Teaching and Learning Use Cases
i) AI in the school workspace
Now that AI is here, the implications for curriculum leaders and teachers are profound for scrutinising its impact on creating teaching and learning that values the productive struggle.
From the outset, therefore, nothing is as important as dealing with the presence of AI technologies on learning concepts and skills as part of the school’s ethical and pedagogical practices.
Consequently, the use cases for Phase 1 explore the teacher’s commitment to students’ academic achievement and wellbeing. The following use cases deal with three areas of the school curriculum workspace in which curriculum leaders and teachers ensure that AI policies and classroom practices align.
- Data & Privacy Hygiene: As a Curriculum Leader, I want to deploy gatekeeper system prompts locked strictly to ACARA v9, VCAA V2, and ST4S privacy bounds, so that I can eliminate hallucinated outputs and ensure our department complies with state data hygiene rules.
- GenAI as Dialogic Partner: As a Curriculum Leader, I want to audit our team's AI workspace protocols against Indigenous Cultural and Intellectual Property (ICIP) safeguards, so that I can prevent cultural misrepresentation and ensure all generated learning materials respect cultural knowledge.
- Assessment for Learning: As a Curriculum Leader, I want to design a ‘HOW-TO’ school checklist to showcase assessment practices that are crucial for an AI Age, so that I can evaluate authentic student learning and preserve pedagogical integrity.
ii) AI for progress mapping
Using AI in progress mapping isn't about automating lesson creation or rushing through curriculum content. It is about deconstructing dense standards into clear, actionable "Know, Understand, Do" targets and designing engaging learning journeys.
Instead of relying on generic worksheets or walls of text, Phase 2 turns the "big ideas" of your curriculum into differentiated, active learning materials that foster deep student inquiry.
- Unpacking Standards (UbD Method): As a Primary Learning Specialist, I want to use GenAI to separate action verbs from subject matter across new curriculum standards, so that I can run a PLC session that teaches my team how to isolate core "Know, Understand, Do" targets.
- Net Workload Reduction: As a Learning Specialist, I want to co-create a student "Field Guide" workbook template with GenAI, so that my department can replace single-use worksheets with a single, structured learning guide for the entire term.
- Differentiating & Personalising: As an EAL Leading Teacher, I want to instruct GenAI to map writing and speaking progressions across EAL continuums, so that I can provide mainstream teachers with a clear baseline map for adjusting classroom expectations.
iii) AI for assessment connections
Effective curriculum design relies on a backward alignment approach, where rubrics and performance tasks are drafted prior to daily lesson plans to ensure every assessed skill is explicitly taught and practiced throughout the unit.
Within this framework, assessment shifts away from a pure output focus toward process-based evaluations—such as sequential drafting, oral defenses, and source analysis—that reward authentic human thinking.
To support students along this trajectory, mandatory low-stress formative checkpoints (Checkpoint 1: Idea, Checkpoint 2: Draft, and Checkpoint 3: Practice Run) are integrated into the learning sequence, creating predictable feedback loops to catch and correct misconceptions well before final submission.
- Backward Design & Alignment Check: As a Primary Learning Specialist, I want to run a PLC session using GenAI to audit department unit plans side-by-side with final rubrics, so that my team can verify that every graded skill is explicitly practiced in earlier lessons.
- Outcomes-Focused Assessment: As a Curriculum Coordinator, I want to shift department assessment policy away from unreliable AI detectors toward process-focused sequential drafting, so that we evaluate authentic student learning and preserve pedagogical integrity.
- Formative Checkpoints: As an Instructional Coach, I want to co-create a department-wide "3-Checkpoint Framework" template with GenAI, so that teachers can embed mandatory milestone checks (Idea, Draft, Rehearsal) across all term programs.
iv) AI for daily planning
Managing daily lessons with AI isn't about following a rigid, multi-week binder or letting technology march chronologically through content regardless of student understanding. It is about building a live, responsive "operating system" in the classroom.
Phase 4 replaces static planning documents with dynamic, 4-tab Google Sheet Command Centers. By using live tablet trackers, qualitative voice-to-text logging, and data-driven reteach pivots, teachers can adjust instruction in real time to meet the actual readiness levels of their students.
- Daily Planning Architecture: As an Instructional Coach, I want to co-create a master 4-tab Google Sheet Command Center template with GenAI, so that my department can replace static paper binders with live, tablet-ready daily lesson trackers.
- Strategic Plan Alignment: As a Principal, I want to upload our School Strategic Plan goals into GenAI, in order to translate school-wide targets (like "improving student agency") into specific, automated operational rules inside teachers' daily planners.
- Live Tracking: As a Classroom Teacher, I want to use my tablet's voice-to-text feature to record quick qualitative observations directly into Tab 3 of my planner, capturing live evidence of student growth without interrupting instruction.
- Data-Driven Revision Protocols: As a Curriculum Coordinator, I want to run a weekly PLC data review process using GenAI, so that teacher teams can analyze Friday tracking sheets together and co-design targeted Monday reteach interventions.
- Responsible AI Modelling: As a Classroom Teacher, I want to project GenAI onto the whiteboard to demonstrate prompt iteration and "think aloud" through its errors, showing students how to use human judgment to correct average AI outputs.