Academic journal article Learning Disability Quarterly

Classification of Students with Reading Comprehension Difficulties: The Roles of Motivation, Affect, and Psychopathology

Academic journal article Learning Disability Quarterly

Classification of Students with Reading Comprehension Difficulties: The Roles of Motivation, Affect, and Psychopathology

Article excerpt

Abstract. Attempts to evaluate the cognitive-motivational profiles of students with reading comprehension difficulties have been scarce. The purpose of the present study was twofold: (a) to assess the discriminatory validity of cognitive, motivational, affective, and psychopathological variables for identification of students with reading difficulties, and (b) to profile students with and without reading comprehension difficulties across those variables. Participants were 87 students who scored more than 1.3 SD below the mean on a standardized reading comprehension battery and 500 typical students in grades 2 through 4. Results using linear discriminant analyses indicated that students with reading comprehension difficulties could be accurately predicted by low cognitive skills and high competitiveness. Using cluster analysis, students with significant deficits in reading comprehension were mostly assigned to a low skill/low motivation group (termed helpless) or a low skill/high motivation group (termed motivated low achievers). Based on these findings, it was concluded that motivation, emotions, and psychopathology play a pivotal role in explaining the achievement tendencies of students with reading comprehension difficulties.

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Recently several researchers have questioned the criteria by which students with learning disabilities (LD) are identified and classified as having specific learning disabilities by use only of the discrepancy between students' cognitive potential and achievement (e.g., Adelman, 1979; Francis et al., 2005; Vaughn & Fuchs, 2003). They have all emphasized the need for more classification/identification studies to enrich our understanding of the attributes and core characteristics of students with LD (e.g., Greenway & Milne, 1999; Kline, Lachar, & Boersma, 1993), and some have suggested the use of affective criteria as well (Vaughn & Fuchs, 2003). Kline et al. (1993), for example, based on the early federal definition on parental input, suggested that personality characteristics can aid identification of the disorder. In a classification study using exploratory hierarchical cluster analysis, the authors drew attention to the fact that, besides having low scores on achievement and intellectual measures, students with LD also had high scores on psychopathology indices (e.g., psychotic features), a finding that agrees with the existence of psychopathological disturbances for students with LD (Breen & Barkley, 1984; Lufi & Darliuk, in press; Lufi, Okasha, & Cohen, 2004; Margalit & Zak, 1984; Martinez & Semrud-Clikeman, 2004; Noel, Hoy, King, Moreland, & Meera, 1992; Swanson & Howell, 1996). In a similar classification study, Sideridis, Morgan, Botsas, Padeliadu, and Fuchs (2006) pointed to the fact that several psychopathology, emotion, and/or motivation variables were significantly more important predictors of learning disabilities than various cognitive and metacognitive measures, although the importance of the latter has been well documented (Botsas & Padeliadu, 2003). Other recent studies have also pointed to the inability of cognitive variables alone to predict specific learning disabilities (e.g., Watkins, 2005). Thus, with regard to the taxonomy of characteristics and behaviors that describe the disorder, the jury is still out.

Most of the problems regarding identification and classification are based on either conceptual or methodological grounds. For example, several researchers have noted limitations in the definition of learning disabilities (e.g., Francis et al., 2005) or the measurement of IQ (MacMillan & Forness, 1998; Stuebing et al., 2002). Some of them took exception to the discrepancy between ability and achievement and proposed alternative models (e.g., Kavale, 2001; Meyer, 2000; Vaughn & Fuchs, 2003) by employing multiple criteria (Sofie & Riccio, 2002). Others expressed concerns regarding overidentification, pointing out problems with the specificity of the criteria used by each state (Scruggs & Mastropieri, 2002), or provided accounts of overidentification (MacMillan & Siperstein, 2001). …

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