Concept Mastery Overview
Sunschool tracks mastery level for every individual concept a learner encounters. This granular tracking enables adaptive learning, identifying both strong areas and concepts needing reinforcement.How Mastery is Calculated
Mastery is a percentage based on correct vs. total attempts for each concept.Mastery Formula
- 7 correct out of 10 attempts = 70% mastery
- 3 correct out of 4 attempts = 75% mastery
Mastery Threshold
Mastery is achieved at 70% accuracy
- Below 70%: Concept needs reinforcement
- 70% and above: Concept is mastered
Concept Mastery Data Structure
Field Descriptions
| Field | Type | Description |
|---|---|---|
conceptName | string | Name of the concept (e.g., “Fractions”, “Photosynthesis”) |
subject | string | Subject area (e.g., “Math”, “Science”) |
correctCount | number | Times answered correctly |
totalCount | number | Total times tested on this concept |
masteryLevel | number | Percentage (0-100) |
lastTested | Date | Most recent quiz date |
needsReinforcement | boolean | True if masteryLevel < 70 |
Updating Mastery After Quizzes
Mastery is updated after every quiz submission.Single Concept Update
Bulk Update from Quiz
Each quiz question can test multiple concepts. The
conceptTags array allows a single question to update mastery for several related concepts.Spaced Repetition
The mastery system supports spaced repetition throughlastTested tracking.
Concepts Needing Reinforcement
Sorting Strategy
Primary Sort: Lowest Mastery First
Concepts with the lowest mastery levels are prioritized.Example: A concept at 30% mastery comes before one at 65%.
This sorting ensures learners review their weakest concepts first, and among weak concepts, prioritizes those that haven’t been practiced recently (spaced repetition principle).
Performance Per Concept
Viewing All Mastery
Mastery Summary
Struggling Areas Identification
Profile Storage
Automatic Detection
Struggling areas can be automatically populated by querying mastery:Visual Indicators
Struggling areas can be highlighted in the UI:- Knowledge Graph
- Progress Dashboard
- Lesson Recommendations
Nodes for struggling concepts shown in orange/red
Integration with Quiz System
Mastery tracking is updated during quiz submission:- Points awarded based on correct answers
- Mastery updated for each concept tested
- Knowledge graph updated with new nodes/edges
- Struggling areas recalculated based on new mastery data
API Endpoints
Next Steps
Knowledge Graph
See how mastery connects to the visual learning map
Adaptive Learning
Learn how mastery drives personalized lesson recommendations