# 3. Learning Patterns & Insights

User Type: **Student**
Source: *Mi Digital Academy - Education CRM Features Document*

---

## 3. Learning Patterns & Insights

### 3.1 Learning Pattern Insights
**What it does:** Analyzes the Student's learning patterns to surface insights: peak performance times, common error patterns, and study habits. The Student sees when they perform best and which errors recur, so they can study more effectively.

**Sub-features:**
- Peak performance times identified
- Common error patterns identified
- Study habit insights (consistency, session length)
- Insights per subject
- Insights update as data accumulates
- Insights available on web and mobile
- Insight event logging (computed)
- Audit logging of the learning pattern insights

**Student User Journey:**
1. Student opens "Progress" → "Insights".
2. The peak performance time is shown (evenings, 7–9 pm).
3. The common error pattern shows sign errors in algebra.
4. The study habit insights show the Student studies best in 30-minute sessions.
5. The insights per subject are listed.
6. As more data accumulates, the insights update.
7. Student opens Profile → "Activity" and confirms the insight events are recorded.

**Rules & Edge Cases:**
- Peak performance times are derived from assessment performance by time of day.
- Common error patterns are derived from repeated wrong answers.
- Study habit insights reflect consistency and session length.
- Insights update as data accumulates.
- Insight events (computed) are logged with the timestamp.
- The learning pattern insights is audit-logged with the account and the timestamp.

### 3.2 Study Consistency and Streaks
**What it does:** Tracks the Student's study consistency: streaks of consecutive study days, consistency over a period, and milestones. Consistency is a key engagement metric and feeds into the Student's gamification. The Student sees their streak and consistency at a glance.

**Sub-features:**
- Study streak (consecutive days)
- Consistency over a rolling period
- Consistency milestones
- Streak and consistency on the dashboard
- Consistency feeds gamification
- Consistency available on web and mobile
- Consistency event logging (streak updated)
- Audit logging of the study consistency and streaks

**Student User Journey:**
1. Student opens the dashboard and sees the study streak (12 days).
2. The consistency over the last 4 weeks is shown.
3. A consistency milestone is celebrated at 30 days.
4. The streak and consistency are on the dashboard.
5. The consistency feeds the Student's gamification points.
6. Student sees the consistency on the mobile app.
7. Student opens Profile → "Activity" and confirms the consistency events are recorded.

**Rules & Edge Cases:**
- A streak counts consecutive days with at least one study action.
- Consistency is computed over a rolling period.
- Milestones are celebrated at defined thresholds.
- Consistency feeds the Student's gamification.
- Consistency events (streak updated) are logged with the timestamp.
- The study consistency and streaks is audit-logged with the account and the timestamp.

### 3.3 Personalized Recommendations
**What it does:** Provides the Student with personalized recommendations based on their performance and patterns: what to study next, which resources to use, and how to improve weak areas. The recommendations are actionable and update as the Student progresses.

**Sub-features:**
- "What to study next" recommendation
- Recommended resources (videos, flashcards, guides)
- Improvement suggestions for weak areas
- Recommendations based on performance and patterns
- Recommendations update as the Student progresses
- Recommendations available on web and mobile
- Recommendation event logging (generated, acted on)
- Audit logging of the personalized recommendations

**Student User Journey:**
1. Student opens "Progress" → "Recommendations".
2. The "what to study next" suggests Trigonometry (the weakest topic).
3. Recommended resources (a video, a flashcard deck) are listed.
4. The improvement suggestion for algebra sign errors is shown.
5. As Student studies, the recommendations update.
6. Student views the recommendations on the mobile app.
7. Student opens Profile → "Activity" and confirms the recommendation events are recorded.

**Rules & Edge Cases:**
- Recommendations are derived from the Student's performance and patterns.
- A recommendation links to a specific resource or action.
- Recommendations update as the Student progresses.
- Acting on a recommendation is recorded.
- Recommendation events (generated, acted on) are logged with the timestamp.
- The personalized recommendations is audit-logged with the account and the timestamp.