What gets generated:
Sheet 1: Raw Data - all students x graded tasks, grouped by category
Sheet 2: Descriptive Stats - count, avg, median, min, max, SD
Sheet 3: Correlation Matrix - how category averages relate
Sheet 4: Linear Regression - predict Attainment from Major Average
Sheet 5: AI Extension - ready-to-use prompts for deeper analysis
οΌ New Chart
β Ώ
Grade Distribution
All students by average score band
β Ώ
Cross-Class Struggle
Students below threshold in N classes simultaneously
β Ώ
Subject Averages
Mean score per subject
β Ώ
Class Performance
Average score per class, sorted ascending
β Ώ
Grade Letter Distribution
Percentage of students achieving each Cambridge grade β select classes from the list
0 selected
Groups
Select classes from the list to see grade distributions
β Ώ
Predicted vs Actual Exam Results
Enter Cambridge exam results to measure variance between internal predictions and actual grades
Cambridge imports:
None yet
Select a class to enter or view exam results
Student Results
Variance Analysis
β Ώ
Students at Risk Across Classes
Identify whether low grades are isolated or a cross-subject trend
80%
Hidden:
Search a student by name, or pick a class and select a student, to open their tracking profile.