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The Conceptualisation Implies the Statistical Model: Implications for Measuring Domains of Teaching Quality

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Title: The Conceptualisation Implies the Statistical Model: Implications for Measuring Domains of Teaching Quality
Language: English
Authors: Mark White (ORCID 0000-0003-2394-3151), Peter A. Edelsbrunner (ORCID 0000-0001-9102-1090), Christian M. Thurn (ORCID 0000-0002-5942-3273)
Source: Assessment in Education: Principles, Policy & Practice. 2024 31(3-4):254-278.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 25
Publication Date: 2024
Document Type: Journal Articles
Reports - Descriptive
Descriptors: Teacher Effectiveness, Classroom Observation Techniques, Evaluation Methods, Scoring Rubrics, Comparative Testing, Formative Evaluation, Concept Formation, Coordination, Test Selection, Goodness of Fit
DOI: 10.1080/0969594X.2024.2368252
ISSN: 0969-594X
1465-329X
Abstract: Classroom observation rubrics are a widely adopted tool for measuring the quality of teaching and provide stable conceptualisations of teaching quality that facilitate empirical research. Here, we present four statistical approaches for analysing data from classroom observations: Factor analysis, Rasch modelling, latent class or profile analysis, and formative measurement models. Each statistical model conceptualises the latent variable differently, which may or may not align with the observation rubric's conceptualisation of teaching quality. We discuss the differences across these models, focusing on the alignment between the rubric's conceptualisation of teaching quality and the model's modelling of the latent variable. We discuss the need to align model selection with observation rubric so that the measured teaching quality reflects the theoretically conceptualised teaching quality.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1441005
Database: ERIC
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  Data: <searchLink fieldCode="AR" term="%22Mark+White%22">Mark White</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-2394-3151">0000-0003-2394-3151</externalLink>)<br /><searchLink fieldCode="AR" term="%22Peter+A%2E+Edelsbrunner%22">Peter A. Edelsbrunner</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-9102-1090">0000-0001-9102-1090</externalLink>)<br /><searchLink fieldCode="AR" term="%22Christian+M%2E+Thurn%22">Christian M. Thurn</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-5942-3273">0000-0002-5942-3273</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Assessment+in+Education%3A+Principles%2C+Policy+%26+Practice%22"><i>Assessment in Education: Principles, Policy & Practice</i></searchLink>. 2024 31(3-4):254-278.
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
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  Data: Classroom observation rubrics are a widely adopted tool for measuring the quality of teaching and provide stable conceptualisations of teaching quality that facilitate empirical research. Here, we present four statistical approaches for analysing data from classroom observations: Factor analysis, Rasch modelling, latent class or profile analysis, and formative measurement models. Each statistical model conceptualises the latent variable differently, which may or may not align with the observation rubric's conceptualisation of teaching quality. We discuss the differences across these models, focusing on the alignment between the rubric's conceptualisation of teaching quality and the model's modelling of the latent variable. We discuss the need to align model selection with observation rubric so that the measured teaching quality reflects the theoretically conceptualised teaching quality.
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        Value: 10.1080/0969594X.2024.2368252
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      – Text: English
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        PageCount: 25
        StartPage: 254
    Subjects:
      – SubjectFull: Teacher Effectiveness
        Type: general
      – SubjectFull: Classroom Observation Techniques
        Type: general
      – SubjectFull: Evaluation Methods
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      – SubjectFull: Scoring Rubrics
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      – SubjectFull: Comparative Testing
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      – SubjectFull: Formative Evaluation
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      – SubjectFull: Concept Formation
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      – SubjectFull: Coordination
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      – SubjectFull: Test Selection
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      – SubjectFull: Goodness of Fit
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      – TitleFull: The Conceptualisation Implies the Statistical Model: Implications for Measuring Domains of Teaching Quality
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            NameFull: Christian M. Thurn
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