Analytics & Report
Last updated
Last updated
The Analytics section in the Operations module of VEGA AI is designed to give you a complete, data-driven picture of how your users are learning, performing, and progressing through their learning journeys.
The Analytics section in VEGA AI is like a report card for your users — but much more powerful.
It is more than just a reporting dashboard—it’s a diagnostic, evaluative, and strategic tool that empowers you to:
Monitor learner engagement
Identify knowledge gaps
Assess content effectiveness
Personalize instruction
Drive better learning outcomes
Whether you’re running a test-prep academy, managing a course, or leading a learning product, real-time performance analytics help you:
Spot struggling learners early
Understand topic-level mastery
Improve curriculum planning
Optimize batch-level instruction
Evaluate the effectiveness of AI tools or test content
By offering a 360-degree view into learner behavior, performance, and progress, analytics becomes the bridge between data and decisions.
Think of it like this:
Imagine you're running a classroom with 100 students. You can’t sit next to each one all day. But what if you had a tool that tells you:
“Hey, 8 students are really struggling in math.”
“This batch is wasting time on easy questions.”
“Your best-performing users finished all tests in half the time.”
That’s what this Analytics page does. It watches how your learners interact with your platform, and then shows you helpful insights.
This helps you:
Focus your energy where it's most needed
Guide users based on real data (not just guesses)
Improve your courses and content over time
At the top of the page, you can switch between different analysis views, each focusing on a specific level of granularity.
Gives a high-level snapshot across all learners
Helps in organizational benchmarking
Useful for leadership and macro-level reports
Focuses on the performance of a selected batch
Allows for comparative analysis between different groups
Perfect for cohort-specific improvement planning
Summarizes the results of scheduled mock tests or assessments
Helps measure readiness and post-test mastery
Ideal for analyzing standardized testing simulations
Deep-dive into individual learner data
Includes time spent, mastery level, accuracy, strengths/weaknesses
Great for 1:1 coaching, tutoring, and personalized feedback
Each mode offers a different lens into the data and can be filtered by course, date range, batch, and even test type depending on what view you are using.
VEGA AI’s Analytics page provides a combination of macro-level (overall trends) and micro-level (user-specific) performance data. These include:
Users are segmented into:
Red Zone: High-risk learners who need immediate help - Needs help urgently
Yellow Zone: Learners showing partial understanding but at risk - Doing okay, but not fully confident
Green Zone: Learners who are confidently mastering the material - Doing well
Why it matters:
This tells you where to focus your time. If many users are in the red zone, you may need to pause and offer support. If most are in green, you’re on the right track.
This makes it easy to know who to help first.
Each user is assigned a mastery score, computed based on their performance across quizzes, practice, tests, and AI-interactions. This score is a key metric used throughout the analytics modules to gauge overall learning success.
For example:
90 = doing great
60 = needs more practice
40 = struggling a lot
Why it matters:
This lets you drill down from the big picture to individuals quickly. If you notice someone with a very low score, you can click “View” and see exactly what they’re struggling with.
You can use this to track progress over time, like a fitness tracker for learning.
Track how long users are taking on each section or type of question. This is critical for exam-prep workflows where time efficiency is as important as accuracy.
Let’s say:
Users spend 2 minutes on Math questions (which is too long)
They rush through Reading questions in 30 seconds (which may lead to mistakes)
Why it matters:
In timed tests like SAT, time is just as important as correctness. If users are too slow, you’ll know where they’re stuck or overthinking. If they’re too fast, they may be rushing.
This tells you if students are using their time wisely — especially useful for exam prep.
Analytics flags which topics or question types are leading to the highest error rates, so you can:
Identify flawed teaching content
Focus remedial sessions on high-error areas
Offer corrective strategies via AI agents or tutors
For example:
50% got questions on grammar wrong
Most math errors are in percentages
Why it matters:
This shows you which topics to revise or reteach. Instead of guessing what learners didn’t understand, you have proof.
This helps you plan review sessions that really matter — not just repeating what they already know.
This is like a leaderboard that shows each user’s:
Mastery Score
Time trained
Number of questions solved
A link to detailed analytics
Why it matters:
This helps you compare learners side-by-side. You can see who is practicing the most, who’s improving, and who needs more support.
Who needs urgent help?
Red Zone / Low Mastery Scores
Offer support or intervention
Which topic is hardest?
Error Frequency or Mastery Levels
Revise or provide more material
Are students using time wisely?
Time Management
Teach time-saving techniques
Who is performing best?
Strengths Table
Acknowledge or reward
Who needs more practice?
Count of attempts or Time trained
Motivate or follow up
Adaptive Teaching: Modify batch sessions based on collective performance
Proactive Intervention: Identify learners at risk before they fall behind
Outcome Reporting: Generate insights for internal teams or external stakeholders
Timely Feedback: Get actionable insights on what to work on
Self-Awareness: See how they rank against peers
Guided Improvement: Receive focused help instead of generic practice
Need more support? Our support team is available 24/7 through:
Email: support@myvega.ai
