a new state policy and while recovering from a cyberattack.
Evidence and measured results
News report quoting district instructional technology staff and a student; no usage data, outcome measures or policy text reproduced.
Limitations and uncertainty
Student newspaper account; the policy document itself was not opened. The specific Illinois policy referenced is not named in the article. No measured outcomes on integrity cases or learning.
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-10-20; this does not change the original publication date. Each role follows the same checklist so takeaways compare across sources.
Sales
Role takeaway
- Customer problem
- A high school has a written AI policy but needs consistent, low-cost classroom routines for authorization, disclosure and review.
- Stakeholders
- Director of instructional technology
- Assistant principal for academics
- Department chairs
- Teachers
- Families
- Discovery questions
- How do teachers signal which assignments allow AI?
- Where are student disclosure statements stored?
- How are suspected undisclosed-use cases reviewed today?
- How much capacity does the technology team have after recent incidents?
- Value hypothesis
- Clear routines and templates could make the policy enforceable without buying detectors; not measured here.
- Potential engagement
- A six-week policy-to-practice package: disclosure templates, teacher review checklist and two PD sessions.
- Unsupported claims
- No evidence of reduced cheating.
- No learning outcome data.
- Policy text not reviewed.
Pre-sales engineering
Role takeaway
- Fit
- Fits districts on Google Workspace for Education using Gemini with student access.
- Architecture and integration
- Use Docs version history and Classroom assignment settings to capture process evidence and per-assignment AI permissions.
- Prerequisites
- Workspace admin access
- Gemini student settings inventory
- Retention settings for Docs history
- Constraints
- Illinois state AI policy requirements
- Technology team capacity after ransomware recovery
- Google feature changes
- Security
- Review who can access revision history and disclosure statements and align retention with student records rules.
- Proof of value
- Per-assignment AI permission visible to students
- Revision history available for sampled assignments
- Disclosure statements captured in one place
Delivery
Role takeaway
- Work
- Turn the AI guidelines into consistent per-assignment authorization, disclosure and review routines.
- Dependencies
- Teacher PD time
- Workspace configuration
- Academic integrity process owners
- Ownership
- Instructional technology team with the assistant principal for academics.
- Skills and adoption
- Late-October PD on when AI supports learning; follow-up coaching by department.
- Governance checkpoints
- Policy-to-routine review
- Mid-semester sample of integrity cases
- End-of-semester policy review
- Acceptance criteria
- Proposed: every department uses the disclosure template
- Proposed: integrity referrals cite process evidence rather than detector scores
- Proposed: teacher survey shows policy is understood
- Risks
- Team overload during cyber recovery
- Inconsistent teacher authorization
- Over-reliance on revision history as proof
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?
Relies on the Google Workspace for Education stack: Gemini Guided Learning for students and Docs revision history as evidence of the writing process. Interpretation: integrity enforcement is being designed into the productivity suite rather than bought as a separate detector.
Governance
Who approves, reviews and stays accountable for outcomes?
Teacher-level authorization with mandatory student disclosure; undisclosed use handled through existing academic dishonesty rules; policy developed over two years with staff input.
Security and privacy
What data, permissions and controls need testing?
The rollout coincided with recovery from a June ransomware attack; the report does not describe AI-specific data protections. Interpretation: AI governance and cyber recovery compete for the same small technology team.
Accessibility and workforce
Who is affected, and what skills or accommodations follow?
Staff framed AI as a free substitute for paid tutoring, an equity argument; PD is limited to a planned session so far.
Procurement
What should contracts, pricing and exit terms secure?
No new AI product purchase described; relies on existing Google for Education tools.
Operating model
Which teams own the service once it runs?
Teacher discretion within a school-wide disclosure rule, supported by the instructional technology team.
Publication history
- 2026-10-20K–12 · Issue 445 resources
Stable resource ID: evanston-eths-teacher-authorized-ai-disclosure-guidelines-20261020