Using RTI Data to Inform SLD Determination: Part 5 of a 5 Part Blog Series

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    In my last blog entry, I detailed our state’s efforts directed at supporting the RTI component of the specific learning disabilities (SLD) eligibility process, and also discussed the importance of a comprehensive tiered instructional delivery system. The need to provide training on how to implement an effective Tier 2 system was identified through the statewide collection and review of SLD eligibility files. Conducting an individualized, comprehensive evaluation was the other area identified as a critical training need for the state.

    Idaho’s revised SLD policy reflected a significant shift in the nature of the evaluation. Under the old model, the state required broad area academic achievement scores and regressed full IQ scores, looking for a discrepancy of 15 points between the two. Every learning disabilities assessment under the old model followed a similar format—administer the two tests, subtract the scores, and compare that value with 15 to make the eligibility decision. Obviously, this description is an oversimplification of the process. Many school psychologists and multidisciplinary teams (MDTs) conducted in-depth evaluations to help inform the intervention for the student; however, some did not, choosing instead to follow the process on paper by administering the tests and subtracting the scores.

    Under the new model, the MDT was being asked to conduct a very individualized, specific evaluation focused on the student’s specific area(s) of concern. The change meant that the “one size fits all” approach to evaluation would no longer be appropriate; instead, the MDT now needed to develop a hypothesis about the student’s learning needs, to administer academic assessment to further diagnose the academic issue or issues of concern, and then to assess psychological processes to help identify the potential underlying causes of the child’s learning difficulty.

    As we began the initial rollout of the policy with information sessions designed to help people understand the new process, this more clinical approach to diagnosis was met with mixed reviews. On the one hand, many people felt that the new eligibility approach was more closely aligned with our current conceptualizations of learning disability and that the new eligibility model more accurately reflected the construct of SLD. However, because so much of our special education system is driven by compliance monitoring (focusing on inputs, not outcomes), school teams also noted concern about implementing the process correctly, and wondered who would decide whether the team had made the right decision when their files were monitored for compliance. This mixed reaction is probably best captured by one school psychologist’s statement to me following a training session:

    “I think this new model is better practice for our kids, but under the discrepancy approach, I knew that compliance monitors and I would agree—I wasn’t concerned that they would say I was out of compliance, because the criteria were so clearly defined. Now I’m worried that whether I am in compliance will be determined by the state representative’s understanding of the process, which may differ from my own.”

    His comment reflects a tension that is important to consider when we think about SLD. There are some common characteristics across students with SLD; however, SLD are also heterogeneous, making the determination of set cut scores or even making the identification of a standard battery for math disability or reading disability that could be universally applied an extremely difficult task. In other words, the identification, evaluation, and treatment of SLD requires a considerable amount of professional knowledge and expertise.

    An increasing body of evidence supports what has been called the “specificity hypothesis” of SLD. This hypothesis essentially says that SLD can have an impact on a very specific area of academic functioning, leaving others intact. It is the specific nature of an SLD that differentiates it from more general learning problems that can mostly be addressed through the delivery of effective Tier 2 interventions as described in my previous post in this blog series. Increasingly, researchers are testing the specificity hypothesis and there is a growing convergence of evidence to support specific subtypes of disability across academic areas. At the same time, there is evidence that children with specific academic deficits also tend to have specific cognitive processing deficits – and the theory is that these underlying cognitive processing deficits provide the explanation for the child’s learning difficulties. These are the common characteristics of SLD, but the specifics vary for the individual child.

    This means that in order to accurately conduct assessments to identify these profiles, an MDT needs to understand this conceptualization of SLD and then needs to be well-versed in a range of academic and cognitive processing measures. Ideally, when a student is referred for a comprehensive evaluation, the team will have a working hypothesis about the nature of the child’s learning difficulties. Through work samples, observation, and the data collected to this point in the process, a team should be able to identify more specifically the area(s) with which the child is struggling, and then frame a comprehensive evaluation designed to more fully understand the child’s particular areas of concern.

    For example, for children being referred for possible reading disabilities, if a team is using oral reading fluency as a way to monitor progress in Tier 2, the team can analyze the student’s performance more closely. For example, the team can assess whether the student is an accurate but slow reader. If so, that may suggest a problem with fluency. Does the student read a lot of words quickly but make a high number of mistakes in sounding out words? If so, a team might want to do untimed word reading and decoding assessments to further investigate whether the child experiences difficulty with decoding. If academic assessments corroborate this theory, then areas of cognitive processing that are thought to underlie decoding ability should be assessed. These include, but are not limited to, phonological processing, language, retrieval, and working memory. The point here is not to explain all of the possible combinations of assessments, but rather to outline the process, with the underlying implication being that an MDT really requires a deep understanding about the nature of SLD and professional expertise in conducting both academic and cognitive assessments.

    Our initial review of state eligibility files showed that MDTs were adhering to the old system—using broad area academic scores and full IQ scores. Training efforts have led to important changes in this area. In our third year of review, there has been a marked increase in the number of files that reflect an evaluation process that is specific to the individual and includes specific academic assessments coupled with a cognitive processing evaluation that seeks to provide the potential explanatory diagnosis of SLD. The goal of this process is ultimately to improve treatment for students with learning disabilities. Interventions and treatments designed to address academic and cognitive processing areas are becoming more prevalent. As these types of interventions become more readily available, the connection between identification, treatment, and improved outcomes should increase for students with learning disabilities.

    This series of blog entries has attempted to explain the process that one state has adopted for identifying students with learning disabilities in ways that are more consistent with our current conceptualizations of the learning disabilities construct, as well as with the understanding that there is much that schools can do to support the needs of students at risk for poor academic outcomes that should not be delivered through the system of special education. What is especially promising about the work in Idaho is that the policy change has been accompanied by a data collection and review system that directly informs training and professional development needs. This system has been driven by strong collaboration of the state department of education, local districts, and school teams and researchers, with the ultimate goal of improved outcomes for students with learning disabilities.

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