HEV9007 Introduction to Rasch Measurement

    • Number of credits
      5
    • Teaching semester
      2026 Spring
    • Language of instruction
      Norwegian/English
    • Campus
      Elverum
    • Required prerequisite knowledge

      Proficiency in basic statistics is recommended. 

Course content

This course is designed to introduce participants to Rasch analysis and the principles of objective measurement. 

  • Properties of the Rasch model 

  • Local independence and response dependency 

  • Fit to the Rasch model 

  • Targeting of scales/instruments 

  • Assessment of response categories 

  • Invariance 

  • Reliability 

Learning Outcome

The course aims to provide an understanding of the principles of measuring latent traits, such as measuring human abilities, performance, attitudes, and opinions.

Upon successful completion of the course, the student will have achieved the following learning outcomes: 

Knowledge

After completing the course, the candidate: 

  • has knowledge of the main principles of modern and classical test theory. 

  • has in-depth knowledge of the properties of the Rasch model. 

  • has in-depth knowledge of the requirements for measuring latent traits. 

  • can assess the appropriateness and application of Rasch analysis in research. 

Skills

After completing the course, the candidate can: 

  • explain the principles of Rasch analysis. 

  • apply various tests to assess the quality of questions/statements included in scales/instruments for measuring latent traits such as performance, knowledge, and attitudes. 

  • conduct Rasch analysis using appropriate software. 

General competence

After completing the course, the candidate can: 

  • evaluate the appropriateness of applying Rasch analyses to assess the psychometric properties of scales/instruments. 

  • justify the choice of analyses to assess the psychometric properties of scales/instruments. 

  • critically evaluate the implications of results from Rasch analyses for the psychometric properties of scales/instruments. 

  • critically assess the validity and reliability of one's own and others' research. 

  • participate in professional debates on the psychometric properties of scales/instruments. 

Teaching and working methods

The course consists of a combination of lectures and seminars. Candidates will have the opportunity to bring and analyse their own data. The software RUMM2030+ is used in the teaching, and candidates will receive a limited license version of the software. 

Examples: 

  • Lectures 

  • Seminars 

  • Student presentations 

  • Self-study 

  • Assignment writing 

  • Guidance 

 

Language of Instruction: 

The instruction is primarily conducted in Scandinavian languages and English, depending on the lecturer's native language. If there are participants who do not use Scandinavian languages, English will be used as the course language. 

Required coursework

  • 80% attendance in class. 

  • presentation of a draft article in the seminar. 

  • peer review of article draft among fellow students. 

Form of assessment

ndividual home examination of 3,500 words structured as a scientific article. The exam assignment should be submitted 3 weeks after the end of the course. The exam assignment is assessed as pass/fail. 

The exam assignment can be written in English or Norwegian. 

Assessments
Form of assessmentGrading scaleGroupingDuration of assessmentSupport materialsProportionComment
Home exam
Passed - not passed

Reading list

Faculty
Faculty of Social and Health Sciences