Two lessons that establish three things: an honest map of where you are starting from (the confidence audit); a working understanding of what TY students actually do with AI today and what the NCCA TY Programme Statement asks of you; and a productive mindset for teaching a topic that is moving faster than any teacher can keep up with on their own.
| Welcome, Confidence Audit and the Lead Learner Mindset for AI | ||
| The TY AI Landscape: What Students Actually Use (and What They Do Not Tell You) |
Two lessons that build the conditions for everything else to work: a sensible classroom AI use policy that you can actually enforce, and a Class AI Charter co-designed with your students so that the rules feel like theirs, not a pasted-in school document. These two artifacts become the foundation Modules 3, 4 and 5 build on.
| Drafting an AI Use Policy for Your TY Classroom | ||
| Co-designing a Class AI Charter with Your Students |
Three lessons covering the practical assessment-design problem at the heart of TY AI delivery: which tasks should be designed so AI cannot easily do them (AI-robust), which should deliberately invite AI use as part of the learning (AI-friendly), why detection tools are not the answer, and how to assess TY projects in a portfolio-led, disclosure-led culture.
| Designing Tasks That Are Ai-robust (and Knowing Which to Leave Ai-friendly) | ||
| Spotting Ai-generated Work, and Why Detection Tools Are Not the Answer | ||
| Ai-aware Assessment for TY Projects: Process, Evidence, Disclosure |
Two lessons covering the content TY students most need from you: how to evaluate AI output critically (hallucination, training-data bias, missing sources, image and audio deepfakes) and how to talk to TY students about AI in a way that is neither breathless hype nor doom-scroll fear.
| Hallucination, Bias, Sources and Deepfakes | ||
| Talking to Students About AI Without Hype or Doom |
Two lessons that close the course. The first treats AI literacy as a cross-curricular project, connecting the conversation a student has in Exploring AI (or in your subject-embedded module) to what their other TY teachers say. The second synthesises everything into your TY AI Year Plan and the final reflection.
| Cross-subject Coherence and Ty's Personal-growth Goals | ||
| Your TY AI Year Plan and Final Reflection |
Two lessons that establish three things: an honest map of where you are starting from (the confidence audit); a working understanding of what TY students actually do with AI today and what the NCCA TY Programme Statement asks of you; and a productive mindset for teaching a topic that is moving faster than any teacher can keep up with on their own.
| Welcome, Confidence Audit and the Lead Learner Mindset for AI | ||
| The TY AI Landscape: What Students Actually Use (and What They Do Not Tell You) |
Two lessons that build the conditions for everything else to work: a sensible classroom AI use policy that you can actually enforce, and a Class AI Charter co-designed with your students so that the rules feel like theirs, not a pasted-in school document. These two artifacts become the foundation Modules 3, 4 and 5 build on.
| Drafting an AI Use Policy for Your TY Classroom | ||
| Co-designing a Class AI Charter with Your Students |
Three lessons covering the practical assessment-design problem at the heart of TY AI delivery: which tasks should be designed so AI cannot easily do them (AI-robust), which should deliberately invite AI use as part of the learning (AI-friendly), why detection tools are not the answer, and how to assess TY projects in a portfolio-led, disclosure-led culture.
| Designing Tasks That Are Ai-robust (and Knowing Which to Leave Ai-friendly) | ||
| Spotting Ai-generated Work, and Why Detection Tools Are Not the Answer | ||
| Ai-aware Assessment for TY Projects: Process, Evidence, Disclosure |
Two lessons covering the content TY students most need from you: how to evaluate AI output critically (hallucination, training-data bias, missing sources, image and audio deepfakes) and how to talk to TY students about AI in a way that is neither breathless hype nor doom-scroll fear.
| Hallucination, Bias, Sources and Deepfakes | ||
| Talking to Students About AI Without Hype or Doom |
Two lessons that close the course. The first treats AI literacy as a cross-curricular project, connecting the conversation a student has in Exploring AI (or in your subject-embedded module) to what their other TY teachers say. The second synthesises everything into your TY AI Year Plan and the final reflection.
| Cross-subject Coherence and Ty's Personal-growth Goals | ||
| Your TY AI Year Plan and Final Reflection |
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