Gamification in assessment and psychometrics presents new opportunities for ways to improve the quality of exams. While the majority of adults perceive games with caution because of their detrimental effect on youngsters’ minds causing addiction, they can be extremely beneficial for learning and assessment if employed thoughtfully. Gamification does not only provide learners with multiple […]
Meta-analysis is a research process of collating data from multiple independent but similar scientific studies in order to identify common trends and findings by means of statistical methods. To put it simply, it is a method where you can accumulate all of your research findings and analyze them statistically. It is often used in psychometrics […]
Test validation is the process of verifying whether the specific requirements to test development stages are fulfilled or not, based on solid evidence. In particular, test validation is an ongoing process of developing an argument that a specific test, its score interpretation or use is valid. The interpretation and use of testing data should be […]
Maximum Likelihood Estimation (MLE) is an approach to estimating parameters for a model. It is one of the core aspects of Item Response Theory (IRT), especially to estimate item parameters (analyze questions) and estimate person parameters (scoring). This article will provide an introduction to the concepts of MLE. Content History behind Maximum Likelihood Estimation Definition […]
Multidimensional item response theory (MIRT) has been developing from its Factor Analytic and unidimensional item response theory (IRT) roots. This development has led to an increased emphasis on precise modeling of item-examinee interaction and a decreased emphasis on data reduction and simplification. MIRT represents a broad family of probabilistic models designed to portray an examinee’s […]
The item pseudo-guessing parameter is one of the three item parameters estimated under item response theory (IRT): discrimination a, difficulty b, and pseudo-guessing c. The parameter that is utilized only in the 3PL model is the pseudo-guessing parameter c. It represents a lower asymptote for the probability of an examinee responding correctly to an item. […]
The item discrimination parameter a is an index of item performance within the paradigm of item response theory (IRT). There are three item parameters estimated with IRT: the discrimination a, the difficulty b, and the pseudo-guessing parameter c. The item parameter that is utilized in two IRT models, 2PL and 3PL, is the IRT item […]
The item difficulty parameter from item response theory (IRT) is both a shape parameter of the item response function (IRF) but also an important way to evaluate the performance of an item in a test. Item Parameters and Models in IRT There are three item parameters estimated under dichotomous IRT: the item difficulty (b), the […]
The One Parameter Logistic Model (OPLM or 1PL or IRT 1PL) is one of the three main dichotomous models in the Item Response Theory (IRT) framework. The OPLM combines mathematical properties of the Rasch model with the flexibility of the Two Parameter Logistic Model (2PL or IRT 2PL). In the OPLM, difficulty parameters, b, are […]
The borderline group method of standard setting is one of the most common approaches to establishing a cutscore for an exam. In comparison with the item-centered standard setting methods such as modified-Angoff, Nedelsky, and Ebel, there are two well-known examinee-centered methods (Jaeger, 1989), the contrasting groups method and the borderline group method (Livingston & Zieky, 1989). […]
