Full-information item bifactor model for mathematical ability assessment in Chinese compulsory education quality monitoring

Frontiers in Psychology

article

Xiangbin Meng¹  Tao Yang²  Ningzhong Shi¹  Tao Xin² 

[1] School of Mathematics and Statistics, KLAS, Northeast Normal University;Collaborative Innovation Center of Assessment for Basic Education Quality, Beijing Normal University

关键词: full-information bifactor item factor model;    Mathematical ability;    item response theory;    China Compulsory Education Quality Monitoring;    Large scale testing;   

DOI  :  10.3389/fpsyg.2022.1049472

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

This study focuses on the measurement of mathematical ability in the Chinese Compulsory Education Qualification Monitoring (CCEQM) framework using bifactor theory. First, we propose a full-information item bifactor (FIBF) model for the measurement of mathematical ability. Second, the performance of the FIBF model is empirically studied using a data set from three representative provinces were selected from from CCEQM 2015--2017. Finally, Monte Carlo simulations are conducted to demonstrate the accuracy of the model evaluation indices and parameter estimation methods used in the empirical study. The obtained results are as follows: (1) The results for the four used model selection indices (AIC, SABIC, HQ, BIC) consistently showed that the fit of the FIBF model is better than that of the UIRT; (2) All of the estimated general and domain-specific abilities of the FIBF model have reasonable interpretations; (3) The model evaluation indices and parameter estimation methods exhibit excellent accuracy, indicating that the application of the FIBF model is technically feasible in large-scale testing projects.

【 授权许可】

CC BY