DollhouseMCP

--- name: "Learning Progress" description: "Tracks learning goals, progress, and personalized educational pathways" type: "memory" version: "1.0.0" author: "DollhouseMCP" created: "2025-07-23" category: "education" tags: ["learning", "progress", "education", "skills", "knowledge-tracking"] storage_backend: "file" retention_policy: default: "perpetual" rules: - type: "achievements" retention: "perpetual" - type: "practice_sessions" retention: "1 year" - type: "mistakes" retention: "6 months" - type: "resources" retention: "perpetual" privacy_level: "user-private" searchable: true schema: learning_profile: type: "object" properties: learner_id: "string" learning_style: "string" goals: "array" current_level: "object" time_investment: "object" progress_tracking: type: "object" properties: skills: "array" completed_modules: "array" current_module: "object" assessments: "array" knowledge_map: type: "object" properties: mastered: "array" in_progress: "array" planned: "array" prerequisites: "object" _dollhouseMCPTest: true _testMetadata: suite: "bundled-test-data" purpose: "General test data for DollhouseMCP system validation" created: "2025-08-20" version: "1.0.0" migrated: "2025-08-20T23:47:24.343Z" originalPath: "data/memories/learning-progress.md" --- # Learning Progress Memory This memory element creates a personalized learning experience by tracking progress, adapting to learning patterns, and maintaining a comprehensive knowledge map. ## Learning Profile ### 1. Learner Characteristics ```yaml learner_profile: id: "{{learner_id}}" created: "{{start_date}}" learning_style: primary: "visual" # visual, auditory, kinesthetic, reading secondary: "kinesthetic" preferences: - "worked_examples" - "interactive_exercises" - "conceptual_diagrams" - "step_by_step_guidance" pace_preference: speed: "moderate" # slow, moderate, fast, adaptive depth: "thorough" # surface, balanced, thorough practice_ratio: 0.7 # theory vs practice balance motivation_factors: - "practical_application" - "skill_mastery" - "career_advancement" - "intellectual_curiosity" ``` ### 2. Skills Tracking ```yaml skills_matrix: programming: python: level: "intermediate" hours_practiced: 124 projects_completed: 8 sub_skills: syntax: "mastered" data_structures: "proficient" algorithms: "developing" frameworks: django: "proficient" fastapi: "learning" pandas: "proficient" javascript: level: "beginner" hours_practiced: 32 projects_completed: 2 sub_skills: syntax: "proficient" dom_manipulation: "learning" async_programming: "not_started" frameworks: react: "learning" node: "not_started" soft_skills: problem_solving: level: "advanced" demonstrated_in: ["bug_fixes", "algorithm_design", "debugging"] communication: level: "intermediate" areas_of_improvement: ["technical_writing", "code_documentation"] ``` ### 3. Learning Goals ```yaml goals: short_term: # Next 30 days - goal: "Complete React fundamentals" deadline: "2025-08-23" progress: 65 milestones: - "Components and Props" ✓ - "State and Lifecycle" ✓ - "Hooks" [in_progress] - "Context API" [pending] time_estimate: "20 hours" actual_time: "13 hours" medium_term: # Next 90 days - goal: "Build full-stack application" deadline: "2025-10-23" progress: 20 prerequisites_met: ["backend_api", "database_design"] prerequisites_pending: ["frontend_framework", "deployment"] long_term: # Next year - goal: "Achieve senior developer skills" areas: - "System design" - "Performance optimization" - "Security best practices" - "Team leadership" ``` ## Progress Analytics ### 1. Learning Patterns ```yaml patterns: effective_times: morning: 0.2 # 20% effectiveness afternoon: 0.5 # 50% effectiveness evening: 0.3 # 30% effectiveness session_duration: optimal: "45 minutes" attention_span: "25 minutes" break_frequency: "every 50 minutes" retention_methods: most_effective: - "hands_on_practice" - "teaching_others" - "real_projects" least_effective: - "passive_reading" - "video_watching_only" struggle_indicators: - "repeated_same_errors" - "long_pause_periods" - "frequent_context_switching" ``` ### 2. Knowledge Retention ```yaml retention_tracking: concepts: - name: "Recursion" first_learned: "2025-06-15" reinforcement_dates: ["2025-06-20", "2025-07-01", "2025-07-15"] retention_score: 0.85 application_count: 12 - name: "Async/Await" first_learned: "2025-07-10" reinforcement_dates: ["2025-07-12"] retention_score: 0.60 application_count: 3 needs_review: true spaced_repetition: due_for_review: - concept: "SQL Joins" last_review: "2025-07-01" next_review: "2025-07-24" interval: 23 # days - concept: "Docker Basics" last_review: "2025-07-20" next_review: "2025-07-25" interval: 5 ``` ### 3. Mistake Patterns ```yaml common_mistakes: - category: "syntax" frequency: "decreasing" examples: - "Forgetting semicolons in JavaScript" - "Indentation errors in Python" improvement_trend: 75 # % reduction - category: "logic" frequency: "stable" examples: - "Off-by-one errors in loops" - "Incorrect base cases in recursion" targeted_exercises: ["boundary_value_practice", "recursion_tracing"] - category: "conceptual" frequency: "improving" examples: - "Confusing pass-by-value vs reference" - "Misunderstanding closure scope" remediation: ["visual_diagrams", "interactive_debugger"] ``` ## Adaptive Learning ### 1. Difficulty Adjustment ```yaml difficulty_calibration: current_level: 6.5 # Scale 1-10 performance_metrics: success_rate: 0.72 time_to_complete: "normal" help_requests: "occasional" adjustments: last_increase: "2025-07-15" last_decrease: "2025-06-28" trend: "gradual_increase" challenge_types: preferred: ["debugging", "optimization"] avoided: ["from_scratch", "mathematics"] ``` ### 2. Learning Path Optimization ```yaml personalized_curriculum: next_topics: 1: topic: "Advanced React Patterns" rationale: "Builds on current React knowledge" prerequisites_met: true estimated_duration: "15 hours" 2: topic: "State Management (Redux)" rationale: "Needed for full-stack goal" prerequisites_met: false blocking_prerequisites: ["React Hooks mastery"] 3: topic: "Testing with Jest" rationale: "Addresses weak area in skill matrix" prerequisites_met: true priority: "high" recommended_resources: - type: "interactive_course" title: "React Advanced Patterns" match_score: 0.92 reason: "Matches visual learning style" - type: "project_based" title: "Build a Task Manager" match_score: 0.88 reason: "Hands-on practice preference" ``` ## Achievement System ### 1. Milestones ```yaml achievements: unlocked: - name: "First Hello World" date: "2025-05-01" category: "beginner" - name: "Bug Squasher" date: "2025-06-15" category: "debugging" criteria: "Fixed 10 bugs independently" - name: "Full Stack Builder" date: "2025-07-20" category: "projects" criteria: "Deployed first full-stack app" in_progress: - name: "Open Source Contributor" progress: 2/5 criteria: "Merge 5 PRs to open source projects" - name: "Performance Optimizer" progress: 60% criteria: "Improve app performance by 50%" ``` ### 2. Skill Certifications ```yaml certifications: internal: - skill: "Python Fundamentals" level: "certified" assessment_score: 92 date: "2025-06-30" - skill: "Web Development Basics" level: "proficient" assessment_score: 85 date: "2025-07-15" external_prep: - certification: "AWS Solutions Architect" readiness: 45% weak_areas: ["networking", "security"] study_plan_generated: true ``` ## Integration Features ### Learning Companions Works with: - **Study Buddy Persona**: Pair learning sessions - **Code Review Agent**: Practice feedback - **Project Templates**: Structured practice - **Research Assistant**: Deep dives ### Progress Reports ``` Weekly Learning Summary - Week of July 17-23, 2025 Time Invested: 12.5 hours Skills Practiced: React (8h), Python (3h), SQL (1.5h) Achievements: ✓ Completed React Hooks module ✓ Built todo app with local storage ✓ Debugged 5 complex issues Areas of Growth: 📈 React component design (+15%) 📈 Debugging skills (+10%) 📊 SQL query optimization (stable) Recommended Focus: 1. Review async/await concepts (retention declining) 2. Start Redux basics (prerequisite for next goal) 3. Practice algorithm complexity analysis Keep up the great work! You're 72% toward your monthly goal. ```