# New Item Analysis Report in Questionmark Analytics: The Summary Page

Posted by Jim Farrell

When I visit customers, I find that the Item Analysis report is one of the most useful reporting capabilities of Questionmark Perception. By using it, you can tell which questions are effective and which are not – and if you don’t use it, you are “running blind:” You hope your questions are good, but do not really know if they are.

Our most recent update to Questionmark OnDemand provides a new classical test theory item analysis report — one of several reports now available in Questionmark Analytics. This report supports all question types commonly used on quizzes, tests and exams and is fully scalable for application to large pool of participants. Let’s take a look at the report!

This is the summary page. The graph show the performance of questions in relation to one another in terms of their difficulty (p-value) and discrimination (item-total correlation). The p-value is a number from 0 to 1, and represents the proportion of people who correctly answer the question. So a question with p-value of 0.5 means that half the participants get it right and half wrong. And a question with p-value of 0.9 means that 90% of respondents get it right.

A rule of thumb is that it’s often useful to use questions with p-value that are reasonably close to the pass score of the assessment. For instance, if your pass score is 60%, then questions with a p-value of around 0.6 will give you good information about your participants. However a very high or very low p-value does not give you much information about a person who answers it. If the purpose of the test is to measure someone’s knowledge or skills, then you will get more information from a question with medium p-value. Using the item analysis report is an easy way to get p-values.

The other key statistic in the item analysis report is the item-total correlation discrimination, which shows the correlation between the question score and the assessment score. Higher positive correlation values indicate that participants who obtain high question scores also obtain high assessment scores. Conversely, participants who obtain low question scores also obtain low assessment scores. Low values for questions here could indicate unhelpful questions and are worth drilling down on.

Below the graph is a table that shows some high-level details of each question composing the assessment. The table can be sorted by any of the columns. By clicking on a row/question the user goes to the detail page, which we will discuss in our next blog post on this subject.

If you are running a medium or high stakes assessment that has to be legally defensible, then you cannot confirm that the assessment is valid if you are not running item analysis. And for all quizzes, tests and exams, running an item analysis report will give you information to help you make the assessment better.