View in EDS HTML Full Text PDF Full Text

A Generalized Objective Function for Computer Adaptive Item Selection.

Saved in:
Bibliographic Details
Title: A Generalized Objective Function for Computer Adaptive Item Selection.
Authors: Doran, Harold1 (AUTHOR), Yamada, Testsuhiro1 (AUTHOR), Diaz, Ted1 (AUTHOR), Gonulates, Emre1 (AUTHOR), Culver, Vanessa1 (AUTHOR)
Source: Journal of Educational Measurement. Mar2025, Vol. 62 Issue 1, p5-32. 28p.
Subject Terms: *Algorithms, *Computers, *Computer adaptive testing, Computer software developers, Conformance testing
Abstract: Computer adaptive testing (CAT) is an increasingly common mode of test administration offering improved test security, better measurement precision, and the potential for shorter testing experiences. This article presents a new item selection algorithm based on a generalized objective function to support multiple types of testing conditions and principled assessment design. The generalized nature of the algorithm permits a wide array of test requirements allowing experts to define what to measure and how to measure it and the algorithm is simply a means to an end to support better construct representation. This work also emphasizes the computational algorithm and its ability to scale to support faster computing and better cost‐containment in real‐world applications than other CAT algorithms. We make a significant effort to consolidate all information needed to build and scale the algorithm so that expert psychometricians and software developers can use this document as a self‐contained resource and specification document to build and deploy an operational CAT platform. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Educational Measurement is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: ehh
DbLabel: Education Research Complete
An: 183951186
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: A Generalized Objective Function for Computer Adaptive Item Selection.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Doran%2C+Harold%22">Doran, Harold</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yamada%2C+Testsuhiro%22">Yamada, Testsuhiro</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Diaz%2C+Ted%22">Diaz, Ted</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gonulates%2C+Emre%22">Gonulates, Emre</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Culver%2C+Vanessa%22">Culver, Vanessa</searchLink><relatesTo>1</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Journal+of+Educational+Measurement%22">Journal of Educational Measurement</searchLink>. Mar2025, Vol. 62 Issue 1, p5-32. 28p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22Computers%22">Computers</searchLink><br />*<searchLink fieldCode="DE" term="%22Computer+adaptive+testing%22">Computer adaptive testing</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software+developers%22">Computer software developers</searchLink><br /><searchLink fieldCode="DE" term="%22Conformance+testing%22">Conformance testing</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Computer adaptive testing (CAT) is an increasingly common mode of test administration offering improved test security, better measurement precision, and the potential for shorter testing experiences. This article presents a new item selection algorithm based on a generalized objective function to support multiple types of testing conditions and principled assessment design. The generalized nature of the algorithm permits a wide array of test requirements allowing experts to define what to measure and how to measure it and the algorithm is simply a means to an end to support better construct representation. This work also emphasizes the computational algorithm and its ability to scale to support faster computing and better cost‐containment in real‐world applications than other CAT algorithms. We make a significant effort to consolidate all information needed to build and scale the algorithm so that expert psychometricians and software developers can use this document as a self‐contained resource and specification document to build and deploy an operational CAT platform. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Educational Measurement is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=183951186
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1111/jedm.12405
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 28
        StartPage: 5
    Subjects:
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Computers
        Type: general
      – SubjectFull: Computer adaptive testing
        Type: general
      – SubjectFull: Computer software developers
        Type: general
      – SubjectFull: Conformance testing
        Type: general
    Titles:
      – TitleFull: A Generalized Objective Function for Computer Adaptive Item Selection.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Doran, Harold
      – PersonEntity:
          Name:
            NameFull: Yamada, Testsuhiro
      – PersonEntity:
          Name:
            NameFull: Diaz, Ted
      – PersonEntity:
          Name:
            NameFull: Gonulates, Emre
      – PersonEntity:
          Name:
            NameFull: Culver, Vanessa
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 03
              Text: Mar2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 00220655
          Numbering:
            – Type: volume
              Value: 62
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Journal of Educational Measurement
              Type: main
ResultId 1