Background: The study focuses on the need to optimise assessment scales for support needs in individuals with intellectual and developmental disabilities. Current scales are often lengthy and redundant, leading to exhaustion and response burden. The goal is to use machine learning techniques, specifically item-reduction methods and selection…

Presents minimization and maximization models for parallel test construction under constraints. The minimization model constructs weakly and strongly parallel tests of minimum length, while the maximization model constructs weakly and strongly parallel tests with maximum test reliability. (Author/SLD)

This paper presents an algorithm for determining the number of items to measure each objective in a criterion-referenced test when testing time is fixed and when the objectives vary in their levels of importance, reliability, and validity. Results of four special applications of the algorithm are presented. (BS)

Previous person-fit research is extended through explication of an unexplored model for generating aberrant response patterns. The proposed model is then implemented to investigate the influence of test properties on the aberrancy detection power of a person-fit statistic. Difficulties of aberrancy detection are discussed. (SLD)

The problem of determining optimal test lengths with fixed total testing time has proved to be a difficult one for criterion-referenced test developers. An algorithm is needed which can be used by test developers to allocate available testing time to maximize the validity of their total criterion-referenced tests or testing programs. To be…