Creating a Mock Test Series

Overview

A mock test series is a named bundle of individual tests, tagged with an examType. Each test is a regular Tuition.in test (you create them in the test editor) added to the series via MockTestSeriesItem rows that set the order.

Series can be isPublic: true (listed in the marketplace) or false (invite-only via direct link). Pricing is one-time per series.

Creating the series shell

1. Go to Tutor dashboard → Mock series → New series.
2. Fill in title (e.g. "JEE Main 2026 — Full-Length Set of 12") and examType (required — see below).
3. Add a description and cover image.
4. Set isPublic and priceInr (0 for free).
5. Click Create.

Supported exam types

These are the exam types currently recognised — they flow through to the rank predictor and per-exam max-score table:

• JEE_MAIN
• JEE_ADV
• NEET
• CAT
• UPSC
• CUET
• GATE
• CLAT

Need an exam type that isn't here? Open a ticket — adding one is a config change.

Adding tests to the series

1. Create the underlying tests first in Tutor dashboard → Tests → New test. Use the exam-matched template (JEE has 75 questions across 3 sections, NEET has 200, etc.).
2. Open the series and click Add test. Pick from your own existing tests.
3. Set order — students see tests in this order on the series page.

Publishing

New series default to isPublic: true and isActive: true. They appear immediately in the marketplace once they have at least one test. Set isActive: false to take a series offline temporarily (e.g. mid-edit).

How the rank is computed

When a student submits any mock in your series:

1. Their attempt is graded (auto-graded for MCQ; AI-graded for subjective).
2. A nationalRankSnapshot is computed: their position among all attempts on that specific test.
3. The snapshot records totalParticipants at that moment, so the rank predictor can map percentile → rank later.

The more students attempt your tests, the more accurate the percentile and rank become for everyone.

Analytics for the creator

On the series page you see:

• Total participants per test.
• Score distribution histogram per test.
• Average percentile of returning students attempt-over-attempt — a real signal of whether your tests are pedagogically useful.
• Revenue per series (if paid).

Each test inside also surfaces per-question accuracy — questions with abnormally high or low accuracy are flagged for review.