Optimizing the length of computerized adaptive testing for the Force Concept Inventory

As a method to shorten the test time of the Force Concept Inventory (FCI), we suggest the use of computerized adaptive testing (CAT). CAT is the process of administering a test on a computer, with items (i.e., questions) selected based upon the responses of the examinee to prior items. In so doing,...

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Autores principales: Jun-ichiro Yasuda, Naohiro Mae, Michael M. Hull, Masa-aki Taniguchi
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Publicado: American Physical Society 2021
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spelling oai:doaj.org-article:9d63b410e9fb4eeeb6bd3964d49cb68a2021-12-02T17:09:41ZOptimizing the length of computerized adaptive testing for the Force Concept Inventory10.1103/PhysRevPhysEducRes.17.0101152469-9896https://doaj.org/article/9d63b410e9fb4eeeb6bd3964d49cb68a2021-03-01T00:00:00Zhttp://doi.org/10.1103/PhysRevPhysEducRes.17.010115http://doi.org/10.1103/PhysRevPhysEducRes.17.010115https://doaj.org/toc/2469-9896As a method to shorten the test time of the Force Concept Inventory (FCI), we suggest the use of computerized adaptive testing (CAT). CAT is the process of administering a test on a computer, with items (i.e., questions) selected based upon the responses of the examinee to prior items. In so doing, the test length can be significantly shortened. As a step to develop a CAT-based version of the FCI (FCI-CAT), we examined the optimal test length of the FCI-CAT such that accuracy and precision [which we measure in terms of bias, standard error, and root-mean-square error (RMSE)] of Cohen’s d would be comparable to that of the full FCI for a given class size. First, we estimated the item parameters of the FCI items based on the three-parameter logistic model of item response theory, which are used in the algorithm of CAT. For this estimation, we used 2882 responses of Japanese university students. Second, we conducted a Monte Carlo simulation to analyze how the bias, standard error, and RMSE of Cohen’s d depend upon the test length. Third, we conducted a post hoc simulation to examine the consistency of the Monte Carlo results with what would have been obtained using empirical responses. For this comparison, we used 86 pairs of pre- and post- test responses of Japanese university students. As a result, we found that for a class size of 40, we may reduce the test length of the FCI-CAT to 15–19 items, thereby reducing the test time of the FCI to 50%–63%, with an accompanying decrease in accuracy and precision of only 5%–10%. The results of the Monte Carlo study and the post hoc simulation were consistent, which supports the adequacy of our Monte Carlo study and its relevance in terms of administering the FCI-CAT in real classrooms.Jun-ichiro YasudaNaohiro MaeMichael M. HullMasa-aki TaniguchiAmerican Physical SocietyarticleSpecial aspects of educationLC8-6691PhysicsQC1-999ENPhysical Review Physics Education Research, Vol 17, Iss 1, p 010115 (2021)
institution DOAJ
collection DOAJ
language EN
topic Special aspects of education
LC8-6691
Physics
QC1-999
spellingShingle Special aspects of education
LC8-6691
Physics
QC1-999
Jun-ichiro Yasuda
Naohiro Mae
Michael M. Hull
Masa-aki Taniguchi
Optimizing the length of computerized adaptive testing for the Force Concept Inventory
description As a method to shorten the test time of the Force Concept Inventory (FCI), we suggest the use of computerized adaptive testing (CAT). CAT is the process of administering a test on a computer, with items (i.e., questions) selected based upon the responses of the examinee to prior items. In so doing, the test length can be significantly shortened. As a step to develop a CAT-based version of the FCI (FCI-CAT), we examined the optimal test length of the FCI-CAT such that accuracy and precision [which we measure in terms of bias, standard error, and root-mean-square error (RMSE)] of Cohen’s d would be comparable to that of the full FCI for a given class size. First, we estimated the item parameters of the FCI items based on the three-parameter logistic model of item response theory, which are used in the algorithm of CAT. For this estimation, we used 2882 responses of Japanese university students. Second, we conducted a Monte Carlo simulation to analyze how the bias, standard error, and RMSE of Cohen’s d depend upon the test length. Third, we conducted a post hoc simulation to examine the consistency of the Monte Carlo results with what would have been obtained using empirical responses. For this comparison, we used 86 pairs of pre- and post- test responses of Japanese university students. As a result, we found that for a class size of 40, we may reduce the test length of the FCI-CAT to 15–19 items, thereby reducing the test time of the FCI to 50%–63%, with an accompanying decrease in accuracy and precision of only 5%–10%. The results of the Monte Carlo study and the post hoc simulation were consistent, which supports the adequacy of our Monte Carlo study and its relevance in terms of administering the FCI-CAT in real classrooms.
format article
author Jun-ichiro Yasuda
Naohiro Mae
Michael M. Hull
Masa-aki Taniguchi
author_facet Jun-ichiro Yasuda
Naohiro Mae
Michael M. Hull
Masa-aki Taniguchi
author_sort Jun-ichiro Yasuda
title Optimizing the length of computerized adaptive testing for the Force Concept Inventory
title_short Optimizing the length of computerized adaptive testing for the Force Concept Inventory
title_full Optimizing the length of computerized adaptive testing for the Force Concept Inventory
title_fullStr Optimizing the length of computerized adaptive testing for the Force Concept Inventory
title_full_unstemmed Optimizing the length of computerized adaptive testing for the Force Concept Inventory
title_sort optimizing the length of computerized adaptive testing for the force concept inventory
publisher American Physical Society
publishDate 2021
url https://doaj.org/article/9d63b410e9fb4eeeb6bd3964d49cb68a
work_keys_str_mv AT junichiroyasuda optimizingthelengthofcomputerizedadaptivetestingfortheforceconceptinventory
AT naohiromae optimizingthelengthofcomputerizedadaptivetestingfortheforceconceptinventory
AT michaelmhull optimizingthelengthofcomputerizedadaptivetestingfortheforceconceptinventory
AT masaakitaniguchi optimizingthelengthofcomputerizedadaptivetestingfortheforceconceptinventory
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