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CROSS-BATTERY ASSESSMENT 3: LD IDENTIFICATION October 11, 2013 TASP Annual Conference Gail Cheramie, Ph.D., LSSP, NCSP

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Page 1: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

CROSS-BATTERY ASSESSMENT 3:

LD IDENTIFICATION

October 11, 2013

TASP Annual Conference

Gail Cheramie, Ph.D., LSSP, NCSP

Page 2: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

SLD EVALUATION – A BALANCED APPROACH

Initial evaluation for suspected SLD should be comprehensive

Data from the RtI process should be part of the SLD determination process (existing data at time of referral or data collected simultaneously within the timeline period for the evaluation)

Evaluation methods for identification and eligibility determination must be varied (not a single measure or method) and include history, measures of academic skills, measures of cognitive abilities/processes, emotional-behavioral characteristics, observations, interviews, etc.

Page 3: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

TRAINING GOALS

What’s new in XBA 3?

Determination of LD – DD/C Model

Case Studies

3

Page 4: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

RE-DEFINED “G”S: THE ORIGINAL “G”S

G

General

Intelligence

Fluid

Intelligence Crystallized

Intelligence

Auditory

Processing

Broad

Visual

Perception

Short Term

Memory Long-Term

Storage &

Retrieval

Broad

Cognitive

Speediness

Processing

Speed

(RT

Decision

Speed)

Gf Gc Ga Gv Gsm Glr Gs Gt

Not

Measured

Page 5: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic
Page 6: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

MORE INCLUSIVE: 800 TESTS

XBA Includes

Cognitive Batteries

Major Achievement Batteries

Selected Neuropsychological Instruments

Special-purpose Tests

Speech-Language Tests

Memory Tests

Phonological Processing Tests

Orthographic Processing

Fine Motor Tests

More associated with TBI

Page 7: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

MORE PSYCHOMETRICALLY SOUND

Inter-rater reliability for classification

Subtests are weighted

No more averaging for “G”s

Use of base rates and critical values

Change in rules:

“Unitary” now called “Cohesive”

“Outliers” now called “Divergent”

If 3 scores, look at distance between scores (Chaplin and Cheramie rules)

Page 8: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

EXTENDED ANALYSIS OF PROBLEM

Task analysis, Demand analysis, Error Analysis

Identified links between cognitive areas and

academic areas

Cognitive Correlates of Reading Disability

Subtypes (i.e. surface dyslexia, mixed dyslexia,

etc.)

Emphasis on Differential Diagnosis (ID vs. LD

vs. GLD)

Page 9: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

WHAT DOES THIS MEAN TO ME?

Accurate Diagnosis Better Treatment

Framework for Recommendations

Specific for academic skill weaknesses + Cognitive processes that link to these weaknesses + Task Demands

Example: Weakness in Reading Comprehension may be due to language foundations such as vocabulary, syntax, and morphology and/or working memory.

Recommendations would be made for specific techniques to address language skills (e.g., pre-teach vocabulary) and processes such as working memory (e.g., use of graphic organizers such as story mapping or story webs, use of “Think Aloud” strategy)

Page 10: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

GUIDING PRINCIPLES

Select Core Battery that is most relevant to referral concerns

Use norm-based clusters/composites from a single battery whenever possible to represent a broad ability

For Broad and Narrow ability clusters, use tests/subtests that have been classified according to an empirically acceptable method

Page 11: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

GUIDING PRINCIPLES

When crossing batteries, select tests

normed within a few years of each other

Select tests from smallest number of

batteries

Establish ecological validity for normative

weaknesses or deficits

Page 12: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

IMPORTANT CONCEPTS

Converging sources of data

Need multiple types of data to determine strengths and weaknesses (e.g., for academic deficit need informal, criterion-referenced, curriculum-based, and norm-referenced)

Ecological Validity

Manifestations of the deficit

The degree to which the behaviors observed and recorded in a study (e.g., test) reflect the behaviors that actually occur in natural settings (e.g., the classroom)

What does this deficit look like in the learning environment; what data provide additional evidence for the deficit

Page 13: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic
Page 14: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

BROAD AND NARROW CLUSTERS

2 diff

narrows &

cohesive=

BROAD

2 same

narrows=

NARROW

Page 15: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

DETERMINATION OF LD

Dual

Discrepancy/Consistency

(DD/C)

LD definition

Page 16: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

DD/C LD DEFINITION

(1) a weakness/deficit in one or more academic area;

(2) a weakness/deficit in cognitive abilities or neuropsychological processes;

(3) pattern of strengths and weaknesses that demonstrate (a) a relationship between the cognitive and academic weakness, (b) general average ability to think and reason, (c) the cognitive deficits that interfere with learning are domain specific, (d) academic area of weakness/deficit is unexpected; and

(4) the deficit areas adversely impact educational performance.

All exclusionary factors have been considered.

Page 17: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

Oval 1

Strengths Average or Better

Overall Ability

Oval 2

Cognitive

Deficit –

Oval 3

Academic

Deficit – Consistent

Page 18: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

REVISED TOOLS

XBA DMIA v 2.0

Test/Graph Index

Graphing options (varying CI)

Enter up to 4 subtests

Analyze data in a Test, then transfer to CHC Analyzer

Analysis of g-Value

PSW-A v1.0

C-LIM v2.0 (Culture-Language Interpretive Matrix)

Page 19: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

Intro Tab

Page 20: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

WISC-IV Tab

Page 21: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

PROFESSIONAL JUDGMENT POINTS

ELL for LD: C-LIM v2.0 English scores before

DMIA

Follow-up on non-cohesive clusters

SS between 85-89

g-Value: Sufficiency

Broad vs. Narrow Ability clusters

Consider ALL sources of data for decision-making

Page 22: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

WHAT ABOUT CLD?

Cultural Differences

Linguistic Differences

Goal of C-LIM is non-discriminatory assessment

of ELLs

Example Profiles: Rosita, Emilio, & Priscilla

Page 23: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

INSTEAD OF SAYING NOT VALID OR VALID,

CONSIDER:

Based on the CLIM analysis, the profile

generated is best explained by cultural and

linguistic factors and not indicative of a

learning disability. OR

The profile generated on the CLIM is not fully

accounted for by cultural and linguistic factors;

therefore the presence of a learning disability

was investigated.

Page 24: October 11, 2013 TASP Annual Conference Gail …...IMPORTANT CONCEPTS Converging sources of data Need multiple types of data to determine strengths and weaknesses (e.g., for academic

CASE STUDIES