Item response theory with fuzzy markup language for parameter estimation and validation

Mei Hui WANG; Chi Shiang WANG; Chang Shing LEE; Olivier TEYTAUD; Jialin LIU; Su-Wei LIN; Pi-Hsia HUNG

doi:10.1109/FUZZ-IEEE.2015.7337884

Item response theory with fuzzy markup language for parameter estimation and validation

Mei Hui WANG, Chi Shiang WANG, Chang Shing LEE, Olivier TEYTAUD, Jialin LIU, Su-Wei LIN, Pi-Hsia HUNG

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Referred Conference Paper › peer-review

2 Citations (Scopus)

Abstract

Owing to advanced technical progress in information and communication technology, computerized adaptive assessment becomes more and more important for the personalized learning achievement. According to the response data from the conventional test and three-parameter logistic (3PL) model of the item response theory (IRT), this paper combines IRT with fuzzy markup language (FML) for an adaptive assessment application. The novel FML-based IRT estimation mechanism includes a Gauss-Seidel (GS) parameter estimation mechanism, a fuzzy knowledge base and a fuzzy rule base, to estimate the item parameters for each item. Meanwhile, it is able to infer the possibility of correct response to each item for each involved student. Additionally, this paper also proposes a static-IRT test assembly mechanism to assemble a form for the conventional test. After that, this paper chooses 5-fold cross validation to validate the research performance. From the experimental results, it shows that the proposed approach performs better than the traditional Bayesian estimation one.

Original language	English
Title of host publication	FUZZ-IEEE 2015 : IEEE International Conference on Fuzzy Systems, August 2-5, 2015, Istanbul, Turkey : Proceedings
Editors	Adnan YAZICI, Nikhil R. PAL, Uzay KAYMAK, Trevor MARTIN, Hisao ISHIBUCHI, Chin-Teng LIN, João M. C. SOUSA, Bülent TÜTMEZ
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	7
ISBN (Electronic)	9781467374286
DOIs	https://doi.org/10.1109/FUZZ-IEEE.2015.7337884
Publication status	Published - 30 Nov 2015
Externally published	Yes
Event	IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015 - Istanbul, Turkey Duration: 2 Aug 2015 → 5 Aug 2015

Publication series

Name	IEEE International Conference on Fuzzy Systems
Publisher	IEEE
Volume	2015-November
ISSN (Print)	1098-7584

Conference

Conference	IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015
Country/Territory	Turkey
City	Istanbul
Period	2/08/15 → 5/08/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

Adaptive Assessment
Fuzzy Markup Language
Fuzzy Ontology
Item Response Theory

Access to Document

10.1109/FUZZ-IEEE.2015.7337884

Cite this

WANG, M. H., WANG, C. S., LEE, C. S., TEYTAUD, O., LIU, J., LIN, S.-W., & HUNG, P.-H. (2015). Item response theory with fuzzy markup language for parameter estimation and validation. In A. YAZICI, N. R. PAL, U. KAYMAK, T. MARTIN, H. ISHIBUCHI, C.-T. LIN, J. M. C. SOUSA, & B. TÜTMEZ (Eds.), FUZZ-IEEE 2015 : IEEE International Conference on Fuzzy Systems, August 2-5, 2015, Istanbul, Turkey : Proceedings Article 7337884 (IEEE International Conference on Fuzzy Systems; Vol. 2015-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FUZZ-IEEE.2015.7337884

WANG, Mei Hui ; WANG, Chi Shiang ; LEE, Chang Shing et al. / Item response theory with fuzzy markup language for parameter estimation and validation. FUZZ-IEEE 2015 : IEEE International Conference on Fuzzy Systems, August 2-5, 2015, Istanbul, Turkey : Proceedings. editor / Adnan YAZICI ; Nikhil R. PAL ; Uzay KAYMAK ; Trevor MARTIN ; Hisao ISHIBUCHI ; Chin-Teng LIN ; João M. C. SOUSA ; Bülent TÜTMEZ. Institute of Electrical and Electronics Engineers Inc., 2015. (IEEE International Conference on Fuzzy Systems).

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title = "Item response theory with fuzzy markup language for parameter estimation and validation",

abstract = "Owing to advanced technical progress in information and communication technology, computerized adaptive assessment becomes more and more important for the personalized learning achievement. According to the response data from the conventional test and three-parameter logistic (3PL) model of the item response theory (IRT), this paper combines IRT with fuzzy markup language (FML) for an adaptive assessment application. The novel FML-based IRT estimation mechanism includes a Gauss-Seidel (GS) parameter estimation mechanism, a fuzzy knowledge base and a fuzzy rule base, to estimate the item parameters for each item. Meanwhile, it is able to infer the possibility of correct response to each item for each involved student. Additionally, this paper also proposes a static-IRT test assembly mechanism to assemble a form for the conventional test. After that, this paper chooses 5-fold cross validation to validate the research performance. From the experimental results, it shows that the proposed approach performs better than the traditional Bayesian estimation one.",

keywords = "Adaptive Assessment, Fuzzy Markup Language, Fuzzy Ontology, Item Response Theory",

author = "WANG, {Mei Hui} and WANG, {Chi Shiang} and LEE, {Chang Shing} and Olivier TEYTAUD and Jialin LIU and Su-Wei LIN and Pi-Hsia HUNG",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015 ; Conference date: 02-08-2015 Through 05-08-2015",

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doi = "10.1109/FUZZ-IEEE.2015.7337884",

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booktitle = "FUZZ-IEEE 2015 : IEEE International Conference on Fuzzy Systems, August 2-5, 2015, Istanbul, Turkey : Proceedings",

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WANG, MH, WANG, CS, LEE, CS, TEYTAUD, O, LIU, J, LIN, S-W & HUNG, P-H 2015, Item response theory with fuzzy markup language for parameter estimation and validation. in A YAZICI, NR PAL, U KAYMAK, T MARTIN, H ISHIBUCHI, C-T LIN, JMC SOUSA & B TÜTMEZ (eds), FUZZ-IEEE 2015 : IEEE International Conference on Fuzzy Systems, August 2-5, 2015, Istanbul, Turkey : Proceedings., 7337884, IEEE International Conference on Fuzzy Systems, vol. 2015-November, Institute of Electrical and Electronics Engineers Inc., IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015, Istanbul, Turkey, 2/08/15. https://doi.org/10.1109/FUZZ-IEEE.2015.7337884

Item response theory with fuzzy markup language for parameter estimation and validation. / WANG, Mei Hui; WANG, Chi Shiang; LEE, Chang Shing et al.
FUZZ-IEEE 2015 : IEEE International Conference on Fuzzy Systems, August 2-5, 2015, Istanbul, Turkey : Proceedings. ed. / Adnan YAZICI; Nikhil R. PAL; Uzay KAYMAK; Trevor MARTIN; Hisao ISHIBUCHI; Chin-Teng LIN; João M. C. SOUSA; Bülent TÜTMEZ. Institute of Electrical and Electronics Engineers Inc., 2015. 7337884 (IEEE International Conference on Fuzzy Systems; Vol. 2015-November).

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Referred Conference Paper › peer-review

TY - GEN

T1 - Item response theory with fuzzy markup language for parameter estimation and validation

AU - WANG, Mei Hui

AU - WANG, Chi Shiang

AU - LEE, Chang Shing

AU - TEYTAUD, Olivier

AU - LIU, Jialin

AU - LIN, Su-Wei

AU - HUNG, Pi-Hsia

PY - 2015/11/30

Y1 - 2015/11/30

N2 - Owing to advanced technical progress in information and communication technology, computerized adaptive assessment becomes more and more important for the personalized learning achievement. According to the response data from the conventional test and three-parameter logistic (3PL) model of the item response theory (IRT), this paper combines IRT with fuzzy markup language (FML) for an adaptive assessment application. The novel FML-based IRT estimation mechanism includes a Gauss-Seidel (GS) parameter estimation mechanism, a fuzzy knowledge base and a fuzzy rule base, to estimate the item parameters for each item. Meanwhile, it is able to infer the possibility of correct response to each item for each involved student. Additionally, this paper also proposes a static-IRT test assembly mechanism to assemble a form for the conventional test. After that, this paper chooses 5-fold cross validation to validate the research performance. From the experimental results, it shows that the proposed approach performs better than the traditional Bayesian estimation one.

AB - Owing to advanced technical progress in information and communication technology, computerized adaptive assessment becomes more and more important for the personalized learning achievement. According to the response data from the conventional test and three-parameter logistic (3PL) model of the item response theory (IRT), this paper combines IRT with fuzzy markup language (FML) for an adaptive assessment application. The novel FML-based IRT estimation mechanism includes a Gauss-Seidel (GS) parameter estimation mechanism, a fuzzy knowledge base and a fuzzy rule base, to estimate the item parameters for each item. Meanwhile, it is able to infer the possibility of correct response to each item for each involved student. Additionally, this paper also proposes a static-IRT test assembly mechanism to assemble a form for the conventional test. After that, this paper chooses 5-fold cross validation to validate the research performance. From the experimental results, it shows that the proposed approach performs better than the traditional Bayesian estimation one.

KW - Adaptive Assessment

KW - Fuzzy Markup Language

KW - Fuzzy Ontology

KW - Item Response Theory

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U2 - 10.1109/FUZZ-IEEE.2015.7337884

DO - 10.1109/FUZZ-IEEE.2015.7337884

M3 - Conference paper (refereed)

AN - SCOPUS:84975721580

T3 - IEEE International Conference on Fuzzy Systems

BT - FUZZ-IEEE 2015 : IEEE International Conference on Fuzzy Systems, August 2-5, 2015, Istanbul, Turkey : Proceedings

A2 - YAZICI, Adnan

A2 - PAL, Nikhil R.

A2 - KAYMAK, Uzay

A2 - MARTIN, Trevor

A2 - ISHIBUCHI, Hisao

A2 - LIN, Chin-Teng

A2 - SOUSA, João M. C.

A2 - TÜTMEZ, Bülent

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015

Y2 - 2 August 2015 through 5 August 2015

ER -

WANG MH, WANG CS, LEE CS, TEYTAUD O, LIU J, LIN SW et al. Item response theory with fuzzy markup language for parameter estimation and validation. In YAZICI A, PAL NR, KAYMAK U, MARTIN T, ISHIBUCHI H, LIN CT, SOUSA JMC, TÜTMEZ B, editors, FUZZ-IEEE 2015 : IEEE International Conference on Fuzzy Systems, August 2-5, 2015, Istanbul, Turkey : Proceedings. Institute of Electrical and Electronics Engineers Inc. 2015. 7337884. (IEEE International Conference on Fuzzy Systems). Epub 2015. doi: 10.1109/FUZZ-IEEE.2015.7337884

Item response theory with fuzzy markup language for parameter estimation and validation

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Keywords

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