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

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  • Author(s): Jessica R. Bagneris (ORCID Jessica R. Bagneris (ORCID 0000-0001-7622-0788); Edward D. Scott (ORCID Edward D. Scott (ORCID 0000-0002-8427-0109)
  • Language:
    English
  • Source:
    Psychology in the Schools. 2025 62(9):2985-2998.
  • Publication Date:
    2025
  • Document Type:
    Journal Articles
    Reports - Research
  • Additional Information
    • Availability:
      Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
    • Peer Reviewed:
      Y
    • Source:
      14
    • Education Level:
      Elementary Education
      Early Childhood Education
      Grade 1
      Primary Education
      Higher Education
      Postsecondary Education
    • Subject Terms:
    • Accession Number:
      10.1002/pits.23517
    • ISSN:
      0033-3085
      1520-6807
    • 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.
    • Abstract:
      As Provided
    • Publication Date:
      2025
    • Accession Number:
      EJ1479962