Random item effects item response theory (IRT) models, which treat both person and item effects as random, have received much attention for more than a decade. The random item effects approach has several advantages in many practical settings. The present study introduced an explanatory multidimensional random item effects rating scale model. The…

The test view is on the Duolingo English Test (DET), an alternative online English proficiency test with a machine-driven characteristic. The review covers essential information of the DET such as test purpose, usage, score-mapping with CEFR scale, price, and publisher. Meanwhile, the test usefulness is discussed with focuses on reliability,…

In open and higher education, digital technologies are increasingly used to enable flexible learning pathways and unbundle programs into separate courses. Whereas technologies have been praised for enhancing the flexibility of curricula, the implications of going digital have yet to be fully explored in curriculum studies. This article aims to…

The concept of sequential estimation is introduced in multidimensional scaling. The sequential estimation method developed in this paper refers to continually updating estimates of a configuration as new observations are added. Using artificial data, the performance of this sequential method is illustrated. (Author/JKS)

Describes a Rasch rating scale analysis of a multi-occasion evaluation that produces confusing results when subjected to separate calibrations. Applies a correction algorithm developed by B. Wright (1996) to show how the Wright algorithm can reduce misfit to the Rasch rating scale model as well as changing the interpretation of change. (SLD)

A general approach for analyzing rating data with latent class models is described, paralleling rating models in the framework of latent trait theory. A general rating model and a two-parameter model with location and dispersion parameters are derived and illustrated. (Author/SLD)

A statistical method for testing the agreement between a judge's assessment of an object or subject and a known standard is developed and shown to be superior to two other methods which appear in the literature. (Author/JKS)

The partial credit model with a varying slope parameter is developed and called the generalized partial credit model (GPCM). Analysis results for simulated data by this and other polytomous item-response models demonstrate that the rating formulation of the GPCM is adaptable to the analysis of polytomous item responses. (SLD)

This study examines the application of the marginal maximum likelihood (MML) EM algorithm to the parameter estimation problem of the three-parameter normal ogive and logistic polychotomous item response models. A three-parameter normal ogive model, the Graded Response model, has been developed on the basis of Samejima's two-parameter graded…

Describes an automated scoring algorithm for a computer-based simulation examination of physicians' patient-management skills. Results with 280 medical students show that scores produced using this algorithm are highly correlated to actual clinician ratings. Scores were also effective in discriminating between case performance judged passing or…

Performance rating systems frequently use multiple raters in order to improve the reliability of ratings. However, unless all candidates are rated by the same raters, some candidates will be at an unfair advantage or disadvantage solely because they were rated by more stringent or lenient raters. To obtain fair and accurate evaluations of…

The present study devised a computerized assignment-by-preference algorithm for a ninth-grade exploratory curriculum. The problem addressed was one of maximally mapping all students into 8 of 12 vocational programs in terms of their preferences for studying each of the programs and the assignment restrictions established by the school. To minimize…