Student Analytics
Understanding and using student data to improve learning outcomes.
Analytics Dashboard
Access analytics: Course Dashboard → Analytics
Overview Tab
High-level metrics:
- Total Active Students: Students who used TutorQ this week
- Average Engagement: Class-wide engagement score (0-100)
- Total Sessions: Number of chat sessions this week
- Average Mastery: Class average across all concepts
Engagement Metrics
Engagement Score Calculation:
- Quality of questions asked (30%)
- Follow-up interactions (25%)
- Time spent actively learning (20%)
- Consistency of use (15%)
- Concept coverage (10%)
Interpreting Scores:
- 80-100: Highly engaged, active learner
- 60-79: Good engagement, regular use
- 40-59: Moderate engagement, could improve
- 0-39: Low engagement, intervention recommended
Concept Mastery
View mastery across your curriculum:
- Heat Map: Visual representation of class understanding
- Concept List: Sortable table of all concepts
- Struggling Areas: Concepts with low average mastery
Example Insights:
- "68% of students have mastered 'Photosynthesis'"
- "Only 32% understand 'Cellular Respiration' - consider review"
Individual Student Analytics
Click any student to see detailed metrics:
Performance Overview
- Overall Mastery Level: Percentage across all concepts
- Concepts Mastered: Count and list
- Study Time: Total and weekly breakdown
- Last Active: When student last used TutorQ
Learning Patterns
- Peak Study Times: When student is most active
- Session Length: Average time per session
- Question Quality: Sophistication of questions asked
- Follow-up Rate: How often student asks follow-ups
Concept Progress
Timeline showing:
- Which concepts studied when
- Mastery progression over time
- Concepts needing review (spaced repetition)
Struggling Concepts
Automatically identified areas where student:
- Asked repeated questions
- Shows declining mastery
- Hasn't achieved threshold understanding
Class-Wide Insights
Common Struggles
TutorQ identifies concepts where:
- Multiple students ask similar questions
- Average mastery is below 60%
- Students repeatedly need help
Action Items:
- Dedicate class time to these topics
- Create supplementary materials
- Adjust teaching approach
Frequently Asked Questions
See what students are asking most:
- Topic breakdown
- Specific question patterns
- Comparison to your learning objectives
Use This To:
- Identify confusing areas in materials
- Prepare targeted FAQs
- Adjust lecture focus
Time Analytics
Understand when students study:
- Peak Hours: When TutorQ is most used
- Pre-Exam Patterns: Study behavior before assessments
- Weekly Trends: Day-by-day usage
Optimize:
- Schedule office hours during peak times
- Release materials when students are most active
- Identify procrastination patterns
Predictive Analytics
At-Risk Student Identification
TutorQ predicts students likely to struggle based on:
- Declining engagement
- Low mastery across multiple concepts
- Decreased usage patterns
- Failed to master prerequisite concepts
Early Warning System:
- Email notifications when students flagged as at-risk
- Suggested interventions
- Progress monitoring dashboard
Success Predictions
Estimate likelihood of student success:
- Based on engagement patterns
- Mastery trajectories
- Historical data from similar courses
Use For:
- Identifying students who need extra help
- Allocating tutoring resources
- Personalized outreach
Comparative Analytics
Course Comparisons
If teaching multiple sections:
- Compare engagement across sections
- Identify which teaching methods work best
- Standardize or differentiate approaches
Historical Comparisons
Compare to previous semesters:
- Is this class more/less engaged?
- Which concepts remain challenging year-over-year?
- Impact of material or teaching changes
Peer Comparisons (Optional)
With permission, compare to anonymized data from:
- Similar courses at your institution
- National averages for the subject
- Best-performing courses
Benefits:
- Benchmark your course
- Identify improvement opportunities
- Share best practices
Exporting Analytics
Reports
Generate pre-built reports:
- Weekly Summary: Engagement and activity overview
- Student Progress: Individual mastery reports
- Concept Analysis: Deep dive into specific topics
- End-of-Semester: Comprehensive course report
Custom Exports
Create custom data exports:
- Analytics → Export Data
- Select date range
- Choose metrics to include
- Select format (CSV, Excel, PDF)
- Download
Scheduled Reports
Set up automatic reports:
- Analytics → Scheduled Reports
- Choose report type
- Set frequency (daily, weekly, monthly)
- Enter email address
- Reports delivered automatically
Using Analytics to Improve Teaching
Strategy 1: Data-Driven Lectures
Before each lecture:
- Review concept mastery from previous week
- Identify struggling areas
- Spend extra time on those concepts
- Use student questions to guide discussion
Strategy 2: Personalized Interventions
Weekly routine:
- Review at-risk student list
- Examine individual analytics
- Send personalized encouragement or resources
- Offer targeted office hours
Strategy 3: Material Optimization
Monthly review:
- Identify concepts with persistently low mastery
- Review course materials for those concepts
- Add examples, diagrams, or explanations
- Upload improved materials
- Monitor for improvement
Strategy 4: Peer Learning
Use analytics to form study groups:
- Pair struggling students with high-mastery peers
- Group students with complementary strengths
- Create discussion groups for challenging topics
Privacy and Ethics
What's Tracked
TutorQ tracks:
- Engagement metrics (time, frequency)
- Concept mastery levels
- General question topics
- Learning patterns
What's Not Tracked
TutorQ does not track:
- Specific questions or answers (without student permission)
- Student activity outside your course
- Personal information beyond educational data
- Student conversations in other contexts
Ethical Use of Data
Best Practices:
- Use data to help students, not penalize them
- Don't make high-stakes decisions based solely on analytics
- Respect student privacy
- Be transparent about what data you collect
- Give students access to their own data
Avoid:
- Sharing student data publicly
- Using analytics for punitive grading
- Making assumptions without context
- Comparing students publicly
Troubleshooting Analytics
"Analytics not updating"
- Data refreshes every hour
- Hard refresh (Cmd/Ctrl + Shift + R)
- Check that students are enrolled and active
"Student data seems inaccurate"
- Verify student is logging in (not a duplicate account)
- Check for technical issues in student's chat sessions
- Contact support if persistent
"Can't export data"
- Check file size (large courses may need filtering)
- Ensure you have educator permissions
- Try different browser if export fails
Next Steps
- Managing Students - Act on analytics
- Best Practices - Proven strategies
- FAQ - Common questions
Questions? Email support@q3learners.com