Flagship course

Teaching with AI: Ethical & Effective Practice

Use AI to cut admin and lift teaching — inside the rules that bind NSW teachers, with your professional judgement in front.

Modules

Each module: clear learning outcomes → short, accurate input → a hands-on activity using the Lessio generator → interactive knowledge checks. Mapped to the Australian Professional Standards for Teachers.

Click a module to read it.

1. 1

   Foundations — what generative AI is (and isn't) for teaching

   How these tools actually work, where they genuinely help, where they don't, and the one principle that runs through everything: teacher-in-the-loop.~45 min

   By the end of this module you'll be able to:

   • Explain, in plain terms, what a generative AI model does — and what it cannot do — for teaching tasks.
   • Choose the right kind of tool (general assistant vs grounded engine) for a given job.
   • Apply the teacher-in-the-loop principle to any AI output.

   Standards2.6 Information and Communication Technology (ICT)6.2 Engage in professional learning

   What a generative AI actually does

   A large language model — the engine behind ChatGPT, Microsoft Copilot, NSWEduChat and Lessio — is, at heart, a next-word predictor. Trained on a vast amount of text, it learns the patterns of language and, given your prompt, generates the most probable continuation. That is a remarkable capability and a precise limitation:

   • It produces writing that is fluent and plausible. Plausible is not the same as true, current, or syllabus-accurate.
   • It has no understanding of your class, yesterday's lesson, or this year's NESA syllabus. It has read text about those things; it does not know them.
   • It is confident by default — it will fill a gap with an invented but convincing answer (a "hallucination") rather than say "I don't know".

   Hold this one idea and the rest of the course follows: treat AI as a fast, tireless, slightly unreliable drafting assistant — never as an authority.

   Two kinds of tool — know which you're holding

   	General assistant	Grounded engine
   Examples	NSWEduChat, Copilot, ChatGPT	Lessio
   Strength	Open-ended help, rewording, ideas, explanations	Syllabus-accurate programming, resources, assessment
   Knows your syllabus?	No — predicts from general text	Yes — drafts to the verbatim NESA outcomes + the DoE template
   Best for	"Reword this for Year 7"; "give me three hooks"	"Build a Stage 5 scope & sequence I can defend at a faculty meeting"

   NSW recommends NSWEduChat — the department-built, secured general tool now available to all staff and Year 5–12 students — for everyday tasks. Lessio is the syllabus-grounded engine for the heavy faculty planning. You'll use both, for different jobs.

   Where AI genuinely helps a teacher

   • A first draft of a program, resource or assessment you then shape — beating the blank page.
   • Rewording for reading level, plain English, or EAL/D learners.
   • Generating variety — differentiation options, extra questions, alternative explanations, hooks.
   • Reformatting and admin boilerplate — turning notes into a parent email, a rubric into student-friendly language.

   Where it doesn't — and you must stay in front

   • Factual and syllabus precision. It can invent outcome codes that look completely real — you'll catch one yourself in Module 4.
   • Knowing your students — their needs, what happened yesterday, what's fair for this particular child.
   • Professional judgement — what is appropriate, safe, inclusive and right.

   The principle that runs through everything: teacher-in-the-loop

   You remain the professional and the author. AI drafts; you direct, verify, and own the result.

   This isn't a slogan — it's the legal and ethical reality. Under the Australian Framework for Generative AI in Schools (Module 2), accountability stays with the teacher: a decision "the AI made" is a decision you made. Lessio is built around this — it grounds every draft in the real syllabus, then hands it to you to review before use.

   Activity — feel the speed and the gap (10 min)

   Open the Lessio generator and produce a scope & sequence for a stage you teach. Then write down: (1) one thing it got right that saved you time, and (2) one thing you'd change for your students. Notice how fast the starting point arrived — and that your judgement was still required. That gap is your job, and it isn't going away.

   Knowledge check

   1True or false: a general AI tool 'knows' the current NSW syllabus.

   Show answer

   2In one sentence, what is the teacher-in-the-loop principle?

   Show answer

   3You need to reword a worksheet into plain English for one EAL/D student, and — separately — a defensible Stage 5 scope & sequence. Which tool for which job?

   Show answer

   Mark this module complete
2. 2

   The rules that bind us — policy, ethics & responsibility

   The three-layer policy stack (national / NSW DoE / NESA), the hard line on student data, the DoE's six ethical checks, and bias, accuracy & transparency.~60 min

   By the end of this module you'll be able to:

   • Locate your AI use inside the national, NSW DoE and NESA policy frameworks.
   • Identify exactly what student information must never enter a general AI tool — and the one nuance for secured tools.
   • Apply the DoE's six ethical checks, and screen outputs for bias, inaccuracy and hallucination.

   Standards4.5 Use ICT safely, responsibly and ethically7.1 Meet professional ethics and responsibilities7.2 Comply with legislative, administrative and organisational requirements

   You are not freelancing — three layers of policy already apply

   Using AI as a NSW teacher sits inside a clear stack. Know it, because "I didn't realise" is not a defence.

   1. National — the Australian Framework for Generative AI in Schools. Six principles (with 25 guiding statements), in force since Term 1 2024, that every Australian school works under:

   • Teaching & Learning — AI should enhance teacher expertise and build students' AI literacy, creativity and critical thinking.
   • Human & Social Wellbeing — it must not harm safety, dignity or wellbeing.
   • Transparency — the school community should know how and when AI is used.
   • Fairness — accessible, inclusive, free from bias, and respectful of Indigenous Cultural and Intellectual Property (ICIP).
   • Accountability — teachers and leaders remain responsible for decisions AI supports.
   • Privacy, Security & Safety — student data is protected by strong privacy and cyber-safety practice.

   2. State — NSW Department of Education guidance. The DoE recommends its own secured tool, NSWEduChat, and sets minimum safety practices for any AI use. Before you trust an output, run the DoE's six ethical checks:

   • Oversight — actively review that the output matches your intent.
   • Diversity — seek varied perspectives; don't accept a single, narrow take.
   • Explainability — be able to describe how you produced it.
   • Knowledge boundaries — only use AI where you can judge whether it's right.
   • Respect for others — protect colleagues', students' and community data and dignity.
   • Community alignment — make sure it fits your school community's values.

   3. Assessment — NESA. Schools decide whether generative AI is permitted for a given assessment task, and must uphold HSC and RoSA integrity. Malpractice — plagiarism, collusion, or presenting AI work as a student's own — can jeopardise a student's award. (More in Module 5.)

   The hard line: student personal information

   The single rule that protects you and your students:

   Never enter personal or identifying information about a student into a general AI tool.

   No names, NESA/student numbers, dates of birth, addresses, health or disability information, behaviour or wellbeing records — anything that could identify a child. This is the Privacy and Personal Information Protection Act 1998 (NSW) and the Child Safe Standards, not just etiquette.

   The one nuance: NSWEduChat is department-built and secured, so DoE guidance permits limited personal information in that approved environment. In any public or general tool — and as a safe default everywhere — strip it out. Lessio sidesteps the question entirely: it is built student-data-free. You describe a cohort, never a child — "mixed-ability Year 9, six EAL/D learners" is fine; a class list is not.

   Bias, accuracy and hallucination

   AI carries the biases of its training data and states falsehoods with total confidence. So:

   • Verify facts and any syllabus code against the official source — never assume.
   • Check examples are inclusive and culturally safe, including Aboriginal and Torres Strait Islander perspectives — and respect ICIP: don't have AI fabricate cultural content.
   • Watch for a single narrow viewpoint. Prompt for range, then judge.

   Transparency & integrity — model what you expect

   If your school or a task requires you to disclose AI use, disclose it. Be open with students that you use AI as a drafting aid you check and own — that honesty is exactly what you're asking of them.

   Activity — pass an output through the checks (12 min)

   Generate an assessment task in Lessio for a class you teach. Run it against the DoE's six ethical checks and the Lessio Ethical-Use Checklist (on this page). Write down one change you'd make before it ever reached a student.

   Knowledge check

   1A colleague pastes a struggling student's name, diagnosis and behaviour notes into a public chatbot to 'get strategies'. What's wrong, and what should they do instead?

   Show answer

   2Name three of the DoE's six ethical checks.

   Show answer

   3Under the Australian Framework, who is accountable for a flawed AI-generated rubric you used in class?

   Show answer

   Mark this module complete
3. 3

   Prompt craft for teachers

   The most practical hour in the course: how to brief AI so it gives you something usable — the RICE structure, before/after examples, and iteration.~50 min

   By the end of this module you'll be able to:

   • Build a strong teaching prompt using the RICE structure (Role, Intent, Constraints, Examples).
   • Diagnose why a weak prompt produced a weak output, and fix it.
   • Iterate on an output rather than restarting, and build in a self-check that surfaces hallucinations.

   Standards2.6 Information and Communication Technology (ICT)3.4 Select and use resources6.2 Engage in professional learning

   Why this module exists

   The difference between disappointing AI and genuinely useful AI is almost never the tool — it's the prompt. A vague ask gets a vague, generic answer you'll throw away. A well-built prompt gets a draft you can actually use. Prompting is a teachable, professional skill, and this is the most practical hour in the course.

   Anatomy of a strong teaching prompt — R.I.C.E.

   A reliable structure you can remember:

   • R — Role & context. Who the AI is acting as, and the de-identified class context. "You are an experienced NSW Stage 4 Science teacher planning for a mixed-ability Year 7 class with six EAL/D learners."
   • I — Intent (the task + the syllabus anchor). Exactly what you want, tied to the outcome. "Draft a five-lesson sequence on the particle model addressing the relevant 'matter' content and Working Scientifically."
   • C — Constraints & format. Length, structure, reading level, what to include or avoid. "Each lesson: learning intention, a hook, an explicit-teaching segment, a formative check. Plain English, Australian spelling, as a table."
   • E — Examples & evaluation. Show the style you want, and ask it to check itself. "Match the tone of this sample I'll paste. At the end, list anything you were unsure of so I can verify it."

   You won't always need all four — but when an output disappoints, the missing piece is almost always context, the syllabus anchor, or the format.

   See the difference

   Weak prompt	Strong prompt
   "Make a worksheet on fractions."	"You are a NSW Stage 3 Mathematics teacher. Create a one-page worksheet introducing equivalent fractions for a mixed-ability Year 6 class. Include six graduated questions (easy → challenging), one worked example, and a short 'explain your thinking' task. Plain English, Australian context. Flag anything you're unsure of."
   "Write feedback for this essay."	"You are a Stage 5 English teacher. Using these success criteria [paste], write three feedback comments on this de-identified student response [paste]: one strength, one priority for improvement, one specific next step. Warm, specific, jargon-free. Don't invent quotes that aren't in the text."

   The strong prompts are longer because they carry role, the de-identified context, the syllabus anchor, the format, and a self-check. That's the craft.

   The professional moves that lift every prompt

   • Anchor to the syllabus. Name the outcome/stage. (In Lessio this is built in — you pick the real outcomes and it grounds the draft for you.)
   • De-identify, always. Cohort context, never a child (Module 2).
   • Ask for a self-check. "List anything you couldn't verify" surfaces the hallucinations for you.
   • Iterate — don't restart. Treat the first output as a draft to refine: "Good. Make question 5 harder, swap the context to bushfire data, and add a marking guide." Three good iterations beat one perfect prompt.
   • Constrain the format to how you actually work — a table, the DoE five-column program, student-facing language.

   Reframing prompting as planning

   Notice what RICE really is: role, intent, constraints, examples — the same thinking you already do when you brief a casual or a pre-service teacher. You're not learning to code; you're learning to brief clearly. Teachers are already good at this.

   A take-away you can use Monday

   This course comes with a prompt library (below the modules) — ready, RICE-shaped, de-identified prompts for common NSW teaching jobs. Copy one, swap in your details, go.

   Activity — rebuild a weak prompt (15 min)

   Take a task you'd hand to AI this week. Write your instinctive one-line prompt. Now rebuild it with RICE — add role, a de-identified context, the syllabus outcome, the format, and a self-check. Run both in NSWEduChat (or your tool) and keep the better output; note which RICE element made the difference. Then try the same task in Lessio and see how much of the syllabus-anchoring is already done for you.

   Knowledge check

   1What does RICE stand for?

   Show answer

   2Your AI worksheet came back generic and off-level. Which RICE elements were probably missing?

   Show answer

   3Why ask the AI to 'list anything you couldn't verify'?

   Show answer

   Mark this module complete
4. 4

   Plan-to-Paper — planning with AI without losing syllabus fidelity

   The connected pipeline (scope & sequence → program → resources → assessment), why grounding matters, a real hallucination case study, and review-before-use.~60 min

   By the end of this module you'll be able to:

   • Produce a syllabus-aligned scope & sequence, program, resource and assessment as one connected set.
   • Catch a plausible-but-wrong outcome code before it reaches a document.
   • Apply the review-before-use discipline to every AI draft.

   Standards2.3 Curriculum, assessment and reporting3.2 Plan, structure and sequence learning programs7.2 Comply with legislative, administrative and organisational requirements

   Planning is connected — so generate it connected

   Good faculty planning is a chain, not a pile of lessons:

   Scope & sequence (the year) → Program / unit (the weeks) → Resources (the materials) → Assessment (the measure) — all pointing at the same outcomes. Generating these as one coherent set is the faculty-level job Lessio is built for, and it's where AI saves the most time. Lessio produces exactly these four artefacts.

   Why grounding changes everything

   A general chatbot writes a program from general text about teaching. Lessio drafts to the NSW DoE's own program template and grounds every draft in the verbatim NESA syllabus for your focus area. That's the difference between output that reads like generic AI and output that reads like your faculty's work. But it is still a strong draft, not a final document — your judgement sets sequence, pace, context and emphasis.

   The DoE template Lessio follows isn't arbitrary: it's the five-column teaching-and-learning sequence — Outcomes & content · Activities · Evidence of learning · Differentiation & adjustments · Registration & evaluation — wrapped around an outcomes list, a needs analysis under the UDL headings, and a reflection block. Knowing the template helps you judge the draft.

   Case study — catch the hallucination (this really happened)

   A generic AI-generated Year 10 Mathematics program — the kind a chatbot produces — labelled the sine rule, cosine rule and area of a non-right-angled triangle as MA5-TRG-C-02, a Core outcome.

   It's wrong. In the NSW Mathematics K–10 syllabus, that content is a Path outcome — MA5-TRG-P-01. MA5-TRG-C-02 is actually bearings, and angles of elevation and depression. The code looked real, sat in a real-looking program, and was completely mislabelled.

   This is exactly the slip an ungrounded tool makes — and exactly why you verify every outcome code against the official syllabus before a program goes anywhere. (Lessio's engine is explicitly built not to relabel Core as Path — but the discipline is yours, whatever the tool.)

   Review-before-use — a 90-second discipline

   Before any draft becomes a real document, check:

   1. Codes — every outcome code matches the current syllabus (Core vs Path, correct focus area).
   2. Coverage — mandatory hours and requirements are respected (Technology Mandatory's range of technologies; PDHPE hours; fieldwork in Geography; and so on).
   3. Sequence — the order builds knowledge sensibly for your students.
   4. Accuracy — worked answers, facts and examples are correct.
   5. Inclusion — language and examples are inclusive and culturally safe.

   If you couldn't defend it in a faculty meeting, it isn't ready.

   Activity — generate, then verify (15 min)

   Generate a program / unit of work in Lessio for a focus area you teach next term. Then verify two outcome codes against the official NESA syllabus, and edit one week of the teaching-and-learning sequence to fit your class. The edits you make are the visible proof of your professional judgement.

   Knowledge check

   1An AI program labels the cosine rule as MA5-TRG-C-02. Why is that a red flag, and what do you do?

   Show answer

   2What are the four connected artefacts of Plan-to-Paper?

   Show answer

   3Name three checks in 'review before use'.

   Show answer

   Mark this module complete
5. 5

   In the classroom — feedback, differentiation, accessibility & integrity

   Where AI helps students most (and where it must stay out): feedback frames, UDL differentiation, EAL/D and accessibility, NESA authorship, and modelling responsible use.~45 min

   By the end of this module you'll be able to:

   • Use AI appropriately for feedback, differentiation and accessibility — without lowering the learning.
   • Assure authorship and integrity the way NESA expects, rather than relying on 'AI detectors'.
   • Model responsible AI use to students and identify what must stay human.

   Standards1.5 Differentiate teaching to meet specific learning needs1.6 Strategies to support students with disability5.2 Provide feedback to students on their learning

   Feedback — frames from AI, judgement from you

   AI is good at structuring feedback fast; it is not good at knowing your student. Use it to draft a frame — a strength, a priority, a next step against your success criteria — then make it specific, accurate and kind for the actual child. Never paste an identifiable student's work into a general tool (Module 2); de-identify, or use your school's approved, secured environment.

   Differentiation & accessibility — where AI genuinely shines

   This is AI's strongest classroom case. From one resource you can quickly generate:

   • Enable versions — more scaffolding, worked examples, sentence starters.
   • Extend versions — greater complexity and open-ended challenge for high-potential and gifted students.
   • EAL/D scaffolds — plain English, glossaries, visuals — aligned to the EAL/D Learning Progression.
   • Accessible formats — larger-print-friendly layouts, simplified instructions, alternative representations.

   This is Universal Design for Learning in practice: multiple means of engagement, representation, and action/expression. Reasonable adjustments for students with disability are also a legal requirement (Disability Standards for Education 2005) — AI helps you produce them faster, but you confirm each adjustment still targets the same outcome.

   Academic integrity — NESA's expectations, your classroom

   Schools decide whether generative AI is permitted for a given task, and you uphold integrity. NESA encourages monitoring authorship for work done over time — review drafts at checkpoints, talk with students about their thinking, and build in self-reflection — rather than relying on unreliable "AI detectors". Design tasks that make process visible (planning, drafts, in-class checkpoints, viva-style questions) so the work is demonstrably the student's own.

   Modelling responsible use to students

   Students will use AI regardless — so teach them to use it with integrity: as a tutor and drafting aid they critique and disclose, not a shortcut that does their thinking. Your visible, honest practice sets the classroom norm and builds the AI literacy the Australian Framework asks for.

   What stays human — non-negotiable

   Relationships and care. Noticing the child who's struggling. Ethical judgement. The contentious grade. The final decision on every output. AI cannot do these — and shouldn't.

   Activity — one resource, two learners (12 min)

   Take a resource and use AI to generate two differentiated versions for a real, de-identified cohort: one enabling, one extending. Check both still target the same outcome, then note one place your professional judgement overrode the draft.

   Knowledge check

   1Give one classroom task that must stay fully human.

   Show answer

   2Rather than relying on 'AI detectors', how does NESA suggest you assure authorship?

   Show answer

   3You generate an 'enable' version of a task. What must you confirm before using it?

   Show answer

   Mark this module complete
6. 6

   Workload & wellbeing — automate the admin, protect the craft

   The automation triage, reclaiming time sustainably, the deskilling risk and how to guard against it, and setting your own boundaries.~30 min

   By the end of this module you'll be able to:

   • Triage your recurring tasks into automate / augment / keep-human.
   • Reclaim time sustainably without taking on more or losing your craft.
   • Set clear personal boundaries for AI use.

   Standards6.2 Engage in professional learning7.1 Meet professional ethics and responsibilities

   The automation triage

   Sort every recurring task into three buckets:

   • Automate (draft with AI): first-pass programs, resource scaffolds, reformatting, variant generation, turning notes into emails or rubrics into student language.
   • Augment (AI helps, you finish): feedback frames, differentiation, brainstorming, summarising.
   • Keep human: pastoral care, the conversation with a struggling student, contentious calls, anything involving a specific identifiable child.

   The test: would I be comfortable telling a colleague — and the student's parent — that AI drafted this? If not, it's not an automate task.

   Reclaim time — sustainably

   The point of the time AI gives back is not to do more — it's to spend your hours on teaching, feedback and rest instead of paperwork. A faster first draft is only a win if it actually closes the laptop earlier. Protect that boundary deliberately, or the time quietly refills with more work.

   Guard your craft — the deskilling risk

   Over-reliance erodes expertise. The guard rail: only ship what you could have written and can critique yourself. Keep planning, designing and judging often enough to stay sharp — let AI accelerate your expertise, not replace it. If you couldn't tell whether the output was any good, you're not ready to use AI for that task yet (the DoE's "knowledge boundaries" check from Module 2).

   Set your boundaries

   Decide, in advance, what you will and won't hand to AI — and stick to it. Wellbeing isn't the absence of AI; it's using it on purpose, for the right tasks, with your judgement intact and your evenings protected.

   Activity — your personal triage (10 min)

   List your recurring weekly admin tasks. Mark each Automate, Augment, or Keep human. Choose one Automate task to trial with Lessio next week — and one boundary you'll hold.

   Knowledge check

   1What's the test for whether a task is safe to automate with AI?

   Show answer

   2What's the guard against deskilling?

   Show answer

   3The real goal of automating admin is…?

   Show answer

   Mark this module complete
7. 7

   Capstone — build, critique & log it

   Build a real, connected unit + assessment with AI, critique it against professional standards, self-assess against the Ethical-Use Checklist, and log it as PD.~60 min

   By the end of this module you'll be able to:

   • Build a connected scope & sequence, program and assessment with AI, end to end.
   • Critique and improve the output against the syllabus and professional standards.
   • Self-assess against the Lessio Ethical-Use Checklist, reflect, and record the hours as PD.

   Standards3.2 Plan, structure and sequence learning programs6.3 Engage with colleagues and improve practice6.4 Apply professional learning and improve student learning

   The task — a real, connected, defensible set

   Choose a topic you'll teach next term. Using Lessio, build and then critique:

   1. A scope & sequence for the stage.
   2. A program / unit of work for one focus area within it.
   3. An assessment with marking guidelines for that unit.

   Then improve each with your professional judgement: verify outcome codes against the official syllabus, fix any factual or sequencing issues, adjust for your cohort, and make the assessment valid (it measures the outcome) and fair (accessible, with reasonable adjustments).

   What good looks like

   A connected, syllabus-accurate set you'd actually use — drafted by AI, unmistakably shaped and owned by you. Your edits are the evidence of your professional judgement, and exactly what the teacher-in-the-loop principle looks like in practice.

   Self-assessment — the Lessio Ethical-Use Checklist

   Run your capstone against all five checklist items on this page. Every box should be honestly tickable. If one isn't, fix the artefact — that is the learning.

   Reflection — write a short response

   • What did AI genuinely save you time on, and what did you have to fix?
   • Where did your professional judgement change the output?
   • Which DoE ethical check (Module 2) mattered most here?
   • One rule you'll keep for using AI responsibly from now on.

   Log it as professional learning

   This module is your assessment: a complete, critiqued artefact plus your ethical-use reflection — keep it as evidence of practice. Since NESA removed the Accredited/Elective PD distinction in 2024, Standards-relevant learning like this counts toward your 100 maintenance hours — record it in your eTAMS PD log against the Standards it addresses (2, 3, 4, 6 and 7). Your school can also run the course as part of its professional-learning plan or a staff development day.

   Knowledge check

   1What turns an AI-generated unit into defensible professional work?

   Show answer

   2How can this course count toward your NESA professional-development hours?

   Show answer

   Mark this module complete

Take-away prompt library

Ready, RICE-shaped prompts for common NSW teaching jobs (Module 3). De-identified — copy one, swap in your details, and use it today.

You are a NSW secondary teacher supporting EAL/D learners. Rewrite the passage below in plain English at roughly a Year 6 reading level, keeping all key content and subject vocabulary (add a short glossary of any term you simplify). Use short sentences and an active voice. Then list any nuance you had to drop so I can decide whether to add it back.

[paste passage]

You are a NSW teacher planning for a mixed-ability class (de-identified: [stage/year, key needs]). From the task below, produce two versions targeting the SAME outcome: an 'enable' version with more scaffolding, a worked example and sentence starters; and an 'extend' version with greater complexity and an open-ended challenge. Keep the outcome constant and tell me what you changed in each.

[paste task]

You are a NSW [subject] teacher. Using these success criteria [paste], write a feedback frame for a de-identified student response [paste]: one genuine strength, one priority for improvement, and one specific next step. Warm, specific, jargon-free, addressed to the student. Do not invent quotes or content that isn't in the response.

You are a NSW [stage] [subject] teacher. Give me three different five-minute lesson hooks to introduce [topic] to a [de-identified class], each with a clear link to the learning and a question that surfaces prior knowledge. Use Australian contexts where possible. Keep them low-prep.

You are a NSW [subject] teacher. Write eight retrieval-practice questions on [topic] for a [de-identified class], graduated from recall to application, with an answer key. Plain English, Australian context. Flag any question where the answer could be ambiguous.

You are a NSW classroom teacher. Turn my rough notes below into a brief, warm, professional email to a parent/carer. Plain English, no jargon, solution-focused, and include no sensitive health or behavioural detail beyond what I've written. Keep it under 150 words.

[paste notes — de-identified]

You are a NSW [subject] teacher. Rewrite the marking guidelines below as student-friendly success criteria ('I can…' statements) for a [de-identified class], keeping them faithful to the original standard. Then add one example of what 'achieved' looks like for the top criterion.

[paste rubric]

You are a NSW [stage] [subject] teacher. Explain [concept] in three different ways for a [de-identified class]: a plain-English explanation, a concrete real-world analogy (Australian context), and a worked example. Note one common misconception to pre-empt — and flag anything I should double-check.

Standards-relevant professional learning, mapped to the APST · content verified against national and NSW frameworks, June 2026 · self-log the hours in eTAMS.