User Analytics Dashboard

User performance metrics and question quality proxies. These numbers reflect how users interact with generated quizzes and should be interpreted with caution — they are not ground-truth accuracy measures.

User Performance

Methodology: User performance is a noisy proxy for question quality and should not be interpreted as ground truth. Well-calibrated questions should produce a range of scores centered around 50–70%. Extreme distributions may indicate questions that are too easy or too hard.

Avg. User Score

40.0%

4.0 / 10 questions

Total Quiz Attempts

110

Across all sessions

Avg. Questions / Quiz

10.0

Target: 10 MCQs

Score Distribution

Question Quality Proxy

Methodology: Topic-wise accuracy below 40% may indicate questions that are misaligned with the source material or too difficult. Topic-wise accuracy above 80% may indicate questions that are too easy or contain obvious clues. Question topic distribution shows content diversity.

Topic-wise Accuracy

Question Topic Distribution

Detailed Topic Accuracy

Topic	Total Answers	Correct	Accuracy	Quality Indicator
Programming Languages	52	21	40.4%	Moderate
Algorithmic Thinking	37	8	21.6%	Review Needed
Compilation	37	15	40.5%	Moderate
C++ Program	31	7	22.6%	Review Needed
Introduction to Programming	30	14	46.7%	Moderate
Purpose of Programming	28	11	39.3%	Review Needed
Errors	28	9	32.1%	Review Needed
Programming Language Definition	28	12	42.9%	Moderate
Java language basics	27	9	33.3%	Review Needed
Variables	25	8	32.0%	Review Needed