The overall assessment analytics show the following:

• Highest score
• Lowest score
• Mean score
• Median score
• Mean elapsed time
• Standard Deviation
• Score distribution graph

The individual questions analytics show the following:

• Item Difficulty
• Mean & Median Earned Points
• Discrimination Index
• Total Correlation Coefficient
• Answer Frequency Summary table
• For MCQs, the count of how many times each answer option was selected by students.

When you know which topics students are struggling with, you can target your review time more effectively. Instead of reteaching entire units or guessing what’s unclear, you can use data to identify learning gaps and focus your time there, leading to better outcomes for the class.

Which data to use:
Look at the Item Difficulty and Mean Earned Points for each question. Questions with a low success rate signal concepts that need revisiting or additional practice materials.

Sometimes low scores reflect not a gap in knowledge, but a confusing or poorly aligned question. Refining these ensures your assessments accurately measure learning and builds student confidence in the fairness of your tests.

Which data to use:
Check the Discrimination Index and Total Correlation Coefficient. Negative or low values indicate that students who perform well overall are still missing this question - a sign that it might need rewording or realignment with your learning objectives.

Strong distractors in multiple-choice questions reveal how deeply students understand a concept. Weak or rarely selected options waste valuable assessment time and reduce reliability.

Which data to use:
Review the Answer Frequency Summary for each question. If one option is almost never chosen, consider replacing it with a more plausible alternative to better gauge comprehension.

An effective quiz includes a mix of easy, moderate, and challenging questions that reflect the right level of difficulty for your course. This balance motivates students and provides a clearer picture of learning progress.

Which data to use:
Use the Score Distribution Graph, Standard Deviation, and Item Difficulty to gauge whether your assessments are too easy, too hard, or well-balanced. Adjusting difficulty levels can help create fairer, more meaningful evaluations.

Seeing how performance changes across assessments (or from one semester to the next) helps you understand the impact of your teaching adjustments. You can catch challenges early, and continuously refine your course design to meet the needs of your students.

Which data to use:
Compare Mean Score, Median Score, and Mean Elapsed Time across multiple assessments. Rising scores and consistent timing indicate stronger mastery and better pacing; stagnation may suggest it’s time to revisit certain concepts.

Learning Analytics is now available for all Blended Teaching assessments. Check out our help center article here, and get started today!