Question Analysis

Item Analysis in Original Course View

Item Analysis provides statistics on overall test performance and on individual test questions. This data helps faculty recognize questions that might not adequately discriminate between students who understand the material and those who do not. Faculty can use this information to improve questions for future tests or to adjust credit on current attempts. Ineffective or misleading question are identified easily, then corrected in the Test Canvas and re-graded automatically.

Item Analysis

Question Analysis in Ultra Course View

Status: Available

Question analysis provides statistics on overall performance, assessment quality, and individual questions. This data helps you recognize questions that might be poor discriminators of student performance. Question analysis is available for assessments with questions, whether those were created as Tests or Assignments. You can run a report before all submissions are in if you want to check the quality of your questions and make changes.

Uses for question analysis:

  • Improve questions for future assessments or to adjust credit on current attempts
  • Discuss assessment results with your class
  • Provide a basis for remedial work
  • Improve classroom instruction

You can run and access a previous question analysis report from these course areas:

  • Course Content page > assessment's menu
  • Assessment page > Question Analysis tab
  • Analytics page > Question Analysis tab
  • Gradebook, list or grid view

Question analysis provides the following statistics:

  • Average score: The score shown is the average score reported for the assessment in the gradebook. The average score can change if more attempts are submitted and graded.
  • Possible questions: The total number of questions in the assessment.
  • Completed attempts: The number of submitted assessments.
  • Average time spent: The average completion time for all submitted attempts.

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Division of IT Service Desk

815-753-8100
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Center for Innovative Teaching and Learning

815-753-0595
citl@niu.edu

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