Classical test theory is regarded as the “true score theory.” The theory starts from the assumption that systematic effects between responses of examinees are due only to variation in ability of interest. Another branch of psychometric theory is the item response theory (IRT).
This approach to testing based on item analysis considers the chance of getting particular items right or wrong. In this approach,each item on a test has its own item characteristic curve that describes the probability of getting each particular item right or wrong given the ability of the test takers (Kaplan & Saccuzzo, 1997)
How is it used? (environment, target groups, premises, facilities, etc)
The approach is indicated o be used with a broad spectrum of audiences as it provides quantitative and qualitative results based on the dynamic of an individual or a group.
When, where and by whom was it created?
Georg Rasch developed an analytical model of the item response theory (IRT) in the 1960s commonly called 1PL (one parameter logistic) (Olsen, 2003). This mathematical model was later popularized by Benjamin Wright in the United States (Linacre, 2011). With raw data in the form of dichotomous data (in the form of right and wrong) that indicate the student’s abilities, Rasch formulates this into a mathematical model that connects students and item interchangeably trough an equal interval scale (Sumintono & Widhiarso, 2015).