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Digital Module 08: Foundations of Operational Item Analysis https://ncme.elevate.commpartners.com
Author(s) -
Yoo Hanwook [Henry],
Hambleton Ronald K.
Publication year - 2019
Publication title -
educational measurement: issues and practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.158
H-Index - 52
eISSN - 1745-3992
pISSN - 0731-1745
DOI - 10.1111/emip.12289
Subject(s) - item response theory , computer science , glossary , test (biology) , sample (material) , selection (genetic algorithm) , classical test theory , information retrieval , data mining , data science , artificial intelligence , statistics , mathematics , psychometrics , paleontology , philosophy , linguistics , chemistry , chromatography , biology
Item analysis is an integral part of operational test development and is typically conducted within two popular statistical frameworks: classical test theory (CTT) and item response theory (IRT). In this digital ITEMS module, Hanwook Yoo and Ronald K. Hambleton provide an accessible overview of operational item analysis approaches within these frameworks. They review the different stages of test development and associated item analyses to identify poorly performing items and effective item selection. Moreover, they walk through the computational and interpretational steps for CTT‐ and IRT‐based evaluation statistics using simulated data examples and review various graphical displays such as distractor response curves, item characteristic curves, and item information curves. The digital module contains sample data, Excel sheets with various templates and examples, diagnostic quiz questions, data‐based activities, curated resources, and a glossary.