Instead of recording only the final percentage, track performance by question type.

For mathematics, categories might include:

Arithmetic | Fractions | Geometry | Data | Word Problems | Reasoning

For English:

Vocabulary | Literal comprehension | Inference | Main idea | Author purpose | Grammar

Then compare results over time.

Suppose your overall score remains around 75%, but your inference accuracy improves from 55% to 80%. That is meaningful progress even if the overall percentage has not changed dramatically.

Timing data is equally useful.

Track:

• Questions answered

• Questions skipped

• Incorrect answers

• Time spent

• Slow correct answers

Look for recurring patterns.

If you consistently lose marks on multi-step mathematics questions, that is more actionable than simply knowing your total score.

Create a simple weekly dashboard:

Skill | Week 1 | Week 2 | Week 3 | Current status

Then classify each skill as:

Improving | Stable | Needs attention

The most valuable part of analytics is the action that follows.

If inference is weak, increase inference practice.

If accuracy drops under time pressure, introduce timed sessions.

If vocabulary is strong but comprehension remains weak, focus on interpretation rather than memorising more words.

This transforms practice testing from a scoreboard into a personal learning system.

The objective is not to chase a perfect score every week. It is to identify whether your underlying skills are becoming stronger, faster and more consistent.