Identifying potentially flawed items in the context of small sample IRT analysis

Fotaris, Panagiotis ORCID: https://orcid.org/0000-0001-7757-7746, Mastoras, Theodoros, Mavridis, Ioannis and Manitsaris, Athanasios (2011) Identifying potentially flawed items in the context of small sample IRT analysis. International Journal on Advances in Intelligent Systems, 4 (1&2). pp. 31-42. ISSN 1942-2679

[thumbnail of intsys_v4_n12_2011_4.pdf]
Preview
PDF
intsys_v4_n12_2011_4.pdf - Published Version

Download (1MB) | Preview

Abstract

Although Classical Test Theory has been used by the measurement community for almost a century, Item Response Theory has become commonplace for educational assessment development, evaluation and refinement in recent decades. Its potential for improving test items as well as eliminating the ambiguous or misleading ones is substantial. However, in order to estimate its parameters and produce reliable results, IRT requires a large sample size of examinees, thus limiting its use to large-scale testing programs. Nevertheless, the accuracy of parameter estimates becomes of lesser importance when trying to detect items whose parameters exceed a threshold value. Under this consideration, the present study investigates the application of IRT-based assessment evaluation to small sample sizes through a series of simulations. Additionally, it introduces a set of quality indices, which exhibit the success rate of identifying potentially flawed items in a way that test developers without a significant statistical background can easily comprehend and utilize.

Item Type: Article
Additional Information: © 2011 The Authors. Published under agreement with IARIA.
Keywords: item response theory, computer aided assessment, item quality, educational measurement, learning assessment, evaluation, e-learning, psychometrics
Subjects: Computing
Depositing User: Vani Aul
Date Deposited: 07 Dec 2013 14:35
Last Modified: 04 Nov 2024 12:22
URI: https://repository.uwl.ac.uk/id/eprint/446

Downloads

Downloads per month over past year

Actions (login required)

View Item View Item

Menu