Feature request: Spaced Repetition for Learning Reinforcement

[LifeBringer]

Feature request: Spaced Repetition for Learning Reinforcement

Problem

When learning new programming concepts, information is initially stored in short-term memory. However, it requires repeated exposure (reinforcement) to become deeply ingrained and easily recalled. While the Discord community provides opportunities for reinforcement through teaching others, we need a more systematic approach to ensure long-term retention of key concepts.

Solution

Implement a spaced repetition system within Boot.dev to reinforce learnings from past quests. Similar to how our wandering character would rest to tell tales form conquests past and hopefully gain new insights upon reflection. This system would:

1. Generate review prompts based on previously completed content
2. Integrate these prompts into the user's learning journey at optimal intervals
3. Adapt the frequency and difficulty of reviews based on user performance

Key Features

• AI-Generated Question/Answer Pairs: Create dynamic review content based on completed lessons and quests
• Intelligent Scheduling: Utilize spaced repetition algorithms to determine optimal review timing
• Progress Tracking: Award XP for completed reviews (regardless of correctness) to incentivize participation and non-gaming of the analytics
• Seamless Integration: Incorporate review prompts naturally within the course flow
• Customization: Allow users to add their own review items or flag content for future review

Implementation Details

1. Spaced Repetition Algorithm: Implement a variation of the SuperMemo 2 or FSRS (Free Spaced Repetition Scheduler) algorithm to determine review intervals
2. Content Generation: Use AI to analyze completed lessons and generate relevant review questions
3. User Interface: Design an intuitive interface for presenting reviews and collecting user feedback
4. Backend Integration: Store user review history and performance metrics to inform the scheduling algorithm

Benefits

• Reinforces key concepts, improving long-term retention
• Identifies areas where users may need additional practice
• Provides a more personalized and adaptive learning experience
• Increases engagement by regularly revisiting past material in new contexts

References

• SuperMemo 2 Algorithm
• Free Spaced Repetition Scheduler (FSRS)
• Anki's Explanation of Spaced Repetition Algorithms

Next Steps

1. Conduct user surveys to gauge interest and gather additional feature ideas
2. Prototype the review interface and test with a small group of users
3. Develop the backend infrastructure for storing and retrieving review items
4. Implement the chosen spaced repetition algorithm
5. Beta test the feature with a wider audience and iterate based on feedback

Fat Marker Sketch

[rgereg]

This is a great suggestion, would love to see some traction on it being implemented quickly and very soon.

[Japhira91]

Really good idea and very important for learning! I would also like open ended questions instead of multiple choice. I think the learning effects in multiple choice are kinda ... meh