Take Your Analysis to the Next Level with the WJ IV

Meet Sarah, Jacob and Janine.

Get comfortable with WJ IV test analysis using these fictional student test scenarios.

The Woodcock Johnson^® Fourth Edition (WJ IV™) is a comprehensive suite of co-normed assessments that includes three batteries: Woodcock-Johnson Tests of Achievement (WJ IV ACH); Woodcock-Johnson Tests of Cognitive Abilities (WJ IV COG); and the Woodcock-Johnson Tests of Oral Language (WJ IV OL), each designed to provide powerful insights into learning and behavior throughout the lifespan. The WJ IV provides a means to analyze the presence and significance of strengths and weaknesses among an examinee’s cognitive, achievement, and linguistic abilities.

What are Variations?

Variation procedures allow an examiner to compare a student’s performances within an administered test battery. They require, at minimum, the administration of a WJ IV battery’s core tests. The core tests include WJ IV ACH: Tests 1–6; WJ IV COG: Tests 1–7; and WJ IV OL: Tests 1–4. Each core test measures a distinct ability; for instance, each core test of the WJ IV COG measures a specific Broad CHC Ability.

Variations can be computed using Riverside Score, the online scoring and reporting platform, after the core tests of a WJ IV battery have been administered. Variation procedures use a specific subset of core tests to calculate a student’s predicted performance. A student’s predicted test/cluster performance is determined by averaging their standard scores across a specific subset of core tests¹. The difference between a student’s actual and expected standard score is then computed, and the magnitude of that difference is assigned discrepancy percentile rank² and discrepancy standard deviation³ scores. These scores offer interpretive value when reviewing your examinee’s profile.

¹ The subset of core tests used to determine predicted performance depends on the test/cluster being targeted. For example, if we are targeting WJ IV COG Test 1: Oral Vocabulary, the predicted score would be based on the average standard score of the remaining WJ IV COG core tests (Tests 2-7).

²  The discrepancy percentile rank is the percentage of peers, with the same predicted test/cluster performance, that had a difference score of the same magnitude or smaller than your examinee. The discrepancy percentile rank can be thought of as a base rate. Base rates provide an estimate regarding how common or rare a score difference was among other children who had a similar level of ability (i.e., similar predicted score) in the WJ IV normative sample. The utility of base rates is in their ability to tell you whether a difference is clinically significant.

³  The discrepancy standard deviation indicates the distance of your examinee’s difference score from the mean difference score of peers who had the similar performance expectations for a given test/cluster. This score can be thought of as a critical value. Critical values serve as a reference point indicating whether a difference between two scores occurred by chance. Differences in scores that meet or each the critical value are unlikely to have occurred by chance, and are considered to be statistically significant.

Each case scenario below highlights how examiners can use the WJ IV’s variation procedures to easily interpret a student’s personal strengths, and areas that may warrant intervention.

WJ IV ACH Variations: Sarah & Math

Sarah is a fifth-grade student who was referred for a private academic screening assessment due to concerns from her mother regarding her math skills. She currently is in a general education classroom and receives supplementary instruction from a special education teacher to improve her math calculation skills. Despite this additional support, she continues to struggle in comparison to her classmates.

As part of the evaluation, a private psychologist administers the core tests of the WJ IV ACH (Tests 1–6) in addition to the math tests that make up the Broad Mathematics Cluster of the WJ IV ACH, including Test 2: Applied Problems, Test 5: Calculation, and Test 10: Math Facts Fluency. Administration of the WJ IV ACH’s core tests allows the psychologist to obtain a profile of Sarah’s academic strengths and weaknesses through the intra-achievement variation procedures.

Based on the above data, the psychologist finds that Sarah has two significant intra-achievement variations in Applied Problems and Math Facts Fluency.

Applied Problems Interpretation: Sarah’s actual math problem-solving skills were found to be more than two standard deviations below expectations, based on her performance across other areas of achievement. Moreover, the difference between her actual and expected performance on Applied Problems is only observed in 1% of her age-peers. The psychologist interprets this to mean that Sarah performed well below expected levels, and that the observed difference is quite rare when compared to her age-peers.

Calculation Interpretation: Using these data, the psychologist also determines that Sarah’s performance on an untimed measure of mathematical operations was approximately .80 standard deviations above expectations. The psychologist surmises that this is likely in response to Sarah’s participation in supplementary instruction that targets her calculation skills.

Math Facts Fluency Interpretation: Sarah’s actual math fluency skills were also lower than expected, by more than 1.5 standard deviations. In terms of frequency, the difference between her actual and predicted performance on Math Facts Fluency would only occur approximately 4 out of 100 times among her same-age peers. Given the magnitude and rarity of this difference, Sarah’s performance on Math Facts Fluency is deemed an area in need of improvement.

Considering these findings, the psychologist recommends further assessment in the domains of Fluid Reasoning and Cognitive Processing Speed, using the WJ IV COG. The psychologist explains that Fluid Reasoning and Cognitive Processing Speed are predictive of performance in applied problem-solving and fluency tasks, respectively. By administering these domains, the psychologist can compare Sarah’s cognitive functioning to these identified weaknesses in academic achievement. Sarah’s mother agrees to further testing. The psychologist also recommends that Sarah’s school shift Sarah’s supplementary math instruction to target her problem-solving and fluency skills, as her calculation skills were found to be almost one standard deviation above expected levels.

*These data are completely fictional and are solely provided for illustrative purposes.

WJ IV COG Variations: Jacob & Memory

Jacob is a 21-year-old college student who self-referred for a private neuropsychological evaluation after suffering a traumatic brain injury during a car accident. He current sees both a generalist and neurologist for ongoing medical treatment. He reports concerns with following complex (multi-step) directions and recalling information from conversations.

As part of the evaluation the neuropsychologist administers the core tests of the WJ IV COG (Tests 1–7) in addition to the remaining tests needed to derive the Short-Term Working Memory (Tests 10 & 16) and Long-Term Retrieval (Test 13) Clusters.

Based on the above data, the neuropsychologist finds that Jacob has three significant intra-cognitive variations in Verbal Attention, Object-Number Sequencing, and Story Recall.

Verbal Attention Interpretation: Jacob’s ability to hold and manipulate information in his immediate awareness, while honing his attention, tested approximately -1.6 standard deviations below expectations. He struggled when asked to listen to a string of animals and digits and answer a specific question about the sequence. The magnitude of the negative difference between Jacob’s actual and predicted Verbal Attention score is rare, as it is only observed in 5% of those his same age.

Object-Number Sequencing Interpretation: Jacob’s actual working memory capacity also tested lower than expected. His observed performance fell approximately 1.89 SD’s below expected levels when he was asked to listen to a series of objects and digits, separate the information into two groups (e.g., objects and numbers), and then repeat information from each group in sequential order.

Story Recall Interpretation: Jacob faced the most challenges when asked to recall details from orated stories. During this task, Jacob’s ability to use his meaningful memory fell approximately -1.95 SD’s below expected levels.

The neuropsychologist explains that short-term working memory is needed to hold information, such as directions, long enough in mind for it to be processed, and share that Verbal Attention and Object-Number Sequencing, two tests tapping this broad ability, were found to be weaknesses in his profile. The neuropsychologist further shares that Jacob’s meaningful memory was found to be particularly underdeveloped based on expectations set by his performances in other cognitive domains. They express that meaningful memory what we use to remember contextualized verbal information, such as data gathered through informal conversations and classroom lessons. These data are validating to Jacob, who was seeking an explanation for his struggles.

Considering these findings, the neuropsychologist recommends a comprehensive measure of memory, to determine a more detailed profile of Jacob’s learning, and immediate, delayed, and recognition memory capabilities. They also suggest additional testing focused on measuring Jacob’s ability to engage in verbal and visual tasks of sustained attention, as weaknesses in honing attention can impact his ability to effectively store information in his short-term working memory.

*These data are completely fictional and are solely provided for illustrative purposes.

WJ IV OL Variations: Janine

Janine is a 9-year-old elementary school student who is being tested as part of an initial special educational evaluation. Her parents report concerns regarding her foundational literacy skills. As part of her initial evaluation, the speech and language pathologist first administers the core tests of the WJ IV OL (Tests 1–4), which serve as the foundation for the analysis of Janine’s relative strengths and weaknesses in oral language.

Based on the above data, the speech and language pathologist discovered that Janine has two significant intra-oral language variations in Picture Vocabulary and Segmentation.

Picture Vocabulary: Janine’s ability to identify and name pictures tested significantly above expectations when compared to the average of her performances across the other core WJ IV OL tests (SD = +1.51). The magnitude of the difference between Janine’s actual and predicted Picture Vocabulary score is rare, and it is only observed in no more than 6% of those her same age in the normative sample.

Segmentation: In contrast, Janine had trouble when asked to break apart real words into their constituent speech sounds (i.e., phonemes). When compared to same-age peers, the magnitude of her Segmentation difference score is rare, only occurring in 1% of the normative sample. This signals to the speech and language pathologist that this difference is clinically significant. Furthermore, Janine’s Segmentation difference score fell approximately 1.72 SD’s below expected levels, which meets the threshold for statistical significance.

Because of the clinical and statistical significance of Janine’s Segmentation standard score, when compared to her other WJ IV OL performances, the speech and language pathologist decides to conduct additional testing to gain a better understanding of Janine’s phonetic coding skills. They decide to administer both Test 7: Sound Blending, and Test 9: Sound Awareness.

Administering Test 7 allows the speech and language pathologist to determine if Janine’s ability to put speech sounds together (i.e., blend phonemes) may also warrant support. Test 9: Sound Awareness was administered considering, Janine’s performance on Test 3: Segmentation, as the skills tapped by Test 9 (i.e., rhyming and deletion) are lower-order/prerequisite skills needed to engage in more advanced phonetic coding tasks (e.g., segmentation and sound blending).

*These data are completely fictional and are solely provided for illustrative purposes.