Results (Subject Analytics)
OMR results rolled up by subject, chapter and topic — overview, student progress, chapter breakdown and a topic heatmap.
What this screen shows
The Results tab for OMR is the Subject Analytics view. Bubble-sheet scores map straight onto your taxonomy — subject → chapter → topic — so a high-volume mock becomes a heat map of strengths and gaps. A highlights strip across the top calls out your strongest subject, the one that needs attention and the most active by attempts, and a monthly performance trend tracks class average and pass rate over time. You pick a board / grade / subject, then move across four sub-tabs: Overview, Student Progress, Chapter Breakdown and Topic Heatmap. The screen resolves to your role — a teacher sees their own subjects (course-wide), an org admin their whole organization, and a superadmin the entire platform (system-wide).
This Subject Analytics screen is shared with Answer Sheet (same route, /app/subject-analytics). It aggregates results from whichever offline channel produced them, so you get one consistent analytics surface.
Common workflow
Select the board / grade / subject to analyse.
Read the Overview for the headline picture.
Open Topic Heatmap to find weak areas, and Chapter Breakdown for chapter-level detail.
Use Student Progress to drill into individuals.
Controls on this screen
Choose which subject’s OMR results to analyse.
Strongest subject, needs attention and most active — a three-card headline before you drill in (comparisons appear once more than one subject has activity).
Monthly class average and pass rate over time for the selected subject.
Auto-scopes to your role — teacher (your subjects), org admin (your organization) or superadmin (platform-wide across all organizations).
Headline scores and trends for the selected subject.
Per-student scores and topic mastery over time.
Accuracy and coverage by chapter.
Colour-coded per-topic accuracy across the cohort.
Ranks & percentile
A high-volume OMR mock is exactly the situation where a raw mark is least useful — 214 out of 300 means nothing until you know that 214 put the student in the top 3% of the hall. So when a batch of sheets is evaluated, every result is given a rank and a percentile alongside its score, worked out across everyone who sat that exam. The percentile is the NTA-style figure: the share of candidates who scored at or below you, so the topper sits on exactly 100 and students on the same mark share the same percentile. It is the same arithmetic the online exams use, deliberately — a student who takes a paper mock on Monday and an on-screen mock on Friday can compare the two figures directly, and a teacher reading a mixed cohort is not silently comparing two different scales. Ranks appear in the exam’s own results table and the CSV export; from there the scores flow into these subject analytics and the gradebook like any other result.
On the online exam side the formula is chosen per exam by its Exam Pattern — General, JEE Main, JEE Advanced, NEET or CUET — so a NEET mock is ranked the way NEET ranks, and JEE Advanced shows ranks with no percentile at all, just like the real exam. Those percentiles then follow the result everywhere: the student result page (class histogram, percentile trend, an estimated All-India Rank on JEE Main and NEET), the teacher Leaderboard and cross-exam Overall ranking under Compare & Ranks, the parent dashboard and weekly digest, and the result PDF and email. See the Online Exam → Results article for the full picture.
Ranks are only produced once sheets have been evaluated, and they are recalculated across the whole batch — so a late stack of scans that you upload and evaluate the next morning will shift the earlier students’ positions. Publish ranks after the last sheet is in, not before.