Amy Lawson Moore, PhD Terissa Miller, MS

Christina Ledbetter, PhD

THEGIBSONAssessment of cognitive skills

Technical Manual (Revised Edition)

Gibson Assessment of Cognitive Skills

Technical Manual

©2020 by Gibson Institute of Cognitive Research

5085 List Drive, Suite 200-A Colorado Springs, CO 80919

719.219.0940 www.gibsonresearchinstitute.org

Part I. Background

Nature of the Test

History of the Test

Theoretical Foundation of the Test

Uniqueness of the Test

Uses of the Test

Part II. Test Content and Administration

Content of the Test

Administering the Test

Material Requirements

User Qualifications

Part III. Test Development and Validation

Normative Information

Sources of Validity Evidence

Sources of Reliability Evidence

Scaling and Scores

TABLE OF CONTENTS

BACKGROUND Nature of the Test

The Gibson Assessment of Cognitive Skills is a

screening tool that informs clinicians, teachers, and

parents about performance on tasks that measure 1)

working memory, 2) processing speed, 3) visual

processing, 4) auditory processing, 5) logic and

reasoning, and 6) word attack skills. The 35- minute

assessment includes eight different mental tasks

presented like puzzles and games. The tasks provide a

snapshot of primary cognitive skills, including

auditory processing and word attack skills that serve

as the foundation for reading.

___________________________________

History of the Test

The first iteration of the test was developed in 2002 by

pediatric behavioral optometrist, Dr. Ken Gibson as a

screening assessment for his clinician-delivered

cognitive training program. To establish a baseline of

cognitive skill functioning in his patients, Gibson used

a variety of different commercial tests. Desiring a

single tool that could provide multiple measures, he

designed the Gibson Cognitive Test Battery which has

been administered more than 90,000 times since then.

In 2014, his team began the process of collecting

updated norms for the original test, culminating in a

complete normative update in 2020 along with an

updated look, automated scoring system, and a new

name, the Gibson Assessment of Cognitive Skills

(GACS). Note: In 2006, Gibson created a digital test

called the Gibson Test of Cognitive Skills and a

revised Version 2 in 2014. About 50% of the digital

tests items are found on the GACS.

Theoretical Foundation

The test framework for The Gibson Assessment of

Cognitive Skills (GACS) was guided by the Cattell-

Horn-Carroll (CHC) model of intelligence, and the

measurement of broad CHC factors (see Schneider &

McGrew, 2018): fluid reasoning (Gf), auditory and

visual working memory (Gwm), processing speed (Gs),

visual processing (Gv), auditory processing (Ga), and

reading and writing (Grw). The ever-evolving CHC

model of intelligence serves as the basis of Gibson’s

Learning Model, a graphical depiction of how we think

and learn. (See Figure 1.)

Figure 1. Gibson’s Learning Model

The Learning Model is independently recognized as an

influential guide in the development of auditory and

visual processing interventions (Press, 2012), and has

been featured in our own peer-reviewed cognition

research studies (Gibson, Carpenter, Moore, &

Mitchell, 2015; Carpenter, Ledbetter, & Moore, 2016).

As demonstrated in Figure 1, there is substantial

overlap between the two models of learning and

cognition which is supported in the concurrent

validation study outlined later in this manual comparing

GACS to other CHC-based assessments.

Uniqueness of the Test Given the number of cognitive tests saturating the market, it is important to highlight some critical differences

between the Gibson Assessment and other cognitive assessments. First, as of this publication, the Gibson

Assessment is currently the only cognitive assessment tool that measures four aspects of auditory processing and

Word Attack skills in its core battery. Auditory processing skills are key components of the CHC model of

intelligence and serve as the foundation for reading ability. This cross-battery approach to cognitive testing

distinguishes the Gibson Assessment from other popular cognitive assessments that require the purchase of add-

ons for comprehensive auditory processing assessment. Further, the Gibson Assessment was designed for use

across the lifespan. The test is normed for ages 5-99 and the psychometric properties of the test are strong in every

age group. Many cognitive tests are limited by age group, either specifically for children or specifically for adults.

Table 1 illustrates age span and primary construct measurement differences among several cognitive tests in

widespread use.

Table 1. Comparison of Gibson and Other Cognitive Assessments

Test Ages

Visu

al

Wor

king

M

emor

y

Audi

tory

W

orki

ng

Mem

ory

Visu

al

Proc

essi

ng

Proc

essi

ng

Spee

d

Flui

d Re

ason

ing

Audi

tory

Pr

oces

sing

: Se

gmen

ting

Audi

tory

Pr

oces

sing

: De

letio

n

Audi

tory

Pr

oces

sing

: Bl

endi

ng

Read

ing/

W

ritin

g

Oth

er

Cons

truc

ts

Gibson Assessment 5-99 X X X X X X x x X

WISC-V 6-16 X X X X X x NEPSY-2 3-16 X X

DAS-2 5-17 x x x x CNS Vital Signs 8-89 X X X X X

MMSE 20-92 X X MoCA 55-85 X X X

CANTAB 4-90 X X X X X KABC-II 3-18 X X X X X X X X KBIT-2 4-90 X X

WAIS-IV 16-90 X X X X CAS-2 5-18 X X X X X X CogAT 5-18 X X X X WJ IV 4-90 X X X X X X X Notes: WISC-V = Wechsler Intelligence Scales for Children - Fifth Edition NEPSY = A Developmental NEuroPSYchological Assessment – Second Edition DAS2 = Differential Abilities Scale – Second Edition MMSE = Mini Mental State Exam MoCA = Montreal Cognitive Assessment CANTAB = Cambridge Neuropsychological Test Automated Battery KBIT-2 = Kaufman Brief Intelligence Test - Second Edition WAIS-IV = Wechsler Adult Intelligence Scale - Fourth Edition CAS-2 = Cognitive Assessment System - Second Edition CogAT = Cognitive Abilities Test WJ IV = Woodcock–Johnson Tests of Cognitive Abilities - Fourth Edition

TEST CONTENT Processing Speed Test The Processing Speed test measures the skill of perceptual speed, or the ability to quickly and accurately search for

and compare visual images or patterns presented simultaneously. This skill falls under the broad CHC construct of

Processing Speed (Gs). The test-taker is shown a page with rows of number or letter combinations and must

identify a matching pair in each row. To indicate the selection, the test-taker must draw a line through the items that

match. There are 38 rows for a total of 38 possible points. Test-takers have 2 minutes to complete as many rows as

possible. An example item is shown below.

Example of an item on the Processing Speed Test

Visual Processing Test The test for visual processing requires the test-taker to identify individual shapes that match sections of completed

puzzles. The test measures visualization under the broad CHC construct of visual processing (Gv). Visualization

is the ability to mentally manipulate objects. The test is comprised of 7 completed puzzles and a total of 35

individual pieces, for a possible total of 35 points. Test-takers have 2 minutes to complete as many puzzles as

possible. An example of a visual processing test item is shown below.

Example of an item on the Visual Processing Test

2 3 1

Logic and Reasoning Test

The Logic and Reasoning Test measures inductive reasoning skill, or the ability to infer a rule based on the

observation of a phenomenon. For each item, the examinee is shown a matrix of designs with a missing space and

he must select from a set of designs the one that fits in the missing space. There are 17 matrices of increasing

difficulty in this subtest for a total of 17 possible points. This subtest has a ceiling of 4 consecutive incorrect

answers.

Example of an item on the Logic and Reasoning Test

Working Memory Test The Working Memory subtest measures both auditory and visual working memory capacity, or the ability to

encode and keep visual and verbal information in one’s primary memory. The examinee is briefly shown a series of

images and told a series of facts about which he is then asked questions. An example of a visual stimulus is shown

below. The examinee studies the picture before the picture is removed by the examiner, then hears an oral story

unrelated to the image, and then answers questions about the story and the picture. There are 24 items on this

subtest for a total of 24 possible points.

Example of an item on the Working Memory Test

Auditory Processing Test

There are three tasks that comprise the Auditory Processing portion of the Gibson Assessment battery: Sound

Blending, Sound Segmenting, and Sound Deletion. The task scores are combined to form a composite AP score.

There are 28 items on the Auditory Processing Test and a total of 90 possible points.

Sound Blending

The Blending test measures phonetic coding-synthesis under the broad CHC construct of auditory processing.

Synthesis is the ability to merge or blend smaller units of speech into a larger one. For this test, the test-taker

listens to the individual sounds in a nonsense word and then must mentally blend the sounds to identify the

completed word. For example, the examiner says, “/a/-/p/” and the examinee must say, “ap.”

Sound Segmenting

The Segmenting test measures phonetic coding-analysis under the broad CHC construct of auditory processing.

Analysis is the ability to segment larger units of speech into smaller ones. For this task, the examiner says a

nonsense word and then the examinee must say all the sounds in the word individually. For example, the examiner

says, “gos’” and the examinee must say, “/g/ - /o/ - /s/.”

Sound Deletion

The Dropping test measures sound awareness under the broad CHC construct of auditory processing. The

examiner says a word and asks the examinee to say a new word with a specific sound deleted. For example, the

examiner says, “Say Cat without the /c/ sound” and the examinee must respond with “at.”

Word Attack Test This test measures reading decoding ability, or the skill of reading phonetically irregular words or nonsense words.

The measure falls under the broad CHC construct of Reading and Writing (Grw). The examiner shows the

examinee lists of nonsense words (pseudowords) in increasing difficulty such as “baf” and “thrate” and asks the

examinee to read them aloud. There are 24 items on this subtest for a total of 24 possible points. The ceiling on this

subtest is four consecutive inaccurate answers.

TEST ADMINISTRATION

Required Materials

• Stimulus book • Score sheets • Stopwatch • Pencils • iPad if using the automated scoring system

Administering the Test

Administer the test in a quiet environment free of distractions. Ensure the examinee has two sharpened pencils in

case of breakage. The examiner is best positioned at a right angle to the examinee in order to see both sides of the

stimulus easel. However, sitting across from the examinee is also acceptable.

User Qualifications

The GACS is an educational screening assessment of underlying learning skills designed to be administered by both

clinicians as well as teachers, allied professionals, and researchers with basic training in administration of

educational assessments. We encourage users to follow the guidance from their professional organizations in

determining if they are adequately prepared to administer the GACS.

Administration Questions Problems

For questions regarding the administration of the Gibson Assessment, email help@GibsonTest.com

NORMATIVE INFORMATION Sample Selection

The Gibson Assessment of Cognitive Skills (GACS) was normed on a sample of 3,490 children and adults (ages 5-93) in 33 states in the USA and 4 provinces in Canada. Norming sites were selected based on representation from the four primary geographic regions of the United States and Canada: Northeast, South, Midwest, and West.

Tests were administered between 2014 and 2019 by psychologists, occupational therapists, speech therapists, behavioral optometrists, and providers of supplemental educational programs who use the Gibson Assessment of Cognitive Skills (formerly the Gibson Cognitive Test Battery) in their practices and centers. Demographics of the sample are presented in Table 2 by age and geographic region, in Table 3 by age and sex, and in Table 4 by race and median household income. Figure 2 shows the mean raw score across age groups.

Table 2. Demographics of Norming Sample by Age and Geographic Region

West South Northeast Midwest Total

Age n % n % n % n % n % 5 7 1% 25 2% 3 1% 6 1% 41 1% 6 30 2% 55 4% 14 3% 9 2% 108 3% 7 66 5% 80 6% 31 6% 29 6% 206 6% 8 105 9% 117 9% 50 10% 44 9% 316 9% 9 84 7% 121 9% 37 8% 48 10% 290 8%

10 86 7% 122 9% 39 8% 34 7% 281 8% 11 70 6% 99 8% 26 5% 25 5% 220 6% 12 46 4% 75 6% 32 7% 24 5% 177 5% 13 46 4% 60 5% 30 6% 18 4% 154 4% 14 32 3% 55 4% 18 4% 19 4% 124 4% 15 24 2% 50 4% 13 3% 14 3% 101 3% 16 21 2% 37 3% 21 4% 12 2% 91 3% 17 10 1% 21 2% 18 4% 6 1% 55 2% 18 50 4% 28 2% 45 9% 18 4% 141 4%

19-24 119 10% 94 7% 64 13% 33 7% 310 9% 25-29 87 7% 24 2% 5 1% 9 2% 125 4% 30-39 124 10% 29 2% 10 2% 12 2% 177 5% 40-49 70 6% 66 5% 2 0% 35 7% 173 5% 50-59 87 7% 73 6% 15 3% 46 9% 222 6% 60-69 40 3% 30 2% 4 1% 29 6% 103 3% 70-79 18 1% 21 2% 3 1% 14 3% 56 2% 80+ 9 1% 4 .3% 0 0% 9 2% 22 1%

Total 1231 35% 1286 37% 480 14% 493 14% 3490 100%

Table 3. Demographics of Norming Sample by Age and Sex

Male Female Total Age n % n % n %

5 21 1% 20 1% 41 1% 6 64 4% 44 3% 108 3% 7 102 6% 104 6% 206 6% 8 171 10% 145 8% 316 9% 9 153 9% 137 8% 290 8%

10 156 9% 125 7% 281 8% 11 131 7% 89 5% 220 6% 12 104 6% 73 4% 177 5% 13 93 5% 61 4% 154 4% 14 72 4% 52 3% 124 4% 15 56 3% 45 3% 101 3% 16 53 3% 38 2% 91 3% 17 30 2% 25 1% 55 2%

18+ 63 4% 78 5% 141 4% 19-24 163 9% 147 9% 310 9% 25-29 45 3% 80 5% 125 4% 30-39 58 3% 117 7% 175 5% 40-49 74 4% 99 6% 173 5% 50-59 89 5% 132 8% 222 6% 60-69 41 2% 62 4% 103 3% 70-79 19 1% 37 2% 56 2% 80+ 12 1% 10 1% 22 1%

Total 1770 1720 3490

Table 4. Demographics of Norming Sample by Race and Household Income1

Age 5-17 Ages 18+ All n % n % n % Race

White 973 42 721 61 1694 48 Black/African American 83 4 81 7 164 5

Asian/Pacific Islander 32 1 34 3 66 2 Hispanic 60 3 114 10 174 5

Other 23 <1 27 2 50 1 Not Reported 1134 49 208 18 1345 39

Household Income1

Under 25,000 - - - - 25,000 – 34,999 115 5 12 1 127 4

35,000-49,999 737 32 126 11 863 25 50,000-74,999 807 35 525 44 1332 38 75,000-99,999 393 17 414 35 807 23 Over 100,000 253 11 108 9 361 10

Total 2305 1185 3490

1 Note: Income estimate based on median household income per ZIP code

15.6

26.532 34.4 34 32.9

30.2

23.3

10152025303540

Processing Speed

9.9

16.3

19.5 20.5 2017.8

15.213.5

8

11

14

17

20

Working Memory

14

24.1

30.3 31.6 30.8 29.427.3

19.5

10

15

20

25

30

Visual Processing

47.5

78.385.2 84.8 83.5 81

76.370

40

50

60

70

80

90

Auditory Processing

6.3

14.9

19.2 20.4 20.5 20 19.4 18.5

58

11141720

Word Attack

5

9.6

1314.5 14.5

13.211.9

10.9

4

7

10

13

Logic & Reasoning

Figure 2. Distribution of Mean Raw Scores Across Age Groups

VALIDITY Sources of Validity Evidence Validity refers to a test’s ability to measure what it is designed to measure. There are multiple sources of validity reported: content validity, construct validity, concurrent validity, and internal structure. Evidence of validity from prior versions and growth curve analysis is also referenced.

Content Validity Each GACS test was developed following an extensive review of the literature and two decades of applied research on cognitive skills that are necessary for learning: memory, attention, processing speed, auditory processing and phonological awareness (segmenting, dropping, and blending), visual processing, logic & reasoning, and word attack skills. The tests were selected after extensive field use of similar tasks by clinicians using the Visual Information Processing (VIP) program and the Processing and Cognitive Enhancement (PACE) program. Subject matter experts were consulted during each phase of development and field testing to ensure that the content of each test adequately represented the skill it aimed to measure. A formal content validation review by three experts was conducted prior to field testing. Inter-rater reliability coefficients ranged from .97 to .99 for all items.

Concurrent Validity Two validation studies were conducted on the GACS. Concurrent validity was established between the GACS and the WISC-IV, NEPSY-II, and PAL-II (Moxley-Paquette, 2013), and with DTLA, LAC, and WJ III (Moore, 2014). Coefficients range from .78 to .93, which support the validity of the test. A Pearson’s product-moment correlation was run to examine if each test on the GT was correlated with other measures of the same skills to determine if the GT measures the skills as well as other standardized measures.

Table 7. Concurrent Validity between GACS and Criterion Tests

Gibson Subtest Criterion Test

r

Processing Speed WISC-IV Symbol Search WJ III Visual Matching

.40

.83 Auditory Processing PAL-II Rimes

Lindamood Auditory Conceptualization WISC-IV Letter Number Sequence

.60

.87

.52 Visual Processing WISC-IV Block Design

NEPSY-II Geometric Puzzles WJ III Visual Closure

.60

.40

.84 Logic & Reasoning WISC-IV Matrix Reasoning

DTLA Symbolic Relations .72 .77

Working Memory DTLA Design Sequence WISC-IV Letter Number Sequence

.75

.73 Word Attack WJIII Word Attack .98

Evidence of Validity Based on Developmental Patterns As seen in the distribution of mean raw scores across age groups in Figure 2, the curves are consistent with patterns of cognitive development across the lifespan. Cognitive growth tends to peak in early adulthood and gradually declines in the thirties across all constructs. The graphs below show the similar cognitive development curve across the lifespan for the CHC factors measured by both the Woodcock Johnson IV (as shown in W score difference from age 6) in Figure 3 and the GACS (shown in norm group z scores converted to standard scores) in Figure 4. Because the Woodcock Johnson IV has been previously validated (McGrew et al, 2014), the comparison of the growth curves of the GACS to a previously validated test introduces an additional source of validity evidence.

Figure 3. Woodcock Johnson IV Growth Curves

Figure 4. Gibson Assessment of Cognitive Skills Growth Curves

Evidence of Validity Based on the Digital Version of the Gibson Assessment of Cognitive Skills The digital Gibson Test of Cognitive Skills contains 50% of the items found on the Gibson Assessment of Cognitive Skills. Therefore, it is important to include this evidence on concurrent validity based on another test in the Gibson test family. The Gibson Test and the Woodcock Johnson III Tests of Cognitive Abilities were both administered to a sample of 53 participants (Moore & Miller, 2016). The resulting correlations range from .60 to .93, indicating moderate to strong relationships between the Gibson subtests and other standardized criterion tests (Table 8). All correlations are significant at an alpha of p < .001.

Table 8. Concurrent Validity of the Digital Version of the GACS (called Gibson Test of Cognitive Skills V2)

Gibson Subtest Woodcock Johnson III r

Auditory Processing Spelling of Sounds

Sound Awareness

.90

.82

Short-Term Memory Numbers Reversed .84

Logic & Reasoning Concept Formation .77

Processing Speed Visual Matching .60

Visual Processing Spatial Relations .82

Word Attack Word Attack .93

Evidence of Validity Based on Internal Structure of the Test

To assess the internal structure validity of the Gibson Assessment of Cognitive Skills, we examined the intercorrelations among all of the tests from the internal consistency reliability sample (n = 103). When tests that measure similar abilities are more highly correlated with one another than tests that measure dissimilar abilities, the internal structure is valid. As shown in the table below, auditory processing and Word Attack, for example, show stronger intercorrelations than with other measures because they measure similar constructs. Visual processing is correlated with logic and reasoning and working memory because they are tasks that require the manipulation or identification of visual images. These examples provide general evidence of convergent and discriminant internal structure validity.

Table 9. Test Intercorrelations – All Ages

Test Auditory Processing

Word Attack

Processing Speed

Logic & Reasoning

Visual Processing

Working Memory

Auditory Processing

- .66 .58 .54 .51 .50

Word Attack

.66 - .71 .60 .57 .43

Processing Speed

.58 .71 - .68 .73 .56

Logic & Reasoning

.54 .60 .68 - .68 .52

Visual Processing

.51 .57 .73 .68 - .52

Working Memory

.50 .43 .56 .52 .52 -

RELIABILITY Sources of Reliability Evidence Reliability of a test refers to the consistency with which the test measures the same trait, characteristic, or ability. Three sources of reliability are reported for the GACS: coefficient alpha, split-half, and test-retest. These metrics represent the estimates of the amount of error in the test scores.

Coefficient Alpha Coefficient alpha represents the internal consistency reliability of the test, or how well the test items correlate with each other. A desired reliability coefficient approximates or exceeds .80. Using jMetrik item analysis, coefficient alphas were calculated for a sub-sample of participants from the norming group. In addition to an overall coefficient alpha for each test, coefficient alphas are reported for subgroups based on age group (Table 10). Overall coefficient alphas range from .80 to .94.

Table 10. Reliability Metrics for GACS Tests by Age Group

Subtest

Statistic

Age 6-17 n = 88

Age 18+ n = 25

Overall n = 113

Working Memory M SD α

SEM

14.9 4.3 .80 1.9

16.5 17.0 .76 1.8

15.2 4.2 .80 1.9

Visual Processing M SD α

SEM

22.9 7.7 .94 1.9

28.7 5.1 .88 1.8

24.3 7.6 .94 1.9

Auditory Processing M SD α

SEM

40.4 8.5 .92 2.4

40.8 8.8 .93 2.3

40.5 8.6 .92 2.4

Logic & Reasoning M SD α

SEM

9.9 3.4 .82 1.4

12.5 2.2 .60 1.4

10.5 3.4 .81 1.5

Processing Speed M SD α

SEM

25.5 6.9 .94 1.7

32.4 3.6 .87 1.3

27.0 7.0 .94 1.7

Word Attack M SD α

SEM

13.7 6.0 .91 1.8

18.7 3.9 .86 1.5

14.9 5.9 .92 1.7

Split-Half Split-half reliability is the estimation of test reliability determined by correlating the scores on two halves of the test. This method is frequently used when retesting the same students is not practical, or when practice effects are a possible threat. To calculate the split-half reliability estimate, the sum of the even numbered items was correlated with the sum of the odd numbered items. A Spearman-Brown formula was applied to the Pearson correlation for each subtest to predict the overall reliability of the test. Overall split-half reliability coefficients ranged from .83 to .96 (Table 11).

Table 11. Split-Half Correlation Coefficients for GTCS

Subtest Children r12

Adults r12

Overall r12

Working Memory .84 .78 .83

Visual Processing .96 .92 .96

Auditory Processing .93 .96 .94

Logic & Reasoning .85 .54 .83

Processing Speed1 .94 .86 .94

Word Attack .93 .92 .94

1Split-half correlation is not an appropriate analysis for a speeded test; the alternative calculation was based on the formula: r11 = 1 – (SEM2 / SD2)

Test-Retest (Delayed Administration) Test-retest reliability is the estimation of test reliability determined by correlating the scores on two different administrations of the test to the same sample of test takers. We administered the test two times one week apart to a sub-sample of the norming group (n = 53). The overall test-retest reliability coefficients ranged from .83 to 98 (Table 12). All coefficients were significant at p < .001

Table 12. Test-Retest Correlation Coefficients for GACS

Subtest

Statistic

Age 6-17 n = 25

Age 18+ n = 28

Overall n = 53

Working Memory M1 (SD) M2 (SD) r12

16.3 (4.2) 19.3 (3.9)

.89

16.6 (3.5) 20.1 (3.1)

.73

16.4 (3.9) 19.7 (3.6)

.83 Visual Processing M1 (SD)

M2 (SD) r12

21.9 (9.1) 25.1 (8.9)

.92

28.7 (5.1) 29.7 (5.1)

.91

25.3 (8.1) 27.3 (7.6)

.92 Auditory Processing M1 (SD)

M2 (SD) r12

73.8 (17.3) 75.7 (16.1)

.97

74.6 (16.7) 77.1 (16.3)

.99

74.3 (16.8) 76.4 (16.1)

.98 Logic & Reasoning M1 (SD)

M2 (SD) r12

10.7 (3.9) 11.4 (3.7)

.97

12.6 (2.3) 12.8 (2.7)

.82

11.6 (3.3) 12.1 (3.3)

.92 Processing Speed M1 (SD)

M2 (SD) r12

25.5 (8.6) 26.9 (8.1)

.97

32.4 (3.6) 33.8 (4.1)

.75

28.9 (7.5) 30.3 (7.3)

.95 Word Attack M1 (SD)

M2 (SD) r12

14.4 (6.5) 15.3 (6.2)

.95

18.58 (3.9) 19.2 (3.8)

.96

16.6 (5.8) 17.2 (5.5)

.96

TYPES OF SCORES Normative Scores

Three types of normative scores are available for each subtest of the GACS: percentiles, standard scores, and age-equivalents. Figure 5 illustrates the distribution of Percentiles and Standard Scores on a normal curve.

Percentile Rank (%tile) Percentile rank is based on the location of the student’s score compared to same-age students in the sample. It is the point in the distribution of scores that is at or below the scores of where a percentage of students fall. For example, a percentile rank of 83 means that the student scored as well as or better than 83% of the other students of the same age in the sample. Percentiles range from 1 to 99. It is important to note that the percentile rank is not the same as the percentage of items the student answered correctly. Percent correct is not a score option for the GT.

Standard Scores (SS) The standard score (SS) is based on a distribution of scores from 50 to 150 with a mean of 100 and a standard deviation of 15. The standard score is determined from the percentile score using a standard psychometric conversion table. For example, if a seven-year old student obtained a percentile rank of 50 on the Word Attack subtest, the student’s standard score would be 100. Standard scores are the best metrics to use in statistical analysis because these scores are on an interval scale.

Age-Equivalents (AE) An age-equivalent is an age that corresponds to the student’s raw score. It is determined by calculating the mean scores of all students in each age group and plotting them on a graph to visually evaluate their correlations. It is important to note that the use of age-equivalents should be approached with caution. Because they are determined through manual smoothing, interpolation, and extrapolation, they are not as reliable as standard scores and percentiles. Age equivalents are presented on the score reports for examinee through age 16 only.

Figure 5. Distribution of Scores

Works Cited McGrew, K. S., LaForte, E. M., Schrank, F. A. (2014). Technical Manual: Woodcock-Johnson IV. Rolling

Meadows, IL: Riverside.

Moore, A.L. (2014). Technical Manual: Gibson Test of Cognitive Skills (Paper-based version). Colorado Springs,

CO: Gibson Institute of Cognitive Research

Moore, A.L., & Miller, T. (2018). Reliability and validity of the revised Gibson Test of Cognitive Skills, a

computer-based test battery for assessing cognition across the lifespan. Psychology Research and Behavior

Management, 11, 25-35. doi:10.2147/PRBM.S152781

Moore, A.L, and Miller, T.M. (2016). Technical Manual: Gibson Test of Cognitive Skills – Digital, Version 2.

Colorado Springs, CO: Gibson Institute of Cognitive Research.

Moxley-Paquette, E. (2013). Testing a structural equation model of language-based cognitive fitness. Doctoral

dissertation. Available at ProQuest Dissertations and Theses. (UMI No. 3728963).

Schneider, W.J., & McGrew, K.S. (2012). The Cattell-Horn-Carroll model of intelligence. In D.P. Flanagan & P.L.

Harrison (Eds.), Contemporary Intellectual Assessment: Theories, tests, and Issues (3rd ed.). New York,

NY: Guilford Press.

Bibliography of Studies Using the GACS/GCTB

Hill, O.W., Zewelanji, S., & Faison, O. (2016). The Efficacy of the LearningRx Cognitive Training Program:

Modality and Transfer Effects. Journal of Experimental Education: Learning, Instruction, and Cognition,

84(3), 600-620. doi: 10.1080/00220973.2015.1065218.

Lin, Y., Washington-Nortey, P., Hill, O.W., et al. (2019). Family Functioning and Not Family Structure Predicts

Adolescents’ Reasoning and Math Skills. Journal of Child and Family Studies, 28, 2700–2707.

https://doi.org/10.1007/s10826-019-01450-4

Moxley-Paquette, E., & Burkholder, G. (2014). Testing a structural equation model of language-based cognitive

fitness. Procedia Social and Behavioral Sciences, 112, 64-76. Retrieved from

http://www.sciencedirect.com/science/article/pii/S1877042814011574

Moxley-Paquette, E., & Burkholder, G. (2015). Testing a structural equation model of language-based cognitive

fitness with longitudinal data. Procedia Social and Behavioral Sciences, 171, 596-605. Retrieved from

http://www.sciencedirect.com/science/article/pii/S1877042815001962

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