About this guide
Who wrote this guide, what it covers and does not, how sources were chosen, and where to send corrections.
Joe Sabado
An AI practitioner working in higher education. This guide is part of the Campus AI Framework ecosystem at campusaiframework.com. It is independent work. It is not affiliated with, endorsed by, or the official policy of any institution, and the views are the author’s own.
Send feedback or corrections to Joepsabado@gmail.com.
Generative AI tools helped draft and design this guide. The author chose the sources, reviewed the content and is responsible for it.
This independent resource offers an AI practitioner’s perspective on AI use in higher education. It helps faculty, students and institutional leaders understand AI-use options, clarify expectations and consider responsible-use and governance implications. It does not prescribe teaching methods, validate assessment designs, or replace disciplinary expertise, instructional-design support or institutional policy.
What this guide covers
- AI capabilities, limitations and use patterns
- AI-use permissions and disclosure expectations
- Privacy, access, accountability and governance questions
- Adaptable decision aids and communication templates
- When to seek local review
Left to faculty and specialists
- How students learn a discipline
- Whether an assessment validly measures mastery
- Instructional sequences and grading rubrics
- Which teaching methods are effective
- Faculty judgment and institutional policy
The Campus AI Framework ecosystem works at three levels. This guide covers course-level AI expectations and links to the other two.
Sources are judged by whether they still apply, not by age alone. Each one is placed in one of three groups: recent findings (new research, policy changes and tool-specific results, mostly November 2025 to November 2026); foundational evidence and frameworks (older work that remains relevant, such as UNESCO guidance and the Russell Group principles); and superseded or historical material (kept with a note on what changed). Publication date and last-reviewed date are tracked separately.
Research is summarized as reported by its authors. Notes marked “author’s interpretation” are practitioner readings, not pedagogical recommendations. Institutional policies and sample syllabus statements are cited as published guidance still in force. Every source links to the original on the References page.
The Campus AI Registry & Governance Framework used on the Policy artifacts page is also the author’s work. It is presented as an original framework, separate from the external research and institutional guidance cited elsewhere.
Last updated 7 November 2026. This guide is not legal advice.
Update protocol. Sources are rechecked at each new version and given a last-reviewed date. A source moves to superseded only when newer evidence or a policy change limits how it applies, and the reason is noted. Corrections sent by readers are reviewed and logged below.
- 2.1 Narrowed to an AI practitioner’s scope: scope statement; AI and learning page trimmed; AI considerations for assignments; faculty guide trimmed.
- 2.0 Six AI roles; student AI competencies; evidence classification; fuller framework comparison; ecosystem.
- 1.6 Site search in the Contents panel; section links.
- 1.5 Glossary; faculty implementation guide; downloads on the home page.
- 1.4 Cognitive offloading and learning-outcome studies; frameworks compared.
- 1.3 For students page; starter kit.
- 1.2 Evidence labels; due process for detectors.
- 1.1 Equity practices; downloads; authorship.
- 1.0 First release.