Introducing a blocked procedure in nonparametric CD-CAT

被引:0
|
作者
Zhang, Jiahui [1 ]
Yuan, Yuqing [2 ]
Qiu, Ziying [2 ]
Li, Feng [3 ]
机构
[1] Beijing Normal Univ, Collaborat Innovat Ctr Assessment Basic Educ Qual, Beijing, Peoples R China
[2] Beijing Normal Univ, Sch Stat, Beijing, Peoples R China
[3] Beijing Normal Univ Zhuhai, Collaborat Innovat Ctr Assessment Basic Educ Qual, Zhuhai, Guangdong, Peoples R China
来源
PLOS ONE | 2024年 / 19卷 / 12期
基金
国家重点研发计划;
关键词
COGNITIVE DIAGNOSIS; MODELS; FEEDBACK;
D O I
10.1371/journal.pone.0312747
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Cognitive Diagnostic Computerized Adaptive Testing (CD-CAT), in conjunction with nonparametric methodologies, is an adaptive assessment tool utilized for diagnosing students' knowledge mastery within smaller educational contexts. Expanding upon this framework, this study introduces the blocked procedure previously used in the parametric CD-CAT, enhancing the flexibility of nonparametric CD-CAT by enabling within-block item review and answer modification. A simulation study was conducted to evaluate the performance of this blocked procedure within the context of nonparametric CD-CAT across varied conditions. With increasing block size, there was a marginal reduction in pattern correct classification rate; however, such differences diminished as item quality or test length augmented. Overall, under a majority of conditions, the blocked procedure, characterized by block sizes of 2 or 4 items, allows item review within-block while attaining satisfactory levels of classification accuracy. The integration of within-block item review and answer modification with nonparametric CD-CAT fosters a more adaptive and learner-centric testing environment.
引用
收藏
页数:16
相关论文
共 20 条
  • [11] Investigating the Performance of Item Selection Algorithms in terms of Measurement Accuracy in CD-CAT
    Asiret, Semih
    Omur Sunbul, Secil
    PAMUKKALE UNIVERSITESI EGITIM FAKULTESI DERGISI-PAMUKKALE UNIVERSITY JOURNAL OF EDUCATION, 2022, (54): : 188 - +
  • [12] Development of a High-Accuracy and Effective Online Calibration Method in CD-CAT Based on Gini Index
    Tan, Qingrong
    Cai, Yan
    Luo, Fen
    Tu, Dongbo
    JOURNAL OF EDUCATIONAL AND BEHAVIORAL STATISTICS, 2023, 48 (01) : 103 - 141
  • [13] An Adaptive Design for Item Parameter Online Estimation and Q-Matrix Online Calibration in CD-CAT
    Wang, Wenyi
    Tu, Yukun
    Song, Lihong
    Zheng, Juanjuan
    Wang, Teng
    FRONTIERS IN PSYCHOLOGY, 2021, 12
  • [14] Development of Online Calibration Method based on SCAD penalty and EM perspective in CD-CAT: G-DINA model
    Tan Qingrong
    Cai Yan
    Wang Daxun
    Luo Fen
    Tu Dongbo
    ACTA PSYCHOLOGICA SINICA, 2024, 56 (05) : 670 - +
  • [15] Two efficient selection methods for high-dimensional CD-CAT utilizing max-marginals factor from MAP query and ensemble learning approach
    Luo, Fen
    Wang, Xiaoqing
    Cai, Yan
    Tu, Dongbo
    BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY, 2023, 76 (02) : 283 - 311
  • [16] A nonparametric procedure for linear and nonlinear variable screening
    Giordano, F.
    Milito, S.
    Parrella, M. L.
    JOURNAL OF NONPARAMETRIC STATISTICS, 2022, 34 (04) : 859 - 894
  • [17] Pointwise Nonparametric Estimation of Odds Ratio Curves with R: Introducing the flexOR Package
    Azevedo, Marta
    Meira-Machado, Luis
    Gude, Francisco
    Araujo, Artur
    APPLIED SCIENCES-BASEL, 2024, 14 (09):
  • [18] From screening to variable selection by an iterative nonparametric procedure based on derivatives
    Giordano, Francesco
    Milito, Sara
    Parrella, Maria Lucia
    STATISTICAL PAPERS, 2025, 66 (04)
  • [19] A New Procedure to Test Mediation With Missing Data Through Nonparametric Bootstrapping and Multiple Imputation
    Wu, Wei
    Jia, Fan
    MULTIVARIATE BEHAVIORAL RESEARCH, 2013, 48 (05) : 663 - 691
  • [20] A Nonparametric Procedure to Assess the Accuracy of the Normality Assumption for Annual Rainfall Totals, Based on the Marginal Statistics of Daily Rainfall: An Application to the NOAA/NCDC Rainfall Database
    Ruggiu, Dario
    Viola, Francesco
    Langousis, Andreas
    JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY, 2021, 60 (04) : 595 - 605