UV9918V7 - Introduction to Item Response Theory
In Psychology and Educational Research, tests or questionnaires are frequently used to measure individual variables of the test takers. The aim of such measurements lies often in deriving estimates for characteristics that cannot directly be observed. Such entities are also called latent traits. Recently, a family of psychometric models, called Item Response Theory (IRT) models, have become very important when it comes model the connection between the responses given on test or questionnaire items and the standing of the test taker on a latent trait of interest. In Educational Measurement, IRT models are applied, for example, in large-scale assessments of student achievement such as PISA, TIMSS, or PIRLS.
The course covers (a) an introduction into the measurement of individual variables, (b) the foundations of IRT, (c) the most common IRT models, and (d) some applications such as differential item functioning, computerized adaptive testing, and large-scale assessments. The workshop will be a mixture of lectures and hands-on exercises. Participants are expected to bring their own computer with the latest version of the statistical software R, R-studio, and the package TAM installed. Prior knowledge of R is not necessary, however, basic R knowledge would be helpful.
After completing the course students will (a) know when and why IRT models are useful, (b) know the foundations of IRT, and (c) are able to conduct IRT analyses on their own.
PhD candidates at the Faculty of Educational Sciences will be given priority, but it is also possible for others to apply for the course. All applicants must hold at least a Master's degree.
Deadline for registration: May 8, 2018.
Candidates admitted to a PhD-program at the Faculty of Educational Sciences (UV): Apply by Studentweb.
Other applicants: apply through nettskjema.
Maximum number of participants is 25.
Dates: May 22-24, 2018
Time: 9 - 15
Lecturer: Professor Andreas Frey, Friedrich Schiller University Jena (FSU), Germany//CEMO, UiO
The course will span three days. On each day there will be mixture of lectures with discussion parts and hands-on exercises. Active participation is expected. At the third day, participants are invited to work on a larger IRT analysis in groups. The group-specific results will be presented and discussed and form the basis for the written paper.
Participants are expected to bring their own computer with the latest version of the statistical software R, R-studio, and the package TAM installed. Prior knowledge of R is not necessary, however, basic R knowledge would be helpful
de Ayala, R. J. (2009). The theory and practice of item response theory. New York: Guilford. (approx. 250 pages from this book)
To obtain 1 credit, 80 % attendance in the course is required.
To obtain 3 credits, 80 % attendance and a submitted and positively rated paper is required. A more specific description of requirement for the paper will be given at the course.