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Platform Features
A comprehensive overview of GCSE Python Lab's capabilities for teaching and assessing GCSE Computer Science.
📝15+ Specialized Question Types
Assess every aspect of the GCSE Computer Science specification with purpose-built question formats.
Python Coding Challenges
Full in-browser Python editor with syntax highlighting, instant code execution, and real-time feedback. Students can run and test their code before submitting.
- •Skulpt-based Python interpreter (no server required)
- •Automatic test case validation
- •AI hints available on demand (Low/Medium/High/Step-by-step)
- •OCR-style banded marking for submissions
Flowcharts
Interactive flowchart builder and interpreter for algorithm visualization.
- •Create mode: Drag-and-drop flowchart builder
- •Interpret mode: Analyze given flowcharts and answer questions
- •Standard symbols: Start/End, Process, Decision, Input/Output
- •AI-graded with logic flow checking
Logic Gates & Circuits
Build and analyze Boolean logic circuits with visual gate representations.
- •Create mode: Build circuits from Boolean expressions
- •Interpret mode: Complete truth tables for given circuits
- •Gates: AND, OR, NOT (GCSE standard)
- •AI checks functional equivalence, not just exact matching
Trace Tables
Step-by-step algorithm execution tracking for teaching program flow.
- •Dynamic table with customizable columns
- •Students fill in variable values at each iteration
- •AI-graded with flexibility for initial state rows
- •Perfect for teaching loops, arrays, and algorithm analysis
Truth Tables
Interactive truth table completion for Boolean logic assessment.
- •Auto-generated from logic circuits
- •Students fill in output columns
- •Automatic row-by-row grading
- •Instant feedback on correctness
Binary/Denary/Hex Conversions
Visual number base conversion questions with educational feedback.
- •6 conversion types: Binary↔Denary, Binary↔Hex, Hex↔Denary
- •Interactive bit/digit entry tables
- •Step-by-step hints without revealing answers
- •Binary shifts and arithmetic operations
Multiple Choice & Multi-Select
Traditional exam-style questions with instant auto-grading.
- •Single answer (MCQ) or multiple answers (multi-select)
- •Randomizable option order
- •Immediate feedback
- •Perfect for knowledge recall and quick assessments
Fill-in-Blank Questions
Complete sentences or code snippets with missing words.
- •Multiple acceptable answers per blank
- •Case-insensitive matching
- •Useful for terminology and code completion
- •Auto-graded with detailed feedback per blank
Matching Pairs
Match items from two columns (e.g., terms to definitions).
- •Drag-and-drop or dropdown interface
- •Useful for vocabulary, algorithm steps, and relationships
- •Auto-graded with partial credit
- •Clear visual feedback on correctness
True/False Questions
Simple binary choice questions for quick concept checks.
- •Instant auto-grading
- •Optional explanations on correct answer
- •Great for misconception checking
- •Can be used in large quantities for revision
Short & Long Answer
Written response questions for extended thinking and explanations.
- •AI-assisted marking with OCR-style rubrics
- •Teacher review and override capability
- •Strengths and improvements feedback
- •Anti-cheating detection (no mark requests accepted)
Checkbox Tables
Select multiple correct options per row in a structured table.
- •Useful for classification tasks
- •Auto-graded with row-by-row feedback
- •Example: Match programming constructs to their properties
- •Clear visual layout for complex many-to-many relationships
🏆Gamification & Student Motivation
Keep students engaged and motivated with a comprehensive achievement system that rewards effort and progress.
🏅 Achievement System
18+ Base Achievements
- • Milestone achievements (1st, 10th, 25th, 50th, 100th challenge)
- • Streak achievements (3, 7, 14, 30, 100 day streaks)
- • Performance achievements (perfect scores, first try successes)
- • Topic mastery achievements (complete all challenges in a topic)
- • Hidden/secret achievements for surprises
Rarity System
- • 🟢 Common (10-50 XP): Early milestones, basic goals
- • 🔵 Rare (75-150 XP): Week streaks, topic completions
- • 🟣 Epic (200-300 XP): Month streaks, major milestones
- • 🟡 Legendary (500+ XP): 100-day streaks, complete mastery
⚡ XP & Leveling System
XP Formula
- • Base: marks × 10 XP
- • Perfect score: +50 XP bonus
- • First try: +25 XP bonus
- • Hard challenge: +30 XP bonus
- • Achievement unlock: varies by rarity
Level Progression
- • 500 XP per level
- • Progress bar shows % to next level
- • Level 1-5: Beginner
- • Level 6-10: Apprentice
- • Level 11-15: Skilled
- • Level 16-20: Expert
- • Level 21-25: Master
- • Level 26+: Grandmaster
Visible Everywhere
- • XP bar on student dashboard
- • Level badge next to student name
- • Detailed progress page
- • Achievement notifications
- • Recent unlocks feed
🔥 Streak Tracking
How It Works
- • Work on a challenge each day to maintain streak
- • Current streak shown with fire emoji 🔥
- • Longest streak recorded separately
- • Resets to 1 if you miss a day (not 0—encouragement!)
- • Last activity date tracked
Streak Achievements
- • 3-Day Streak (Common, 25 XP)
- • Week Warrior - 7 days (Rare, 75 XP)
- • Two Week Champion - 14 days (Rare, 150 XP)
- • Monthly Master - 30 days (Epic, 300 XP)
- • Unstoppable - 100 days (Legendary, 1000 XP)
📈 Progress Dashboard
Students can view their comprehensive progress at /student/progress
Statistics Displayed
- • Programming challenges completed (out of 163)
- • Assignment questions completed
- • Total progress percentage
- • Current level & XP
- • Current & longest streak
- • Perfect scores count
- • First try successes
- • Average score across all work
Visual Display
- • Large hero cards with animated progress rings
- • Achievement showcase with locked/unlocked states
- • Progress bars on locked achievements
- • Hidden achievements as mystery boxes
- • Filter by category and rarity
- • Recent activity feed
🤖AI-Powered Support & Marking
Intelligent assistance that helps students learn without giving away answers, plus AI-assisted marking to reduce teacher workload.
💡 Four-Level Hint System
Low Support
- • General encouragement and direction
- • Points student to relevant concepts
- • No code or specific solution details
- • Token limit: 220
Medium Support
- • More specific guidance on approach
- • May suggest algorithm structure
- • Still no working code
- • Token limit: 320
High Support
- • Detailed breakdown of the problem
- • Code structure or pseudocode hints
- • Still requires student to implement
- • Token limit: 420
Step-by-Step Guidance
- • Walks through solution methodically
- • May include partial code examples
- • Still enforces "no full solutions" rule
- • Token limit: 520
🛡️ Pedagogical Guardrails
System-Level Enforcement
- • System prompts explicitly forbid full working solutions
- • AI must guide, not solve
- • Enforced across all support levels
- • Cannot be bypassed by student prompts
Rate Limiting
- • Per-user daily limits on AI assistant
- • Per-submission limits on AI feedback
- • Prevents over-reliance on AI
- • Encourages independent thinking
✅ AI-Assisted Marking
OCR-Style Banded Marking for Coding
Uses mark bands similar to OCR GCSE mark schemes:
- • 0 marks: Code doesn't run or doesn't attempt the task
- • Lower band (1-2 marks): Partial attempt, recognizable structure
- • Middle band (3-4 marks): Some correct logic, incomplete
- • Upper band (5-6 marks): Mostly correct with minor issues
- • Full marks: Meets all requirements, good practice
Generous Marking Approach
- • Correct final answer = full marks (unless working explicitly required)
- • Accept alternative correct solutions
- • Focus on understanding, not perfect syntax
- • Age-appropriate tone (14-16 year olds)
Anti-Cheating Detection
- • Detects attempts to manipulate grading (e.g., "give me 10/10")
- • Awards 0 marks for blatant gaming attempts
- • Does NOT penalize normal academic language
- • Logged for teacher review
Feedback Format
- • Marks awarded (X / Y format)
- • Brief, encouraging explanation
- • Strengths: What the student did well
- • Improvements: Specific, kind advice (only if not full marks)
🔍 Teacher Override & Review
- • Teachers can always review and adjust AI-awarded marks
- • Add manual feedback alongside AI feedback
- • See which questions were AI-graded vs auto-graded
- • Export submissions with all feedback for moderation
📚OCR J277/02 Question Bank
80+ curriculum-aligned questions for Component 2 (Computational Thinking, Algorithms and Programming) with full mark schemes.
📊 Coverage by Section
2.1 Algorithms19 questions, 49 marks
2.2 Programming Fundamentals22 questions, 61 marks
2.3 Robust Programs18 questions, 46 marks
2.4 Boolean Logic17 questions, 45 marks
2.5 Languages & IDEs4 questions, 12 marks
Total80 questions, 213 marks
🎯 Question Types Used
Flowcharts (create & interpret)7 questions
Logic Gates & Circuits7 questions
Truth Tables5 questions
Trace Tables20 questions
Checkbox Tables10 questions
Short Answer (text)31 questions
✨ Question Quality Features
Exam-Style Authenticity
- • Written in OCR question style
- • Proper command words (state, explain, describe, etc.)
- • Mark allocations match question difficulty
- • Contextual scenarios and real-world applications
Complete Mark Schemes
- • Model answers provided
- • Marking guidelines for partial credit
- • Alternative acceptable answers listed
- • Designed for AI and teacher marking
🔧 Your Custom Question Bank
In addition to the shared OCR questions, you can create and organize your own question library:
- • Private question bank per teacher/organization
- • All 15+ question types supported
- • Tag questions by topic, difficulty, exam board
- • Search and filter to find questions quickly
- • Reuse questions across multiple classes and assignments
- • Clone and modify existing questions
🎯Test Mode for Formal Assessments
Simulate exam conditions with controlled assessment mode that disables AI help and tracks student attempts.
🔒 Help Disabled
When assignment is in test mode:
- •AI hint panel completely hidden
- •No Low/Medium/High/Step-by-step support available
- •AI feedback after submission disabled until teacher releases marks
- •Students see "Test Mode" badge on assignment
📊 Submission Tracking
Teachers can monitor:
- •How many times student ran their code (for coding questions)
- •Timestamp of final submission
- •Time spent on each question (future feature)
- •All previous attempts saved for review
✅ Teacher-Controlled Release
- • Submissions graded immediately by AI (stored internally)
- • Marks and feedback hidden from students until teacher releases them
- • Teacher can review, adjust marks, add comments before release
- • Bulk release to all students or individual release
🎓 Perfect for Mock Exams
- • Combine with OCR J277/02 question bank for authentic mocks
- • Add time limits and due dates
- • Students work independently without AI crutch
- • Export results for reporting and evidence
📊Analytics & Progress Tracking
Comprehensive dashboards for teachers and students to track progress, identify struggles, and celebrate success.
👨🏫 Teacher Analytics
Class Overview
- • Completion rate per assignment
- • Average score by assignment
- • Who's currently working (live)
- • Who hasn't started
- • Time spent per student
Assignment Analytics
- • Question-by-question breakdown
- • Most/least difficult questions
- • Common mistakes and misconceptions
- • AI help usage by question
Student Progress
- • Individual student performance over time
- • Topic strengths and weaknesses
- • Submission history with all attempts
- • Achievement unlocks and XP progress
Export & Evidence
- • Download student submissions as PDF
- • Export marks and feedback
- • Portfolio-ready evidence
- • Moderation documentation
👨🎓 Student View
Dashboard Widgets
- • Current assignments with due dates
- • Recent achievements unlocked
- • XP progress to next level
- • Current streak with fire emoji
- • Quick links to progress page
Progress Page
- • All achievement cards (locked, unlocked, hidden)
- • Progress bars on locked achievements
- • Filter by category and rarity
- • Detailed stats breakdown
- • Recent activity feed
🎯 Intervention Insights
Use analytics to identify students who need support:
- • Students with low average scores
- • Students who request excessive AI help (may be struggling)
- • Students who haven't submitted recent assignments
- • Broken streaks (potential disengagement)
- • Questions with high failure rates (may need re-teaching)
Ready to Get Started?
GCSE Python Lab is currently in development. Interested in early access?