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Start with the instructional problem, not the product. A district should adopt an AI teaching tool only when it can show a plausible, evidence-backed benefit for a defined group of learners; protect student and educator information; preserve educator judgment; serve students accessibly and equitably; and support implementation, measurement, and an exit decision. The U.S. Department of Education’s August 20, 2026 education-technology guidance, its 2023 report on AI and teaching, and related privacy resources provide a practical sequence for making that decision.
What learning problem does it solve?
Write the use case before looking at feature lists or demonstrations. State the educational need in terms a teacher, principal, and family would recognize: for example, improving formative feedback on a particular writing task, helping a teacher differentiate practice, or giving students guided support during a defined part of a lesson. A general promise to “use AI in the classroom” is not a use case.
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The Department of Education’s August 2026 guidance frames product evaluation around five questions. The first is: “What learning problem does it solve?” The remaining questions prevent a tool from expanding beyond its purpose:
- When should it be used? Identify the lesson, intervention, planning task, or assessment context.
- For whom should it be used? Specify grade, subject, language needs, disability-related needs, and whether the users are students, educators, or both.
- For how long should it be used? Define a session, unit, term, or pilot period rather than allowing indefinite use.
- What evidence demonstrates that it improves student learning? Name the outcome the district expects to change and how that change will be measured.
Also record what the tool will not do. A tutoring system might provide hints but not determine grades. A planning assistant might draft materials but not make placement decisions. Clear boundaries make later monitoring and staff training possible.
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What evidence demonstrates that it improves student learning?
Ask the provider for the studies, analyses, and implementation records behind every learning claim. Then test whether the evidence matches the district’s intended students, subject, setting, duration, and outcome. Evidence that a product is popular, engaging, fast, or frequently used does not establish that students learned more.
Check relevance and independence
- Identify the population studied and compare it with the students who would use the tool.
- Check whether the measured outcome is the district’s outcome, such as improved reading comprehension or better feedback quality, rather than a proxy such as time on task.
- Ask who designed, funded, analyzed, and published the evaluation. Treat a vendor description of its own product as a claim to verify, not as independent confirmation.
- Confirm the intervention’s length and the conditions required to reproduce the result, including teacher involvement and training.
- Look for limitations, missing groups, and results that did not improve.
The 2026 Department guidance urges districts to choose tools with proven results, seek independent evidence, review effectiveness regularly, and support educator training. Its 2023 report similarly warns against adopting technology because it is exciting; discussions should begin and end with students’ educational needs and effectiveness against those needs.
Define success before a pilot
Write a short evaluation plan before licenses are issued. It should name a baseline, the target outcome, the comparison or reference point, the collection method, the review dates, and who can pause the pilot. A district might examine common assessment results, rubric-scored work, attendance in an intervention, or teacher-verified error rates, depending on the use case. Avoid claiming causation from a single usage dashboard.
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What student and educator data does the service collect?
Complete the privacy review before procurement or student access. Read the privacy policy, terms of service, product documentation, and any data-processing or security materials supplied for the district edition. Map every category of information that enters the service, where it goes, how long it remains, and who can use it.
Build a data map
| Question | What to document |
|---|---|
| What is collected? | Account identifiers, student work, prompts, voice or image inputs, device information, usage logs, and educator content, as applicable. |
| Why is it used? | Instructional response, account administration, safety, analytics, model improvement, or another stated purpose. |
| Where is it transmitted? | Provider systems, subprocessors, integrations, or destinations identified in the service documentation. |
| How long is it retained? | Default retention, deletion triggers, backups, and what the district can request or control. |
| Who controls access? | District administrators, teachers, students, provider personnel, and any other parties. |
| What controls exist? | Role permissions, account deletion, export, correction, audit information, and settings that limit collection or sharing. |
Use the Department of Education’s Privacy and Education Technology resources, including its guidance on online educational services and Model Terms of Service checklist, as a structured review aid. The checklist does not replace district counsel or prove that a particular product satisfies every applicable requirement. The tool’s actual practices and the district’s state and local obligations determine the legal analysis; the general framework here is not a product-specific legal conclusion.
Resolve ambiguous contract language
Ask the provider to explain undefined terms such as “improve services,” “business purposes,” “de-identified,” or “partners.” Require the contract and configuration to match the provider’s answers. Establish what happens to accounts, prompts, student work, and logs when a pilot ends or a contract is terminated. Do not permit staff to upload sensitive information merely because a free or trial account is easy to create.
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Questions for a live demonstration
- What inputs produced this recommendation or response?
- Can a teacher see relevant reasoning, confidence information, source material, or known limitations without exposing confidential data?
- How does the system signal uncertainty, missing context, or a possible error?
- Can a teacher edit, reject, or override an output before it reaches a student or affects a record?
- Is there a non-AI workflow when the system is wrong, unavailable, or inappropriate?
- Can the district disable a feature, restrict a role, or review an audit history?
Test incorrect prompts and edge cases with instructional staff. Record whether a teacher can identify a fabricated explanation, biased assumption, unsuitable reading level, or unsafe suggestion quickly enough to protect the learner. “Human in the loop” is meaningful only when the human has time, information, authority, and a workable alternative.
Will the tool work for the intended learners?
Evaluate accessibility and equity as part of instructional fit, not as a post-purchase check. Pennsylvania Department of Education guidance highlights accessibility and whether a tool meaningfully supports instruction. Federal AI guidance connects adoption with equity and human judgment, while UNESCO’s human-centered guidance raises data privacy, age-appropriate use, and ethical validation.
Accessibility checks
- Test keyboard navigation, screen-reader output, captions, transcripts, contrast, zoom, and alternative input where relevant.
- Check whether generated text, audio, images, and feedback can be adjusted for reading level, language, and disability-related needs.
- Verify that essential activities do not require a device, bandwidth, microphone, camera, or account that some students cannot access.
- Confirm that teachers can provide an equivalent non-AI task without penalizing a student who cannot use the tool.
Equity and age-appropriateness
Compare outputs across languages, dialects, disability-related contexts, and cultural references relevant to the district. Look for different error rates, refusal patterns, or quality of feedback among groups. Ask whether the product’s minimum age, consent flow, content controls, and data practices fit the intended learners. Include instructional, special-education, English-learner, accessibility, and technology expertise in the review rather than assigning the decision to one enthusiastic adopter.
Parents and other affected stakeholders should have a meaningful opportunity to understand and comment on adoption and deployment. The Department’s July 2025 AI guidance emphasizes stakeholder engagement, especially with parents. Explain the tool’s purpose, the information it handles, when students will encounter it, how teachers remain responsible, and how families can raise concerns.
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What implementation support is required?
A technically available product can still fail if educators do not know when to use it, how to check its output, or how to teach without it. Require a practical implementation plan that names training, coaching, technical support, communication, and time for teachers to adapt lessons.
Prepare educators
- Train staff on the defined use case, privacy rules, accessibility settings, verification of outputs, and the human override process.
- Provide sample lessons and non-AI alternatives, then allow educators to practice with realistic and intentionally flawed outputs.
- Define who answers instructional, technical, safeguarding, and privacy questions during the pilot.
- Tell staff what they may not enter, how to report an incident, and how to preserve a student’s access to human help.
Communicate with students and families
Publish a plain-language explanation of when the tool is used, what it can and cannot decide, what data is involved, and how a person can review or challenge an output. Explain whether use is required, optional, or limited to a particular intervention. Keep a channel for complaints and document how the district responds.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should a district compare two or more tools?
Use the same defined use case, evidence request, privacy questions, accessibility tests, and pilot measures for every candidate. The following comparison frame reflects the federal and state guidance; it is not a government-mandated scorecard.
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|---|---|---|
| Instructional fit | Use-case description, supported grades and subjects, workflow demonstration | Does it address the stated learning problem for the intended group? |
| Learning evidence | Independent and provider studies, methods, outcomes, limitations | Does evidence match the district’s students and desired outcome? |
| Privacy and data handling | Privacy policy, terms, data map, retention and deletion controls, subprocessors | Can the district control collection, use, transmission, and deletion? |
| Human control | Explanation, uncertainty signals, edit and override functions, auditability | Can educators exercise professional judgment and provide a human alternative? |
| Accessibility and equity | Assistive-technology tests, language and subgroup checks, age safeguards | Can intended learners use it fairly and meaningfully? |
| Implementation | Training, support, family communication, incident process | Can the district deploy it without shifting unreasonable work or risk to teachers? |
| Monitoring and exit | Outcome measures, review dates, pause, export, and termination procedures | Can the district detect failure and stop or change course? |
The cited guidance does not prescribe a universal weighting for these dimensions. Set weights locally according to the learning need, student population, legal obligations, and risk. A tool that performs well on convenience but fails a non-negotiable privacy or accessibility requirement should not remain eligible merely because its total score is high.
What should the pilot and approval record contain?
Before approval, assemble one record that another administrator could audit without relying on a sales presentation.
- Use-case statement: learning problem, users, setting, duration, boundaries, and human responsibilities.
- Evidence file: studies and claims, relevance assessment, conflicts, limitations, and the outcome the district will measure.
- Privacy review: completed data map, policy and terms review, contract questions, retention and deletion decisions, and counsel’s assessment where required.
- Human-control test: examples of normal and incorrect outputs, override steps, fallback workflow, and staff sign-off.
- Accessibility and equity record: test environments, affected stakeholders consulted, unresolved barriers, and accommodations.
- Implementation plan: training dates, support contacts, family communication, student instructions, and incident escalation.
- Measurement and exit plan: baseline, success criteria, review calendar, pause authority, renewal conditions, and data-deletion steps.
Run the pilot for the duration specified in the use case, not simply until users report that the interface feels useful. Review both learning measures and implementation conditions: whether teachers had time to verify outputs, whether students could access alternatives, and whether privacy or safety incidents occurred.
When should the district stop or change course?
The 2026 Department guidance says districts should change course when evidence shows a tool is not improving learning and remove it when repeated findings show persistent shortcomings. Define those triggers before results arrive. Examples include no improvement against the agreed outcome after the planned review, recurring inaccurate or discriminatory outputs that staff cannot reliably catch, an unresolved accessibility barrier, data practices that do not match the contract, or implementation demands that prevent responsible teacher oversight.
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A stop decision should include student continuity: tell teachers and families what changes, preserve access to instruction, export or delete information according to the contract and district policy, and document the reason. A tool can be useful in one narrow context and unsuitable in another; narrowing the use case is a valid corrective action when the evidence supports it.
Common procurement mistakes
- Starting with a feature demo: reverse the order and define the learning problem first.
- Treating engagement as impact: require outcome evidence tied to the intended learners.
- Accepting a generic privacy statement: map actual inputs, uses, recipients, retention, and controls.
- Assuming a teacher can “just check” everything: test whether explanations, time, and override authority are practical.
- Leaving accessibility until rollout: include assistive-technology and alternative-workflow testing before approval.
- Ignoring families and students: communicate purpose, data handling, human review, and complaint routes.
- Renewing by inertia: tie continuation to scheduled learning results and documented implementation conditions.
What this framework does—and does not—decide
This is general U.S.-oriented district due diligence, not legal advice and not a finding that any particular product complies with law. State and local rules, contract language, edition-specific features, and actual data practices matter. Vendor terms, capabilities, and available evidence can change, so verify them during the district’s own review. The cited government and international guidance supplies evaluation principles, not a vendor ranking, universal price, or endorsed product.
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