Always Learning
 
 
 
International Sites
Cart

  Change Community

Spotlight on Research and Practice

  

In this section, we provide suggested references and information on issues pertinent to our quarterly topic or recent research. We’re focusing on some current research references relevant to our work with children and adults.

Did you know?

Yes, the Law (and Research) Is on Your Side: Applying PSW to a Psycho-Educational Evaluation

Adam Scheller, PhD
Senior Educational Consultant
Pearson Clinical Assessment

Amy is a young elementary student living in the southeastern U.S. She has higher than average ability, but has not been successful in her pursuit to acquire and apply math knowledge. She has a story most of us who have practiced in public school systems have heard at some point in our careers. She frequently fails her 4th grade math tests and homework is a constant struggle. Not only is math tough, but she recently began exhibiting anxiety any time the subject is addressed. Amy is the daughter of an author and chemical engineer; her family history is very academically strong except for some admitted math weaknesses on the maternal side. However, there is nothing that throws up a red flag when it comes to learning or cognitive disabilities in the family. How can Amy’s school help her learn?

As clinicians, we walk along two paths parallel paths to answer this question. One path was formed by legal expectations, while the other by best practice and theory. Even though they are meant to be the same path, the two paths often diverge and become juxtaposed.

How do we form an accurate picture of a child’s learning strengths and weaknesses while making sure both feet are balanced on a path of both legal and theoretical expectations? In Amy’s case, our questions are complex. What drives her bumpy road to math success; how does she learn best; and more importantly what pattern of strengths and weaknesses does she exhibit? Does Amy have a learning disability in math?

The Law

Our legal story starts with the Individuals with Disabilities Education Act, or IDEA. Per law, the diagnostic process for schools is multifaceted, with one layer requiring the identification of a “condition” or “disability.” In practice, this is the layer that proves to be the most variable across the country and stirs up disagreement among professionals. For a long time, the use of a discrepancy model (Ability-achievement Discrepancy, AAD) was required to indicate that a child’s academic skills were below what we should expect given their ability. However, in 2004 the law expanded to open the door for Response to Intervention (§ 300.309 (a) (2) (i)) modeling along with AAD. If a child was not making adequate progress in one of eight areas (oral expression, listening comprehension, written expression, reading comprehension, basic reading skills, reading fluency skills, mathematics calculation, and/or mathematics problem solving; 300.309, a, 1) a child’s lack of response to scientific, research-based intervention could be used to identify an academic disability. While variations of an RTI model are successfully implemented in many schools across the US, there remain many clinicians who believe that while RTI is necessary, it is not sufficient when it comes to the diagnosis of a disability (Flanagan, Fiorello, and Ortiz, 2010; Hale et al ., 2010; Hale, Kaufman, Naglieri, and Kavale, 2006).

The Theoretical Revolution

The profession of school psychology has undergone a significant paradigm shift over the past 15 years. Researchers such as Virginia Berninger, Alan and Nadeen Kaufman, Cathy Fiorello, Brad Hale, George McCloskey, Dawn Flanagan, and Dan Miller (and many others) have helped move our field into “the matrix.” No, not the (awesome) sci-fi movie series starring Keanu Reeves as our hero NEO, but the matrix regarding multifaceted and theoretically driven neuro-developmental learning evaluations. That comes into play specifically when we discuss the “other” option or the third party candidate, otherwise known as a “pattern of strengths and weaknesses” approach (PSW)(§300.309 (a) (2) (ii)). PSW analysis takes into account processes and patterns of learning that are either indicative or exclusionary. Think neuropsychology meets school psychology meets connected education practices, or as I like to call it, Franken-analysis.

What is PSW?

There are several approaches to conduct a Pattern of Strengths and Weaknesses analysis. Hale and Fiorello (2004) outline three of the most prominent research-based methods: Concordance-discordance method (C-DM; Hale & Fiorello, 2004); Discrepancy/consistency method (Naglieri & Das, 1997); and the cross-battery assessment approach (Flanagan, Ortiz, & Alfonso, 2013). As indicated in the Hale and Fiorello (2004) review, all of the PSW approaches have several commonalities. All rule out exclusionary factors as part of the definition of a learning disability; all identify a cognitive processing weakness that is related to the achievement weakness; and all identify one or more areas of strength that are unrelated to the achievement weakness. However, all three methods differ in several key areas, including the criteria for defining strength and weakness.

While it’s important for you to choose a method based on your own professional analysis, in this article I focus on one, the Hale and Fiorello (2004) Concordance-discordance method (C-DM). It is described as a legally acceptable and clinically sound approach to PSW in schools (Hale & Fiorello, 2004; Hale et al., 2010). The model can be used within research-supported cognitive and neuropsychological approaches to assessment such as Cognitive hypothesis-testing model (e .g., Hale & Fiorello, 2004), cross-battery assessment approach (e .g., Flanagan et al ., 2013) Cattell-Horn-Carroll (CHC) theory (e.g., Flanagan, Alfonso, Mascolo, & Sotelo-Dynega, 2012), Lurian approaches (e .g., Luria, 1973), and PASS theory, as utilized by the Das-Naglieri Cognitive Assessment System (CAS; Naglieri & Das, 1997; Naglieri, 1999) and the NEPSY–II (as discussed in Kemp & Korkman, 2010).

One of the driving forces behind PSW is the idea that a child with a specific learning disability (SLD) requires individualized instruction responsive to their processing strengths and weaknesses. The PSW C-DM approach focuses our analyses on the identification of a processing weakness that differentiates between SLD and underachievement that occurs for other reasons. The methodological and statistical requirements for PSW stipulate that score comparisons must be significantly different to meet criteria for SLD identification (comparing a processing strength vs. an achievement weakness and a processing strength vs. a processing weakness). You must determine if there is a consistency between the achievement weakness and the processing weakness, which in turn provides you with a rationale for SLD. Score comparisons in C-DM are evaluated using the simple-difference method rather than the predicted-score (regression) method. It’s important to remember that this is not an implicit causal relationship, as is the case with AAD. If comparisons are not statistically significant, the child does not demonstrate a pattern consistent with an SLD. However, it is imperative that you use clinical judgment and multiple data points to validate your hypothesis.

Differences between PSW and AAD

There are several key differences between PSW and AAD. The first is that for PSW two score comparisons are required, rather than the single comparison used in the AAD analysis. And second, statistical evidence of a processing weakness is an essential requirement of only the PSW analysis. A processing weakness is a defining characteristic of a learning disability (IDEA Sec. 300 .8[c][10)]). If using the AAD model properly, you may also include a supplementary evaluation of processing weaknesses; however, this analysis is not essential to the general model (Wechsler, 2014).

PSW and the WISC-V

The PSW model in the Wechsler Intelligence Scale for Children, 5th Edition (2014) (WISC®-V) most closely resembles the C-DM model. PSW analysis is possible on the WISC-V when scoring using the Q-global® system. The development of WISC-V was unique, in that it included specific tests of learning processes as a sidecar to traditional cognitive analysis. The WISC-V Naming Speed Literacy and Symbol Translation subtests give standard scores (as opposed to scaled) and are directly comparable to other frequently used scores in PSW (such as WISC–V index scores, and subtest and composite standard scores on achievement measures linked to the WISC–V).

Steps for Conducting the PSW Analysis with WISC-V and WIAT-III and/or KTEA™-3

Step 1: Select the achievement weakness

  1. Subtest or composite score that corresponds to primary achievement weakness (below average (i.e., standard score less than 85))
    i. Consider selecting a subtest or composite score that corresponds to IDEA-specified areas of achievement for identifying an SLD

  2. Examine subtest variability within a composite score before selecting the composite as the achievement weakness.
    i. Use subtests

Step 2: Select the WISC–V standard score that represents the processing weakness (generally associated with the achievement weakness)

  1. Examine subtest variability within the WISC–V standard scores before selecting a processing weakness
    i. Preferable (not always necessary) to use a different standard score

Step 3: Select the WISC–V standard score that represents the processing strength (processing strength not typically related to the achievement weakness)

  1. Examine subtest variability within the WISC–V standard scores before selecting the processing strength (see 2b)

  2. Avoid using WMI, PSI, AWMI, any of Naming Speed process or subtest scores, or SRI as the strength in PSW analysis

What about Amy?

In reality, the point of this article is to answer the question, what about Amy? What is causing her to experience such academic distress and in turn emotional turmoil? As described throughout this article, an analysis of her learning and cognition will require a multifaceted approach that takes into account both her strengths and weaknesses. Her prognosis for a bright future improves with us taking steps to ensure that while we meet the legal rigor driving our education system, the theoretical research-based practice of neuro-developmental learning assessment guides us.

To be continued…

Please consider attending the webinar (or listening to the recorded session), “How can we help students like Amy who are struggling in Math?” During this one-hour webinar, Dr. Scheller will discuss the case of Amy, an elementary school student, who continues to miss math benchmarks, despite receiving a level of instruction that is effective for her peers. This is a case of math learning disability as shown through identification, intervention, and progress monitoring. The webinar will be broadcast on 12/12/16 at 3:30 Eastern Standard. Go to the following link to register (https://cc.readytalk.com/r/vpcripx1p8hq&eom).  If you miss the live session, you may find the recording and others by going to http://www.pearsonclinical.com/events/webinars/currentlisting.html.

References

  1. Flanagan, D. P., Fiorello, C. A., & Ortiz, S. O. (2010). Enhancing practice through the application of Cattell-HormCarroll Theory and research: A “third method” approach to specific learning disability identification. Psychology in the Schools, 47(7), 739-760.

  2. Flanagan, D. P., Alfonso, V. C., Mascolo, J. T., & SoteloDynega, M. (2012). Use of ability tests in the identification of specific learning disabilities within the context of an operational definition. In D. P. Flanagan & P. L. Harrison (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (3rd ed., pp. 643–669). New York, NY: Guilford Press.

  3. Flanagan, D. P., Ortiz, S. O., & Alfonso, V. C. (2013). Essentials of cross-battery assessment (3rd ed.). New York, NY. Wiley.

  4. Hale, J. B., & Fiorello, C. A. (2004). School neuropsychology: A practitioner’s handbook. New York: Guilford Press.

  5. Hale, J. B., Kaufman, A., Naglieri, J. A., & Kavale, K. A. (2006). Implementation of IDEA: Integrating response to intervention and cognitive assessment methods. Psychology in Schools, 43, 753–770.

  6. J. Hale, V. A., V. Berninger, B. Bracken, C. Christo, E. Clark, M. Cohen, A. Davis, S. Decker, M. Denckla, R. Dumont, C. Elliott, S. Feifer, C. Fiorello, D. Flanagan, E. Fletcher-Janzen, D. Geary, M. Gerber, M. Gerner, S. Goldstein, N. Gregg, R. Hagin, L. Jaffe, A. Kaufman, N. Kaufman, T. Keith, F. Kline, C. Kochhar-Bryant, J. Lerner, G. Marshall, J. Mascolo, N. Mather, M. Mazzocco, G. McCloskey, K. McGrew, D. Miller, J. Miller, M. Mostert, J. Naglieri, S. Ortiz, L. Phelps, B. Podhajski, L. Reddy, C. Reynolds, C. Riccio, F. Schrank, E. Schultz, M. Semrud-Clikeman, S. Shaywitz, J. Simon, L. Silver, L. Swanson, A. Urso, T. Wasserman, J. Willis, D. Wodrich, P. Wright, & J. Yalof. (2010). Critical issues in response-tointervention, comprehensive evaluation, and specific learning disabilities identification and intervention: an expert white paper consensus. Learning Disabilities Quarterly, 33, Summer. 223-236.

  7. Korkman, M., Kirk, U., & Kemp, S. (2007). NEPSY–Second edition. Bloomington, MN: Pearson.

  8. Luria, A.R. (1973). The working brain: An introduction to neuropsychology. New York, NY: Basic Books, Inc.

  9. Naglieri, J. A., & Das, J. P. (1997). Cognitive Assessment System. Administration and scoring manual. Interpretive handbook. Itasca, IL: Riverside.

  10. Naglieri, J.A. (1999). Essentials of CAS Assessment. New York, NY. Wiley.

  11. Wechsler, D. (2014). Wechsler intelligence scale for children-fifth edition. Bloomington, MN: Pearson.