Data-Driven Teaching, Without the Admin
AI copilot suggestions, curriculum coverage heatmaps, at-risk student alerts — all in one dashboard. Free for every Australian teacher.
Start Using Qwizflow — Free4B Science & Maths
| Name | Avg Score | Quizzes | Streak |
|---|---|---|---|
Mia Thompson | 88% | 38 | 14d |
Liam Nguyen | 92% | 42 | 12d |
Chloe Patel | 78% | 30 | 7d |
Jack Williams | 52% | 18 | 2d |
Sophie Brown | 91% | 40 | 10d |
Oliver Chen | 87% | 36 | 9d |
Ava Singh | 72% | 25 | 5d |
Noah Kim | 44% | 12 | 1d |
Mr. Chen’s Year 4 Classroom
Mr. Chen teaches Year 4 Science and Maths at a government school in Melbourne. Before Qwizflow, he spent hours each week marking quizzes and trying to work out which students were falling behind. Differentiation meant guesswork, and parent communication was a constant challenge.
Now his Teacher Dashboard shows a curriculum heatmap — green for topics the class has mastered, amber for areas needing revision, and red for gaps. The Affective Heatmap layered on top shows engagement and frustration signals per topic, k-anonymised so individual students stay private. At a glance, he knows exactly where to focus next week's lessons. The AI copilot even suggests targeted assignments based on class performance patterns.
When Jack's engagement dropped and his quiz scores fell below 55%, a safety flag appeared in Mr. Chen's queue. The safeguarding escalation ladder gave him five clear next steps — acknowledge, action, resolve, dismiss, or escalate to the school counsellor — each requiring a note that becomes part of an audit trail. Mr. Chen acknowledged the flag, contacted Jack's parents, and created a catch-up plan, all from one panel. It is not surveillance — it is duty of care, built into the platform.
Later that week, three students hit the Ask Teacher button after getting stuck. Their requests landed in Mr. Chen's help queue with PII-scrubbed AI briefs explaining what each student was trying. He answered them in batch on Friday afternoon. Mr. Chen does not see AI transcripts or chat logs. He sees aggregated, anonymised insights about his classroom. The platform respects student privacy while giving teachers the data they need to teach effectively.
“He sees aggregated, anonymised insights about his classroom. The platform respects student privacy while giving teachers the data they need.”
AI Teaching Copilot
3 students need attention
Coverage gap: Decimals & Angles
Suggested: Perimeter & Area Practice
Built for the Modern Australian Classroom
Owl Tutor — Single Front Door for Students
Your students now reach every AI tool through one chat — they describe what they need in plain language and the right tool happens inside the same window. From a teaching perspective: every classroom AI policy, every safety flag rule, every per-feature consent gate, and your aggregated-only privacy promise still applies. Affective heatmap, help queue and at-risk detection all keep working unchanged over the larger surface students now actually use.
AI Copilot
Lesson suggestions based on real classroom data. Identify gaps, recommend revision, and differentiate instruction automatically.
Curriculum Heatmap
Visual overview of Australian Curriculum v9 + Victorian Curriculum 2.0 coverage. See which topics your class has mastered and where gaps remain.
Affective Heatmap
Per-topic engagement and frustration signals across your class, k-anonymised at 5 contributing learners so individual students stay private.
Live Class Quizzes
Run Kahoot-style interactive quizzes with a 6-character room code. Real-time leaderboard, per-question accuracy insights, animated podium.
Teacher Nudges
Send 200-character nudges to specific students with active sessions. Rate-limited 1-per-student-per-5-min so it stays meaningful.
Help Request Queue
Students hit "Ask Teacher" from any quiz; their requests land in your inbox with a PII-scrubbed AI brief. State machine: open → acknowledged → answered or dismissed.
Smart Groups
AI-suggested student groupings based on learning levels and complementary strengths for collaborative activities.
Safeguarding Escalation Ladder
5-step duty-of-care state machine — open → acknowledged → actioned → resolved → escalated to counsellor. Append-only audit trail with mandatory transition notes.
Predictive Analytics
Early warning system that identifies students at risk of falling behind, so you can intervene before it is too late.
Frequently Asked Questions
Setting up a classroom takes just a few minutes. Create a classroom from your Teacher Dashboard, give it a name (for example, "4B Science & Maths"), and the system generates a unique class join code (CLS-XXXX). Share this code with your students — they enter it during sign-up or from their student dashboard to join your class. You can create multiple classrooms for different subjects or year levels. Each classroom has its own roster, analytics, and curriculum tracking.
Yes. Qwizflow is built to meet the Safer Technologies for Schools (ST4S) framework, which is the Australian standard for evaluating educational technology safety. All AI features require explicit parental consent. Student data is stored in Firebase’s Melbourne region. Personal information is scrubbed before AI processing. Duty-of-care tools are built in, including safety flags for student wellbeing concerns. Full compliance documentation, audit trails, and incident response plans are included. Sub-processor details are published in our Privacy Policy.
No — and this is by design. Teachers see aggregated classroom analytics, curriculum coverage heatmaps, and flagged wellbeing concerns. You do not see AI chat transcripts, personal conversations, or raw AI interactions. This protects student privacy while still giving you the teaching insights you need. Safety flags provide relevant context when a student shows concerning patterns, but the specific content of AI interactions remains private to the student.
The AI copilot analyses classroom performance patterns and surfaces actionable suggestions. It highlights students who need attention (declining scores, low engagement), identifies curriculum coverage gaps against the Australian Curriculum and Victorian Curriculum 2.0, suggests targeted assignments to address knowledge gaps, and recommends differentiation strategies. Actions are prioritised by urgency — high, medium, or low — so you know what to address first. The copilot learns from your classroom’s data, not from other schools or students.
Yes, completely free. There are no per-seat fees, no school licences, no premium tiers, and no hidden costs. Every feature — including the AI copilot, classroom analytics, curriculum heatmaps, live quizzes, safety flags, and predictive analytics — is available at no charge. Qwizflow is funded independently to ensure equitable access to AI-powered teaching tools for every Australian educator, whether at a well-resourced private school or a rural government school.
The safety flag system monitors for concerning student patterns and raises discreet alerts to the teacher. Flags are triggered by engagement drops (extended absence, declining participation), emotional indicators (distress language detected during AI tutor sessions, with PII scrubbed), and academic decline (repeated failures, sharp score drops). Each flag follows a 5-step escalation ladder — open → acknowledged → actioned → resolved → dismissed, with a separate path to escalated when a student needs the school counsellor. Every transition requires a non-empty note that becomes part of an append-only audit trail. Escalating to "counsellor" requires a configured school counsellor in the School Admin dashboard, with an optional notify-parent-on-escalate toggle.
The Affective Heatmap shows per-topic engagement and frustration signals across your class, derived from how students interact with the AI tutor and adaptive quizzes (e.g. frustration count, idle time, retry patterns). It is k-anonymised at 5 — topics with fewer than 5 contributing learners are suppressed and rendered as neutral cells, so individual students cannot be identified by elimination. Teachers see classroom-level patterns; never individual student affective data. The heatmap pairs naturally with the curriculum coverage heatmap to show "this topic has gaps AND students are frustrated when they try it" — a strong signal to revisit the lesson.
You have two complementary tools for in-the-moment student support. Teacher Nudges let you send a 200-character message to any student with an active session — useful for "I noticed you're stuck on Q3, try the Read-Aloud button" or "well done on the streak!". Nudges are rate-limited to 1 per student per 5 minutes so they stay meaningful and not spammy. The Help Request Queue is the inverse: students hit an Ask Teacher button from any quiz or rationale screen, which lands in your inbox with a PII-scrubbed AI brief explaining what the student was trying. You acknowledge, answer, or dismiss — each transition is logged. Together they replace ad-hoc messaging with a structured, auditable support flow.