Discovering the associations between test items in an examination. Issue 1 (3rd September 2018)

• Record Type: Journal Article
• Authors: Dong, Ligang; Tang, Liujun; Liu, Shihuan; Jiang, Xian
• Is Part Of: Expert systems. Volume 36:Issue 1(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-09-03
• Subjects: correlation coefficient -- data mining -- item pairs -- precision teaching; Expert systems (Computer science); 006.33
• DOI: 10.1111/exsy.12331
• Languages: English
• ISSNs: 0266-4720

Abstract

Abstract: An examination is .an important approach to comprehensively evaluate students' abilities. An examination paper is composed of test items. Most studies assume that test items are independent, but there may, in fact, be associations among test items. How to select test items with low correlations into a test paper is our concern. Meanwhile, fordiagnostic learning, students must perform highly relevant exercises to help them efficiently understand the concepts included in the test items. People usually find the associations among test items based on properties of individual test items. This paper proposes a test item association model to represent the correlations of test item pairs by mining the response data of examinees. Then, a hypothesis test and an empirical analysis were used to verify and analyse the relationship between the test item correlation and similarity. Next, the effects of test item parameters on the correlation are investigated by applying the model to the simulated response data which are produced by Item Response Theory (IRT) simulation data generation software. Finally, three applications of this test item association model are listed. After verification, the proposed model can be used for precise teaching.