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Direct linkFélix González-Carrasco; Felipe Espinosa Parra; Izaskun Álvarez-Aguado; Sebastián Ponce Olguín; Vanessa Vega Córdova; Miguel Roselló-Peñaloza – British Journal of Learning Disabilities, 2025
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…
Descriptors: Artificial Intelligence, Intellectual Disability, Developmental Disabilities, Individual Needs
Yi-Jui I. Chen; Yi-Jhen Wu; Yi-Hsin Chen; Robin Irey – Journal of Psychoeducational Assessment, 2025
A short form of the 60-item computer-based orthographic processing assessment (long-form COPA or COPA-LF) was developed. The COPA-LF consists of five skills, including rapid perception, access, differentiation, correction, and arrangement. Thirty items from the COPA-LF were selected for the short-form COPA (COPA-SF) based on cognitive diagnostic…
Descriptors: Computer Assisted Testing, Test Length, Test Validity, Orthographic Symbols
Ying Xu; Xiaodong Li; Jin Chen – Language Testing, 2025
This article provides a detailed review of the Computer-based English Listening Speaking Test (CELST) used in Guangdong, China, as part of the National Matriculation English Test (NMET) to assess students' English proficiency. The CELST measures listening and speaking skills as outlined in the "English Curriculum for Senior Middle…
Descriptors: Computer Assisted Testing, English (Second Language), Language Tests, Listening Comprehension Tests
