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

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. GEORGIOS D. SIDERIDIS, University of Crete, Institute of Language & Speech Processing. ANGELIKI MOUZAKI, University of Crete, Institute of Language & Speech Processing. PANAGIOTIS SIMOS, University of Crete, Institute of Language & Speech Processing. ATHANASSIOS PROTOPAPAS, University of Crete, Institute of Language & Speech Processing. 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 & Volume 29, Summer 2006 159 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). Yet other researchers have attempted to address the problematic issues of heterogeneity, comorbidity, social, emotional, or cultural disadvantages, and inadequate instruction by focusing on how individuals react to learning (i.e., responsiveness to treatment) (e.g., Gresham, 2002; Vaughn & Fuchs, 2003). Finally, some authors have even raised concerns regarding the mere existence of the construct of LD (e.g., Fuchs, Fuchs, Mathes, Lipsey, & Roberts, 2001). Thus, there may be a need to broaden the classification criteria of students with LD in order to understand the specifics of the disorder with the ultimate goal of developing effective interventions. In terms of motivation, the literature has been compelling with regard to the fact that students with learning deficits lack the motivation to engage in academic tasks (Bouffard & Couture, 2003; Fulk, Brigham, & Lohman, 1998; Lepola, 2004; Lepola, Salonen, & Vauras, 2000; Olivier & Steenkamp, 2004; Valas, 1999, 2001). Thus, lack of motivation or maladaptive motivational thinking may account for the large discrepancy between typical student groups and those with LD on their engagement with academic tasks (e.g., Pintrich, Anderman, & Klobucar, 1994). For example, students with LD appear to possess the typical characteristics of helplessness (Sabatino, 1982; Sutherland & Singh, 2004). In a series of studies, Sideridis found that students with LD gave up significantly more easily compared to students without LD, viewed academic tasks as threats, developed negative emotions and cognitions both prior to and following an academic task, and employed regulatory systems that have their basis in avoidance motivation (Sideridis, 2003, 2005b, 2006a, 2006b, in press). The above effects were associated with regulation failure (i.e., students’ inability to regulate academic-related behaviors that are conducive to learning and achievement). Given the salient role of these factors for reading behaviors in general, it is even more important to examine the contribution of motivational characteristics in students’ learning and school experience (Guthrie & Cox, 2001; Guthrie & Wigfield, 1999; Lepola, Salonen, Vauras, & Poskiparta, 2004). Affect and Learning Disabilities Limited research has investigated the affective experience of students with learning disabilities. For example, Yasutake and Bryan (1995) noted that students with LD are at a greater risk for experiencing negative affect than their peers. Affective reactions (a) are thought to be primary and to precede cognitive processing (Forgas, 1991; Zajonc, 1980); (b) are considered automatic, not dependent on controlled processes; and (c) are believed to have an important impact on subsequent cognitive processing and behavior (De Houwer & Hermans, 2001). Therefore, the role of affective processing is of particular importance because it may contribute substantially to defining types of engagement and motivational states during engagement. With regard to negative affect, students with LD usually have higher levels than their typical peers (Manassis & Young, 2000). This finding has been linked to the difficulty of students with LD to socialize (Bryan, Burstein, & Ergul, 2004), in addition to their low achievement. Further, both outcomes have been associated with Learning Disability Quarterly 160 these students’ confusion, anxiety, and frustration at school (Bay & Bryan, 1991). Psychopathology and Learning Disabilities Another class of variables that may expand the classification scheme of LD is psychopathology. In a recent meta-analysis, the prevalence of depression among students with LD was estimated to be at about 88% of the reviewed studies (Sideridis, 2006a), with LD students exceeding normative levels (either compared to typical peers or compared to prevalence rates in the general population) (see also Maag & Reid, 2006). Similarly, the prevalence of anxiety disorders among LD students has been found to be well above normative levels (e.g., Lufi & Darliuk, in press; Lufi et al., 2004; Paget & Reynolds, 1984). Additionally, Sideridis et al. (2006) pointed to the fact that psychopathology accounted for significant amounts of variability in achievement, compared to several cognitive and metacognitive variables. Based on the above, we suggest that classification studies are needed for at least three reasons: (a) because the identification criteria of the disorder have been questioned (Francis et al., 2005; Vaughn & Fuchs, 2003), and several researchers have asked for a reconceptualization of the disorder (Kavale, 2001; Sofie & Riccio, 2002); (b) because cognitive variables are sometimes poor predictors of LD (Forness, Keogh, MacMillan, Kavale, & Gresham, 1998; Watkins, 2005; Watkins, Kush, & Glutting, 1997; Watkins, Kush, & Schaefer, 2002); and (c) because empirical classification studies provide evidence of the presence of comorbid characteristics (e.g., Kline et al., 1993), which often are stronger predictors of LD-related outcomes than those from cognitive variables. Expanding the taxonomy of LD characteristics may be particularly important for the development of interventions that target both academic and nonacademic (e.g., social) outcomes. We propose that the role of the above variables as indicators of LD has been greatly underestimated and hypothesize that motivation, affect, and psychopathology, along with cognition, will contribute to a fuller understanding of the disorder. Such an understanding will aid the development of interventions targeting both academic and nonacademic outcomes through various means (e.g., the development of motivated behavior). Thus, one goal of the present study was to identify factors that significantly differentiate bewteen students with and without reading comprehension difficulties. Our decision to focus on text comprehension ability was based on the notion that extraction of meaning from text reflects the ultimate goal of the reading process, which in turn depends on several basic language and reading processing abilities (e.g., phonological awareness and decoding, and word recognition). Additionally, we sought to understand how individual predictors and linear combinations of those predictors explain the presence of subgroups of students with specific motivational and cognitive characteristics that are (or not) conducive to learning and achievement. Thus, the present study was designed to answer the following two research questions: 1. Are motivation, emotions, and psychopathology significant predictors of reading comprehension difficulties? 2. How do motivational, emotional, and psychopathology indices interact with cognitive variables to form clusters of student profiles, and how are students with reading comprehension difficulties allocated into those profiles?