Facilitator guide · staff development day
AI for TAS Teachers
Everything you need to run this course with your staff — 5 sessions, ~4 hours total.
How to run it
Run this with your TAS faculty as a twilight, half a staff development day, or faculty-meeting-by-meeting — it's ~4 hours. It assumes staff have done the flagship 'Teaching with AI' course (or will): this playbook is the TAS-specific layer, so don't re-litigate general ethics — point back to it and go deep into TAS. Each module has a session plan, three discussion prompts and a 'watch for'. Before you start: make sure everyone can log in to Lessio and to NSWEduChat; ask each teacher to bring one real, de-identified TAS task from their own teaching (a design brief they set, a project they run, a procedure or recipe, a folio task they're about to write); and — this is the TAS non-negotiable — have your school's WHS / risk-assessment process and the relevant safety guidance (workshop machinery, electrical, food hygiene, chemicals) open in the room, because the safety message only lands if it is concrete. Capture two things across the cohort: a faculty rule for 'how we use AI in TAS' (with the WHS line and the student-authorship line written in bold), and each teacher's capstone reflection for their eTAMS PD record.
Session plans
- 1
Where AI actually helps in TAS — and where it fails
~50 minSession planOpen with a deliberately confronting live demo: ask a general AI for 'a step-by-step procedure for a Year 9 class to cut and join timber on the workshop machines' (or 'a quick way to sanitise the food room') and read the output to the room — then pull out the WHS gaps together (guards? PPE? lock-out? ventilation? food temperature control? compatible chemicals?). That single demo earns the whole course's safety discipline. Then build the eight-row use-case grid on the board from the staff's own examples, and have each teacher stress-test one Lessio output for the three failure modes.
Discussion prompts- Which of our practical procedures would an AI-drafted method be genuinely tempting for — and genuinely risky?
- Where in our courses is the line between 'AI scaffolds the task' and 'AI does the student's designing' — and where have we seen it crossed?
- Which technical details (dimensions, quantities, costings, material properties) would a confident AI error damage most before we'd notice?
Watch forTwo camps: the over-trusting ('the procedure looked fine to me') and the dismissive ('so it's useless for a hands-on subject'). The truth is in between — superb for drafting briefs, scaffolds, task sheets and rubrics; never trusted for safety, for the student's designing, or for raw technical detail. Don't let the safety demo become 'AI is dangerous, ban it'; the message is 'AI drafts, a qualified human verifies and signs off the safety'.
Standards2.1 Content and teaching strategies of the teaching area2.6 Information and Communication Technology (ICT)4.4 Maintain student safety - 2
Subject-specific prompt craft for TAS
~50 minSession planThe hands-on hour. Live-build one TAS prompt with the room: take a vague 'make a project on X', add the real focus area and outcome code (have the relevant NSW Technology syllabus open to grab one), add the design-process stage, add the measurement/spec and WHS guard-rails and the keep-it-the-student's-design line, and watch the output improve on screen. Then everyone rebuilds a prompt from their own week and pairs up to critique. Keep the Technology outcomes list and your school's WHS/risk-assessment process both visible.
Discussion prompts- Which TAS guard-rail (measurements/specs, WHS hand-back, keep-it-the-student's-design) does our faculty most often forget to ask for?
- What's a TAS task you'd never thought to give AI that a well-built, grounded prompt makes possible?
- Let's write one faculty prompt — fully grounded, with the safety hand-back and the authorship line — that we can all reuse across our courses.
Watch forStaff will write good content prompts but drop the self-check, the safety hand-back and the authorship line — exactly the bits that matter most in TAS. Insist all three are in every prompt before it's 'done'. Watch for prompts that quietly ask the AI to produce the student's design ('give me three good design solutions') — redirect to scaffolds and prompts. Confidence varies; pair a strong prompter with a hesitant one.
Standards2.1 Content and teaching strategies of the teaching area2.6 Information and Communication Technology (ICT)3.4 Select and use resources - 3
Planning & resources for TAS with Lessio
~50 minSession planA faculty-team build. Each teacher (or pair) generates a real program for next term in Lessio — a Technology Mandatory project, an elective unit, or a senior module — and runs the TAS review-before-use checklist on it live. Teach code-verification by having everyone confirm two of their own outcome codes against the relevant NSW Technology syllabus, and teach technical-verification by having each person find and confirm-or-fix one measurement, quantity or material claim. End by collecting every practical/make activity named across the units into one list to be risk-assessed.
Discussion prompts- Where would a hallucinated outcome code, a wrong dimension, or an under-covered Technology Mandatory range do the most damage in our programs?
- Which mandatory requirements (the range of technologies and project count; the elective focus areas; the senior major project) must our reviews always check?
- Could a colleague defend this program in a registration audit — and is every practical in it safe to run?
Watch forThe risk is treating a polished Lessio draft as finished — emphasise that the verifying and editing ARE the professional work, and in TAS that includes checking the *numbers* and the *safety*, not just the layout. Watch for programs that name a make activity without a risk assessment attached, and for Technology Mandatory scopes that quietly under-deliver the technology range.
Standards2.2 Content selection and organisation2.3 Curriculum, assessment and reporting3.4 Select and use resources - 4
Assessment, feedback & integrity in TAS
~50 minSession planTwo halves. First, an assessment make-and-verify: each teacher generates a TAS design-folio or project task with a rubric in Lessio, then swaps with a colleague to check every criterion against the outcomes and the design process, verify any technical requirement, and check the marks — surfacing how often a confident rubric measures the wrong thing or sets an unachievable spec. Second, an integrity redesign: map current folios and major projects against 'could a student outsource the designing to AI?' and redesign one to make the process visible (staged submissions, in-class making evidence, a viva).
Discussion prompts- Which of our TAS assessment tasks are most exposed to AI doing the student's designing — and how would we redesign them around staged, in-class evidence of their own making?
- Where could AI legitimately scaffold a folio or major project (structure, guiding questions, rubric) without ever doing the student's design work?
- How will we teach students to use AI ethically in their projects — as a research aid they acknowledge, not a ghost-designer?
Watch forIntegrity anxiety runs high around senior major projects. Steer firmly from 'detection' (unreliable) to task design, staged folio evidence and the viva. Watch for staff trusting an AI rubric without checking it maps to the design process and the outcomes — make the swap-and-verify step mandatory. Keep reinforcing the line: AI scaffolds the teacher's frame; the designing, making and evaluating are the student's.
Standards2.3 Curriculum, assessment and reporting5.1 Assess student learning5.2 Provide feedback to students on their learning - 5
Capstone — build a real TAS resource and critique it
~50 minSession planRun as a longer workshop or directed time. Each teacher builds their connected TAS set in Lessio and self-assesses against the TAS Ethical-Use Checklist — with a partner sign-off specifically on the WHS items (no practical passes without a completed risk assessment) and the authorship items (the designing stays the student's). Collect the reflections: they're your evidence of a Standards-relevant PD day and the teachers' eTAMS record. Finish by agreeing the faculty's 'how we use AI in TAS' rule, with the WHS line and the student-authorship line written in bold.
Discussion prompts- What's our shared standard for 'ready to use' AI-drafted TAS material — and where do safety and student authorship sit in it?
- What one faculty rule for responsible AI use in TAS should we adopt from today?
- How will we log this as PD and keep building our TAS prompt library from here?
Watch forSome will want to skip the reflection — but it's what makes this real PD and the eTAMS evidence, so protect the time. The capstone's hard edges are the WHS sign-off and the authorship line: don't let any practical-containing artefact be called 'done' without a completed risk assessment, or any folio scaffold that quietly does the student's designing. Capture the faculty rule — that's what leadership takes forward.
Standards2.1 Content and teaching strategies of the teaching area6.2 Engage in professional learning7.1 Meet professional ethics and responsibilities
After the day
Collect each teacher's capstone artefact and reflection — that's your evidence of a Standards-relevant PD day, and theirs to log in eTAMS. Part of the 'Subject AI Playbooks' line, included in the whole-school Lessio programme; also available standalone per teacher or per faculty. Because NESA removed the Accredited/Elective PD categories in 2024, this playbook counts as Standards-relevant PD without an endorsement gate — a TAS faculty can run it as a twilight or staff development day, with Lessio doing the NSW-grounded TAS generation (design briefs, projects, procedures, folio assessments) underneath, teacher-verified and safety-checked.
- Every measurement, specification, quantity, costing and material-property claim verified against a reliable source — never assumed from the AI.
- No AI-generated practical procedure or risk assessment used without a qualified WHS check against the school's safety guidance (machinery, electrical, food hygiene, chemicals).
- The design/making remains the student's own work — AI scaffolds the task and the rubric; it never does the student's designing, making or evaluating.
- No student personal data entered into general AI tools; cohorts described, never children — and every outcome code checked against the official NSW Technology syllabus.
- Every AI output reviewed and owned by the teacher; AI use disclosed where policy requires, and students taught to use AI with integrity in their folios and projects.
Standards-relevant professional learning, mapped to the APST · verified against national and NSW frameworks, June 2026.