A Rasch Analysis of the Self-Determination, Purpose, Identity, and Engagement in Science (SPIRES) Survey: Instrument Validation and Recommendations

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Bibliographic Details
Title: A Rasch Analysis of the Self-Determination, Purpose, Identity, and Engagement in Science (SPIRES) Survey: Instrument Validation and Recommendations
Language: English
Authors: Courtney Donovan (ORCID 0000-0001-5911-3294), Hannah Huvard (ORCID 0000-0003-0799-8814), Angela Rexwinkle (ORCID 0009-0007-6162-0878), Robert Talbot (ORCID 0000-0002-6821-0675)
Source: International Journal of Education in Mathematics, Science and Technology. 2025 13(4):992-1015.
Availability: International Journal of Education in Mathematics, Science and Technology. Necmettin Erbakan University, Ahmet Kelesoglu Education Faculty, Meram, Konya, 42090, Turkey. e-mail: ijermst@gmail.com; Web site: https://www.ijemst.net/index.php/ijemst/index
Peer Reviewed: Y
Page Count: 25
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Item Response Theory, Student Surveys, Test Validity, Student Motivation, Undergraduate Students, Biology, Self Concept, Learner Engagement, Identification (Psychology), Scientists, Peer Relationship
ISSN: 2147-611X
Abstract: The purpose of the present study was to perform a cross-validation of an existing measure of science students' motivational traits using the Rasch modeling approach. The validity of the Self-determination, Purpose, Identity, and Engagement in Science (SPIRES) survey was originally investigated using factor analysis, but a secondary validation of this instrument has not yet been published. This is a recommended practice when using a psychometric instrument within a new context or with a different student population. In this validity study, we took a Rasch modeling approach instead of factor analysis because, unlike factor analysis, Rasch modeling is sample-independent. The original factor analysis validation of the SPIRES suggested the survey is composed of three larger ideas or constructs, while our Rasch modeling results suggest there are four constructs. Since our Rasch analyses were sample-independent, we conclude that the SPIRES survey is a four construct survey and may be treated as such across educational contexts without further need to validate using factor analysis, which could continuously produce inconsistent results. These results provide the basis for a validity argument for researchers using the SPIRES in their work. Our work also demonstrates an advantage to using a Rasch modeling approach over factor analysis for instrument validation.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1475652
Database: ERIC
Description
Abstract:The purpose of the present study was to perform a cross-validation of an existing measure of science students' motivational traits using the Rasch modeling approach. The validity of the Self-determination, Purpose, Identity, and Engagement in Science (SPIRES) survey was originally investigated using factor analysis, but a secondary validation of this instrument has not yet been published. This is a recommended practice when using a psychometric instrument within a new context or with a different student population. In this validity study, we took a Rasch modeling approach instead of factor analysis because, unlike factor analysis, Rasch modeling is sample-independent. The original factor analysis validation of the SPIRES suggested the survey is composed of three larger ideas or constructs, while our Rasch modeling results suggest there are four constructs. Since our Rasch analyses were sample-independent, we conclude that the SPIRES survey is a four construct survey and may be treated as such across educational contexts without further need to validate using factor analysis, which could continuously produce inconsistent results. These results provide the basis for a validity argument for researchers using the SPIRES in their work. Our work also demonstrates an advantage to using a Rasch modeling approach over factor analysis for instrument validation.
ISSN:2147-611X