Literature DB >> 28290109

Continuous Online Item Calibration: Parameter Recovery and Item Utilization.

Hao Ren1, Wim J van der Linden2, Qi Diao2.   

Abstract

Parameter recovery and item utilization were investigated for different designs for online test item calibration. The design was adaptive in a double sense: it assumed both adaptive testing of examinees from an operational pool of previously calibrated items and adaptive assignment of field-test items to the examinees. Four criteria of optimality for the assignment of the field-test items were used, each of them based on the information in the posterior distributions of the examinee's ability parameter during adaptive testing as well as the sequentially updated posterior distributions of the field-test item parameters. In addition, different stopping rules based on target values for the posterior standard deviations of the field-test parameters and the size of the calibration sample were used. The impact of each of the criteria and stopping rules on the statistical efficiency of the estimates of the field-test parameters and on the time spent by the items in the calibration procedure was investigated. Recommendations as to the practical use of the designs are given.

Keywords:  Bayesian optimal design; D-optimality; adaptive testing; item calibration

Mesh:

Year:  2017        PMID: 28290109     DOI: 10.1007/s11336-017-9553-1

Source DB:  PubMed          Journal:  Psychometrika        ISSN: 0033-3123            Impact factor:   2.500


  1 in total

1.  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

  1 in total
  4 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.  On-the-fly parameter estimation based on item response theory in item-based adaptive learning systems.

Authors:  Shengyu Jiang; Jiaying Xiao; Chun Wang
Journal:  Behav Res Methods       Date:  2022-09-09

3.  A Shadow-Test Approach to Adaptive Item Calibration.

Authors:  Wim J van der Linden; Bingnan Jiang
Journal:  Psychometrika       Date:  2020-06-17       Impact factor: 2.500

4.  Optimal Item Calibration for Computerized Achievement Tests.

Authors:  Mahmood Ul Hassan; Frank Miller
Journal:  Psychometrika       Date:  2019-06-10       Impact factor: 2.500

  4 in total

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