UV9291 – Principles of Measurement

Schedule, syllabus and examination date

Course content

In this course you get acquainted with the foundational theories and concepts in measurement.

The course covers the following overarching topics:

  1. Fundamental issues in measurement
  2. Technical and statistical foundations in educational measurement
  3. Reliability
  4. Validity
  5. Testing applications and interpretations

UV9291 Principles of Measurement is the PhD-level version of MAE4011 Principles of Measurement, a compulsory course in the master's program, Assessment Measurement and Evaluation. The content, schedule and reading list for UV9291 Principles of Measurement are the same as for MAE4011 Principles of Measurement.

Learning outcome

Knowledge:

  • Understand the basic principles of measurement, particularly as they pertain to classical test theory, including reliability and validity.
  • Understand why and what we measure in education and related social science.
  • Problematize classical and contemporary issues around educational measurement, including the metric of measurement and sources of error.

Skills:

  • Use classical test theory techniques to evaluate the quality of test data and to produce basic scale scores for examinees and survey respondents.
  • Interpret test scores.

Competencies:

  • Apply the basic principles and procedures of statistics and measurement theory to educational and psychological measurement.
  • Incorporate the evaluation of the adequacy of reliability and validity evidence into decisions regarding the use of educational and psychological measurements.

Admission to the course

There is a limited number of seats due to joint teaching with the master’s level version of the course.

PhD candidates at the Faculty of Educational Sciences will be given priority, but it is also possible for others to apply for the course.

The deadline for registration is on the corresponding semester page for the course. 

Candidates admitted to a PhD-program at the Faculty of Educational Sciences (UV) can apply in StudentWeb.

Other applicants can apply by filling out and sending in a electronic registration form, which is found on the corresponding semester page for the course. 

Formal prerequisite knowledge

Basic knowledge of R is required.

Overlapping courses

Teaching

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

The course has joint teaching with the master course MAE4011 Principles of Measurement.

Lectures are held by Associate Professor Esther Ulitzsch.

Obligatory course components:

  • 80% attendance requirement for the lectures
  • Participation in seminars and computer labs
  • Completion of three individual written assignments

Schedule and literature: Please see the applicable semester page for the course. 

Examination

To obtain 5 credits, 80 % attendance, successful completion of the mandatory assignments and paper is required.

A more specific description of the mandatory assignments and paper will be given at the course.

Language of examination

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

Grading scale

Grades are awarded on a pass/fail scale. Read more about the grading system.

More about examinations at UiO

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

Last updated from FS (Common Student System) May 24, 2024 11:16:24 AM

Facts about this course

Level
PhD
Credits
5
Teaching
Autumn
Examination
Autumn
Teaching language
English