zeba_academy_revision_scheduler 0.0.1
zeba_academy_revision_scheduler: ^0.0.1 copied to clipboard
Smart revision scheduler using forgetting curve algorithm, review reminders and learning analytics.
Changelog #
All notable changes to this project will be documented in this file.
The format follows Keep a Changelog, and this project follows Semantic Versioning.
0.0.1 - 2026-06-12 #
Added #
- Initial release of
zeba_academy_revision_scheduler
Features #
- Added forgetting curve algorithm engine
- Added memory retention calculation
- Added smart revision scheduling system
- Added spaced repetition workflow
- Added review interval calculation
- Added revision reminder service
- Added learning progress analytics
- Added review history tracking models
- Added revision item management
Core Components #
-
Added
RevisionItemmodel- Stores learning topics
- Tracks review count
- Manages next revision date
- Supports difficulty levels
-
Added
ReviewRecordmodel- Stores revision attempts
- Tracks success/failure
- Records review ratings
-
Added
ForgettingCurve- Calculates memory retention score
- Detects revision requirements
- Generates recommended review intervals
-
Added
SmartScheduler- Sorts revision priorities
- Updates revision schedule
- Adjusts intervals after reviews
-
Added
ReminderService- Provides upcoming revision tasks
- Filters daily revision items
-
Added
RevisionAnalyticsEngine- Calculates revision performance
- Tracks success rate
- Generates learning statistics
Documentation #
- Added production-ready README documentation
- Added installation instructions
- Added usage examples
- Added API examples
- Added project structure documentation
Testing #
- Added initial unit tests
- Added forgetting curve validation tests
License #
- Added GNU General Public License v3.0 (GPL-3.0)
Upcoming Releases #
Planned for Future Versions #
0.1.0 #
- Persistent local storage support
- Hive database integration
- SQLite support
- Revision history storage
- Export/import learning data
0.2.0 #
- Advanced AI-based scheduling
- Adaptive difficulty prediction
- Personalized learning recommendations
- Improved retention prediction