Schools have worked diligently to identify reading disabilities in their students as early as first- and second-grade, but schools also should focus on the early identification of students who have potential math disabilities (MD), write a group of researchers in a recent study published in Exceptional Children.
Math disabilities (MD) are as common as reading disabilities in students, but have been the focus of far less attention, the study points out.
Screening first-graders for potential math disabilities would allow educators to provide early interventions and to gauge responsiveness-to-intervention (RTI), one of the more promising models for better identification of learning disabilities, report the researchers. “Identifying this risk pool early, in kindergarten or first grade, permits students to participate in prevention services before the onset of substantial academic deficits,” they write.
Researchers tested several screening measures on a sample of first graders in a southeastern metropolitan school district. The screening measures included: fact retrieval, Curriculum-Based Measurement (CBM) Computation, Number Identification/Counting and CBM Concepts/Applications. They conclude that CBM Concepts/Applications and CBM Computation were good predictors of math disabilities, with CBM Concepts/Applications the superior predictor of the two, while CBM Computation demonstrated greater validity for progress monitoring.
“Our results suggest that educators can efficiently use CBM Concepts/Applications and CBM Computation in a first-cut effort to identify risk for poor math development, perhaps in conjunction with short-term progress monitoring to verify risk status,” the researchers write. “For progress monitoring, study findings indicate that CBM Computation may provide valid information about the development of math competence across first grade.”
In screening for math development, it’s important to distinguish between students with disabilities for math word problems and those with disabilities for calculations, the researchers advise, because profile analysis showed distinctive patterns of cognitive abilities for each.
For the study, researchers derived their sample from 667 1st-grade students in 41 classrooms whose parents had given consent for their children to participate in an intervention study. The children took a broad set of math measures (Woodcock-Johnson III, Word Identification, Calculation and Applied Problems subtests). Based on the results, 139 students were identified as low performers (below the 21st percentile) and randomly assigned to receive tutoring or not to receive tutoring. Another group of 180 students with average scores served as controls. High performers were not included in the study.
After attrition, the final sample in the three groups numbered 225. Researchers monitored the progress of these students with weekly assessments over the course of 1st grade. When the tutored group showed significant gains over the untutored low-performers, they were eliminated from the study because they provided limited predictive value for MD, the researchers explain, which left an untutored sample of 170 students.
Prevalence of math disabilities
The prevalence of MD for the average students in the study was 2.7% for MD-calculation and 4.4% for MD-word problems; among the low-scoring group it was 35.1% for MD-calculation and 33.3% for MD-word problems, the researchers report. (Many students had disabilities in both areas). For the original group of 667 students, the researchers estimate the prevalence of MD-calculation at 9.3% and of MD-word problems at 10.20%.
The researchers used 10th percentile as the cut-point in the screening measures results. “The MD literature sometimes employs cut-points as high as the 35th percentile to designate math difficulty,” the researchers write. “We, by contrast, selected the 10th percentile so we could generalize findings to school contexts, which reserve the designation of disability for extremely poor performance.”
Unlike previous studies, the researchers note, they examined week-by-week progress with single-skill and multiple-skill measures during 1st grade. Previous studies have used single-skill measures and collected one-time following data. The researchers also assessed MD at the end of second grade, nearly 2 years after collecting the initial screening data. In the spring of 2nd grade, the researchers administered two outcome measures (WRAT-3 Arithmetic and Jordan’s story problems).
Multiskill screening measures
The most effective screening measures proved to be multiskill screeners and not simple screeners, the researchers note. “This finding challenges the notion that a single math task may serve as a viable predictor of subsequent mathematics difficulties in school as the range of skills required for success grows,” the authors note. Not only does a multiskill screener assess a larger set of competencies, but a single-skill screener may insufficiently discriminate at the lower end of the distribution scale. The relatively easy single-skill screener, Number Identification/Counting, may hold some promise for forecasting second-grade MD for calculations, they note, but this needs further study. This tool did not function as well for monitoring progress, they note.
“Mathematics Screening and Progress Monitoring at First Grade: Implications for Responsiveness to Intervention” by Lynn Fuchs, Douglas Fuchs, Donald Compton et. al. Exceptional Children, Volume 73, Number 3, pp. 311-330.
Published in ERN April 2007 Volume 20 Number 4