Patterns of Learning in Young Children with Autism Spectrum Disorders

Background:

Understanding the cognitive profile of children with autism spectrum disorders (ASD) is important to determining whether there is a pattern that is unique to this learning style, potentially informing prognosis and targeting appropriate interventions.

Objectives:

The purpose of this pilot study was to examine the pattern of language and nonverbal intelligence in young children with ASD as measured on standardized developmental and achievement testing as a way to guide future therapeutic and educational interventions.

Methods:

The study design was a retrospective chart review of 168 children with ASD (median age 4.11 years; SD=1.08) evaluated at Lurie Children’s Development Clinic from 8/1/11 to 8/1/16. The following data was extracted from the electronic medical record: date of visit, date of birth, sex, race and ethnicity, educational and therapeutic interventions, and testing results.

Statistical analyses utilized included Student’s t-test and paired t-test, Chi-squared tests and the use of the Bonferroni correction when appropriate. A two-sided p value ≤ 0.05 was considered statistically significant.

Results:

Of the 168 children, 80% were male and 20% were female. In regards to ethnicity, 56% were Caucasian, 26% Hispanic, 13% African American, and 5% responded as “other” or did not report ethnicity.

Sixty-six percent of the sample attended school. Ten percent attended a general education preschool classroom with the remaining in special education settings. Forty-three percent received school based therapy services. Sixteen percent participated in applied behavior analysis therapy (ABA).

Fifty-three participants were evaluated using the Bayley Scales of Infant Development- Third Edition due to lower developmental attainment. They were significantly younger when first diagnosed with ASD (x=4.27, SD=0.9, p<0.0005), suggesting that they required increased levels of support.

One hundred nineteen children completed all of the subtests on the Differential Abilities Scales, Second Edition. The mean GCA score was 77; the mean verbal score was 73; the mean nonverbal score was 82; the mean spatial score was 83. A significant difference was found between verbal and nonverbal reasoning scores, with nonverbal skills being higher (mean difference 7.5, p<0.0005).

Eighty-five children completed all of the subtests on the Bracken School Readiness Assessment. Composite scores fell in the average range (mean 93, SD=16.7). Significant differences between subtests on the Bracken were found. Identifying colors, shapes, letters and numbers were strengths in our population as all fell in the average range. Understanding of size/set comparisons (B-R-S/C), a more language based skill, fell significantly below the mean (x=4.17, SD= 3.736). Performance on this subtest was found to be significantly higher among subjects attending school (mean 4.53, SD=3.836, p=0.004).

Conclusions:

School attendance correlated with more flexible thinking as indicated by improved scores on the set comparisons subtest of the Bracken. Children with ASD display a unique learning style characterized by strengths in visual learning and memory. Future research is required to understand the effects of school and socioeconomic status on learning performance.