The Optimal Item Pool Design in Multistage Computerized Adaptive Tests With the p -Optimality Method.
The present study extended the p -optimality method to the multistage computerized adaptive test (MST) context in developing optimal item pools to support different MST panel designs under different test configurations. Using the Rasch model, simulated optimal item pools were generated with and with...
| Publicado en: | Educational & Psychological Measurement Vol. 80; no. 5; pp. 955 - 975 |
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| Autores principales: | , |
| Formato: | Artículo |
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Sage Publications Inc.
Oct2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=145141363&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 145141363 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00131644 EPM jtl: Educational & Psychological Measurement issn: 00131644 maglogo: Y pubinfo: dt: Oct2020 vid: 80 iid: 5 pid: 344 pub: Sage Publications Inc. artinfo: ui: 145141363 10.1177/0013164419901292 ppf: 955 ppct: 20 formats: tig: atl: The Optimal Item Pool Design in Multistage Computerized Adaptive Tests With the p -Optimality Method. aug: au: Yang, Lihong Reckase, Mark D. affil: Shandong Jianzhu University, Jinan, Shandong, People's Republic of China Michigan State University, East Lansing, MI, USA su: Algorithms Computer adaptive testing Experimental design Research evaluation Statistics Data analysis Sampling errors sug: subj: Algorithms Computer adaptive testing Experimental design Research evaluation Statistics Data analysis Sampling errors keyword: item pool design item pool development multistage computerized adaptive testing item pool design item pool development multistage computerized adaptive testing ab: The present study extended the p -optimality method to the multistage computerized adaptive test (MST) context in developing optimal item pools to support different MST panel designs under different test configurations. Using the Rasch model, simulated optimal item pools were generated with and without practical constraints of exposure control. A total number of 72 simulated optimal item pools were generated and evaluated by an overall sample and conditional sample using various statistical measures. Results showed that the optimal item pools built with the p -optimality method provide sufficient measurement accuracy under all simulated MST panel designs. Exposure control affected the item pool size, but not the item distributions and item pool characteristics. This study demonstrated that the p -optimality method can adapt to MST item pool design, facilitate the MST assembly process, and improve its scoring accuracy. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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