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Social perception and metaperception among children with learning and emotional disabilities: A social relations analysis

Gretna Rae Niemi, University of Massachusetts Amherst

Abstract

Social perception has been identified as a significant contributor to how students know themselves and how they are known within the general classroom. These abilities can impact how successfully they negotiate their learning environment. This study addressed how students with learning disabilities (LD) and emotional handicaps (EH) compare on peer, teacher, and self assessments of social and academic domains of behavior. Subjects were 28 students classified as EH and 55 students classified as LD. This study was based on Kenney's Social Relations Model. A round-robin design was used to collect Likert ratings on 18 task and socio-emotional dimensions among peers. Subjects in grades 3 through 9 and their teachers completed an additional set of ratings on six classroom oriented dimensions. All ratings included a self and metaperception judgment. Results yielded consensus among peers on five task and socio-emotional oriented dimensions. Peer and self judgments and metaperceptions indicated that subjects rated themselves less similar to how they predicted their cohorts would rate them. A positive linear trend was found for the task but not for the socio-emotional construct across grade level predictions among the task consensus dimensions. Correlations between student and metaperception ratings of these traits were strong (r's ranging from.58 to .91). Findings are discussed in terms of how students with LD and EH view themselves and others both socially and academically as participants in the natural context of classrooms, and how the accuracy of these perceptions affect their ability to function within their educational environment.

Subject Area

Special education|Elementary education

Recommended Citation

Niemi, Gretna Rae, "Social perception and metaperception among children with learning and emotional disabilities: A social relations analysis" (2002). Doctoral Dissertations Available from Proquest. AAI3056265.
https://scholarworks.umass.edu/dissertations/AAI3056265

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