Volume 17 Number 4 (Jul. 2022)
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JSW 2022 Vol.17(4): 149-157 ISSN: 1796-217X
doi: 10.17706/jsw.17.4.149-157

A Novel Method Considering Guesses and Slips for Item Ordering: Noise-Filter Ordering Theory and Item Relational Structure Theory

Li-Wen-Yuan Zhou, Sheng-Hong Dong*, Xing-Gao Li
School of Psychology, Key Laboratory of Psychology and Cognition Science of Jiangxi, Jiangxi Normal University, Nanchang, Jiangxi, China.

Abstract—art's ordering theory algorithm and Takeya's item relational structure algorithm are the two classical ordering algorithms, but both of them have a common problem, that is, the item ordering results depend on the setting of threshold. The reason for this problem is that the ordering index fluctuates greatly due to guessing and slipping noise. This paper presents an improved algorithm, which can effectively filter out the noise of guessing and slipping. It is more effective than the two traditional methods. This paper also develops a computer program and carries out simulation experiments to prove the advantages of this method.

Index Terms—ordering theory algorithm, item relational structure algorithm, item ordering index, DINA model, noise-filter ordering theory

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Cite: Li-Wen-Yuan Zhou, Sheng-Hong Dong, Xing-Gao Li, "A Novel Method Considering Guesses and Slips for Item Ordering: Noise-Filter Ordering Theory and Item Relational Structure Theory," Journal of Software vol. 17, no. 4, pp. 149-157, 2022.

Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0)

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly 
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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