> For the complete documentation index, see [llms.txt](https://docs.myvega.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.myvega.ai/operations/analytics-and-report/user-analytics.md). # User Analytics Think of **User Analytics** as your private tutor’s notebook for every student. It helps you understand how one specific learner is performing — what they’ve mastered, where they’re struggling, how they manage their time, and even what kind of errors they keep making. If Batch Analytics is about the **group**, User Analytics is about the **individual story**.
*** ### Why Use It? Let’s say your student, Dhiren, took a few diagnostic and full-length tests, and now you want to know: * Is he improving? * What are his weakest areas? * Is he solving too slowly or too fast? * Is he ready for the real SAT? Instead of guessing, User Analytics gives you a **complete learning health check**. *** ### Where to Find It? * Go to **Operations > Users** * Click on the **“View”** button next to the student’s name You’ll land on the User Analytics dashboard, like this:
*** ### What You’ll See (Overview) The User Analytics page is split into different tabs for different types of test activity: * **Diagnostic** – Quick assessments to understand initial level * **Play** – Practice sessions and mini-modules * **Full Length** – Full mock exams like SAT, GRE, etc. *** #### Score Analysis At the very top, you’ll see a bar or line graph showing the **predicted SAT scores** across different sections (Reading/Writing, Math, and Overall). For example, Dhiren’s Diagnostic Test 1 result looks like this: | Section | Score | | ----------------- | ----- | | Reading & Writing | 640 | | Math | 260 | | Overall | 900 | This gives you a **quick sense of test readiness**. > 💡 *If Math is lagging behind but Reading is strong, you know where to focus your tutoring time.* *** #### Mastery Score Breakdown (Per Topic) Below the score graph is a topic-by-topic breakdown of how the student did in different subjects. Here’s an example from the Reading section:
Each topic has a: * **% Correct** * **Mastery Level Label** (Novice, Intermediate, Advanced, Expert) This helps you know: * Which specific topic (like “Words in Context” or “Central Idea”) the student needs help with. * What’s working well and can be reinforced. *** #### Strengths and Weaknesses This section is **AI-generated** based on recent tests. It shows: * **Top 3 Areas of Strength** — what the student is doing really well in * **Top 3 Areas of Weakness** — what they struggle with most
> 📌 *This list updates automatically as the student progresses.* For example: * Dhiren is strong in “Linear Functions” and “Data Analysis” * He’s weak in “Linear Equations” and “Trigonometry” *** #### Test Results Summary Every test the student has taken is listed at the bottom with: * Test Name * Date * Projected SAT Score * Review Link
Clicking **“Review Test”** lets you deep dive into every question, correct answer, and solution (we’ll cover that in next part). ### Time Management, Accuracy, and Deep Mastery Insights Once you've seen the student's overall score and strengths/weaknesses, the next step is understanding **how** they got those results. This is where VEGA AI’s User Analytics goes deeper — analyzing **time spent**, **accuracy**, and **topic-level mastery** across different tests and question types.
*** #### Time Management > *“Are they solving too slowly? Are they rushing through tricky questions?”* The **Time Management** section shows how much time the student spends per topic — and compares it with their peers. This helps you spot pacing issues. Example:
Here’s what you’ll see: * A bar graph comparing **Your Average Time** (blue) vs **Peers' Average Time** (grey) * A summary sentence like:\ \&#xNAN;*“You took 53 secs on average to solve a Reading question.”* * AI-generated **Top 3 Time Management Weaknesses**, e.g. * Inferences * Text Structure * Cross Text Connections > 💡 *If the student spends too long on easy topics or rushes through hard ones, this section will tell you.* *** #### Deeper Topic Mastery Score (LQ Mastery) This is the **heart** of User Analytics. It tells you how well the student understands each topic — across different test attempts. Example:
Each topic is tagged with a **mastery label**: | Label | Meaning | | ------------ | ---------------------------- | | Novice | Just getting started | | Intermediate | Basic understanding | | Advanced | Confident in the topic | | Expert | Very strong mastery | | Master | Consistently perfect answers | You’ll also get **AI-generated weaknesses** based on this score. > Use this to assign revision material, easier practice sets, or 1-on-1 help sessions. *** #### Accuracy Analysis While mastery shows *understanding*, **accuracy** shows *performance*. Example:
* You’ll see the student’s **accuracy % per topic** * A visual bar graph helps you compare across subjects * AI suggests the **Top 3 Accuracy Weaknesses** This tells you: * Are they making consistent mistakes in certain areas? * Are they overconfident in topics they haven’t mastered? > 🔍 *If a topic shows “Advanced” in mastery but has poor accuracy, it might be a guessing issue.* *** #### ✅ Result Table with Win/Loss At the end of the analytics tab, you’ll see a **detailed breakdown of test questions** and how the student performed. Example:
| Topic | Date | Mastery | Win/Loss | | ---------------- | ------ | ------- | -------- | | Words in Context | Aug 18 | Expert | ✅ WON | | Text Structure | Aug 18 | Novice | ❌ LOST | > Use this table to zoom in and see what’s working and what needs fixing. ### Reviewing Questions, Understanding Mistakes & Taking Action Once you've seen the scores, pacing, and accuracy of a student, the final step is **reviewing their actual answers**. This is where learning becomes personal — because now you’re looking at what they clicked, what they misunderstood, and how you can help them improve. Let’s walk through how to do this.
*** #### Reviewing Test Questions To review a student’s test attempt: 1. Scroll to the **Test Results** section 2. Click **“Review Test”** next to the test you want to open
You’ll land on a screen like this:
Each test is broken into modules (like Reading Module 1, Math Module 2), with: * Difficulty level (Mixed / Hard) * Number of correct answers * Total questions Click **“Review Module”** to go deeper. *** #### Question-by-Question Breakdown When you review an individual question, you’ll see:
* The **full question text** * The **correct answer** (in green) * The **student’s selected answer** (in red if incorrect) * A clear, readable **solution explanation** * Time taken to solve that question This allows you to: * Understand where the student’s logic went wrong * Identify if it’s a reading mistake, concept confusion, or poor elimination * Train them on how to approach similar questions next time > *This is the most actionable part — because it shows their thought process.* *** #### Full-Length Test Analytics Report When students complete a full-length test, VEGA AI generates a **complete summary report**. Example:
What you’ll see: * Overall predicted SAT score + breakdown by section * Mastery level by topic * Accuracy graph * Time management analysis * Cross-topic scores and sub-scores * ACT conversion (for US colleges)
At the bottom is a **visual grid** of question performance — blue for correct, red for wrong — giving you a bird’s-eye view of strengths and mistakes.
*** #### Turning Insights Into Action Now that you know what the student got wrong and why, here’s how you can use that data: | What You See | What It Means | What You Can Do | | ------------------------------------- | ----------------------------- | -------------------------------------------- | | High mastery but low accuracy | Careless mistakes or guessing | Teach double-checking strategies | | Low time on tough questions | Rushing or skipping | Train on time balance & test pacing | | Weakness in one topic (e.g. Geometry) | Conceptual gaps | Assign easier questions / revision resources | | Strong topic (e.g. Words in Context) | Confidence area | Challenge with harder questions | | Same error repeated | Misconception | Re-teach concept using analogies/examples | *** ### Summary: Why This Matters User Analytics is like your **co-pilot tutor**. It doesn’t just show marks — it helps you understand **why** a student is struggling and **how** to fix it. Whether you're: * Running a coaching class * Helping students prepare for SAT/GRE * Offering 1-on-1 support …it helps you personalize your teaching and boost results. *** For further help, reach out to our support team at 📧 **** — we’re available 24/7. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.myvega.ai/operations/analytics-and-report/user-analytics.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.