# ChatwithGPT expansion roadmap: research reference ledger

Published 2026-10-13. Supports a proposed roadmap, not verified pilot results.

These primary-source references informed the plan and opportunities. Access was checked on the stated date. External pages can change; the support and limit notes describe what each reference can establish.

### W3C: Web Content Accessibility Guidelines 2.2

**Reference:** [W3C: Web Content Accessibility Guidelines 2.2](https://www.w3.org/TR/WCAG22/)

**Checked:** 2026-10-13

**Supports:** A current normative target for accessibility review, including reflow, keyboard operation, focus, contrast, labels and target size.

**Limits:** A checklist, automated scan or selected-page review does not establish whole-site conformance.


### W3C WAI: Evaluating Web Accessibility

**Reference:** [W3C WAI: Evaluating Web Accessibility](https://www.w3.org/WAI/test-evaluate/)

**Checked:** 2026-10-13

**Supports:** Combine tools with knowledgeable human evaluation and include people with disabilities.

**Limits:** No evaluation tool alone determines accessibility. This roadmap does not claim an audit has been completed.


### NIST AI 600-1: Generative Artificial Intelligence Profile

**Reference:** [NIST AI 600-1: Generative Artificial Intelligence Profile](https://www.nist.gov/publications/artificial-intelligence-risk-management-framework-generative-artificial-intelligence)

**Checked:** 2026-10-13

**Supports:** Risk-aware design, use and evaluation of generative AI across sectors.

**Limits:** Voluntary guidance. A cited risk framework neither certifies the site nor demonstrates that a teaching workflow is effective.


### DORA: Software delivery performance metrics

**Reference:** [DORA: Software delivery performance metrics](https://dora.dev/guides/dora-metrics/)

**Checked:** 2026-10-13

**Supports:** Small changes, a baseline and balanced delivery and instability measures for the same service over time.

**Limits:** Use site-specific observations; do not compare unlike teams, turn deployment frequency into a quota, or call page output productivity.


### Google SRE: Monitoring Distributed Systems

**Reference:** [Google SRE: Monitoring Distributed Systems](https://sre.google/sre-book/monitoring-distributed-systems/)

**Checked:** 2026-10-13

**Supports:** Check externally visible behavior and make alerts actionable.

**Limits:** Adapt narrowly to this small static site; no elaborate telemetry platform or claim of Google-scale reliability is implied.


### OpenAI: Evaluation best practices

**Reference:** [OpenAI: Evaluation best practices](https://developers.openai.com/api/docs/guides/evaluation-best-practices)

**Checked:** 2026-10-13

**Supports:** Task-specific objectives, representative test cases, explicit criteria and human-calibrated review.

**Limits:** Vendor guidance, not an independent efficacy study. Example thresholds are not universal targets. Product availability and deprecations require a fresh check before implementation.


### PRISMA 2020 statement

**Reference:** [PRISMA 2020 statement](https://www.prisma-statement.org/prisma-2020)

**Checked:** 2026-10-13

**Supports:** Transparent reporting of a review question, search, selection and synthesis.

**Limits:** The site can borrow reporting disciplines; an editorial scan is not a systematic review or PRISMA-compliant review by default.


### Cochrane Handbook, Chapter 14: Certainty of evidence

**Reference:** [Cochrane Handbook, Chapter 14: Certainty of evidence](https://www.cochrane.org/authors/handbooks-and-manuals/handbook/current/chapter-14)

**Checked:** 2026-10-13

**Supports:** Make limitations and differences between the studied setting and the proposed use visible.

**Limits:** Clinical evidence-grading methods are not mechanically transferred into a numerical grade for website lessons.


### GOV.UK Service Manual: Moderated usability testing

**Reference:** [GOV.UK Service Manual: Moderated usability testing](https://www.gov.uk/service-manual/user-research/using-moderated-usability-testing)

**Checked:** 2026-10-13

**Supports:** Observe people attempting defined tasks to discover usability problems.

**Limits:** Small opt-in sessions find problems; they do not establish population-level learning gains. Recruitment, recording and publication require appropriate approval and consent.


### Google Search Central: Helpful, reliable, people-first content

**Reference:** [Google Search Central: Helpful, reliable, people-first content](https://developers.google.com/search/docs/fundamentals/creating-helpful-content)

**Checked:** 2026-10-13

**Supports:** Prioritize a real audience, clear purpose, original useful work and transparent sourcing.

**Limits:** Search guidance is not a promise of indexing, rankings, traffic or audience growth.


### Education Endowment Foundation: Effective Professional Development

**Reference:** [Education Endowment Foundation: Effective Professional Development](https://educationendowmentfoundation.org.uk/education-evidence/guidance-reports/effective-professional-development)

**Checked:** 2026-10-13

**Supports:** Deliberate professional-learning design, reflection and implementation support.

**Limits:** Education-focused evidence does not establish effects of the proposed AI practice packets.


### UNESCO: AI competency frameworks for students and teachers

**Reference:** [UNESCO: AI competency frameworks for students and teachers](https://www.unesco.org/en/articles/what-you-need-know-about-unescos-new-ai-competency-frameworks-students-and-teachers)

**Checked:** 2026-10-13

**Supports:** Teacher AI competence includes human agency, ethics, pedagogy, foundations and continuing professional development.

**Limits:** A competency framework is guidance, not evidence that this site improves teaching or student learning.


### ACTE: Applied Co-Intelligence report announcement

**Reference:** [ACTE: Applied Co-Intelligence report announcement](https://www.acteonline.org/blog/cte-policy-watch/new-report-applied-co-intelligence-preparing-career-and-technical-education-learners-for-an-ai-driven-workforce/)

**Checked:** 2026-10-13

**Supports:** The announced CTE framework emphasizes human capacity to critique, direct and collaborate with AI, beyond tool use.

**Limits:** Announcement reviewed; the underlying report was not independently evaluated. No program alignment, accreditation or effectiveness claim follows.


### NIST MEP: Manufacturing Workforce Development

**Reference:** [NIST MEP: Manufacturing Workforce Development](https://www.nist.gov/mep/manufacturing-workforce-development)

**Checked:** 2026-10-13

**Supports:** Manufacturing training includes structured onboarding, communication, teamwork, problem solving and technical skills.

**Limits:** Supports relevant learning tasks, not demand for this website. Older statistics and performance anecdotes on the page are not used.


### TechSoup: AI for Nonprofits resources and education hub

**Reference:** [TechSoup: AI for Nonprofits resources and education hub](https://page.techsoup.org/ai-for-nonprofits)

**Checked:** 2026-10-13

**Supports:** The nonprofit learning hub pairs practical work with use-policy, governance and data-protection guidance.

**Limits:** A provider resource hub is evidence of an existing learning offering, not quantified unmet demand or independent impact evidence.


### NTEN: Equity Guide for Nonprofit Technology

**Reference:** [NTEN: Equity Guide for Nonprofit Technology](https://www.nten.org/change/equity-guide-for-nonprofit-technology)

**Checked:** 2026-10-13

**Supports:** NTEN recommends recurring consideration of equity in nonprofit technology strategy, policy review and evaluation.

**Limits:** The guide does not validate a specific AI workflow; local capacity and community needs still require review.


### Government Digital Service: Artificial Intelligence Playbook

**Reference:** [Government Digital Service: Artificial Intelligence Playbook](https://www.gov.uk/government/publications/ai-playbook-for-the-uk-government/artificial-intelligence-playbook-for-the-uk-government-html)

**Checked:** 2026-10-13

**Supports:** Public-sector AI guidance emphasizes meaningful human control, testing, lifecycle maintenance and choosing an appropriate tool.

**Limits:** UK public-sector guidance is context-specific. This research makes no compliance or legal-advice claim.


### U.S. Small Business Administration: AI for small business

**Reference:** [U.S. Small Business Administration: AI for small business](https://legacy.sba.gov/business-guide/manage-your-business/ai-small-business)

**Checked:** 2026-10-13

**Supports:** SBA recommends starting small, testing whether a tool adds value, and human review of generated work.

**Limits:** Verified official legacy page; the main-domain route redirects. Broad legal, security and productivity assertions on the legacy page are not adopted.


### OpenAI: Evaluation best practices

**Reference:** [OpenAI: Evaluation best practices](https://developers.openai.com/api/docs/guides/evaluation-best-practices)

**Checked:** 2026-10-13

**Supports:** Use task-specific evaluation, explicit success criteria, expert-informed cases and human calibration; repeat evaluation as systems change.

**Limits:** Vendor technical guidance, not validation of this curriculum. Durable evaluation methods are separated from changing platform features.


### Anthropic: Building effective agents

**Reference:** [Anthropic: Building effective agents](https://www.anthropic.com/engineering/building-effective-agents)

**Checked:** 2026-10-13

**Supports:** Begin with simple adequate designs and add agent complexity only when evaluation demonstrates value.

**Limits:** Vendor engineering experience is not a universal causal result or a guarantee for a new use case.


### NIST: Generative Artificial Intelligence Profile

**Reference:** [NIST: Generative Artificial Intelligence Profile](https://www.nist.gov/publications/artificial-intelligence-risk-management-framework-generative-artificial-intelligence)

**Checked:** 2026-10-13

**Supports:** A voluntary cross-sector resource addresses trustworthiness across AI design, development, use and evaluation.

**Limits:** This brief does not claim NIST certification, complete implementation or compliance.


### OpenAI: Deprecations

**Reference:** [OpenAI: Deprecations](https://developers.openai.com/api/docs/deprecations)

**Checked:** 2026-10-13

**Supports:** The Evals platform transition includes a scheduled read-only stage and shutdown of its dashboard and API.

**Limits:** This is a specific product lifecycle notice, not withdrawal of evaluation methodology or all OpenAI APIs. Recheck before implementation.


### ACTE: High-quality CTE framework update

**Reference:** [ACTE: High-quality CTE framework update](https://www.acteonline.org/high-quality-cte-update/)

**Checked:** 2026-10-13

**Supports:** ACTE is updating its quality framework with stakeholder input and literature review.

**Limits:** An announced update is not a released replacement framework; no formal alignment is claimed.


### Harvard University Information Technology: AI Basics

**Reference:** [Harvard University Information Technology: AI Basics](https://www.huit.harvard.edu/ai-basics)

**Checked:** 2026-10-13

**Supports:** The public guide covers use cases, specific objectives and boundaries, source checking, review and iterative feedback.

**Limits:** Institutional guidance is not small-business impact research; Harvard-specific tool and policy rules do not transfer to other organizations.


### ACTE: High-quality CTE Tools

**Reference:** [ACTE: High-quality CTE Tools](https://www.acteonline.org/professional-development/high-quality-cte-tools/)

**Checked:** 2026-10-13

**Supports:** The professional-body hub provides a program-quality framework, self-evaluation resources and links to learning opportunities.

**Limits:** This is program-quality guidance, not AI workflow certification. The online assessment may collect information; it was not completed.


### Education Endowment Foundation: Effective Professional Development recommendations

**Reference:** [Education Endowment Foundation: Effective Professional Development recommendations](https://d2tic4wvo1iusb.cloudfront.net/production/eef-guidance-reports/effective-professional-development/EEF-Effective-PD-Recommendations-Poster.pdf)

**Checked:** 2026-10-13

**Supports:** The recommendations include modeling, rehearsal, feedback, action planning and context-specific repetition in professional development.

**Limits:** Mechanism-level guidance does not establish that this proposed pack, scaffold sequence or AI use will be effective.