MAE4120 ¨C Item Response Theory

Course content

In this course you will learn the core concepts and techniques of item response theory (IRT) which underlie current test design strategies, psychometric analyses, and evaluation of assessment instruments.

The course covers the following five key topics

1. Item Characteristic Curves
2. Item & Test Information
3. Item fit & Person fit
4. Item Banking: Scaling and Linking
5. Multidimensional IRT

Learning outcome

Knowledge

• demonstrate an understanding of the basic principles and models within Item Response Theory (IRT)
• understand how IRT is used in education and psychology to conduct individual-level and population-level inference
• recognize the differences between classical and IRT test design approaches

Skills

• conduct IRT analyses to evaluate assessments and construct scales
• fit IRT models to test data using the open source statistical software environment R

Competencies

• outline a research program that can support the development of an assessment within an IRT framework
• evaluate the appropriateness of assessments for their intended purpose by utilizing IRT techniques and tools

Admission to the course

Students who are admitted to study programmes at UiO must each semester register for courses and exams in Studentweb.

If you are not already enrolled as a student at UiO, please see our information about?admission requirements and procedures.

This course is a compulsory course in the master's programme in Assessment, Measurement and Evaluation. All students enrolled in the master's programme have equal access to the course. Qualified exchange students or students from other master's programmes at UiO may be given admission based on capacity.?

Contact us if you want to apply for the course. If you are unsure of whether or not you have sufficient prior knowledge, please send us documentation of the previous relevant courses you have taken.?

PhD candidates can apply for the PhD version of the course: UV9293 - Item Response Theory

Recommended previous knowledge

Having completed MAE4000 Data Science or equivalent.?If you are unsure of whether your prior knowledge is sufficient, please contact studentinfo@cemo.uio.no

Overlapping courses

• 5 credits overlap with UV9293 ¨C Item Response Theory.

Teaching

This course combines lectures, seminars and computer labs with data analysis tasks in statistical software environments.

Obligatory course components:

• completion of two written assignments
• participation in the two seminars

Examination

The exam consists of an individual written assignment covering the course contents.

The assignment should be between 2500 and 3500 words long, not including bibliography and appendices.

Students are to submit a one-page written summary of their chosen topic and present it in one of the obligatory seminars. Written and verbal feedback will be given.?

Previous given exams and grading guides

Language of examination

The examination text is given in English, and you submit your response in English.

Grading scale

Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.

More about examinations at UiO

• Use of sources and citations
• Special exam arrangements due to individual needs
• Withdrawal from an exam
• Illness at exams / postponed exams
• Explanation of grades and appeals
• Resitting an exam
• Cheating/attempted cheating

You will find further guides and resources at the web page on examinations at UiO.