A Quotient Effect Size for Educational Interventions

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Title: A Quotient Effect Size for Educational Interventions
Language: English
Authors: Foster, Colin (ORCID 0000-0003-1648-7485)
Source: International Journal of Research & Method in Education. 2023 46(5):528-537.
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: 10
Publication Date: 2023
Document Type: Journal Articles
Reports - Evaluative
Descriptors: Effect Size, Intervention, Bias, Randomized Controlled Trials, Program Effectiveness, Scores, Quasiexperimental Design
DOI: 10.1080/1743727X.2023.2182877
ISSN: 1743-727X
1743-7288
Abstract: This paper introduces a simple, quotient effect size, termed (for 'quotient'), suitable for reporting on the effectiveness of educational interventions. The quotient effect size for a pre-test-post-test design is defined as the gain score (i.e. post-test minus pre-test) for the intervention group, divided by the gain score for the control group. This quotient effect size measure is easy to calculate and interpret, and, like Cohen's d, is scale-free. However, it achieves scale independence without acquiring the well-reported difficulties that arise with standardized effect sizes, such as Cohen's d, as a result of incorporating the standard deviation. Since the standard deviation is sensitive to many factors that are unrelated to 'the effect', Cohen's d is not a pure measure of 'effect'. By contrast, the quotient effect size, q, is dimensionless, without needing to involve the standard deviation, and is consequently intuitively easy to comprehend and communicate. For example, a q of 1.2 would mean that the intervention group improved by 20% more than the control group did. This paper explores the advantages of using as an effect size for reporting on the effectiveness of educational interventions, as compared with Cohen's d, and addresses some possible objections.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1395111
Database: ERIC
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  Data: A Quotient Effect Size for Educational Interventions
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  Data: <searchLink fieldCode="AR" term="%22Foster%2C+Colin%22">Foster, Colin</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0003-1648-7485">0000-0003-1648-7485</externalLink>)
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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: <searchLink fieldCode="DE" term="%22Effect+Size%22">Effect Size</searchLink><br /><searchLink fieldCode="DE" term="%22Intervention%22">Intervention</searchLink><br /><searchLink fieldCode="DE" term="%22Bias%22">Bias</searchLink><br /><searchLink fieldCode="DE" term="%22Randomized+Controlled+Trials%22">Randomized Controlled Trials</searchLink><br /><searchLink fieldCode="DE" term="%22Program+Effectiveness%22">Program Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Scores%22">Scores</searchLink><br /><searchLink fieldCode="DE" term="%22Quasiexperimental+Design%22">Quasiexperimental Design</searchLink>
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  Data: This paper introduces a simple, quotient effect size, termed (for 'quotient'), suitable for reporting on the effectiveness of educational interventions. The quotient effect size for a pre-test-post-test design is defined as the gain score (i.e. post-test minus pre-test) for the intervention group, divided by the gain score for the control group. This quotient effect size measure is easy to calculate and interpret, and, like Cohen's d, is scale-free. However, it achieves scale independence without acquiring the well-reported difficulties that arise with standardized effect sizes, such as Cohen's d, as a result of incorporating the standard deviation. Since the standard deviation is sensitive to many factors that are unrelated to 'the effect', Cohen's d is not a pure measure of 'effect'. By contrast, the quotient effect size, q, is dimensionless, without needing to involve the standard deviation, and is consequently intuitively easy to comprehend and communicate. For example, a q of 1.2 would mean that the intervention group improved by 20% more than the control group did. This paper explores the advantages of using as an effect size for reporting on the effectiveness of educational interventions, as compared with Cohen's d, and addresses some possible objections.
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      – Text: English
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      – SubjectFull: Effect Size
        Type: general
      – SubjectFull: Intervention
        Type: general
      – SubjectFull: Bias
        Type: general
      – SubjectFull: Randomized Controlled Trials
        Type: general
      – SubjectFull: Program Effectiveness
        Type: general
      – SubjectFull: Scores
        Type: general
      – SubjectFull: Quasiexperimental Design
        Type: general
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      – TitleFull: A Quotient Effect Size for Educational Interventions
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