MIRRA
Comprehension Signal
📱
Audience
Enter your session code. Tap your comprehension after each section.
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🎙
Speaker
Create a session. Fire check-ins. See real-time AI insight.
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📊
Program Overview
Cross-session intelligence across every speaker and session — patterns, not performance reviews.
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Student
Saved on your device. Only you see your individual data.
6-character code from your instructor.
👋
Hey there
Connected
⏸Instructor-paced
Standing by — check-in coming soon
Your session
No check-ins yet.
SECTION
How did that land?
Tap the color that matches where you are right now.
Logged
Response saved.
Your session arc0 check-ins
AI SUMMARY
Generating your learning insight…
Instructor
Sign in to access your sessions and dashboard.
New Session
Configure, then share your session code
Used to calculate response density percentage.
Students see these labels when a check-in fires.
How MIRRA decides when to send check-ins.
🎙
Manual
You fire each check-in when ready
⏱
Timed
Auto-pings at a set interval
📑
Per section
Fires when you advance sections
Ping interval
You can always fire manually regardless of the timer.
Session
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↓
⚙
Check-in mode
Manual
00:00
0 fired
0
Responses
0
Participants
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Avg quality
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Response rate
⚠
Comprehension spike
High confusion signal.
✦
Peak engagement
Strong comprehension signal.
Live distribution
Current check-in
LIVE
Red
0
Orange
0
Yellow
0
Green
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Blue
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Quality trend
Avg score · 0 = frustrated · 4 = engaged
Fire two or more check-ins to see the trend line.
Session heatmap
Y = quality · X = time · temperature = density
Engaged
Understands
Challenged
Confused
Frustrated
AI Session Insight
Curriculum intelligence · Generated from session data
AI INSIGHT
Fire check-ins to generate curriculum insight.
Response log
0
No responses yet.
Export session data. Every response, timestamped, named, section-labeled.
Observer
🔒No individual data
0
Responses
0
Check-ins
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Avg quality
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Response rate
⚠
Comprehension spike
High red + orange on latest check-in.
✦
Peak engagement
Strong green + blue on latest check-in.
Current distribution
Most recent check-in
LIVE
Red
0%
Orange
0%
Yellow
0%
Green
0%
Blue
0%
Quality trend
Fire two or more check-ins to see the trend.
Session heatmap
Y = quality of submission · X = time through session
Engaged
Understands
Challenged
Confused
Frustrated
🔒
No individual data on this view
This observer dashboard shows only anonymized aggregates. No names, no individual response sequences, no personally identifiable information. Individual learning records are owned by the learner — visible only to them. What you see here is the room, not who is in it.
Program Overview
📊
A tool for speakers, not against them
Every instructor sees this same data about their own sessions first. Nothing shown here to a program owner is hidden from the person who delivered the session. Transparency runs both ways.
12
Sessions tracked
4
Speakers
2.6
Program avg
312
Total responses
Speaker performance
Avg comprehension score across all their sessions
Content friction map
Topics that consistently lose the room, regardless of speaker
Protected — requires 3+ instructors
Set by your program's data policy. MIRRA doesn't decide this for you — your institution does.
Program Insight
Curriculum-level pattern, not individual evaluation
AI INSIGHT
Across all tracked sessions, "Application" modules score 0.9 points lower on average than "Introduction" modules — consistent across every speaker who has taught one. This points to a structural gap between concept delivery and practical application materials, not an individual delivery issue. Consider revising the application-stage materials program-wide before attributing the pattern to any one speaker.
All sessions
Full program data, exportable. For accreditation, renewal, or board reporting.