Advanced Activities
Standalone AI, journal, and game experiences students complete in the browser — assign per class, link to assessments, and track completion.
What are Advanced Activities?
Advanced Activities are standalone mini-apps students open and complete independently — separate from lessons, with their own URL, persistent state, and score history. Unlike widgets (which live inside lesson slides), Advanced Activities are full experiences: interactive AI tools, reflective journals, scored games, and external platform integrations.
🔌 Widgets (lesson slides)
- • Embedded inside a lesson slide
- • Lesson-scoped, no persistent state
- • Used during class teaching
✨ Advanced Activities
- • Full standalone application
- • Persistent state and score history
- • Can link to assessments
You assign activities per class from the Activities tab. Students see only the activities you have enabled — you stay in control of what is available and when it unlocks.
Activity types
ML Activities (Computer Vision & AI)
Browser-based artificial intelligence and machine learning experiences — no downloads or installs. Students train real models, see AI working in real time, and build interactive demos.
Teachable Machine — Image
Train a real image classifier using the webcam. Capture training photos, train the model, test it live.
Teachable Machine — Sound
Train a sound classifier. Record voice commands and teach the AI to recognise them.
Teachable Machine — Pose
Use body pose detection to classify poses or gestures. Students train on their own movements.
Air Writing
Write letters in the air with a finger. AI reads hand gestures in real time via webcam.
Face Filters
Apply real-time AR face filters. Explore face detection and landmark tracking.
Hand Tracking
Track hand and finger position in real time — the basis for gesture-controlled interfaces.
Gesture Math
Solve maths problems by showing hand gestures. Combines gesture detection with curriculum content.
Pose Game
A game controlled by body pose — strike the right pose to score points.
Sign Language Detection
Recognise sign language letters using a trained AI model and live camera feed.
Visual Coding
Block-based and Python coding environment with an AI assistant. Works without a camera.
ℹ️ Note
All ML processing happens locally on the student's device using TensorFlow.js. No camera footage or student data is sent to any server.
Journal
A rich-text reflective writing activity. Students write journal entries in response to a prompt you set — linked to a lesson or as a standalone reflection. You can read and comment on every entry. See the Student Journals section below for full details.
Assigning activities to your class
Open your class → Activities tab
Click the Activities tab in your class. All available Advanced Activities are listed — each is disabled by default.
Click 'Manage Activities'
Opens the activity library. Browse all available activities and enable the ones you want your class to access.
Configure each activity
Set the unlock week (controls when students can see it), XP reward, and whether it is required or optional.
Add teacher instructions (optional)
Write custom instructions that appear for students when they open the activity — useful for task-specific context.
Link to a lesson (optional)
If the activity relates to a specific lesson, link it. The activity card will appear for students after that lesson.
💡 Pro Tip
Enable activities one at a time as you introduce each concept. Showing all activities at once can overwhelm students who are new to AI tools.
Student Journals
The Journal activity gives students a dedicated space to reflect on their learning. You can assign a journal with a specific prompt (e.g. "Document your design process") or leave it open-ended. All entries from your class appear in one place:
Read entries
Browse all journal entries from your class. Filter by student or date.
Leave a comment
Add a teacher comment on any entry. Students see it the next time they view their journal.
Track frequency
See how regularly each student is writing — a proxy for reflective engagement.
Private by default
Entries are private between the student and their teacher. Students cannot see each other's entries.
Access journals via the Student Journals link in your class Activities tab.
💡 Pro Tip
A quick comment on a journal entry shows students you read their work — even two sentences makes a significant difference to engagement.
Linking activities to assessments
Advanced Activities can be attached to a formal assessment in three ways. The assessment type (project, practical, portfolio) stays unchanged — the activity is where the work happens.
📋 Full submission
The activity is the submission. Example: a journal is the full deliverable for a practical assessment, or a Teachable Machine model is the entire project submission. The student opens the activity instead of the standard project workspace, and you grade the activity output.
🧩 One component
The activity is one task within a larger assessment. Example: a project has a design document (written in-app), a working prototype (ML activity), and a reflection (journal) — each appears as a task card in the student's project workspace alongside the written sections.
📁 Portfolio task
The activity is a required or optional task within a portfolio assessment. It appears alongside lesson completion cards in the student's portfolio view, and contributes to completion % and/or quality score.
ℹ️ Note
Assessment linking is configured in the activity settings when you assign it to your class. Select the assessment and choose the role — the rest is automatic.
Monitoring completion
Completion counts
The Activities tab shows how many enrolled students have completed each enabled activity.
Journal entries
Click Student Journals to read and comment on student reflections.
XP awarded
Students earn XP when they complete an activity for the first time. Completions appear in their progress profile.
Student profile
Open any student in the Students tab to see their full activity completion history.
Device requirements
Webcam required
Image, Sound, and Pose classifiers; Air Writing; Face Filters; Hand Tracking; Gesture Math; Pose Game; Sign Language Detection.
No camera needed
Visual Coding and Journal activities work on any device with a browser.
Browser only
All activities run in Chrome or Edge. Safari is not supported for camera-based ML activities.
Good lighting
Camera-based activities work best with consistent overhead lighting. Bright backgrounds can cause detection errors.
ℹ️ Note
Check your classroom setup before enabling camera-based activities. Not all school laptop webcams have the resolution needed for good pose detection — test in advance.