Research Note
AI Tutor Source Pack Design Framework
Treat source selection as curriculum and evidence design. A source-grounded system inherits the pack's authority, versions, conflicts, gaps, rights, and data sensitivity.
In this article
AI Tutor Source Pack Design Framework
Design principle
Treat source selection as curriculum and evidence design. A source-grounded system inherits the pack's authority, versions, conflicts, gaps, rights, and data sensitivity.
Source manifest
| Field | Evidence to record |
|---|---|
| Learning objective | What the learner must explain, decide, or do |
| Source identity | Exact title, author, publisher, URL or file, and version |
| Authority | Why this source can support the intended claim |
| Date | Publication, effective, revision, and access dates |
| Scope | Questions it answers and questions it does not |
| Status | Current, historical, superseded, draft, or disputed |
| Rights | Permission, license, access, and sharing boundary |
| Data class | Public, internal, confidential, personal, regulated, or prohibited |
| Conflicts | Material disagreement with another included source |
| Representation | What an import omits or transforms |
Method
Write the learning objective and a small set of test questions first.
Prefer primary authority for rules, specifications, policy, and original research. Add explanatory sources when they help a learner understand primary material, and label their role.
Preserve disagreements rather than forcing false consensus. Include a conflict note that explains the question, competing positions, dates, and evidence needed to resolve it.
Remove duplicates, unreadable scans, unneeded personal data, and material the user lacks permission to upload.
Test the pack with answerable, conflicted, and deliberately unanswerable questions. The system should not be rewarded for filling a documented gap with plausible prose.
Decision boundary
A coherent pack can support a bounded study job. It cannot authorize uploading copyrighted, confidential, personal, regulated, or institutionally restricted content.
High-impact questions still require authoritative systems and qualified human judgment outside the notebook.
Sources
Follow the evidence.
- support.google.com: 16322204support.google.com
- support.google.com: 17003757support.google.com
- support.google.com: 17004255support.google.com
- blog.google: notebooklm new features december 2024blog.google
- studentprivacy.ed.gov: privacy and education technologystudentprivacy.ed.gov
- support.google.com: 16212820support.google.com
- NIST AI Risk Management Frameworknist.gov
- www2.ed.gov: ai reportwww2.ed.gov
- daltonanderson.net: googles ai tutor the future of personalized learningdaltonanderson.net
- support.google.com: notebooklmsupport.google.com
- support.google.com: 16213268support.google.com
- journals.sagepub.com: fulljournals.sagepub.com
- youtu.be: 6BwWKkZ7aeAyoutu.be
- support.google.com: 16179559support.google.com
- NIST Generative AI Profilenvlpubs.nist.gov
- blog.google: notebooklm audio overviewsblog.google
- support.google.com: 16164461support.google.com
- open.spotify.com: 1YXy6yyC4u2mnqeARVB5qvopen.spotify.com
- edu.google.com: ai notebooklmedu.google.com
- support.google.com: 16215270support.google.com
- daltonanderson.ghost.io: googles ai tutor the future of personalized learningdaltonanderson.ghost.io