1. Issues and Solutions Regarding Dual Discrepancy Rationale for the shift to the DD model : There were a number of problems with using IQ as the predictor variable, summarized below; –For students with IQ scores between 84 and 71 (“below average”), it was quite difficult to be identified as SLD using a 16 to 20 severe point discrepancy criteria –Likewise, students with IQ scores between 116 and 129 (“above average”) required much more than a 16 to 20 point discrepancy in order to show a need for services (in other words, to have an academic achievement score of 84 or below) –When using the Severe Discrepancy model, a student was often tested in academics during a single session (or two/several within a short period of time). The DD model requires at least two academic achievement data points for Factor 2. Thus, performance over time is considered in the DD model, unlike with the SD approach. –When using the District Average score on a grade level standards and benchmarks measure as the predictor variable, it can be argued that one is using a predictor that is directly more relevant to academic achievement than is IQ

2. DD and the Shifting Role of the SAT Team Previously the SAT team was the gatekeeper for special education referrals with an implicit goal of getting the child the needed services as quickly as possible. Currently the SAT team will be the de facto IEP team for 85% to 95% of students, including those Tier 2 children who formerly were referred for testing The role of the SAT team has shifted from referral management to case management. Likewise, the role has shifted from making referrals as quickly as possible to helping children stay in the “least restrictive environment”

3. DD and the Changing Role of the Diagnostician –By calculating the DD data during the SAT process, the SAT members can know what the likely outcome of the Tier 3 evaluation result will be prior to making a referral for testing. –But is it unimportant to know the child’s IQ test, even if that factor is not the best predictor variable? NO!!! –A referral may be still be made, even in the case where a child doesn’t meet Factor 1 in the DD analysis in order to determine why Tier 2 interventions have not proven effective Shifting Diagnostician Role –The role of the Diagnostician is shifting from determination of eligibility to expert in cognitive processing in the learning process –The most important part of the diagnostic report will now become: a) the cognitive processing analysis and b) suggested interventions to deal with processing deficits and individualized learning style –Diagnosticians will need to learn more about the theory and practice of reading/math/writing instruction –Diagnosticians will likely need to shift somewhat to a preventative model via increased consultation with SAT team

4. Cognitive Information Processing and the Learning Process Auditory Sound Perception Sound/Word Discrimination Oral Expression/Vocabulary Receptive Language Sound-Symbol Association Knowledge Phonological/Phonemic Awareness Short Term Auditory Memory Long Term Auditory Memory Auditory Complex Reasoning Integration of Verbal-Visual Processing Auditory Fluency Attention Span/Concentration Organization Anticipation/Planning Self-Monitoring Self-Direction Impulse Control Cognitive Fluency Visual Perception Visual-Motor Integration Visual Discrimination Visual Orientation and Sequencing Visual Tracking Visual Short Term Memory Visual Categorizing of Concepts Visual-Spatial Abstract Reasoning Integration of Visual-Verbal Processing Visual-Spatial Fluency

5. Challenges With Using the Dual Discrepancy Model Challenge One: Late Fall or Early Spring Referrals At present the PED short cycle data bank has included fall and spring scores, but not winter. This has several significant implications for the SAT team (and diagnosticians). Since the only DD comparison that can be made is between August and April short cycle scores, it is thus most expedient to work referrals that come to conclusion shortly before the final short cycle testing in April. This will have the impact of pressing the diagnosticians for completion before the end of the school year. Referrals made during fall or early spring semester will thus not be able to include the Factor 2 part of Dual Discrepancy using state norms (and since the diagnosticians have the 60 day timeline, testing must proceed as soon as the referral comes to conclusion).

6. Challenges With Using the Dual Discrepancy Model Challenge Two: What To Do When Factor 2 DD Analysis Is Not Available At present, the PED state-wide norms do not appear to include slope or difference data. Thus, the Factor 2 analysis is a challenge to accomplish. It is recommended that local district-wide data be used for a Factor 2 comparison between fall and winter be conducted in lieu of state normative data. That is, local data is preferable to no data at all when addressing the 2 nd factor in the DD equation. In order to do this, someone in the district will be responsible for a fairly significant grade level data input analysis. Data will be need to be entered in a spreadsheet for every student in the district for the grade under consideration. The data to be entered is the fall and winter short cycle scores for the area(s) of referral. (NOTE: It could also be appropriate to compare winter and spring scores.) Additionally, the difference between the winter and fall score will need to be calculated for each student in the grade within the district. The mean and standard deviation of the difference scores for the grade level must be calculated at the district level – then the “local norms” DD assessment for Factor 2 can occur for the individual student.

7. Challenges With Using the Dual Discrepancy Model Challenge Three: Deciding What Additional Information (To Establish A Pattern Of Strengths and Weaknesses ) Is Necessary When Factor 2 Is Not Significant or Not Available A Severe Discrepancy analysis should be conducted in the areas of concern. However, even if that analysis is positive for an SD in the area(s) of concern, additional information is needed. That is, a single SD on a single academic achievement test is not sufficient to replace the lack of Factor 2 in the Dual Discrepancy analysis. If possible and when appropriate, use a second academic achievement test in the Dual Discrepancy analysis. Include NMSBA results from previous school year in the area(s) of identified concern. Include Curriculum Based Measures (CBM) in the area(s) of identified concern

8. Challenges With Using the Dual Discrepancy Model Challenge Four: Deciding What Information Can Be Analyzed When No Short Cycle Results Are Available PED guidelines require each district to have a measurement of key academic skills in each grade level (from K through 12). However, a review of the PED aggregate test results from 2009-2010 shows fewer measures available in kindergarten and 1 st grades than 2 nd or 3 rd. The SLD categories of Oral Expression and Listening Comprehension are not often reflected in the short cycle testing options at many school districts. In distinguishing reading from written expression while using a DD analysis, use diagnostic academic achievement test evaluation testing results in order to make an argument for a distinction between reading and language arts if the short cycle results combine these factors.