Constructing a Computerized Adaptive Test for Multidimensional Mathematical Competence: Development, Simulation, and Validation

This study utilized Item Response Theory (IRT) and Computerized Adaptive Testing (CAT) techniques to develop and preliminarily evaluate a multidimensional Mathematics Competence Assessment and Diagnosis (MCAD). The research consisted of three studies: First, we followed a five-step process to construct the item bank, which included Item Construction, Booklet Design, Participants, Procedure, and Data Analysis. Second, we conducted a simulation study to assess measurement precision and testing efficiency. The results indicated that MCAD’s measurement precision exceeded that of unidimensional CAT and random administration of items, requiring less than 33% of the items needed by these methods to achieve equivalent reliability. Third, after developing the MCAD system, we carried out a preliminary empirical study involving 105 tenth-grade students. We used their Comprehensive Assessment Program for Junior High School Students (CAP) mathematics test as a criterion to examine the MCAD’s criterion-related evidence, which was found to be over 0.7. However, the high correlations among dimensions and the characteristics of the empirical sample suggest that dimension-specific interpretations should be made cautiously. Overall, the findings provide preliminary support for MCAD as a potentially efficient tool for assessing mathematical competence.

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Publication Details

Journal
International Journal of Science and Mathematics Education
Published
2026-07-01
DOI
https://doi.org/10.1007/s10763-026-10701-y
Primary Topic
Psychometric Methodologies and Testing
Type
article
Field-Weighted Citation Impact
0.00

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article

Constructing a Computerized Adaptive Test for Multidimensional Mathematical Competence: Development, Simulation, and Validation

Yu-Chun Lien, Yeh-Tai Chou, Wei-Hong Yang, Yao-Ting Sung
International Journal of Science and Mathematics Education
Psychometric Methodologies and Testing
article

Constructing a Computerized Adaptive Test for Multidimensional Mathematical Competence: Development, Simulation, and Validation

Yu-Chun Lien, Yeh-Tai Chou, Wei-Hong Yang, Yao-Ting Sung
article en

Abstract

This study utilized Item Response Theory (IRT) and Computerized Adaptive Testing (CAT) techniques to develop and preliminarily evaluate a multidimensional Mathematics Competence Assessment and Diagnosis (MCAD). The research consisted of three studies: First, we followed a five-step process to construct the item bank, which included Item Construction, Booklet Design, Participants, Procedure, and Data Analysis. Second, we conducted a simulation study to assess measurement precision and testing efficiency. The results indicated that MCAD’s measurement precision exceeded that of unidimensional CAT and random administration of items, requiring less than 33% of the items needed by these methods to achieve equivalent reliability. Third, after developing the MCAD system, we carried out a preliminary empirical study involving 105 tenth-grade students. We used their Comprehensive Assessment Program for Junior High School Students (CAP) mathematics test as a criterion to examine the MCAD’s criterion-related evidence, which was found to be over 0.7. However, the high correlations among dimensions and the characteristics of the empirical sample suggest that dimension-specific interpretations should be made cautiously. Overall, the findings provide preliminary support for MCAD as a potentially efficient tool for assessing mathematical competence.

International Journal of Science and Mathematics EducationVol. 24(6)
National Taiwan Normal University (TW)
National Taiwan Normal University, Institute for Research Excellence in Learning Sciences, National Taiwan Normal University
Openalex Percentile: Top 5%
Psychometric Methodologies and Testing
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Constructing a Computerized Adaptive Test for Multidimensional Mathematical Competence: Development, Simulation, and Validation — Yu-Chun Lien, Yeh-Tai Chou, et al. · International Journal of Science and Mathematics Education (2026) | TGRS Research Map | TGRS