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Guher Gorgun; Okan Bulut – Educational Measurement: Issues and Practice, 2025
Automatic item generation may supply many items instantly and efficiently to assessment and learning environments. Yet, the evaluation of item quality persists to be a bottleneck for deploying generated items in learning and assessment settings. In this study, we investigated the utility of using large-language models, specifically Llama 3-8B, for…
Descriptors: Artificial Intelligence, Quality Control, Technology Uses in Education, Automation
Carragher, Natacha; Templin, Jonathan; Jones, Phillip; Shulruf, Boaz; Velan, Gary – Educational Measurement: Issues and Practice, 2019
In this ITEMS module, we provide a didactic overview of the specification, estimation, evaluation, and interpretation steps for diagnostic measurement/classification models (DCMs), which are a promising psychometric modeling approach. These models can provide detailed skill- or attribute-specific feedback to respondents along multiple latent…
Descriptors: Measurement, Classification, Models, Check Lists
Allalouf, Avi; Gutentag, Tony; Baumer, Michal – Educational Measurement: Issues and Practice, 2017
Quality control (QC) in testing is paramount. QC procedures for tests can be divided into two types. The first type, one that has been well researched, is QC for tests administered to large population groups on few administration dates using a small set of test forms (e.g., large-scale assessment). The second type is QC for tests, usually…
Descriptors: Quality Control, Scoring, Computer Assisted Testing, Error Patterns