Review: Item Response Theory Models Analysis | ||
| مجلة العلوم التجارية والبيئية | ||
| Volume 4, Issue 3, July 2025, Pages 162-179 PDF (548.43 K) | ||
| Document Type: مراجعة أدبية | ||
| DOI: 10.21608/jcese.2025.376986.1109 | ||
| Authors | ||
| Ahmed A. Elsheikh; Heba M Saidelahl* | ||
| Faculty of Graduate Studies for Statistical Research, Giza 12613, Egypt | ||
| Abstract | ||
| This review paper provides a comprehensive overview of Item Response Theory (IRT), its fundamental concepts in the 1940s, major models, practical applications, and recent developments, and its current status as a cornerstone of modern analysis across different fields. The evolution of IRT represents a remarkable journey in psychometric advancement, characterized by continuous theoretical refinement and expanding practical applications. In recent years, IRT has established itself as an indispensable framework in psychometrics, educational testing, and human behavior assessment. Also, significant methodological developments in IRT have been witnessed, particularly in parameter estimation techniques. The integration of artificial intelligence approaches has revolutionized parameter estimation methods, offering new possibilities for model optimization and implementation. This paper traces the historical development of IRT. We examine the theoretical evolution, computational advancements, and implementation challenges that have shaped IRT over the decades, while highlighting recent developments in methodology and applications. | ||
| Keywords | ||
| Item Response Theory; Item Response models; Rasch model; latent class; Mixture Item Response; Dynamic Item Response | ||
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