Establishing Cognitive Item Models for Fair and Theory-Grounded Automatic Item Generation: A Large-Scale Assessment Study with Image-Based Math Items

Authors

Mark J. Gierl (ORCID: https://orcid.org/0000-0002-2653-1761)
Philipp Sonnleitner (ORCID: https://orcid.org/0000-0002-4861-4023)
Steve Bernard
Caroline Hornung (ORCID: https://orcid.org/0000-0003-0061-200X)
Pedro Cardoso-Leite (ORCID: https://orcid.org/0000-0002-2848-5527)
Michael Andreas Michels
Ulrich Keller (ORCID: https://orcid.org/0000-0002-2927-6479)
Pamela Inostroza-Fernandez

Institutions

University of Alberta (CA)
University of Luxembourg (LU)
Universidad de Los Andes (BO)

Publication Details

Journal: Applied Measurement in Education
Published: 2025-04-03
DOI: https://doi.org/10.1080/08957347.2025.2563889
Citations: 2
Primary Topic: Psychometric Methodologies and Testing
Type: article
Field-Weighted Citation Impact: 4.21

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article

Establishing Cognitive Item Models for Fair and Theory-Grounded Automatic Item Generation: A Large-Scale Assessment Study with Image-Based Math Items

Mark J. Gierl, Philipp Sonnleitner, Steve Bernard, Caroline Hornung et al.

Apr 3, 2025

2 citations

Applied Measurement in Education

Psychometric Methodologies and Testing

4.21

article

Establishing Cognitive Item Models for Fair and Theory-Grounded Automatic Item Generation: A Large-Scale Assessment Study with Image-Based Math Items

Mark J. Gierl, Philipp Sonnleitner, Steve Bernard, Caroline Hornung, Pedro Cardoso-Leite, Michael Andreas Michels, Ulrich Keller, Pamela Inostroza-Fernandez

April 3, 2025article en

2 citations

Abstract

No abstract available for this paper.

Applied Measurement in EducationVol. 38(2)

University of Alberta (CA), University of Luxembourg (LU), Universidad de Los Andes (BO)

Openalex Percentile: Top 5%

Psychometric Methodologies and Testing

4.21

DOI Open Access PDF OpenAlex

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