Investigating Content Multidimensionality in a Large-scale Science Assessment: A Mixed Methods Approach

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dc.contributor.advisorScalise, Kathleen
dc.contributor.authorMalcom, Cassandra
dc.date.accessioned2024-08-07T21:37:05Z
dc.date.available2024-08-07T21:37:05Z
dc.date.issued2024-08-07
dc.description.abstractScience, Technology, Engineering, and Math (STEM) skills are increasingly required of students to be successful in higher education and the workforce. Therefore, modeling assessment outcomes accurately, often using more types of student data to get a complete picture of student learning, is increasingly relevant. The Program for International Student Assessment (PISA) is promoted as a summative assessment opportunity that includes a science framework. As with many science assessments, the framework includes Life, Physical, and Earth science, which alone seems to imply multidimensionality, and also there are other sources of dimensionality that seem to be described conceptually in the framework. Using data from the 2015 PISA science assessment, a multidimensional item response theory (MIRT) model was fit to see how a multidimensional model operates with the data. Before developing the MIRT model, a qualitative review of the framework for multidimensionality took place and exploratory analyses were implemented for the quantitative data, including a data science technique to explore multidimensionality and some factor analysis techniques. After fitting the MIRT model, it was compared to several unidimensional IRT (UIRT) models to determine the model that explains the most variation. The qualitative analyses generated evidence of multidimensional science content domains in the 2015 PISA science framework, which should require a MIRT model, but quantitative analyses indicate a unidimensional model is more practically significant. Once quantitative results were triangulated with the qualitative review of the framework for multidimensionality, the implications on equity and history of harm with regards to science assessments were discussed. Findings from the qualitative and quantitative aspects of the study were used to generate recommendations for different stakeholders.en_US
dc.identifier.urihttps://hdl.handle.net/1794/29749
dc.language.isoen_US
dc.publisherUniversity of Oregon
dc.rightsAll Rights Reserved.
dc.subjectItem Response Theoryen_US
dc.subjectLarge-scale Assessmenten_US
dc.subjectMultidimensionalityen_US
dc.subjectQualitative Framework Reviewen_US
dc.subjectSTEM Educationen_US
dc.subjectSummative Assessmenten_US
dc.titleInvestigating Content Multidimensionality in a Large-scale Science Assessment: A Mixed Methods Approach
dc.typeElectronic Thesis or Dissertation
thesis.degree.disciplineDepartment of Educational Methodology, Policy, and Leadership
thesis.degree.grantorUniversity of Oregon
thesis.degree.leveldoctoral
thesis.degree.namePh.D.

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