Aptos psychologist: Improve social skills for autistic spectrum children is crucial…. see why

Discrepancies Between Academic Achievement and Intellectual Ability in Higher-Functioning School-Aged Children with Autism Spectrum Disorder
Annette Estes1, 2 , Vanessa Rivera2, Matthew Bryan3, Philip Cali2, 4 and Geraldine Dawson5, 6

(1) Department of Speech and Hearing Sciences, University of Washington, Seattle, WA, USA
(2) University of Washington Autism Center, Box 357920, Seattle, WA 98195, USA
(3) Department of Biostatistics, University of Washington, Seattle, WA, USA
(4) Department of Educational Psychology, University of Washington, Seattle, WA, USA
(5) Autism Speaks, New York, NY, USA
(6) Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

Annette Estes
Email: estesa@uw.edu

Published online: 2 November 2010

Abstract
Academic achievement patterns and their relationships with intellectual ability, social abilities, and problem behavior are described in a sample of 30 higher-functioning, 9-year-old children with autism spectrum disorder (ASD).

Both social abilities and problem behavior have been found to be predictive of academic achievement in typically developing children but this has not been well studied in children with ASD. Participants were tested for academic achievement and intellectual ability at age 9. Problem behaviors were assessed through parent report and social functioning through teacher report at age 6 and 9.

Significant discrepancies between children’s actual academic achievement and their expected achievement based on their intellectual ability were found in 27 of 30 (90%) children. Both lower than expected and higher than expected achievement was observed.

Children with improved social skills at age 6 demonstrated higher levels of academic achievement, specifically word reading, at age 9. No relationship was found between children’s level of problem behavior and level of academic achievement.

These results suggest that the large majority of higher-functioning children with ASD show discrepancies between actual achievement levels and levels predicted by their intellectual ability. In some cases, children are achieving higher than expected, whereas in others, they are achieving lower than expected. Improved social abilities may contribute to academic achievement. Future studies should further explore factors that can promote strong academic achievement, including studies that examine whether intervention to improve social functioning can support academic achievement in children with ASD. Keywords Academic achievement – Autism – School-aged – Intellectual ability

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Introduction
Current estimates are that over two hundred fifty thousand children in the US received educational services for Autism under IDEA in 2007 (U.S. Department of Education 2007). This represents a significant effort on the part of federal and state education programs, school districts, educators and families to support children with autism spectrum disorders (ASD). An increasing proportion of children with ASD make significant gains in intellectual ability and behavioral functioning due to early intervention (e.g., Dawson et al. 2010) and as many as 70% of individuals with ASD are now thought to have intellectual ability in the average to above average range (Chakrabarti and Fombonne 2005). As a result, many higher-functioning, school-aged children with ASD are placed in classrooms with same-aged, typically developing peers and are working toward similar academic goals as these peers. However, patterns of academic achievement in higher-functioning children with ASD are not currently well characterized and the factors associated with positive academic outcomes are not well understood. A wide range of academic achievement outcomes, from significantly above expected to far below expected, based on grade placement, has been reported in this population (Griswold et al. 2002). Reading and spelling may be specific areas of challenge (Gross 1994). Impaired reading comprehension, sometimes coexisting with normative reading accuracy, has been reported in children with ASD (Minshew et al. 1994; O’Connor and Klein 2004; Grigorenko et al. 2003; Nation et al. 2006). However, achievement domains such as math and spelling, as well as the factors that may be associated with variability in academic achievement, are not yet well studied in children with ASD.

The relationship between academic achievement and intellectual ability in the general population has been extensively investigated and these domains are closely related in normative samples (e.g., Elliott 1990a). The presence of a significant discrepancy between intellectual ability and academic achievement is, by definition, uncommon in the general population and provides a necessary, but not sufficient, basis for diagnosing a learning disability since federal law PL94-142 was introduced. However, it is important to note that a great deal of complexity surrounds the use of a discrepancy model for diagnosing learning disability and a complete discussion is beyond the scope of this paper (see Evans 2001; Fletcher et al. 2005; Reynolds 1992 for more information). Despite the foregoing caveat, intellectual ability is important to consider as a potential contributor to the variability in academic achievement observed in higher-functioning children with ASD (Mayes and Calhoun 2003; Eaves and Ho 1997). Overall IQ may not adequately describe intellectual ability in ASD because children with ASD often demonstrate discrepancies among various intellectual ability domains. Relative strengths in verbal ability frequently exist alongside visual-spatial processing deficits in individuals with higher functioning autism (Williams et al. 2008). The opposite pattern has also been reported, with strength in visual processing and relative deficit in verbal processing reportedly common in ASD (Happe 1994). These strengths and deficits may be caused by underlying neuropsychological factors that in turn may also impact academic achievement (see Rourke et al. 2002 for an example of this approach). Another complicating factor when investigating the role of IQ in academic achievement in children with ASD is that there may also be developmental changes that systematically impact these discrepancies. In a group of children with ASD followed from preschool through elementary school, Mayes and Calhoun (2003) noted that discrepancies between verbal and nonverbal IQ tend to decrease over time. This was observed in both low and high IQ groups, but this decrease began at an earlier age for the children with high IQs.

Based on the existing literature, it is likely that the typical close relationship between full scale IQ and academic achievement may be more complex in children with ASD. Jones et al. (2009) found that approximately 70 percent of adolescents with ASD from 14 to 16 years of age demonstrated a significant discrepancy between intellectual ability and one or more achievement domains. Achievement strengths and weaknesses were detected in reading, spelling, reading comprehension, arithmetic, and broader mathematical skills. They reported four, largely mutually exclusive, achievement subgroups: reading peak, reading dip, arithmetic peak, and arithmetic dip. Additional research is warranted to replicate this initial study and investigate factors that may contribute to the complicated picture presented by children with ASD in terms of academic achievement.

Social functioning may be another important contributor to the variability in academic achievement observed in children with ASD. Research on academic achievement in children without cognitive impairment suggests a strong relationship between academic achievement and social functioning (DiPerna and Elliot 1999; Welsh et al. 2001). Academic achievement has been shown to correlate with a number of facets of social functioning such as peer acceptance and sociability with peers (for a review, see Wentzel 2005). The absence of reciprocated friendships has been associated with lower levels of academic achievement in middle school while having friends has been positively associated with classroom engagement (Wentzel et al. 2004). Children with positive peer relationships have been found to be more involved in academic tasks in school relative to children who have difficulties with peers (Wentzel 2003). Prosocial peer relationship processes might promote both peer acceptance and academic achievement in children and adolescents (Buhs and Ladd 2001; Wentzel and Caldwell 1997). Rourke and colleagues have developed a neuropsychological framework in which deficits in academic achievement and social functioning may be connected, namely nonverbal learning disability (NLD; see Rourke 2005 for a review). However, the relationship between social functioning and academic achievement in children with ASD is not currently well understood.

Problem behaviors are another important correlate of academic achievement in the general, non-ASD, population. Externalizing behaviors such as aggression and attention problems are known to relate to lower achievement in all core academic areas (McIntosh et al. 2008; Nelson et al. 2004). Moreover, attention-related behaviors such as impulsivity, hyperactivity and poor concentration have been linked to academic failure and problem behaviors (Hinshaw 1992; Fleming et al. 2004). This same cluster of problem behaviors have also been linked to reading difficulties (Rabiner et al. 2000). Recent research on comorbidity in ASD indicates that 55% of children with ASD demonstrate attention problems, 31% meet full criteria for ADHD and 7% meet criteria for oppositional defiant disorder (Leyfer et al. 2006; Lecavalier 2006). Further research is needed to understand whether there is a link between academic achievement and problem behavior in children with ASD.

The present study investigated academic achievement in a sample of children with ASD who were part of a larger longitudinal study. Academic achievement was assessed directly when the children were 9 years of age. Level of problem behavior was based on parent report whereas level of social functioning was based on teacher report at ages 6 and 9 years. It was hypothesized that (1) children with ASD would be more likely to demonstrate observed academic achievement scores that were discrepant from predicted academic achievement scores. A discrepancy was defined as the absolute difference between observed academic achievement and predicted academic achievement, with predicted achievement based on intellectual ability, (2) children with increased problem behaviors at age 6 and 9 would have decreased academic achievement, after controlling for IQ, (3) children with decreased social functioning at age 6 and 9 would have lower academic achievement, after controlling for IQ.

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Methods
Participants
Thirty children with ASD were recruited from a larger longitudinal study on the neurobiology and developmental course of ASD at the University of Washington Autism Center. The full study sample from which these children were recruited consisted of 74 children diagnosed with an ASD at age 3 and followed at ages 6 and 9 years (see Dawson et al. 2004 for details). These thirty children all demonstrated nonverbal IQ over 70 at age 9 to ensure that the academic achievement battery was appropriate to administer. Thus, this study necessarily focused on a subset of the total sample with higher cognitive abilities. Participants obtained an initial research diagnosis at the first time point of the study, between age 3–4 years, using the Autism Diagnostic Interview-Revised (ADI-R; Rutter et al. 2003), Autism Diagnostic Observation Schedule-Generic (ADOS-G; Lord et al. 2003), and clinical judgment. The ADI-R, a parent interview, and the ADOS-G, a semi-structured play observation, are both standardized measures used to diagnose autism spectrum disorders. In addition, information from family history, medical records, cognitive test scores and clinical observation made during the course of the research assessments were considered when assigning the DSM-IV diagnosis. All children who had a history of significant sensory or motor impairment, serious traumatic brain injury, major physical anomalies, genetic disorders associated with ASD (e.g., Fragile X) or neurological disease were excluded from this study. Data reported for the current study was obtained when participating children were aged 6 and 9. Twenty-five children in the sample were boys and 70% were Caucasian. Mothers were on average highly educated, with only 7% reporting no college, 20% reporting some college and 63% reporting college completion. At age 9, 22 children in this sample were placed in regular education classrooms, 5 children spent part of the day in special education classrooms and part of the day in regular education classrooms, and 3 children were placed in mixed regular education/special education classrooms.

Procedures
Intellectual ability was measured at age 6 and 9 and academic achievement was assessed at age 9 by a licensed clinical psychologist or doctoral students in clinical psychology under the supervision of a licensed clinical psychologist at the University of Washington Autism Center. Social functioning was measured by teacher-reported questionnaire at age 6 and 9. Problem behavior was measured by parent-reported questionnaire at age 6 and 9.

Measures
Intellectual Ability and Academic Achievement
The Differential Ability Scales (DAS; Elliott 1990b) was used to measure intellectual ability and academic achievement. It is designed for use with children from ages 2 years 6 months to 17 years 11 months. The School Age Level was administered at ages 6 and 9 and included six core subtests, yielding a General Conceptual Ability (GCA) score reflecting conceptual and reasoning ability and cluster scores measuring verbal and nonverbal skill areas. The DAS Achievement Tests consist of three academic subtests: Basic Number Skills, Spelling, and Word Reading.

Social Functioning and Problem Behavior
The Social Skills Rating System-Teacher Rating Form (SSRS; Gresham and Elliot 1990) is a 57-item assessment of student social skills with normative data based on a diverse sample of 4,000 children from preschool through grade 12. For the current study, the Social Skills scale was used to measure social functioning. The teacher-rated Social Skills scale is divided into three subdomains: Assertion (e.g., introduces self to others), Self-control (e.g., compromises by changing own ideas), and Cooperation (e.g., uses time appropriately). Ratings are based on classroom behavior and indicate how often specific behaviors occurred and the importance of these behaviors for classroom functioning.

The Aberrant Behavior Checklist (ABC; Aman and Singh 1986) is a reliable and valid 58-item measure of problem behaviors known to occur in individuals with moderate to profound developmental disability. The scales were empirically derived by factor analysis. The following scales were used as measures of problem behavior in this study: (1) Irritability (irritability, agitation, crying) and (2) Hyperactivity (hyperactivity, noncompliance). The child’s primary caregiver, usually the mother, completed this questionnaire.

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Results
Academic Achievement Discrepancies
DAS IQ and achievement scores for this sample are described in Table 1. In this sample, IQ increased between ages 6 and 9 for GCA, Verbal and Nonverbal IQ. On average, participants had higher Nonverbal IQ score than GCA and Verbal IQ. However, the majority of this sample (n = 21) demonstrated no difference between Verbal IQ and Nonverbal IQ greater than 1 SD at age 9. We identified only one individual with a Verbal IQ over 1 SD greater than Nonverbal IQ. Eight individuals demonstrated Nonverbal IQ over 1 SD greater than Verbal IQ. No pattern of academic achievement (low or high) was evident when examining these IQ profile patterns. (See below for a description of low and high achievement.) Achievement scores in the Spelling and Word Reading domains centered approximately on the population average of 100, whereas Basic Number Skills scores were lower on average. Word Reading scores demonstrated the expected standard deviation of about 15. Spelling and Basic Number Skills scores were more variable than expected.
Table 1 Intellectual Ability, Academic Achievement, Social Skills and Behavior Problem Scores in Children with ASD
Variable
Age 6 M (SD)
Age 9 M (SD)

Intellectual ability GCA IQ
89.57 (15.75)
97.57 (14.48)

Verbal IQ
88.63 (18.76)
90.73 (18.01)

Nonverbal IQ
93.33 (12.21)
100.20 (16.78)

Academic achievement

Spelling
98.00 (19.35)

Word reading
99.53 (14.42)

Basic number skills
92.70 (18.29)

Social skills

SSRS
91.00 (12.40)
85.00 (15.09)

Problem behaviors

ABC irritability
7.53 (6.63)
8.11 (7.51)

ABC hyperactivity
12.40 (11.25)
11.32 (9.58)

To address hypothesis one, we investigated whether children with ASD were more likely to demonstrate observed academic achievement scores discrepant from predicted academic achievement scores. Predicted scores were based on the reported score distributions in the DAS normative sample (Elliott 1990a). A discrepancy is defined as the absolute difference between observed academic achievement and predicted academic achievement, with predicted achievement based on GCA. More specifically, a discrepancy at age 9 is defined in the DAS technical manual (Elliott 1990a) as an absolute difference between observed achievement score and predicted achievement score of 10 or more in Spelling, 8 or more in Word Reading, and 11 or more in Basic Number Skills. Elliott (1990a) indicates these absolute differences are significant at the .05 level. Figure 1 provides a scatter plot of the discrepancy score and observed score for each of the three academic achievement domains. The dashed lines indicate the boundaries for a discrepancy between observed and predicted score as defined above.

Fig. 1 Observed academic achievement plotted against the discrepancy score in academic achievement in the domains of Spelling, Word Reading, and Basic Number Skills. The dashed lines represent the boundaries of a significant discrepancy

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A majority of the sample demonstrated a discrepancy in academic achievement in all three domains (see Fig. 1). Furthermore, in total, 27 participants in this study were discrepant in at least one of these domains (21 in Spelling, 19 in Word Reading, and 16 in Basic Number Skills). We labeled discrepancies in which observed academic achievement was significantly less than predicted achievement “low achievement”. In this sample, 18/30 participants (60%) had low achievement in at least one domain (9 in Spelling, 8 in Word Reading, and 12 in Basic Number Skills). However, there were also 18 participants (60%) who had at least one area in which observed academic achievement was higher than predicted (high achievement; 12 in Spelling, 11 in Word Reading, 4 in Basic Number Skills). These results suggest that the typically strong association between observed achievement and predicted achievement, with predicted achievement based on the close relationship between achievement and intellectual ability in normative samples, may not hold among children with ASD.

To better understand the large number of discrepancies between observed achievement scores and predicted achievement scores, we investigated the relationship between the three academic achievement domain scores and General Conceptual Ability IQ (GCA) in this sample of children with ASD. The relationship between the three academic achievement domains and GCA, all measured at age 9, is illustrated in Fig. 2. Two lines are used in each plot. The dashed line is the regression line for predicted achievement plotted against GCA based on data from the normative sample (Elliott 1990a). The solid line is the regression line for observed achievement plotted against GCA in the current sample of children with ASD. The association between GCA and spelling was not significant (95% CI (−5.87, 4.46), p = 0.78). GCA was significantly related to the Word Reading (95% CI (0.70, 7.69), p = 0.02) and Basic Number Skills (95% CI (6.71, 12.89), p < 0.0001) domains. Figure 2 illustrates that this relationship between GCA and the Word Reading domain and GCA and the Basic Number Skills domain is consistent with normative sample tables (Elliott 1990a).

Fig. 2 Academic achievement plotted against IQ at age 9. The dashed line is the regression line between academic achievement and GCA IQ in normative sample. The solid line is the regression line between academic achievement and GCA IQ observed in the current sample

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Problem Behavior and Social Functioning
Table 1 provides a summary of the SSRS Social Skills and ABC Hyperactivity and Irritability scores (means and standard deviations) for this sample at ages 6 and 9. The SSRS and the ABC Irritability and Hyperactivity scales were not highly correlated within each time point (Age 6 r values; SSRS/Irr = −.38, SSRS/Hyp = −.20, Irr/Hyp = .43 Age 9 r values; SSRS/Irr = −.09, SSRS/Hyp = .−18, Irr/Hyp = .24). Table 2 provides results from the regression models described next. To address hypothesis two, that children with increased problem behaviors at age 6 and 9 would have decreased academic achievement at age 9, after controlling for IQ, the following strategy was used. Longitudinal relationships between academic achievement and problem behavior were assessed by regressing ABC Problem Behavior scores at age 6 against achievement scores at age 9, controlling for age 6 nonverbal IQ. The domains of Word Reading, Spelling and Basic Number Skills were assessed using three separate models. ABC Irritability and ABC Hyperactivity scores were regressed simultaneously against each achievement domain. This is because conceptually, they are both part of a larger category of problem behavior. Cross sectional relationships between problem behavior and academic achievement were assessed by regressing ABC Problem Behavior scores at age 9 against each academic achievement domain score at age 9, while controlling for nonverbal IQ at age 9.
Table 2 The relationship between social skills, problem behavior and academic achievement in children with ASD
Measures
Longitudinala
Cross sectionalb

Coef
95% CI
p
R 2
Coef
95% CI
p
R 2

Spelling

SSRS score
4.48
[−6.46, 15.42]
.43
.19
3.97
[−4.60, 12.55]
.37
.07

ABC score
.24
.05

Irritability
−13.46
[−28.74, 1.81]
.10
−8.68
[−26.23, 8.86]
.34

Hyperactivity
4.59
[−4.45, 13.64]
.33
3.34
[−10.35, 17.03]
.64

Word reading

SSRS score
8.06
[1.14, 14.98]
.04*
.23
1.51
[−4.30, 7.32]
.62
.26

ABC score
< .01 .01 Irritability 1.04 [−11.97, 14.06] .88 3.74 [−8.66, 16.14] .56 Hyperactivity −1.64 [−9.35, 6.07] .68 −2.51 [−12.19, 7.16] .62 Basic number skills SSRS score 4.44 [−6.03, 14.90] .42 .12 2.58 [−2.98, 8.15] .37 .59 ABC score .03 .01 Irritability −7.68 [−22.97, 7.60] .33 2.62 [−8.89, 14.14] .66 Hyperactivity 5.75 [−3.30, 14.80] .22 −0.73 [−9.71, 8.26] .88 The SSRS and the ABC scores were regressed in separate models with adjustment for nonverbal IQ as measured at the time of the problem behavior or social skills measurement. The ABC Irritability and Hyperactivity scores were included in the same model *p < .05 aLongitudinal analysis of social skills and problem behavior as measured at age 6 against academic achievement at age 9 bCross sectional analysis of social skills and problem behavior as measured at age 9 against academic achievement at age 9 To address hypothesis three, that children with decreased social functioning at age 6 and 9 would have lower academic achievement at age 9, a similar strategy was used. The longitudinal association between social skills and academic achievement was assessed first. The age 6 SSRS Social Skills score was regressed against each age 9 academic achievement domain score, with adjustment for age 6 nonverbal IQ to assess the impact of social skill over and above IQ. The cross-sectional associations were examined by regressing age 9 achievement domain scores against age 9 SSRS Social Skills score, controlling for age 9 nonverbal IQ. Results are provided in Table 2.

Better social skills tended to be associated with better academic achievement in the Word Reading domain for both longitudinal and cross-sectional analyses. The only association to reach statistical significance was between social skills at age 6 and Word Reading at age 9 (95% CI (1.14, 14.06), p = .04). In this analysis, a 15 point difference in SSRS Social Skills score at age 6 was associated with a difference of 8.06 points in Word Reading score at age 9 between subjects of the same nonverbal IQ. No other significant associations between SSRS Social Skills and academic achievement were found.

ABC Problem Behavior scores were not significantly related to academic achievement in this sample. A likelihood ratio test was used to test the overall significance of the effect of ABC Irritability and Hyperactivity scores on academic achievement domain scores for each of these models. No significant relationships were found for either the longitudinal or cross-sectional analyses.

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Discussion
The current study investigated levels of academic achievement in a sample of higher functioning children with ASD. Results showed that school-aged children with ASD demonstrate significant discrepancies between their actual academic achievement and the level of academic achievement predicted from their overall intellectual ability. Of the 30 children in the sample, the large majority, 27/30 or 90%, demonstrated at least one discrepancy in Spelling, Word Reading, or Basic Number Skills. Lower than predicted achievement, in which actual achievement was significantly less than predicted based on intellectual ability, was observed in at least one domain in 18 children (60%). Notably, an equal number of children demonstrated at least one area of higher than predicted achievement. The large proportion of children whose academic achievement was above that predicted by their intellectual ability was unexpected. A more detailed examination of the relationship between achievement in specific domains and intellectual ability provides some additional insight into the findings reported above. On average, Word Reading and Basic Number Skills were related to IQ, whereas Spelling was not. This may reflect shared method variance since Spelling is not tapped specifically on an IQ test, whereas reading and number skills are tapped either indirectly or directly on such tests.

Given that level of social abilities and problem behaviors are correlated with level of academic achievement in typically developing children, we were interested in whether such relationships also exist for children with ASD. Results showed that, after controlling for IQ, level of social skills at age 6 was predictive of level of academic achievement at age 9. Most strongly, social skills at age 6 were related to Word Reading scores at age 9. This relationship is consistent with findings from studies of typically developing children in which various aspects of social functioning are related to academic achievement. Interestingly, concurrent measures of social skills at age 9 were not associated with academic achievement at age 9, over and above Nonverbal IQ. Furthermore, level of problem behaviors assessed at either age 6 or 9 years of age, was not significantly correlated with level of academic achievement at age 9. Thus, the relationships that are present in typically developing samples of children do not appear to apply to children with ASD in all domains.

The current study was limited in several regards. First, our findings are based on academic achievement scores and intelligence testing alone, and do not include, for example, classroom observation, direct assessment of student work, or qualitative parent and teacher report of student ability. Although achievement scores are powerful indicators of the learning that has taken place for some students, these scores alone are not sufficient to conclude that the children who demonstrated low achievement also have a learning disability. A second, but related point, is that the validity of using IQ-discrepancy models to identify learning disabilities is controversial (Fletcher et al. 2005; Kavale 2005). Even proponents of this model agree that the presence or absence of a discrepancy is not sufficient to diagnose a learning disability (Reynolds 1992). Additional research is needed to investigate whether particular patterns of academic achievement may be indicative of learning disabilities in this population.

Finding such heterogeneity in academic achievement was not hypothesized a priori. In particular, we did not expect to find such high rates of both higher and lower than expected achievement. Future research is needed to investigate the etiology of strengths and weakness in reading, spelling or arithmetic in higher-functioning children with ASD. Neuropsychological processes may play a causal role in the specific patterns of academic achievement observed in this sample. Measures of neuropsychological abilities may be useful to extend the measures of IQ reported in this study. For example strengths in various forms of memory may be associated with higher achievement, whereas phonological processing or executive function deficits may be associated with lower achievement.

It has been proposed that NLD may be a helpful construct for understanding both the academic achievement, social difficulties, and other neuropsychological deficits seen in some children with ASD (e.g., Klin et al. 1995). NLD is purported to involve a pattern of poor reading and spelling ability and poor social skills. Our research found only partial support for this pattern, with a significant relationship between word reading and social skills but not spelling ability. There are several significant ways in which descriptions of NLD are not consistent with what is known about ASD more generally and do not fit this sample of higher-functioning children more specifically. ASD is recognized as early as 12-months of age and is reliably diagnosed by 36-months, but children with NLD reportedly do not demonstrate disturbed social functioning below age 4 (Rourke 2005). Additionally, all children in this sample manifested serious social deficits prior to age 4, as they were entered into the longitudinal study between age 3 and 4 years due to a diagnosed autism spectrum disorder. Furthermore, only one child manifested a pattern of higher verbal IQ compared with nonverbal IQ at age 9. Thus, although low achievement patterns were identified in this longitudinal sample of children, future studies are needed to address whether low achievement is linked to specific types of learning disability such as NLD in this population.

Future research is also needed to better understand children with high achievement. Although demonstrating important skills, this group may have academic difficulties and needs that we were not able to identify in the current study, but that may nevertheless greatly impact their academic achievement over time. For example, assessing other aspects of academic success such as independent functioning, ability to work and learn in groups, and creativity could identify areas of unmet need in this group of children.

Future research is needed to replicate these finding in independent samples of children with ASD, and also to extend these findings. For example, utilizing measures of reciprocated friendships, positive peer relationships and prosocial behavior that have been found to be related to academic achievement in typically developing children could help understand the functioning of children with ASD in the classroom. A theoretical model of processes involved in the observed link between social functioning and academic achievement is needed to develop effective targets for intervention. It would also be useful to assess academic functioning more broadly. If neuropsychological strengths and deficits are associated with high and low achievement patterns, intervention approaches could be tailored to these different subgroups of individuals. For example, executive function difficulties, including the ability to plan, organize, and generate novel ideas, may hinder even high achievers as they progress to higher grades in which multiple classes, more complex writing assignments, and novel applications of skills are increasingly required. Importantly, this is a high functioning group of children, with IQs over 70, who had functional speech and other signs of positive outcomes. Early intervention outcome studies should include measures of academic achievement to better characterize the impact of very early autism intervention on later outcomes.

Higher-functioning children with ASD are typically expected to be able to achieve academically, often through instruction in regular education classrooms. This study provides evidence of academic strengths in 9-year-olds with ASD. Thus, these data have the potential to increase awareness of academic potential in children with ASD. In addition, the longitudinal data provides preliminary evidence that social functioning at age 6 may influence later academic achievement. This highlights the need for continued intervention that extends to the early elementary years, even after early intervention in the toddler and preschool years, has ceased. It may be that continued support for social skill development in children with ASD is particularly important. As previous research has shown, individuals with ASD who have higher intellectual abilities and better social skills may be aware of their own deficits and may experience difficulties that increase risk for depression and anxiety (Estes et al. 2007; Sterling et al. 2008). Academic achievement is a potential source of self-worth and mastery that may be available to school-aged children with ASD. Success in school can be a building block toward many positive experiences, including providing important skills needed for independent living and meaningful career choices. Better understanding of risk and protective factors for academic success will assist in the search for effective targets for intervention and educational programming for school-aged children with ASD.

Acknowledgments We wish to thank the children and parents who participated in this study. This research was supported by grants from the National Institute of Child Health and Human Development (U19HD34565, P50HD066782, and R01HD-55741) and the National Institute of Mental Health (U54MH066399).

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References
Aman, M. G., & Singh, N. N. (1986). Aberrant behavior checklist (abc). East Aurora, NY: Slosson Educational Publications, Inc.

Buhs, E., & Ladd, G. (2001). Peer rejection as an antecedent of young children’s school adjustment: an examination of mediating processes. Developmental Psychology, 37(4), 550–560.

Chakrabarti, S., & Fombonne, E. (2005). Pervasive developmental disorders in preschool children: Confirmation of high prevalence. American Journal of Psychiatry, 162, 1133–1141.

Dawson, G., Rogers, S., Munson, J., Smith, M., Winter, J., Greenson, J., Donaldson, A., & Varley, J. (2010). Randomized controlled trial of the early Start Denver Model, a developmental behavioral intervention for toddlers with autism: Effects on IQ, adaptive behavior, and autism diagnosis. Pediatrics, 125, 17–23.

Dawson, G., Toth, K., Abbott, R., Osterling, J., Munson, J., Estes, A., et al. (2004). Defining the early social attention impairments in autism: Social orienting, joint attention, and responses to emotions. Developmental Psychology, 40, 271–283.

DiPerna, J. C., & Elliot, S. N. (1999). Developmennt and validation of the academic competence evaluation scales. Journal of Psychoeducational Assessment, 17, 207–225.

Eaves, L. C., & Ho, H. H. (1997). School placement and academic achievement in children with autism spectrum disorder. Journal of Developmental and Physical Disabilities, 9(4), 277–291.

Elliott, C. D. (1990a). Differential ability scales: Introductory and technical handbook. San Antonio, TX: The Psychological Corporation.

Elliott, C. D. (1990b). Differential ability scales (DAS). San Antonio, TX: The Psychological Corporation.

Estes, A., Dawson, G., Sterling, L., & Munson, J. (2007). Level of intellectual functioning predicts different patterns of associated symptoms in children with autism spectrum disorder. American Journal of Mental Retardation, 112(6), 439–449.

Evans, L. (2001). A conceptual overview of the regression discrepancy model for evaluation severe discrepancy between IQ and achievement scores. Journal of Learning Disabilities, 23(7), 406–412.

Fleming, C. B., Harachi, T. W., Cortes, R. C., Abbott, R. D., & Catalano, R. F. (2004). Level and change in reading scores and attention problems during elementary school as predictors of problem behavior in middle school. Journal of Emotional and Behavioral Disorders, 12(3), 130–144.

Fletcher, J. M., Francis, D. J., Morris, R. D., & Lyon, G. R. (2005). Evidence-based assessment of learning disabilities in children and adolescents. Journal of Clinical Child and Adolescent Psychology, 34(3), 506–522.

Gresham, F. M., & Elliot, S. N. (1990). Social skills rating system (ssrs). Circle Point, MN: American Guidance Service.

Grigorenko, E. L., Klin, A., & Volkmar, F. (2003). Annotation: Hyperlexia: Disability or superability? Journal of Child Psychology and Psychiatry, 44, 1079–1091.

Griswold, D. E., Barnhill, G. P., Myles, B. S., Hagiwara, T., & Simpson, R. L. (2002). Asperger syndrome and academic achievement. Focus on Autism and Other Developmental Disabilities, 17, 94–102.

Gross, J. (1994). Asperger syndrome: A label worth having? Educational Psychology in Practice, 10, 104–110.

Happe, F. G. (1994). Wechsler IQ profile and theory of mind in autism: a research note. Journal of Child Psychology and Psychiatry, 35(8), 1461–1471.

Hinshaw, S. P. (1992). Academic underachievement, attention deficits, and aggression: Comorbidity and implications for intervention. Journal of Consulting and Clinical Psychology, 60, 893–903.

Jones, C. R. G., Happe, F., Golden, H., Marsden, A. J. S., Tregay, S. E., Pickels, A., et al. (2009). Reading and arithmetic in adolescents with autism spectrum disorders: Peaks and dips in attainment. Neuropsychology, 23(6), 718–728.

Kavale, K. A. (2005). Identifying specific learning disability: Is responsiveness to intervention the answer? Journal of Learning Disabilies, 38, 553–562.

Klin, A., Volkmar, F. R., Sparrow, S. S., Cicchetti, D. V., & Rourke, B. (1995). Validity and neuropsychological characterization of Asperger syndrome: Convergence with nonverbal learning disabilities syndrome. Journal of Child Psychology and Psychiatry, 36(7), 1127–1140.

Lecavalier, L. (2006). Behavioral and emotional problems in young people with pervasive developmental disorders: Relative prevalence, effects of subject characteristics, and empirical classification. Journal of Autism and Developmental Disorders, 36, 1101–1114.

Leyfer, O. T., Folstein, S. E., Bacalman, S., Davis, N. O., Dinh, E., Morgan, J., et al. (2006). Comorbid psychiatric disorders in children with autism: Interview development and rates of disorders. Journal of Autism and Developmental Disorders, 36, 849–861.

Lord, C., Rutter, M., DiLavore, P. C., & Risi, S. (2003). Autism diagnostic observation schedule manual. Los Angeles, CA: Western Psychological Services.

Mayes, S. D., & Calhoun, S. L. (2003). Ability profiles in children with autism: Influence of age and IQ. Autism, 7, 65–80.

McIntosh, K., Flannery, K. B., Sugai, G., Braun, D., & Cochrane, K. L. (2008). Relationships between academics and problem behavior in the transition from middle school to high school. Journal of Positive Behavior Interventions, 10, 243–255.

Minshew, N. J., Goldstein, G., Taylor, H. G., & Siegel, D. J. (1994). Academic achievement in high functioning autistic individuals. Journal of Clinical and Experimental Neuropsychology, 16, 261–270.

Nation, K., Clarke, P., & Wright, B. (2006). Patterns of reading ability in children with autism spectrum disorder. Journal of Autism and Developmental Disorders, 36, 911–919.

Nelson, J. R., Benner, G. J., Lane, K., & Smith, B. W. (2004). Academic achievement of K-12 students with emotional and behavioral disorders. Exceptional Children, 71(1), 59–73.

O’Connor, I. M., & Klein, P. D. (2004). Exploration of strategies for facilitating the reading comprehension of high-functioning students with autism spectrum disorders. Journal of Autism and Developmental Disorders, 34, 115–127.

Rabiner, D., Coie, J. D., & Conduct Problems Prevention Research Group. (2000). Early attention problems and children’s reading achievement: A longitudinal investigation. Journal of the American Academy of Child and Adolescent Psychiatry, 39, 859–867.

Reynolds, C. (1992). Two key concepts in the diagnosis of learning disabilities and the habilitation of learning. Learning Disability Quarterly, 15, 2–12.

Rourke, B. (2005). Neuropsychology of learning disabilities: Past and future. Learning Disability Quarterly, 28, 111–113.

Rourke, B., Ahmad, S., Collins, D., Hayman-Abello, B., Haymen-Abello, S., & Warriner, E. (2002). Child clinical/pediatric neuropsychology: Some recent advances. Annual Review of Psychology, 53, 309–339.

Rutter, M., LeCouteur, A., & Lord, C. (2003). Autism diagnostic interview revised: WPS edition manual. Los Angeles, CA: Western Psychological Services.

Sterling, L., Dawson, G., Estes, A., & Greenson, J. (2008). Characteristics associated with presence of depressive symptoms in adults with autism spectrum disorder. Journal of Autism and Developmental Disorders, 38(6), 1011–1018.

U. S. Department of Education. (2007). Table 1.3. Students ages 6 through 21 served under IDEA, Part B, by disability category and state: 2007. Retrieved November 14, 2009, from the Individuals with Disabilities Education Act data Web site: https://www.ideadata.org/TABLES31ST/AR_1-3.htm.

Welsh, M., Parke, R. D., Widaman, K., & O’Neil, R. (2001). Linkages between children’s social and academic competence: A longitudinal analysis. Journal of School Psychology, 30, 463–481.

Wentzel, K. R. (2003). Sociometric status and academic adjustment in middle school: A longitudinal study. Journal of Early Adolescence, 23, 5–28.

Wentzel, K. R. (2005). Peer relationships, motivation, and academic performance at school. In A. J. Elliott & C. S. Dweck (Eds.), Handbook of competence and motivation ( (pp. 279–296). New York: Guilford.

Wentzel, K. R., Barry, C. M., & Caldwell, K. A. (2004). Friendships in middle School: Influences on motivation and school adjustment. Journal of Educational Psychology, 96, 195–203.

Wentzel, K. R., & Caldwell, K. (1997). Friendships, peer acceptance, and group membership: relations to academic achievement in middle school. Child Development, 68(6), 1198–1209.

Williams, D. L., Goldstein, G., Kojkowski, N., & Minshew, N. J. (2008). Do individuals with high functioning autism have the IQ profile associated with nonverbal learning disability? Research in Autism Spectrum Disorders, 2(2), 353–361.

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