Table of technical terms
Terms introduced in the playbook
| Term | Explanation | Also used in |
| Automation bias |
Accepting a machine's suggestion without independently checking it |
|
| AI Detector |
Software claiming to identify machine-written text. What it actually measures is predictability. |
1.5 |
| AI Pedagogical Competency Framework |
Structure that sorts AI-related teaching competencies into dimensions & levels and links them to outcomes & assessments. |
|
| Bias | Slants inherited from the material a system learned from and not reliably reduced by making the system bigger | 1.4, 1.5 |
| Cognitive offloading | Handing mental work to something outside your head. It is useful when knowledge is in place, and damaging when it is still forming. | 1.4 |
| Competence | What a teacher knows, can do & is willing to do, described so that it can be taught and checked. | |
| Deskilling | The slow erosion of professional exptertise when a tool absorbs the work through which that expertise is maintained. | 1.4 |
| False positive | A correct, honest piece of work wrongly flagged. The error that damages students | 1.4, 1.5 |
| Hallucination | Fluent, confident, false. Not a defect awaiting a patch but a consequence of how the systems generate text | 1.4, 1.5 |
| Guardrails | Limits built into a system so that it supports thinking instead of replacing it. | 1.4, 1.5 |
| Knowledge-action gap | The measured distance between knowing about AI and teaching differently because of it. | 1.4, 1.5 |
| Schema | Person's organised knowledge | 1.4 |
| Teaching about AI | Making AI itself the subject of the lesson, so that students understand how it works & where it fails. | |
| Teaching with AI | Using AI as a tool for your own teaching work, from planning to feedback. | |