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Predictors of Assumed "Bad" Behavior: A Classification and Regression Tree Analysis.

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Title: Predictors of Assumed "Bad" Behavior: A Classification and Regression Tree Analysis.
Authors: Bagneris, Jessica R. (AUTHOR), Scott, Edward D. (AUTHOR)
Source: Psychology in the Schools. Sep2025, Vol. 62 Issue 9, p2985-2998. 14p.
Subjects: Racism, Sex discrimination, Statistical bias, Social skills, Classroom management, Externalizing behavior, CART algorithms, Teachers
Geographic Terms: United States
Abstract: Bias influencing teachers' classroom management is increasingly clear, but the circumstances that influence the likelihood of relying on those biases are less understood. This study employed Classification and Regression Tree (CART) analysis, resulting in four models examining how teachers' appraisals of first‐grade students' externalizing problem behaviors are influenced by students' demographics and teachers' assessments of objective and subjective socioemotional skills. Results from a sample of 3305 teachers in the United States indicated that gender and racial biases are more likely to be relied upon when teachers are assessing subjective skills rather than objective ones. The potential inaccuracies in teachers' subjective assessments of socioemotional skills and behaviors highlight the need for enhanced preservice teacher training and increased school support for socioemotional learning. These measures are critical to improving the accuracy of teacher evaluations and minimizing the influence of bias. Summary: Teachers are more prone to gender and racial biases when evaluating subjective socioemotional skills, often leading to higher perceived externalizing behaviors in Black boys.Lower ratings of self‐control and interpersonal skills often result in higher externalizing behavior evaluations, with boys, especially Black boys, receiving harsher assessments.Training in socioemotional learning and implicit bias is crucial to ensure fair and accurate assessment of student behaviors, fostering a more equitable educational environment. [ABSTRACT FROM AUTHOR]
Copyright of Psychology in the Schools is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Predictors of Assumed "Bad" Behavior: A Classification and Regression Tree Analysis.
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  Data: <searchLink fieldCode="AR" term="%22Bagneris%2C+Jessica+R%2E%22">Bagneris, Jessica R.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Scott%2C+Edward+D%2E%22">Scott, Edward D.</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Psychology+in+the+Schools%22">Psychology in the Schools</searchLink>. Sep2025, Vol. 62 Issue 9, p2985-2998. 14p.
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  Data: <searchLink fieldCode="DE" term="%22Racism%22">Racism</searchLink><br /><searchLink fieldCode="DE" term="%22Sex+discrimination%22">Sex discrimination</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+bias%22">Statistical bias</searchLink><br /><searchLink fieldCode="DE" term="%22Social+skills%22">Social skills</searchLink><br /><searchLink fieldCode="DE" term="%22Classroom+management%22">Classroom management</searchLink><br /><searchLink fieldCode="DE" term="%22Externalizing+behavior%22">Externalizing behavior</searchLink><br /><searchLink fieldCode="DE" term="%22CART+algorithms%22">CART algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Teachers%22">Teachers</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22United+States%22">United States</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Bias influencing teachers' classroom management is increasingly clear, but the circumstances that influence the likelihood of relying on those biases are less understood. This study employed Classification and Regression Tree (CART) analysis, resulting in four models examining how teachers' appraisals of first‐grade students' externalizing problem behaviors are influenced by students' demographics and teachers' assessments of objective and subjective socioemotional skills. Results from a sample of 3305 teachers in the United States indicated that gender and racial biases are more likely to be relied upon when teachers are assessing subjective skills rather than objective ones. The potential inaccuracies in teachers' subjective assessments of socioemotional skills and behaviors highlight the need for enhanced preservice teacher training and increased school support for socioemotional learning. These measures are critical to improving the accuracy of teacher evaluations and minimizing the influence of bias. Summary: Teachers are more prone to gender and racial biases when evaluating subjective socioemotional skills, often leading to higher perceived externalizing behaviors in Black boys.Lower ratings of self‐control and interpersonal skills often result in higher externalizing behavior evaluations, with boys, especially Black boys, receiving harsher assessments.Training in socioemotional learning and implicit bias is crucial to ensure fair and accurate assessment of student behaviors, fostering a more equitable educational environment. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Psychology in the Schools is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1002/pits.23517
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      – Code: eng
        Text: English
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        PageCount: 14
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        Type: general
      – SubjectFull: Sex discrimination
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      – SubjectFull: Statistical bias
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      – SubjectFull: Social skills
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      – SubjectFull: Classroom management
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      – SubjectFull: Externalizing behavior
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      – SubjectFull: CART algorithms
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      – SubjectFull: Teachers
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      – SubjectFull: United States
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      – TitleFull: Predictors of Assumed "Bad" Behavior: A Classification and Regression Tree Analysis.
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            NameFull: Bagneris, Jessica R.
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            NameFull: Scott, Edward D.
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              M: 09
              Text: Sep2025
              Type: published
              Y: 2025
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