**Abstract**

This chapter focuses on the implementation of a response to intervention model for assessment and treatment of dyslexia, dysgraphia and dyscalculia, which is illustrated through a longitudinal case study. The model links learning and adjustment difficulties to multivariate treatment, and through this to firm diagnosis and classification. In applying the model, initial diagnosis of learning disabilities is treated as provisional, based on functional indicators as well as test data. Treatment is then multidimensional, using graded materials that are applied in clinical teaching. The case study shows how firm classification becomes possible through longitudinal assessment and progress evaluation, analysis of response to multivariate intervention as well as response to specific treatment programmes. Diagnosis can then be linked both to concessions and ongoing treatment of areas of functional difficulty in learning and adjustment to school.

**Keywords:** dyslexia, dysgraphia, dyscalculia, reading, writing, spelling, numeracy, working memory, assessment, evaluation, response to intervention, incremental validity, multivariate treatment

#### **1. Introduction**

This chapter provides a longitudinal case study of a dyslexic child (Child H), whose programme included work on a number of fluency-based interventions focused on his difficulties with reading, writing and spelling. Assessment has been based on a response to intervention model (Note 1), linked to treatment using a multivariate approach based on Luria's theories of cerebral organisation [1–4]. In applying the model in working with Child H over a five-year period, labels such dyslexia, dysgraphia or dyscalculia were avoided until such time as treatment programmes had been implemented and Child H was both physically and neurologically mature.

At time of initial assessment, there were a number of different areas in which Child H's reading, writing and spelling were below age level, indicating the need for multivariate treatment. This involved a number of different interventions that were implemented over Child H's years at primary school. In his final year at primary

school, response to intervention assessment was conducted. At this point, a dyslexic label was applied, with a view to motivating for concessions at high school level.

The aim of this chapter is to demonstrate that classification of learning disabilities based on response to intervention is not only possible, but also enhances validity. The case study should be read in conjunction with previous publications in which the approaches and methods used in multivariate assessment and treatment are described in more detail [5–9]. These can be accessed from the publisher free of charge online.

#### **1.1 What is an response to intervention approach to classifying learning difficulties?**

The multivariate assessment and treatment programme implemented with Child H follows Luria's theories in conceptualising competencies in reading, writing, spelling and numeracy as hierarchical and based on the development of automaticity [10]. Automaticity in reading, writing and spelling is linked to fluency on both functional and neurological levels [11], and provides a basis for the development of higher-order mental processing. Following Luria, there is thus value in providing fluency-based interventions which can develop basic skills and competences in reading, writing, spelling as well as numeracy, as these can then form a platform on which the scaffolding necessary to develop higher order functions can be built [12–14].

In working with Child H, the aim was to provide this type of functional platform, by focusing on those areas of his functioning in which he had not yet developed competencies based on automaticity. These areas were identified through assessment based on ICD10 linked indicators (Note 2), which enabled Child H's development as well as his difficulties to be described functionally. Functional assessment then enabled labelling to be avoided until such time as Child H had benefit of focused multivariate treatment, and until such time as he was more developmentally and neurologically mature.

As maturation took place, firm diagnosis and classification as dyslexic then became to Child H's benefit, as the classification could be linked both to longitudinal response to interventions as well as to concessions related to his areas of ongoing difficulty. Firm classification of Child H's learning disability could also be based on incremental validity [15–17] as the dyslexic label could be linked both to cross-sectional assessment as well as longitudinal progress evaluation of his response to multivariate treatment using particular types of methods and materials.

#### **1.2 What is the logic of response to intervention classification?**

There has been intense debate in the literature on assessment and classification of learning difficulties between those who have advocated or rejected the practice of classifying and labelling different types of reading disabilities, as outlined by Elliott and Grigorenko [18]. The debate is based on a number of issues [19], in terms of which response to intervention classification offers the possibility of more valid evidence-based classification of learning disabilities.

The theoretical basis of the response to intervention model we use has been described by others in the literature [20–23] as well as in a previous publication on our work in this practice [9]. A response to intervention approach to classification of learning disabilities has potential benefits in enabling labelling of learning difficulties to be avoided until such time as there is compelling longitudinal evidence concerning the particular nature of a child's learning difficulties. This can be based both on

assessment and evidence concerning how a child copes with school while being provided with learning support.

There are a number of reasons why response to intervention classification of learning disability is logical. One reason is that there is lack of agreement as to typologies of learning disabilities, as well as to how these apply to children and adults. Another is that there is a lack of consensus as to whether it is better to base diagnosis of learning disabilities on purely functional descriptions of the behaviours associated with how learning disabilities manifest in particular children (using terms such as "backward reading", "specific learning disorder, with impairment in reading" or "specific reading retardation"). A third reason is that there is also concern as to whether it is helpful to apply a label such as "dyslexia", "developmental dyslexia", "dysgraphia" or "dyscalculia" to children for diagnostic purposes, and whether this type of labelling can be prejudicial to children and their families.

In addition, much of the literature is based on the evidence that children's learning difficulties are specific [24–40], indicating that some developmental learning difficulties in children may be built-in and immutable, whilst others may be trainable. Assessment procedures and treatment programmes based on a response to intervention model of classification are thus potentially valuable both to therapists and children [20–22], as they work from the standpoint that classifications of learning difficulties are provisional and emergent until such time as they can be based on treatment validity [41].

On the one hand, this standpoint is based on the belief that it makes more sense scientifically to work from a standpoint that treatment validity is increased if one focuses on the evidence one sees, and if one bases treatment directly on evidence of functioning, as well as the errors made by children. On the other hand, it is based on clinical evidence that it makes more sense to work from diagnoses which have the potential of changing from hypotheses to firm and persistent categories as treatment progresses, based on a process of incremental validity [15, 17]. This is the logic of the case study presented in this chapter.

#### **2. Methodological issues**

Unlike my doctoral research which involved an evaluative case study of curriculum development in a programme based on participant observation [42–45], the case study reported in this chapter has been based on a single case (N = 1) design involving longitudinal observation and repeated measurement [46–50]. One purpose has been to implement a changing criterion design to identify the effects of treatments that have been continuously applied as well as varied [51, 52]. Another purpose has been to analyse evidence from a number of indicators to establish gains made over time [49, 53]. A third purpose has been to use common indicators to enable aggregation with the results of other similar N = 1 case studies [54–57].

One limitation is that this case study is based on ex post facto analysis [58, 59]. As human memory is limited and ex post facto analyses are subject to misinterpretation [60–63], a behavioural diary based on a computer-based treatment file supported by longitudinal written file notes has been used to record work done in the sessions worked with the child [64–66]. This activity-based evidence of focuses and types of longitudinal intervention has then been combined with analysis of school reports as well as repeated measurement of outcomes based on use of psychometric testing. The aim has been to link both focuses and sequences of treatment to progress in a time line recording use of methods and materials focused on the development of basic skills in reading, writing and spelling as well as working memory for both written words and written words in sequence. This type of treatment evidence has then been combined with psychometric testing to enable firm classification of learning disability, based on the suggestions made by Vaughn and Fuchs [21], and Fletcher and Vaughn [22].

As readers may have interests in methods and materials used in treatment, instruments used in assessment as well methods used for evaluation of progress, this chapter describes methods used in treatment, materials used in treatment as well as evidence of outcomes based on longitudinal psychometric testing, using the types of psychometric instruments commonly used in our country as indicators of underlying learning disabilities [6, 7]. Progress and outcomes are then presented descriptively, linked to graphs.

There are many limitations in this type of descriptive case study on a methodological as well as on an inferential level. One limitation is that ex post facto analysis is best suited to description of relationships as opposed to statistical testing of results [60, 62], and for this reason the case study focuses on practical as opposed to statistical significance of test results [67, 68]. Other limitations are implicit in the use of interpretive multimethod analysis and reporting [69, 70], based on evidence from repeated measurement, analysis of trends in school reports as well as visual analysis of graphs of standard scores on psychometric tests [71, 72]. To counter these limitations and increase the likelihood of unbiased and valid interpretation, a colleague has been involved in both the psychometric testing and the analysis of Child H's progress and results [Note 3]. The aim has been to enable data, investigator and time triangulation of longitudinal evidence, based on the suggestions for prolonged engagement and use of multiple data points and multiple investigators made by Denzin [73, 74], and by Guba and Lincoln [75, 76].

Ethically, in addition to parental permission, this case study follows the suggestions made by Yin [59], who has recommended use of pseudonyms for purposes of anonymity in reporting, and the checking of both reporting and interpretation both by participants and by at least one external source [77]. The use of testing and test data would comply with the standards applied by other practitioners working in our country [6], as well as the suggestions for use of response to intervention assessment made by others working internationally [23, 78].

#### **2.1 Classification of particular type of learning disability on the basis of response to intervention: a longitudinal case study**

The purpose of the rest of this chapter is to present a longitudinal case study of a single child (Child H), which illustrates the way in which children can be assessed and then taught using a response to intervention approach. Learning difficulties in children are defined as functional difficulties in learning and adjustment to school and conceptualised as multivariate [79–82] requiring a combination of different types of interventions (Note 4).

Initial assessment is thus conducted functionally, with the aim of establishing the child's areas of difficulty. Interventions are then normally longitudinal and conducted side by side with the curriculum taught in the child's school. Firm classification as dyslexic, dysgraphic or dyscalculaic can then be based on evidence which is incremental as well as multimethod, based on a process of both cross-sectional and longitudinal triangulation [83–85].

#### *Multivariate Treatment of Dyslexia, Dysgraphia and Dyscalculia DOI: http://dx.doi.org/10.5772/intechopen.110287*

The model for classification has been described in a previous publication [9], and the aim of the case study provided in this chapter is to provide evidence of how the model can be applied in practice. This will be done through an extended case study of a child with learning difficulty, who has been involved in working with my practice for a number of years. The child's development will be described longitudinally from the time he was first assessed at age nine through to the time of transition from primary school to high school at age thirteen. At this point, based on longitudinal evidence, firm classification as dyslexic was made, linked to concessions in reading, spelling and rate of work.

The model for response to intervention classification of learning disabilities is reflected in **Figure 1** below. It will be noted that the model is multimethod, based on summative assessment linked to progress evaluation of longitudinal interventions conducted across a number of areas of functional difficulty. The model enables incremental validity, based on triangulation across different data points over time [15, 86].

In applying the model, firm classification of Child H's learning disability was avoided until such time as there was longitudinal and cumulative evidence concerning his response to the particular methods used in his multivariate treatment programme. At the point of transition from primary school to high school level, classification as dyslexic, dysgraphic or dyscalculaic could be based on both incremental and treatment validities, through analysis of evidence of his response to particular methods, materials as well as teaching techniques. It could also be based on a combination of assessment methods [17, 41].
