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Using teacher perceptions to screen for primary students with high risk behaviours

Published online by Cambridge University Press:  26 February 2016

George Sugai  and
David Evans
George Sugai*
Affiliation:
University of Oregon
David Evans*
Affiliation:
University of Western Sydney - Macarthur
*
Address for Correspondence: George Sugal, University of Oregon, 275 College of Education, Eugene, Oregon 97403, or David Evans, University of Westem Sydney - Macarthur, P. O. Box 555, Campbelttown, 2560 (email: [email protected]).
Address for Correspondence: George Sugal, University of Oregon, 275 College of Education, Eugene, Oregon 97403, or David Evans, University of Westem Sydney - Macarthur, P. O. Box 555, Campbelttown, 2560 (email: [email protected]).
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Abstract

One of the first steps toward meeting the educational needs of the increasing number of students who display high risk behaviours is to identify who these students are and how many exist in public school classrooms. The purpose of the present study was twofold in nature: (a) to use teacher ratings to determine the proportion of students who were judged to be high risk for academic and social behaviour failure; and (b) to determine the efficiency and accuracy with which a screening instrument, the High Risk Screening Survey, could determine the proportion of students judged to be high risk. This paper provides a preliminary examination of the usefulness and efficiency of teacher reports and the High Risk Screening Survey. Three hundred and nine teachers, representing 29 schools in a large metropolitan area in Western Australia, rated 8,722 students in preschool and first through seventh grades. Preliminary field validation results indicated that the High Risk Screening Survey appeared to be an efficient, useful, and descriptive tool for assessing the general risk status of students in preschool and grades one through seven. In addition, across seven variables, most students were seen by their teachers as about or above average; in reading, math, and language arts, approximately 7% of all students were judged by their teachers as significantly behind their peers; and in self-management and social interactions with peers and adults, approximately 2% of students were judged by their teachers as significantly behind their peers. Additional findings, limitations, and recommendations are discussed.

Type
Research Article
Information
Australasian Journal of Special Education , Volume 21 , Issue 1 , January 1997 , pp. 18 - 35
Copyright
Copyright © The Australian Association of Special Education 1997

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References

Aksamit, , (1990). Mildly handicapped and at-risk students: The graying of the line. Academic Therapy, 25, 277–89.Google Scholar
Carnine, D. (1991). Curricular interventions for teaching higher order thinking skills to all students; Introduction to the special series. Journal of Learning Disabilities, 24,261–269.Google Scholar
Carnine, D., & Kameenui, E. (1990). The general eduction initiative and children with special needs: A false dilemma in the face of true problems. Journal of Learning Disabilities, 23, 141–144, 148.Google Scholar
Cronbach, L. & Meehl, P. (1955). Construct validity in psychological test. Psychological Bulletin, 52, 281–302.Google Scholar
Evans, D. (1996). Systematic monitoring of beginning reading skills. Paper presented at the 20th National Conference of the Australian Association of Special Education, Hobart.Google Scholar
Fuchs, D., & Fuchs, L. (1989). Prereferral interventions: Using mainstream assistance teams to accommodate difficult-to-teach students in general education. (Abstract 24, September). ERIC/OSEP Special Project on Interagency Information Dissemination. Washington, D.C.: ERIC Clearinghouse.Google Scholar
Gerber, M., & Semmel, M. (1984). Teacher as imperfect test. Reconceptualizing the referral process. Educational Psychologist, 19, 137–148.Google Scholar
Hopkins, K., George, C., & Williams, D. (1985). The concurrent validity of standardised achievement tests by content area using teacher’s ratings as criteria. Journal of Educational Measurement, 22, 177–182.Google Scholar
Juel, C. (1988). Learning to read and write: A longitudinal study of 54 children from first through fourth grades. Journal of Educational Psychology, 80,437–447.Google Scholar
Lombardi, T., Odell, K., & Novotny, D. (1990). Special education and students at-risk: Findings from a national study. Remedial and Special Education, 21(1), 56–62.Google Scholar
Odom, S., McConnell, S., & McEvoy, M. (1992). Social competence of young children with disabilities: Issues and strategies for intervention. Baltimore, MD: Paul H. Brookes.Google Scholar
Slavin, R., & Madden, N. (1989). What works for students at risk: A research synthesis. Educational Leadership, 46,4–13.Google Scholar
Tindal, G., & Marston, D. (1990). Classroom-based assessment: Evaluating instructional outcomes. Columbus, OH: Merrill.Google Scholar
Tindal, G., Nolet, V., & Hall, T. (April, 1990). The technical adequacy of curriculum-based measures in making educational decisions: A look at construct validity. Paper presented at the 1990 American Educational Research Association Annual Meeting, San Francisco, CA.Google Scholar
Westwood, P. (1991). A shrinking service. Australian Journal of Remedial Education, 23(1), 1.Google Scholar
Will, M. (1986). Educating children with learning problems: A shared responsibility. Exceptional Children, 52,411–415.CrossRefGoogle ScholarPubMed