NeuroLearning Dyslexia Test

The NeuroLearning Dyslexia Screening Test App was designed, built, and tested by dyslexia assessment experts, using the most up-to-date principles of evidence-based dyslexia assessment, and scored with advanced techniques in psychometric analysis.

• Its nine subtests were designed to mirror an expert assessment, measuring four basic processing skills that contribute to dyslexia risk, and two reading achievement skills whose development lags in dyslexia.
• In tests of over 1000 individuals, Neurolearning's Dyslexia Screening Test correctly identified (as High or Very High Total Dyslexia Score) over 90% of the individuals identified by our dyslexia assessment experts as dyslexic in the test population  (sensitivity).
• In the same testing, fewer than 4% of individuals assessed as POSITIVE (HIGH or VERY HIGH risk range) on the Test were identified as NEGATIVE (LOW or VERY LOW risk range) by the expert diagnosticians (the Test's positive predictive value).
• The Test was also designed to incorporate features of Rasch Modeling, in that it measures both how many and which questions a person answers correctly or incorrectly. This provides a very powerful way of measuring misfit, or whether an individual's pattern of correct and incorrect answers corresponds to the pattern a truly dyslexic individual would show, as compared for example with someone who missed questions due to inattention or to an attempt to falsely qualify as dyslexic by intentionally missing a number of questions.

• The Test was designed by dyslexia assessment experts to determine an individual’s risk or likelihood of dyslexia.
• Its nine subtests were designed to imitate an expert assessment process by measuring four basic processing features known to contribute to dyslexia risk, and two reading achievement skills whose development typically lags in dyslexia.
• In testing with over 1000 individuals, when compared with the determination of dyslexia experts, the Test correctly identified as POSITIVE (HIGH or VERY HIGH risk range) over 90% of the individuals identified by the dyslexia experts in the test population (the Test’s sensitivity).
• In the same testing, only 2% of individuals assessed as POSITIVE (HIGH or VERY HIGH risk range) on the Test were identified as NEGATIVE (LOW or VERY LOW risk range) by the expert diagnosticians (the Test’s positive predictive value).
• The Test was also designed to incorporate features of Rasch Modeling, in that it measures both how many and which questions a person answers correctly or incorrectly. This provides a very powerful way of measuring misfit, or whether an individual’s pattern of correct and incorrect answers corresponds to the pattern a truly dyslexic individual would show, as compared for example with someone who missed questions due to inattention or to an attempt to falsely qualify as dyslexic by intentionally missing a number of questions.
• More detailed descriptions of the test’s design and characteristics are available in the sections below.

The Dyslexia Screening Test App provides users with 3 kinds of information:

1. the likelihood that a particular test subject will experience dyslexia-related challenges at school or work
2. information about a subject’s cognitive learning and processing features, and especially those that often accompany a dyslexic processing style, which will be relevant to providing that individual with appropriate learning and instruction
3. individualized recommendations regarding instruction, accommodations, remediation, and/or need for additional assessment

The two most commonly used definitions of dyslexia in the English-speaking world[1],[2] agree in two key respects:

• That dyslexia’s core diagnostic feature is difficulty developing fast and accurate reading and spelling skills (particularly at the level of sounding out and spelling words) which are unexpected in relation to an individual’s intelligence, age, and education.
• That challenges with the phonological component of language (essentially the way the brain identifies and processes sounds in words) are a key component of the brain-based differences underlying dyslexic reading and spelling challenges.[3] (See Shaywitz, S. Overcoming Dyslexia for a good review of the phonological aspects of dyslexia.)

The Rose Review, which is used in the UK, also notes that challenges with verbal memory and processing speed have also been shown to play a role in dyslexic learning challenges. (See ref. 2)

Both definitions were based on a comprehensive review of the research on dyslexia available at the time of its formulation, and each reflected the broad consensus of understanding current among dyslexia researchers at the time of its formulation.[4]

As additional research has been accumulated, several important additional points about dyslexia have been recognized:

• Dyslexia has increasingly been recognized as a syndrome that is multifactorial in origin, having many possible underlying cognitive contributors rather than just one (i.e., phonological impairments). These factors include not only verbal memory and processing speed (as per the Rose Review), but also word retrieval and naming speed[5], visual attention[6], and overall language ability. (See ref. 4)
• Consistent with the growing recognition of this multifactorial origin, it has been increasingly recognized that the overall likelihood that an individual will show dyslexic reading and spelling challenges rises with the number of risk factors that the individual possesses.[7] As a result, dyslexia risk assessment requires a clear and well-defined way of integrating the results from a wide variety of assessments of different cognitive skills.
• It has also become increasingly clear that students with high verbal ability may experience highly significant challenges with reading and spelling (especially with speed or fluency of reading, stamina for reading, ability to decode unfamiliar words, spelling and writing) that are clearly dyslexic in nature, despite scoring at or above population means on tests of phonological awareness, reading comprehension, and/or other traditional dyslexia assessments.[8] (Verbal IQ, as measured on the WISC, has a correlation of approximately 80% with Vocabulary[9], as measured both on the WISC and our app, so our app uses Vocabulary as a stand-in for Verbal IQ.) For such students, proper identification depends the recognition of discrepancies between their own personal areas of strength and weakness, rather than on comparisons of their weaknesses with population norms.[10] For example, a very bright third grade student who tests into a gifted program with a verbal IQ of 135 (99th percentile), and who tests at the 80th percentile on an untimed reading comprehension test (i.e., reading short stories or informational paragraphs) but who also tests at the 50th percentile on tests of phonological awareness and single word decoding and spelling, will very likely also show academically significant difficulties keeping up class work in reading and writing, and will show difficulties spelling, making “silly mistakes” in reading test items, etc., that are dyslexic in nature and require special intervention, even though by most traditional measures they don’t qualify for a diagnosis of dyslexia. Similarly, among the age 5-6 pre-reading population, individual discrepancies between verbal ability and word and sub-word level reading skills can already be seen, and these often provide the only tip-off that the child is at high risk of dyslexia-related reading and spelling challenges. No other assessment currently in use identifies these children.
• In addition, our series of more than 100 consecutive dyslexic students examined in our own clinic has revealed patterns of relationships between scores on different cognitive measures that are highly distinctive and robust for dyslexic students, and highly predictive both of academic challenges and potentially successful interventions[11]. We’ve appended a graph to this document showing how these students scored on WISC-IV IQ and WIAT-III achievement tests. This graph reveals the characteristic relationships between scores on the various subtests that dyslexic students show, and which are almost entirely preserved across the range of IQs. Note, for example, the consistent broad gap between relatively higher verbal and non-verbal comprehension scores on WISC IQ, and the relatively lower working memory and processing speed scores. Also note the across-the-board reductions in academic fluency skills in such areas as math calculation, reading rate, and essay production. These internal relationships are highly consistent at the individual as well as the population level, and form another signature for dyslexic processing that we have found to have value both in diagnosis, and in recommending interventions.
• Finally, we have found that an individual student’s variations from these characteristic patterns have predictive value in deciding upon what form of interventions they’ll be most likely to benefit from. For example, in the areas of reading and spelling, there are many different kinds of interventions available, some of which use muscle memory, others speech-related memory, others training of auditory processing functions, others visualization or verbal memory (mnemonics), etc. Based upon a student’s unique combination of results in the kinds of subtests featured in our app, we can guide instructors toward the use of interventions that will be especially likely to work successfully with an individual student (and away from less successful methods). The specificity with which we can deliver these results also means that our highly individualized recommendations will fit quite in instructional settings using UDL concepts and methods. [These patterns will be used to make recommendations, but will mostly not be part of the risk assessment algorithm]

In contrast with our assessment tool, most current dyslexia assessments (like the CTOPP, RAN/RAS), and early reading screeners that predict reading acquisition without using the term dyslexia (like DIBELS), do not take into account these more recent discoveries about dyslexia. As such, they often do a poor job both of identifying dyslexic students, and suggesting appropriate interventions.

For example, these tests attempt to measure various aspects of phonological processing (like the ability to segregate, manipulate, identify, retrieve, and remember the kinds of basic sound units that make up words) and/or word retrieval or naming speed, but they all fall short in several ways:

• Although each of these tests measures one or more cognitive skills known to predispose to dyslexic reading and spelling challenges, no single test assesses all or even most of these cognitive skills.
• Some of the skills that predispose to reading and spelling challenges are not included in any current common test (e.g., visual attention).
• Though all currently common tests provide normative information on where an examinee falls in relation to others in their age group on certain cognitive skills, all fail to provide strict criteria for using these results to make a concrete assessment of the likelihood of dyslexia. This is because they all fail to provide examiners with concrete guidance in how to integrate information from the various subtests, or how to use the data generated to calculate an overall likelihood assessment. One result is examiner variability, and uncertainty and inaccuracy in making diagnosis, as a result of which an estimated one in four dyslexic students are not being identified.
• All currently used tests fail to provide guidance regarding individual discrepancy and strength-weakness patterns as discussed above. As a consequence, all routinely fail to identify high verbal “stealth” dyslexic students, or to take advantage of the full range of cognitive skills that can be used to learn basic reading skills and/or build compensatory skills.

In addition, these tests typically require highly time and resource intensive one-one-one administration, and their formats are relatively unengaging for students.

Our screener provides specific results and recommendations in line with the most up to date research-based thinking on dyslexia.

​Citations:

​[1] National Institute of Child Health (2002). Definition of dyslexia. Washington, DC: National Institute of Child Health and Human Development. The key part of the definition reads: ‘Dyslexia…. is characterized by difficulties with accurate and/or fluent word recognition, and by poor spelling and decoding abilities. These difficulties typically result from a deficit in the phonological component of language that is often unexpected in relation to other cognitive abilities and the provision of effective classroom instruction’.

[2] Rose, J. (2009). Identifying and teaching children and young people with dyslexia and literacy difficulties. Available from: http://www.teachernet.gov.uk/wholeschool/sen/ [last accessed 5 July 2009]. This definition reads: ‘Dyslexia is a learning difficulty that primarily affects the skills involved in accurate and fluent word reading and spelling. Characteristic features of dyslexia are difficulties in phonological awareness, verbal memory and verbal processing speed’.

[3] Shaywitz, S. (2003). Overcoming Dyslexia. New York: Simon and Shuster.

[4] Snowling, M, & Rose, J. (2012). Annual Research Review: The nature and classification of reading disorders – a commentary on proposals for DSM-5. Journal of Child Psychology and Psychiatry 53:5. (2012), pp 593–607.

[5] Wolf, M, & Bowers, P. (1999). The double-deficit hypothesis for the developmental dyslexias.. Journal of Educational Psychology 91:3. pp 415–438.

[6] Schneps MH, Thomson JM, Sonnert G, Pomplun M, Chen C, et al. (2013) Shorter Lines Facilitate Reading in Those Who Struggle. PLoS ONE 8: e71161 doi:10.1371/journal.pone.0071161.

[7] Pennington, B.F. (2006). From single to multiple deficit models of developmental disorders. Cognition, 101, 385–413.

[8] Eide, Bl, & Eide, F. (2006). The Mislabeled Child. New York; Hyperion. Eide, BL, & Eide, F. (2011) The Dyslexic Advantage. New York: Hudson Street Press. Eide, BL, & Eide, F., 2e Newsletter. October 2005. Hoeft, Fumiko, in preparation.

[9] WISC-IV. (2003). San Antonio: Pearson.

[10] Turner, M. (1997). Psychological Assessment of Dyslexia. London: Whurr.

[11] Eide, BL, & Eide, F.