nach oben

Prevention Science

Erschienen in:

01.12.2014

What Affects Teacher Ratings of Student Behaviors? The Potential Influence of Teachers’ Perceptions of the School Environment and Experiences

verfasst von: Elise T. Pas, Catherine P. Bradshaw

Erschienen in: Prevention Science | Ausgabe 6/2014

Einloggen, um Zugang zu erhalten

Abstract

Teachers serve as the natural raters of students within the school and classroom contexts. Yet teachers’ ratings of their students may vary based on these contextual factors. The current study explored the extent to which teacher perceptions of the school environment predict their longitudinal ratings of student behaviors. Data for this study come from 702 teachers in 42 elementary schools. Teachers self-reported their perceptions of the school context at a single time point, and provided ratings of their students’ behavior via the Teacher Observation of Classroom Adaption-Checklist (TOCA-C) across three school years. Latent profile analysis identified three latent classes of teachers based on their ratings of school organizational health, burnout, and efficacy. A regression framework demonstrated an association between the baseline profiles in relation to TOCA-C ratings of student behavior across 3 years. Teachers with more favorable perceptions of the environment had lower initial ratings of concentration problems, disruptive behavior, and internalizing symptoms, and higher ratings of prosocial behaviors and family involvement. They also showed slower growth in their ratings of emotion dysregulation and greater increases of their ratings of family involvement over time. This work is particularly important for determining the extent to which teacher ratings may be biased by teacher and contextual factors, and may have implications for the identification of teachers who may rate students poorly over time.

Achenbach, T. M., McConaughy, S. H., & Howell, C. T. (1987). Child/adolescent behavioral and emotional problems: Implications of cross-informant correlations for situational specificity. Psychological Bulletin, 101, 213–232. doi:10.1037/0033-2909.101.2.213.CrossRefPubMed

Berg-Nielsen, T. S., Vika, A., & Dahl, A. A. (2003). When adolescents disagree with their mothers: CBCL-YSR discrepancies related to maternal depression and adolescent self-esteem. Child: Care, Health and Development, 29, 207–213.

Bradshaw, C. P., Pas, E. T., Goldweber, A., Rosenberg, M., & Leaf, P. J. (2012). Integrating school-wide positive behavioral interventions and supports with tier 2 coaching to student support teams: The PBISplus model. Advances in School Mental Health Promotion, 5, 177–193.CrossRef

Conduct Problems Prevention Research Group. (2002). Evaluation of the first 3 years of the fast track prevention trial with children at high risk for adolescent conduct problems. Journal of Abnormal Child Psychology, 30, 19–35.CrossRef

Crocker, L., & Algina, J. (1986). Introduction to classical and modern test theory. Belmont: Wadsworth.

Debnam, K., Pas, E. T., & Bradshaw, C. P. (2012). Secondary and tertiary support systems in place among schools implementing universal School-wide Positive Behavioral Interventions and Supports (SWPBIS): A descriptive analysis. Journal of Positive Behavior Interventions, 14, 142–152. doi:10.1177/1098300712436844.CrossRef

Dobbs, J., & Arnold, D. H. (2009). Relationship between preschool teachers’ reports of children’s behavior and their behavior towards those children. School Psychology Quarterly, 24, 95–105.PubMedCentralCrossRefPubMed

Dwyer, S. B., Nicholson, J. M., & Battistutta, D. (2006). Parent and teacher identification of children at risk of developing internalizing or externalizing mental health problems: A comparison of screening methods. Prevention Science, 7, 343–357.CrossRefPubMed

Espinosa, L. M., & Laffey, J. M. (2003). Urban primary teacher perceptions of children with challenging behaviors. Journal of Children and Poverty, 9, 135–156.CrossRef

Glisson, C., & Green, P. (2006). The effects of organizational culture and climate on the access to mental health care in Child welfare and Juvenile Justice systems. Administration and Policy in Mental Health and Mental Health Services Research, 33, 433–448.CrossRefPubMed

Hagenaars, J. A., & McCutcheon, A. L. (2002). Applied latent class analysis. Cambridge: Cambridge University Press.CrossRef

Hamre, B. K., & Pianta, R. C. (2005). Can instructional and emotional support in the first-grade classroom make a difference for children at risk of school failure? Child Development, 76, 949–967.CrossRefPubMed

Hoy, W., & Feldman, J. (1987). Organizational health: The concept and its measure. Journal of Research and Development in Education, 20, 30–38.

Hoy, W. K., & Woolfolk, A. E. (1993). Teachers’ sense of efficacy and the organizational health of schools. The Elementary School Journal, 93, 356–372.CrossRef

Ialongo, N. S., Werthamer, L., Kellam, S. G., Brown, C. H., Wang, S., & Lin, Y. (1999). Proximal impact of two first-grade preventive interventions on the early risk behaviors for later substance abuse, depression, and antisocial behavior. American Journal of Community Psychology, 27(5), 599–641. doi:10.1023/a:1022137920532.CrossRefPubMed

Ialongo, N. S., Poduska, J. M., Werthamer, L., & Kellam, S. G. (2001). The distal impact of two first-grade preventive interventions on conduct problems and disorder in early adolescence. Journal of Emotional and Behavioral Disorders, 9, 146–160.CrossRef

Jennings, P. A., & Greenberg, M. T. (2009). The Prosocial Classroom: Teacher social and emotional competence in relation to child and classroom outcomes. Review of Educational Research, 79, 491–525. doi:10.3102/0034654308325693.CrossRef

Kam, C.-M., Greenberg, M. T., & Walls, C. T. (2003). Examining the role of implementation quality in school-based prevention using the PATHS curriculum. Prevention Science, 4, 55–63.CrossRefPubMed

Kellam, S. (1990). Development epidemiological framework for family research on depression and aggression. In G. R. Patterson (Ed.), Depression and aggression in family interaction (pp. 11–46). Hillsdale: Erlbaum.

Kellam, S.G. (1994). Testing theory through developmental epidemiologically-based prevention research (pps. 37–57). In A. Cazares & A. Beatty (Eds.), Scientific Methods for Prevention Research. National Institute on Drug Abuse Research Monograph No. 139. DHHS Pub. No. 94-363.

Kellam, S. G., & Rebok, G. W. (1992). Building developmental and etiological theory through epidemiologically based preventive intervention trials. In J. McCord & R. E. Tremblay (Eds.), Preventing antisocial behavior: interventions from birth through adolescence (pp. 162–195). New York: Guilford Press.

Kellam, S. G., Branch, J. D., Agrawal, K. C., & Ensminger, M. E. (1975). Mental health and going to school: the Woodlawn program of assessment, early intervention and intervention and evaluation. Chicago: University of Chicago Press.

Kellam, S. G., Ling, X., Merisca, R., Brown, C. H., & Ialongo, N. S. (1998). The effect of the level of aggression in the first grade classroom on the course and malleability of aggressive behavior into middle school. Development and Psychopathology, 10, 165–185.CrossRefPubMed

Koth, C. W., Bradshaw, C. P., & Leaf, P. J. (2009). Teacher Observation of Classroom Adaptation-Checklist (TOCA-C): Development and factor structure. Measurement and Evaluation in Counseling and Development, 42, 15–30.CrossRef

Little, R. J. (1995). Modeling the dropout mechanism in repeated measures studies. Journal of the American Statistical Association, 90, 1112–1121.CrossRef

Lo, Y., Mendell, N., & Rubin, D. (2001). Testing the number of components in a normal mixture. Biometrika, 88, 767–778.CrossRef

Mangelsdorf, S. C., Schoppe, S. J., & Buur, H. (2000). The meaning of parental reports: A contextual approach to the study of temperament and behavior problems in childhood. In V. J. Molfese & D. L. Modfese (Eds.), Temperament and personality development across the lifespan (pp. 121–140). London: Erlbaum.

Mascendaro, P. M., Herman, K. C., & Webster-Stratton, C. (2012). Parent discrepancies in ratings of young children’s co-occurring internalizing symptoms. School Psychology Quarterly, 27, 134–143. doi:10.1037/a0029320.CrossRefPubMed

Maslach, J., & Jackson, S. E. (1981). The measurement of experienced burnout. Journal of Occupational Behaviour, 2, 99–113.CrossRef

Maslach, C., Jackson, S. E., & Leiter, M. P. (1996). Maslach Burnout Inventory manual (3rd ed.). Palo Alto: Consulting Psychologists Press, Inc.

McDermut, J. F., Haaga, D. A. E., & Bilek, L. A. (1997). Cognitive bias and irrational beliefs in major depression and dysphoria. Cognitive Therapy and Research, 21, 459–476.CrossRef

Merrell, K. W. (2001). Assessment of children’s social skills: Recent developments, best practices, and new directions. Exceptionality, 9, 3–18.CrossRef

Muthén, B. (2004). Latent variable analysis: Growth mixture modeling and related techniques for longitudinal data. In D. Kaplan (Ed.), Handbook of quantitative methodology for the social sciences (pp. 345–368). Thousand Oaks: Sage.

Muthén, L. K., & Muthén, B. O. (1998–2010). Mplus user’s guide (6th ed.). Los Angeles: Author.

Nagin, D. S. (2005). Group-based modeling of development over the life course. Cambridge: Harvard University Press.CrossRef

Nylund, K. L., Asparouhov, T., & Muthén, B. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling, 14, 535–569.CrossRef

Petras, H., Chilcoat, H. D., Leaf, P. J., Ialongo, N. S., & Kellam, S. G. (2004). Utility of TOCA-R scores during the elementary school years in identifying later violence among adolescent males. Journal of the American Academy of Child and Adolescent Psychiatry, 43, 88–96.CrossRefPubMed

Pianta, R. (1999). Enhancing relationships between children and teachers. Washington: American Psychological Association.CrossRef

Ramaswamy, V., Desarbo, W. S., Reibstein, D. J., & Robinson, W. T. (1993). An empirical pooling approach for estimating marketing mix elasticities with PIMS data. Marketing Science, 12, 103–124.CrossRef

Renk, K., & Phares, V. (2004). Cross-informant ratings of social competence in children and adolescents. Clinical Psychology Review, 24, 239–254.CrossRefPubMed

Schwartz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6, 461–464.CrossRef

Skaalvik, E. M., & Skaalvik, S. (2007). Dimensions of teacher self-efficacy and relations with strain factors, perceived collective teacher efficacy, and teacher burnout. Journal of Educational Psychology, 99, 611–625.CrossRef

Skiba, R. J. (1989). The importance of construct validity: Alternative models for the assessment of behavioral disorders. Behavioral Disorders, 14, 175–185.

Stanger, C., & Lewis, M. (1993). Agreement among parents, teachers, and children on internalizing and externalizing behavior problems. Journal of Clinical Child Psychology, 22, 107–115. doi:10.1207/s15374424jccp2201_11.CrossRef

Thorndike, E. L. (1920). A constant error in psychological ratings. Journal of Applied Psychology, 4, 25–29.CrossRef

Webster-Stratton, C., & Hammond, M. (1988). Maternal depression and its relationship to life stress, perceptions of child behavior problems, parenting behaviors, and child conduct problems. Journal of Abnormal Child Psychology, 16, 299–315.CrossRefPubMed

Werthamer-Larsson, L., Kellam, S., & Wheeler, L. (1991). Effect of first grade classroom environment on shy behavior, aggressive behavior, and concentration problems. American Journal of Community Psychology, 19, 585–602.CrossRefPubMed

Wright, D., & Torrey, G. K. (2001). A comparison of two peer-referenced assessment techniques with parent and teacher ratings of social skills and problem behaviors. Behavioral Disorders, 26, 173–182.

Titel: What Affects Teacher Ratings of Student Behaviors? The Potential Influence of Teachers’ Perceptions of the School Environment and Experiences
verfasst von: Elise T. Pas
Catherine P. Bradshaw
Publikationsdatum: 01.12.2014
Verlag: Springer US
Erschienen in: Prevention Science / Ausgabe 6/2014
Print ISSN: 1389-4986
Elektronische ISSN: 1573-6695
DOI: https://doi.org/10.1007/s11121-013-0432-4

Springer Medizin

Abstract

Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten

Weitere Artikel der Ausgabe 6/2014

Fit for Purpose: A Form and Function-Based Taxonomy for Prevention is Arguably More Refined, Accurate, and Predictive

Prevention 2.0: Targeting Cyberbullying @ School

Commentary on Crowley et al.’s Research Priorities for Economic Analysis of Prevention

Understanding Proximal–Distal Economic Projections of the Benefits of Childhood Preventive Interventions

School Engagement Mediates Long-Term Prevention Effects for Mexican American Adolescents

School Victimization and Substance Use among Adolescents in California