Literature DB >> 31853155

New Efficient and Practicable Adaptive Designs for Calibrating Items Online.

Yinhong He1,2, Ping Chen1, Yong Li1.   

Abstract

When calibrating new items online, it is practicable to first compare all new items according to some criterion and then assign the most suitable one to the current examinee who reaches a seeding location. The modified D-optimal design proposed by van der Linden and Ren (denoted as D-VR design) works within this practicable framework with the aim of directly optimizing the estimation of item parameters. However, the optimal design point for a given new item should be obtained by comparing all examinees in a static examinee pool. Thus, D-VR design still has room for improvement in calibration efficiency from the view of traditional optimal design. To this end, this article incorporates the idea of traditional optimal design into D-VR design and proposes a new online calibration design criterion, namely, excellence degree (ED) criterion. Four different schemes are developed to measure the information provided by the current examinee when implementing this new criterion, and four new ED designs equipped with them are put forward accordingly. Simulation studies were conducted under a variety of conditions to compare the D-VR design and the four proposed ED designs in terms of calibration efficiency. Results showed that the four ED designs outperformed D-VR design in almost all simulation conditions.
© The Author(s) 2019.

Entities:  

Keywords:  adaptive design; computerized adaptive testing; item response theory; online calibration; optimal design; sequential design

Year:  2019        PMID: 31853155      PMCID: PMC6906388          DOI: 10.1177/0146621618824854

Source DB:  PubMed          Journal:  Appl Psychol Meas        ISSN: 0146-6216


  7 in total

1.  Minimax D-optimal designs for the logistic model.

Authors:  J King; W K Wong
Journal:  Biometrics       Date:  2000-12       Impact factor: 2.571

2.  THE IMPACT OF FALLIBLE ITEM PARAMETER ESTIMATES ON LATENT TRAIT RECOVERY.

Authors:  Ying Cheng; Ke-Hai Yuan
Journal:  Psychometrika       Date:  2010-06       Impact factor: 2.500

3.  A New Online Calibration Method for Multidimensional Computerized Adaptive Testing.

Authors:  Ping Chen; Chun Wang
Journal:  Psychometrika       Date:  2015-11-25       Impact factor: 2.500

4.  Developing new online calibration methods for multidimensional computerized adaptive testing.

Authors:  Ping Chen; Chun Wang; Tao Xin; Hua-Hua Chang
Journal:  Br J Math Stat Psychol       Date:  2017-02       Impact factor: 3.380

5.  Optimal Bayesian Adaptive Design for Test-Item Calibration.

Authors:  Wim J van der Linden; Hao Ren
Journal:  Psychometrika       Date:  2014-01-10       Impact factor: 2.500

6.  Characterizing Sources of Uncertainty in IRT Scale Scores.

Authors:  Ji Seung Yang; Mark Hansen; Li Cai
Journal:  Educ Psychol Meas       Date:  2011-08-25       Impact factor: 2.821

7.  Application of optimal designs to item calibration.

Authors:  Hung-Yi Lu
Journal:  PLoS One       Date:  2014-09-04       Impact factor: 3.240

  7 in total
  2 in total

1.  Optimal Online Calibration Designs for Item Replenishment in Adaptive Testing.

Authors:  Yinhong He; Ping Chen
Journal:  Psychometrika       Date:  2019-09-17       Impact factor: 2.500

2.  Online Calibration of Polytomous Items Under the Graded Response Model.

Authors:  Jianhua Xiong; Shuliang Ding; Fen Luo; Zhaosheng Luo
Journal:  Front Psychol       Date:  2020-01-23
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.