An Examination of Language and Reading Comprehension in Late Childhood and Early Adolescence

DISSSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy

in the Graduate School of The Ohio State University

By

Margaret Beard

Graduate Program in Education: Physical Activity and Education Services

The Ohio State University

2017

Dissertation Committee:

Kisha M. Radliff, Ph.D., Advisor

Antoinette Miranda, Ph.D.

Stephen A. Petrill, Ph.D.

Copyrighted by

Margaret E. Beard

2017

Abstract

The simple view of reading suggests that proficient reading comprehension is the product of two factors, decoding (word recognition) and language comprehension

(understanding spoken language), that are developmental in nature. Decoding accounts for more variance and predicts reading abilities in younger children, then as children age, language comprehension becomes more of a primary influence and predictor for comprehension ability. This study fills a gap by assessing the relationship between language ability and reading comprehension in older children.

This study sample included participants in late childhood (n=582) and late adolescence (n=530) who were part of a larger longitudinal twin project. Results suggested significant positive correlations between decoding, vocabulary, language comprehension, and reading comprehension during both late childhood and early adolescence. Decoding and language comprehension explained 48.5% of the variance in reading comprehension in late childhood and 42.7% of the variance in early adolescence.

Vocabulary made a unique contribution to reading comprehension above and beyond that made by decoding and language comprehension and significantly explained an additional

9.4% of the variance in late childhood and 17.3% in early adolescence. In late childhood, vocabulary and decoding were similarly important predictors of reading comprehension, while in early adolescence the importance of decoding had faded and vocabulary was the

ii most important predictor. Implications of these findings, limitations, and future directions for this research are discussed.

iii Acknowledgments

I would like to thank my dissertation committee for giving their time, support, and feedback. You have helped me to grow as a clinician and researcher. I would like to express my gratitude to my advisor, Dr. Kisha Radliff, for her support, patience, and encouragement throughout my graduate studies. Her technical and editorial advice was essential to the completion of this dissertation. I would like to specifically thank Dr.

Stephen Petrill. I would not be where I am today personally or professionally without your belief in me. Thank you for introducing me to the wonders and frustrations of scientific research. You have provided immeasurable amounts of opportunity and have supported me in a number of ways throughout this journey and I am especially thankful for your mentorship along the way. Finally, I would like to thank my husband and children for being patient and understanding as I tried to simultaneously balance being a full-time graduate student with a full-time job. It’s been a long tough journey with a lot of sacrifices. I could not have accomplished any of this without the assistance of you all.

iv Vita

2002...... A.A.B. Telecommunications and

Networking, Edison CC

2007...... B.A. Speech and Hearing Science, The Ohio

State University

2011...... M.A. Human Development and Family

Science, The Ohio State University

2012 to present ...... Graduate Student, Department of

Educational Studies, The Ohio State

University

Publications

Beard, M. E., (2017). Considering specific language impairment (SLI) when assessing

learning disabilities. The Ohio School Psychologist, 62 (2).

Beard, M.E. (2015). Conceptualizing Problems by focusing on Cultural Context, Bias,

and Generalization. In A. H. Miranda (Ed.), Consultation across cultural context:

Consultee-centered case studies. New York: NY Routledge Publishers.

v Fields of Study

Major Field: Graduate Program in Education: Physical Activity and Education Services

vi Table of Contents

Abstract ...... ii

Acknowledgments ...... iv

Vita ...... v

Publications ...... v

Fields of Study ...... vi

List of Tables ...... x

Chapter 1: Introduction ...... 1

Purpose of the Study ...... 1

Research Aims ...... 3

Definition of Terms ...... 3

Chapter 2: Literature Review ...... 6

Big Ideas of Reading ...... 7

Basic Components of Language ...... 13

Models of Reading Comprehension: From Past to Present ...... 19

Chapter 3: Methods ...... 66

Participants ...... 67

vii Data Collection Procedures ...... 69

Constructs and Measurement ...... 69

Chapter 4: Results ...... 76

Testing Assumptions for Linear Regression Model ...... 76

Aim 1: Examining the Correlation Between Decoding, Language Comprehension,

Vocabulary and Reading Comprehension in Late Childhood and Reading

Comprehension in Early Adolescence...... 79

Aim 2: Investigating the Unique and Combined Contribution for the Simple View

Variables (Language Comprehension and Decoding) on Reading Comprehension

During Late Childhood and Early Adolescence...... 84

Aim 3: Examining Whether Vocabulary Adds a Unique Contribution to the Simple

View Model During Late Childhood or Early Adolescence...... 86

Chapter 5: Discussion ...... 92

Aim 1: Correlation Between Study Variables in Late Childhood and Early Adolescence

...... 93

Aim 2: Contribution for the Simple View Variables on Reading Comprehension during

Late Childhood and Early Adolescence ...... 94

viii Aim 3: What Vocabulary adds to the Simple View Model during Late Childhood and

Early Adolescence ...... 95

General Conclusions ...... 96

Limitations ...... 97

Directions for Future Research ...... 98

References ...... 100

ix List of Tables

Table 1. Descriptive Statistics ...... 80

Table 2. Pearson Correlations Between Measures of Available Data ...... 82

Table 3. Simple Regression Analyses for Variables Predicting Reading Comprehension in Late Childhood and Early Adolescence ...... 85

Table 4. Hierarchical Regression Analyses for Reading Comprehension in Late

Childhood and Early Adolescence ...... 88

x Chapter 1: Introduction

Purpose of the Study

The purpose of this study is to examine developmental changes in the components for the Simple View Model of Reading. The simple view of reading indicates that reading comprehension is a product of decoding and language comprehension (Hoover & Gough,

1986, 1990). This well established conceptual model of reading is widely accepted and has a large research base of support. Studies have shown that measures of word recognition and listening comprehension skills account for a large amount (45–85%) of the variance in reading comprehension (Adlof, Catts, & Little, 2006; Braze, Tabor,

Shankweiler, & Mencl, 2007; Catts, Hogan, & Adlof, 2005; Hoover & Gough, 1990;

Joshi & Aaron, 2000; Kershaw & Shatschneider, 2012; Young-Suk, Wagner, & Foster,

2011). Additionally, studies indicate that the relative contributions of these components change over time (Catts et al., 2005; Francis, Fletcher, Catts, & Tomblin, 2005; Gough,

Hoover, & Peterson, 1996). In the early grades, reading comprehension is mostly explained by word recognition skills. As students move to more linguistically difficult texts in later grades, the contribution of listening comprehension increases, whereas the contribution of word recognition decreases (Adlof et al., 2006; Florit & Cain, 2011;

Gough, Hoover, & Peterson, 1996; Kershaw & Schatschneider, 2012). Despite these findings, there is still a proportion of unexplained variance in reading comprehension not accounted for by decoding and language comprehension. Educationally, a better

1 understanding of how the components of the simple view model change over time could have a significant impact on how we conceptualize and treat reading comprehension difficulties. This study also has the potential to contribute to gaps in the literature for older children as many preliminary studies have suggested more research be conducted.

A number of research studies investigating the influence of vocabulary and fluency as additional components of the simple view model, found a plethora of evidence where decoding explained more variance in reading comprehension at a younger age or grade level, while language comprehension explained more variance in reading comprehension at older ages or grade levels (Adlof et al., 2006; Florit & Cain, 2011;

Gough, Hoover, & Peterson, 1996; Kershaw & Schatschneider, 2012). This suggests that there is an age-dependent relationship between reading and language, thus meriting a deeper investigation of this relationship and how the relationship between these constructs change over time. Thus far, results from studies investigating the simple view model of reading have suggested that language comprehension is of greater importance for later reading comprehension abilities (i.e., grade four and above).

Given the developmental relationship between reading and language, a goal of this study was to further understand decoding and language comprehension as a product of reading comprehension during late childhood and early adolescence. Also, vocabulary was evaluated as a potential, and unique, contributor to the reading comprehension process during late childhood (M = 9.81 years) and early adolescence (M = 12.21 years).

Reading and language data during these time points was extracted from a longitudinal twin sample. Regression models were used to examine language and reading during two periods of development suggested by previous researchers to be specifically important in 2 terms of their overall contribution within the simple view model as well as their unique contribution given the influence of age. Finally, vocabulary was added into the model to examine whether or not vocabulary added a unique contribution above and beyond decoding and language comprehension and whether or not it accounted for more overall variance when added into the model.

Research Aims

Specific Aim 1. First, examine the correlation between decoding, language comprehension, vocabulary and reading comprehension in late childhood and reading comprehension in early adolescence.

Specific Aim 2. Next, investigate the unique and combined contribution for the simple view variables (language comprehension and decoding) on reading comprehension during late childhood and early adolescence.

Specific Aim 3. Finally, examine whether or not vocabulary adds a unique contribution to the simple view model during late childhood or early adolescence?

Definition of Terms

Alphabetic Principle – The understanding that letters represent sounds which form words.

Early Adolescence – A sub stage of adolescent development between the ages of 11-14 where critical and rapid physical, cognitive, and social/emotional development occur.

Expressive Language - The production of spoken or written language.

Grammar – A set of structural rules governing the composition of clauses, phrases, and words. Typically, it is comprised of morphology and syntax.

Grapheme – A letter or a number of letters that represent a phoneme in a word. 3 Late Childhood – A period within the developmental stage of childhood marked by a period of development from ages 9 through 12, generally ending with the onset of puberty.

Metalinguistic Ability – The ability to reflect on language. To have an understanding that language goes beyond what is said and how it is used.

Morpheme – The smallest linguistic unit within a word that can carry a meaning, such as

“un-“, “break”, and “-able” in the word “unbreakable.”

Bound Morpheme – Morphemes that are not full words on their own and have to

be attached to a free morpheme (i.e., prefixes, suffixes, or other linguistic pieces).

Derivational Morphemes – Bound morphemes that change the way a word is

used in a sentence or utterance (i.e., happy – happiness; construct – construction).

Free Morpheme – Morphemes that are used alone as a word.

Morphology – The study of words, how they are formed, and their relationship to other words in the same language.

Phonemic Awareness – The ability to hear, identify, and manipulate individual phonemes. Phonemic Awareness is the basis for learning phonics.

Phoneme – The smallest unit of sound, which is combined with other phonemes to form words. They correspond to sounds of the alphabet, but there is not always a one-to-one relationship between a letter and a phoneme. The English language has approximately 45 different phonemes, which correspond to letters or combinations of letters.

Phonetics –The study of speech sounds and their physiological production and acoustic qualities.

4 Phonics – The method of teaching reading and writing by developing learners’ phonemic awareness in order to teach the correspondence between the sounds and the letter or group of letters (grapheme) that represent them.

Phonological Awareness – The ability to hear and manipulate larger units of sound, such as onsets, rimes, and syllables. It also includes the ability to hear and manipulate individual phonemes (Phonemic Awareness).

Phonology – The study of speech sounds.

Pragmatics – The ways that language is used in different settings and for different purposes. Pragmatics involves using language for different purposes, changing language according to the needs of listener, and following rules for conversation or storytelling.

Receptive Language – The comprehension of language, as in listening or reading.

Regular Word Reading – Words that have sound letter correspondence for their sounds, or words that are decodable.

Semantics- The aspect of language that involves word meanings/vocabulary.

Syntax- A set of rules for constructing full sentences out of words and phrases. All languages have some form of syntax, but every language has different syntactic rules.

5 Chapter 2: Literature Review

Reading comprehension and language comprehension are both multi-faceted, and consist of a number of integrated skills and processes (Kamhi & Catts, 2013; Kirby &

Savage, 2008; Leslie & Caldwell, 2009). Thus, it is the general consensus of the field that the two are not well operationalized and are highly overlapping constructs (Kamhi &

Catts, 2013; Paris, Carpenter, Paris, Hamilton, 2005; Tunmer & Greaney, 2010). Despite the lack of clarity in definitions regarding what constitutes each broad construct within the field, a great deal of progress has indeed been made to understand the contribution of language and various reading skills, such as phonological skills, decoding, word identification, vocabulary, and fluency on reading comprehension abilities.

Reading is complex and developmental in nature; and it encompasses a number of distinct skills. Reading is not a straight forward process. In fact, it is a complex cognitive process that involves processing visual print, decoding of sights and sounds, and infusing text with meaning. It requires the synthesis of several cognitive skills (i.e., phonological awareness, letter recognition, word reading accuracy, and fluency) and a number of interactive reading skills that vary by the reader (i.e., reader’s knowledge base, type structure, topic of text, reading purpose, and understanding of reading strategies). It requires continuous practice, development, and refinement. Reading comprehension, the end goal of learning to reading, is a widespread construct comprised of a number of skills and processes, making it more difficult to disentangle.

6 Language is an essential process to almost everything we do, and has a large impact on reading. Language is developmental in nature and for the most part is unconscious.

Language development and the ability to effectively communication are highly dependent on and integrated with other developmental domains (i.e., phonology, morphology, syntax, semantics, and pragmatics). Language skills are a reflection of one’s knowledge and capability and are comprised of both production and understanding. Thus, reading and language are intricate and complex processes that are closely related and dependent upon one another. It was originally suggested that phonological skills played the largest role in influencing reading comprehension ability (Gillon, 2004; Gough & Tunmer, 1986;

Stanovich, 1988, 1991); however, over time research studies began to see patterns of language difficulties in children who previously observed as exhibiting reading difficulties (Cain & Oakhill, 2006; Cain, Oakhill, & Bryant, 2000; Catts, 1993, 1997;

Catts & Kamhi, 2005; Nation & Snowling, 2004). Thus it became increasingly important to investigate and further understand the influence that language has on reading comprehension collectively.

Reading comprehension and language are multi-faceted by nature, such that they both consist of multiple underlying skills. Understanding the role of language as it relates to reading comprehension, is a topic that has been of concern in the field for quite some time.

Big Ideas of Reading

A vast number of children have difficulty learning to read and often fall behind, struggling with reading and other academic subjects throughout childhood and well into adulthood. An immense amount of research across multiple disciplines has sharpened our 7 understanding of the skills necessary for becoming a good reader. Theoretical concepts have been developed and refined over time, allowing us to conclude that there is common agreement for the basic skills necessary for becoming a good reader. More importantly, an abundance of research has led to an even better understanding for the underlying skills and processes that, when not developed, often lead to reading difficulties.

The overall goal of reading is to be able to extract meaning from, or comprehend what is read. While it sounds relatively simple, 10-15% of the population struggle with reading comprehension (Nation Snowling, 1997; Yuill & Oakhill, 1991). Thus, a great deal of effort has been invested in understanding why comprehension is a difficult skill for some to ascertain. Reading comprehension is indeed a complex construct to investigate and to understand, simply because it requires integration of multiple skills and processes. Wagner and colleagues state that reading comprehension is a complex skill because it requires readers to recognize and decode individual words, access their meanings, and determine their grammatical structure (Wagner, Schatschneider, &

Phythian-Sence, 2009). A lot of research has gone into understanding the individual components and processes that encompass reading comprehension ability. For numerous years, many argued that impaired phonological abilities (i.e., difficulty parsing word sounds) were the cause for reading comprehension difficulties. However, over time we have learned that while phonological abilities are indeed influential, they are not the sole contributor for children’s struggle to gain meaning from text.

Researchers have continued to examine other factors, like language ability, vocabulary, word reading ability, background knowledge, strategy instruction, and inference making ability, which is important given the number of kids who have 8 difficulty with comprehension. The alarming rates of children reading below proficient levels caused Congress to take action. In 1997, Congress asked the National Institute of

Child Health and Human Development (NICHD), along with the U.S Department of

Education, to form the National Reading Panel to review and synthesize current research to evaluate the most effective methods of reading instruction to improve comprehension.

Their findings revealed that there are five essential components stemming from this instruction that are necessary for every child to develop basic reading skills. They are phonemic awareness, phonics, fluency, vocabulary, and comprehension, which are now recognized as the “Big Ideas of Reading” (NICHD, 2000).

Phonemic Awareness. Phonemic Awareness is the ability to hear, identify, and manipulate the individual sounds of phonemes of spoken words, and the understanding that spoken words and syllables are made up of sequences of speech sounds (Yopp,

1992). It requires children to be able to recognize how letters represent specific sounds, and overall, children must be able to understand that words are broken down into sounds or phonemes, and that these sounds can be put back together to make words. Within this, phonemic awareness is just one aspect of phonological awareness, and is purely auditory

(not involving printed words). It is an important skill because it serves as a prerequisite to reading words. Phonemic awareness is not phonics, but without phonemic awareness, phonics would make little sense. In fact, phonemic awareness skills are important because they help individuals learn to spell and improve word reading and comprehension abilities. Adams (1990) and Stanovich (1986) indicated that phonemic awareness is one of the best predictors for a child’s reading ability within the first few years of school. It is developed through a variety of activities like sound identification 9 and categorization, sound blending to form words, addition or deletion of sounds to form new words, and sound substitutions to make new words (Adams, 1990; Stanovich, 1986).

Phonics. Phonics represents one’s ability to understand that written letters have specific correspondence to sounds. Phonics also may be understood in terms of the alphabetic principle. Phonics is the method of educating children about the alphabetic principle by teaching the relationship between printed letter (graphemes) and the sounds of spoken language (phonemes). The alphabetic principle is composed of two parts: alphabetic understanding and phonological recoding. Alphabetic understanding is knowledge that words are composed of letters, which represent sounds. Phonological recoding is being able to use systematic relationships between letter and phonemes

(letter-sound correspondence) to retrieve the pronunciation of an unknown printed string, or to spell words. Phonological recoding consists of regular word reading, irregular word reading, and advanced word analysis (NICHD, 2000).

Decades of research have provided evidence that there is a connection between the sounds of speech and print. There is very little disagreement that phonics is an important prerequisite skill for other basic reading skills. Research has demonstrated that phonics relates to effective word identification, and is an important prerequisite for developing fluency skills so that children can more accurately connect the unknown sounds of words as they read (Pikulski & Chard, 2005; Torgesen, 2002). Understanding the relationship of letters to sounds is also a foundational component for spelling. Letter- sound knowledge serves as a prerequisite to effective word identification, such that being able to apply this skill is usually the primary difference between good and poor readers

(Juel, 1991). Stanovich (1986) suggests that students who are able to attain and apply the 10 alphabetic principle early on will likely have long term benefits and reduce the risk of reading difficulties.

Fluency. Fluency is being able to read aloud with accuracy, speed, and expression. Good fluency skills allow children to read words automatically with little to no mental effort. This requires children to have word recognition skills that are accurate and automatic. This is important, because children who have fluent reading skills are able to conserve their mental efforts, enabling them to comprehend material more readily.

Also, research has indicated that there is a strong correlation between a student’s ability to read grade level text orally, and also have the ability to comprehend what they read.

Much of this is believed to be attributed to the automaticity theory (LaBerge & Samuels,

1974), as automatic word recognition frees cognitive resources necessary for higher-level processing required for comprehension. Proficient readers are so automatic with each component skill (phonological awareness, decoding, and vocabulary) that it allows them to achieve a greater focus of extracting meaning from what they have read (Kuhn &

Stahl, 2000). Finally, fluency has been shown to consistently correlate with reading comprehension, and is commonly used as a predictor of comprehension abilities in young readers (Miller & Schwanenflugel, 2006).

Vocabulary. Vocabulary refers to understanding the meaning of words. A relationship between vocabulary and reading ability was established in the early days of reading research, and has been found to be consistent over time. Carroll (1993) suggested that reading comprehension ability and vocabulary are also highly correlated in both children and in adults. Not only is it a good predictor of one’s reading comprehension ability, it is also a good predictor of verbal IQ (Anderson & Freebody, 1981; Ouellette, 11 2006Sternberg & Powell, 1983). There are two types of vocabulary, oral and reading.

Oral vocabulary refers to being able to understand the words of one’s speech, and reading vocabulary refers to being able to understand and recognize the meanings of printed words. The earliest research on reading established a relationship between vocabulary and comprehension and this relationship has been supported over time (Cain, Oakhill, &

Lemmon, 2004; Ouellette, 2006). However, a lot is still unknown about the nature, mechanisms, facilitation and acquisition for which vocabulary develops. Prior to literacy, vocabulary and meaning were acquired through speech. However, literacy has allowed individuals the ability to read and gain meaning, and refine the meaning of words through their reading experience (Verhoeven & Perfetti, 2011).

Comprehension. Lastly, comprehension is defined as the process of constructing meaning by coordinating a number of complex processes (i.e., phonological skills, word reading, word knowledge, fluency, language comprehension, memory, etc.).

Understanding how to extract meaning from what is read is complex and intentional.

Klingner, Vaughn, and Boardman (2007) suggest that reading has little meaning if students are unable to construct meaning from the text, and while fundamental skills such as phonics and word recognition are basic building blocks of reading, there are a number of other processes and skills that are required for successful comprehension abilities.

Difficulties with the foundational skills of reading impede successful growth in language, which has a significant impact on later reading abilities. More importantly, even though children may have established relatively good foundational skills in reading, they can still struggle in the ability to learn from text.

12 Basic Components of Language

While it is true that the “Big 5” have been found to be the primary components of reading, there is also an overwhelming amount of research that asserts oral language skills as an important component of reading. Language is essential to our society and is the foundation of our perceptions, communication, and daily interactions. Individuals must be able to both acquire language, and then use it appropriately and effectively in a variety of settings. Language is the medium of communication both with others and within ourselves (Otto, 2002). The American Speech-Language Hearing Association defines language as the comprehension and/or use of a spoken (i.e., listening and speaking), written (i.e., reading and writing), and/or other communication symbol system

(i.e., American Sign Language). Language is often classified as receptive (i.e., listening and reading) or expressive (i.e., speaking and writing). Individuals are usually able to perceive specific characteristics of language (receptive), but are not able to produce

(expressive) language until they can learn the various elements of language. Therefore, an individual’s receptive language abilities are typically better than their expressive language abilities (Kaderavek, 2015).

Speech and language skills are essential for academic success and learning, and children acquire these skills at various rates and ages. Considering language is necessary for communication, it is foundational to reading, writing, listening, and speaking. Thus, in the presence of impairment, poor language skills naturally affect the child’s ability to interact with others and learn. Language acquisition is one of the key milestones of early childhood development. There are benchmarks for what is considered to be normal language acquisition, based on a child’s age and language development. Children with 13 language difficulties may have trouble understanding language, following directions, and choosing appropriate words to combine into comprehensive sentences. The entire future of a child can hinge on this milestone as it affects social, emotional, intellectual and academic achievement and development. Poor language acquisition can lead to isolation and withdrawal and poor academic performance, which will lead to the development of learning disabilities and social problems (Kamhi & Catts, 2014).

Language is considered to be a natural learning process, while reading is not, thus making reading a much harder task to master, as it must be consciously learned. Piper

(2003) describes reading as the dominant language-learning task that children face as they enter school. Readers must be able to transform graphemes (letters) into their corresponding phonemes. From there, they must acquire the knowledge and skills for phonological awareness. These skills then are important for vocabulary and fluency development, and these primary reading skills then all tie together to account for comprehension abilities. Language abilities are an underlying component of all of these skills, which is in part why many have argued that there is a relationship between children’s spoken language skills, and their reading development. Most children learn the concepts of oral language overall, making reading acquisition somewhat easier. However, some children still struggle with a variety of reading skills, simply because they have or have had difficulty learning and using language appropriately.

There are components of language that are involved in nearly every aspect of reading. Individuals must be able to bring a variety of oral language skills to the reading process. Most theorists in the field studying various aspects of language have agreed that language refers to five basic language domains: phonology, morphology, syntax, 14 semantics, and pragmatics. Gleason and Ratner (2012) suggest that these individual language domains comprise the spoken language and written language and their associated components and do not develop in isolation from each other.

Phonology (Phonological Awareness). Phonology is the study of speech sound

(phonemes) system and includes rules for combining and using phonemes. Phonemes are the specific sounds of speech, yet the smallest units of sound that makes up a language.

They are the building blocks for word production when speaking. Phonology of spoken language is the ability to identify and distinguish phonemes while listening (phonological awareness). It also involves the appropriate use of phonological patterns while speaking.

The phonology of written language is the understanding of letter-sound associations while reading (phonics) or the accurate spelling of words while writing.

Phonology has a significant impact on both listening and reading skills (Nation &

Snowling, 2004). Children must first be able to understand that speech consists of phonological properties, such that words are broken down into individual language sounds or phonemes. This is an important step for being able to process language.

Phonological awareness requires the conscious ability to notice that unique differences exist between words and that not all sounds are the same. As children develop phonological awareness skills, they begin to understand that words are made up of small sound units (phonemes) and that words are can be segmented into larger sound chunks known as syllables. Phonological awareness is the basis for phonics. Phonics (another big idea of reading) is the understanding that sounds and print letters are connected, which is one of the very basic skills towards reading. Children with good phonological awareness

15 skills are able to break words into syllables, rhyme, blend phonemes into syllables and words, and identify beginning and ending sounds that make smaller and larger words.

Phonemic awareness (another big idea of reading) then is the skill within the larger construct of phonological awareness that is a conscious language skill. Phoneme awareness abilities allow children to be able to perceive the smaller sounds of spoken words and be aware of the differences between phonemes that allow for the substitution and manipulation of words. Children who have developed good phonemic awareness skills are able to understand that phonemes are blended together to make words and that changing even one phoneme changes the entire word and its meaning (Torgesen, Wagner,

Rashotte, Burgess, Hecht, 1997). Thus, they are able to understand that each sound of a word affects its meaning. Decades of research illustrate the importance of phonemic awareness in reading acquisition skills, and have demonstrated that poor phonemic awareness is often been associated with poor reading skills (Ehri, Nunes, Willows,

Schuster, Yaghoub-Zadeh, & Shanahan, 2001). Once children have achieved a fairly good mastery of phonemic awareness skills they are generally able to understand the unique phonological differences within language. There is a distinction between phonological awareness and phonemic awareness, but often the two are used interchangeably; especially in reading literature. Phonological awareness is a broad skill that involves the manipulation of units of language (i.e., words, syllables and onsets and rimes), while phonemic awareness is the identification of individual sounds (phonemes) in spoken words. These basic reading skills serve as building blocks to a number of other advanced language and reading skills that serve as an integral part of reading comprehension. 16 Grammar (Morphology and Syntax). Grammar typically refers to how words and their component parts are combined to form phrases, clauses, sentences, and other units. Typically, it is comprised of morphology and syntax. Morphology is the study of word structure and is comprised of the smallest units of meaning that make words. These are called morphemes. Morphemes include base words like “mat”, “cat”, or “run,” as well as prefixes and suffixes like “un-,” “re-,” and “s,” “es,” and “ed.” Words may consist of multiple morphemes. Words are morphemes if they cannot be further divided without losing their meaning. Morphemes that are words are usually further divided into content words or function words. Content words (i.e., verbs, nouns, adjectives, and adverbs) carry a message and function words (i.e., prepositions, conjunctions, and articles) usually denote relationships. Morphemes can be free morphemes (stand alone) or bound morphemes (must be attached to another morpheme). Bound morphemes are further defined as inflectional or derivational morphemes. Inflectional morphemes can only be suffixes, while derivational morphemes can include prefixes and suffixes.

Grammatical morphemes indicate the inflections of case, number, and person agreement and are attached to the base word without changing the meaning (e.g., play, played, playing). Derivational morphemes actually do change the meaning of the base, deriving new words (e.g., drink vs. drinkable). Knowledge of the morphology of language is critical to vocabulary and comprehension.

Syntax is the rule that pertains to the ways in which words are combined to form sentences, phrases, and clauses to form meaningful units. Syntax allows individuals to both construct and understand sentences by correctly sequencing words; it provides the rules of grammar for language. There are also other rules that govern the ordering of the 17 parts of speech. For example, adjectives signifying color never precede adjectives signifying size when modifying a noun. Thus, it would be incorrect to say, “The green big tractor raced through the field.” Instead it is grammatically correct to say, “The big green tractor raced through the field.” Word order and levels of complexity may increase, but still hold the same meaning. For example, “The boy hit the ball” and the “The ball was hit by the boy” refer to the same thing, but the word order of the sentences are different. Many of us are able to naturally distinguish and produce a meaningful grammatical sentence without even thinking about it.

Semantics. Semantics refers to the ideas, intention, and feelings that speakers wish to communicate to others. It is more or less the relationship between language and thought, and is the way in which we convey meaning and define the relationship between words and sentences. Vocabulary is an important part of semantics. Semantics often moves beyond the literal meaning of words to convey a specific message, and can often include slang. For example, “The boy gave the girl the cold shoulder” does not necessarily imply handing a cold shoulder to her, but instead means he ignored her. In order to understand, the individual usually has to have experience with it personally, and be able to move beyond the literal meaning of the sentence. This is why semantics can be difficult for other cultures to understand. It often requires experience and familiarity with words or phrases to be able to understand the implied meaning rather than the literal meaning of certain words.

Pragmatics. Pragmatics refers to the rules that are associated with the communicative use of language, especially in social-cultural contexts. Different contexts are characterized by the differences in the way that the language is used. Pragmatics 18 involves three major communication skills: using language, changing language, and following rules. Pragmatic difficulties often coexist with other language problems like vocabulary development and grammar. Individuals need to be able to use language for different purposes (e.g., greeting, demanding, requesting, promising, informing, etc.).

They also need to be able to change language to meet the needs of a specific listener or situation (e.g., talking differently to a child than an adult or speaking differently during a presentation than with peers at recess). Finally, individuals should be able to follow the rules of conversation and storytelling (e.g., taking turns in conversation, staying on topic, using verbal and nonverbal signs of communication, and maintaining appropriate eye contact and facial expressions). Pragmatic rules vary from culture to culture, so it is important for one to understand the social context they are embedded within, while also considering the person or persons with whom you are conversing.

Understanding the role of language on the individual processes of reading has helped advance our understanding of reading comprehension. Over time, models of reading comprehension have been created, revised, and updated, but there is still a great deal of progress to be made.

Models of Reading Comprehension: From Past to Present

Early Research: A Phonological Model of Reading

Original theories of reading comprehension development suggest that impaired phonological skills were the culprit for poor comprehension skills. There are a number of theories regarding reading development, but the vast amount of attention has been given to those highlighting the importance of phonological skills in learning to read (Snowling,

2000). To date, it is believed that children who do not do well with phonemic awareness 19 tasks are at a greater disadvantage when learning to read, simply due to complications with their phonological skills in comparison to those who have age-appropriate phonological skills (Byrne, 1998; Ehri et al., 2001; National Early Literacy Panel

[NELP], 2008; Ouellette & Sénéchal, 2017). Further, a number of empirical studies have suggested that impaired phonological skills account for a large portion of the variance in reading disabilities, as well as the prediction of reading difficulties overall. Stanovich

(1988), among others, proposed that the core problem for many reading difficulties was due to a breakdown in phonological skills. He derived the “Phonological-Core-Variable-

Difference Model” which was based from the assumption that reading difficulties are closely associated with language difficulties, but that they were more phonological than syntactically or semantically based.

Ehri (1992) suggests that children acquiring reading skills must be able to map the phonemes of spoken words to the letters and graphemes of written words. This is one of the main reasons researchers suggest that phonological skills are the primary component underlying reading skills. As mentioned previously, phonological skills serve as a predictor for a child’s reading ability. Thus children who do well on tasks of phonological awareness are at an advantage when learning to read. Children who are able to map phonological and orthographic representations are able to not only read words they are familiar with, but are also able to map sounds to letters, and are able to figure out and read words that they are unfamiliar with. A great deal of research has gone into understanding the influence of phonological skills on decoding, and less research has been conducted to better understand the connection between language skills and decoding. 20 Phonological skills played a key role in predicting reading comprehension, and could be seen as the building blocks for many other aspects of reading skills embedded within comprehension abilities (i.e., decoding, word identification, vocabulary, and fluency), but later research found support for language contributions. Studies suggested that other broader, non-phonological language abilities were found to be more influential to successful reading comprehension in comparison to phonological skills (Catts, et al.,

1999; Deacon & Kirby, 2004; Nation & Snowling, 1998, 2004; Nation, Snowling, and

Clarke, 2007; Oulette & Beers, 2010). Nation et al., (2007) found that despite fluent and accurate reading, age-appropriate phonological skills, and normal nonverbal abilities, children who poorly comprehend what they have read showed a variety of oral language weaknesses in a non-phonological domain. These findings suggested that the field begin to consider other elements for predicting an individual’s reading comprehension abilities.

A Shift in Views: Broad Language Contributions Beyond Phonological Skills.

Phonological models of reading development have indicated a great deal of significance and contribution related to reading. Therefore, they can serve as a theoretical foundation moving forward, instead of being disregarded, but yet cannot be the sole predictor of one’s reading ability. A great deal of research has actually found evidence that phonological models of reading are not able to predict a number of reading difficulties after all (Catts, et al., 1999; Deacon & Kirby, 2004; Nation & Snowling,

1998, 2004; Nation, et al., 2007; Oulette & Beers, 2010). On the contrary, researchers found that reading skills were in fact predicted by both phonological skills and oral language skills in preschool and early elementary (Catts et al., 1999; Scarborough, 1998;

21 Schatschneider, Fletcher, Francis, Carlson, & Foorman, 2004; Storch & Whitehurst,

2002).

Phonological models of development were the sole indicator for a long period of time, simply due to the fact that the underlying impact of language was not given a great deal of attention. However, more and more research found evidence that both phonological skills and broad language skills were important for the development of literacy. The language skills of preschoolers were found to be significant predictors for future reading abilities (Catts et al., 1999; Scarborough, 1989, 1990; Torgesen, Wagner,

Rashotte, Burgess, & Hecht, 1997). Further, it was found that language continued to play a significant role in reading comprehension ability as children aged, deeming this collective evidence significant because it illustrated that phonological skills were not the sole contributor to reading difficulties. Thus, further investigation of other skills and processes as contributors to reading difficulties merited a more in-depth review. From there, a great deal of evidence began to accumulate with updated theories suggesting that reading difficulties extended beyond phonological skills.

Researchers began to investigate children with specific comprehension problems

(Cain, Oakhill, Barnes, & Bryant, 2001; Nation, Clarke, Marshall, & Durand, 2004).

Cain, Oakhill, and Bryant (2000a) identified a subset of children, nearly 10%, who had comprehension difficulties despite having age-appropriate reading abilities. They identified these children as having impaired language comprehension abilities. If you recall, in the original simple view model, the authors proposed that reading ability could only result from a combination of decoding and language comprehension ability. Thus, a child would only have good reading comprehension skills if they had good word 22 recognition ability and good language comprehension ability. Therefore, a reading disability could result from poor word recognition skills, poor language comprehension, or both. Empirical evidence soon followed that supported this idea as well. In fact, a number of studies have shown that language comprehension and decoding abilities make separate contributions to reading comprehension abilities.

While this literature is sound, it is important to revisit the overall goal of comprehension, which is to understand what one is reading. Although a child may be good at decoding, it does not guarantee that they will be able to successfully comprehend what they have read. A classic example of this was illustrated by Gough, Hoover, and

Peterson (1996) when they discussed an older gentleman, John Milton, who, due to failing eyesight, was unable to reread the Greek and Latin Classics. He had taught his daughters how to decode the text in order to read it aloud to him, but they were not able to understand what they were reading. Hence, despite their accurate decoding skills, they could not comprehend what they were reading due to a lack of language comprehension.

If the simple view model holds true then, those with poor comprehension possess underlying difficulties in the area of language comprehension, considering by definition they generally have normal or near-normal word recognition abilities. Along with this, an emerging body of research would agree that individuals with poor comprehension exhibit difficulty with tasks measuring a wide range of language abilities, in comparison to typically developing readers. As mentioned previously, a number of language components (e.g., morphology, semantics, and syntactic knowledge) have been shown to influence reading comprehension. This point again illustrates the importance of studying more specific individual language skills that comprise language comprehension abilities. 23 A number of researchers have examined the language abilities in those with poor comprehension, and found that they do indeed have deficits in language, but typical age- appropriate abilities in phonological processing (e.g., Catts, Adlof, & Weismer, 2006;

Nation, Clarke, Marshall, & Durand, 2004; Nation, Cocksey, Taylor, & Bishop, 2010).

These results line up with the simple view of reading, such that children with good comprehension skills but poor decoding skills, would be expected to also have good language comprehension skills. In addition, children with poor comprehension abilities but good decoding skills would be expected to have poor language comprehension skills.

Studies have consistently shown that there is indeed a relationship between reading and language, and more importantly that oral language skills predict reading comprehension, both concurrently and longitudinally (Nation, Cocksey, Taylor & Bishop, 2010; Nation &

Snowling, 2004; Storch & Whitehurst, 2002).

Moreover, reading comprehension is said to be a broad construct of a number of reading and language indicators including phonological skills, decoding, vocabulary, fluency, and language comprehension skills. Children that have a breakdown in any or multiple areas are at-risk for reading difficulties. Further, phonological skills are the premise for many higher level-reading skills, and thus, it is relatively easy to understand why many would argue that impaired phonological skills are to blame for reading difficulties (especially comprehension difficulties). More specifically, children who struggle with early reading and language skills generally see a trickle-down effect, and typically, these difficulties impact the very basic beginning of phonological skills that later influence a number of critical reading and language skills.

24 Additionally, accuracy and fluency, which are two core components of comprehension, are said to be problematic for those with low phonemic awareness

(Perfetti, 1985; Snowling, 1987; Stanovich, 1988). Typically, individuals begin with a weakness in phonological skills, which then leads to weak attainment of phonological awareness overall. Thus, it becomes difficult for the child to grasp the alphabetic principle that is necessary for understanding grapheme-phoneme correspondences, which is required for decoding printed words. When an individual is unable to accurately decode or recognize words quickly and efficiently, it tends to negatively impact their reading fluency skills. Slower readers then typically use the majority of their cognitive resources for understanding the syntactic, semantic, and logical relationships among words (LaBerge & Samuels, 1974; Perfetti, 1985). The lack of fluency makes it difficult for them to grasp the words, concepts, and facts that are necessary for comprehending text. Moreover, a lack of reading comprehension or difficulty ascertaining information from what one reads, can lead to deficits in vocabulary, IQ and general knowledge (Catts

& Kamhi, 2005; Committee on the Prevention of Reading Difficulties of Young

Children, 1998; McCardle and Chhabra, 2004; Stanovich & Siegel, 1994).

To contextualize what the emergent research has revealed, Scarborough (2005) describes a number of fallacies she feels research studies across multiple disciplines have exposed about the phonological model. First, phonological skills are not the only predictors for future reading skills. In fact, research has indicated that after controlling for kindergarten differences in phonological awareness and other phonological skills, lexical and grammatical differences still accounted for significant variance in reading outcomes

25 (Catts et al., 1999; Scarbourgh, 1990; Share & Leikin, 2004; Storch & Whiteurst, 2002;

Torgeson et al., 1997; Wood & Hill, 2002).

Second, different language skills predict future reading skills at various ages among preschoolers. To illustrate, studies have been conducted that compared preschoolers who later developed reading disabilities, to those of typical readers, matched on socioeconomic status and intellectual abilities. They found that these groups were differentiated by syntactic and speech production abilities, but not vocabulary at ages 2.5 to 3 years old, syntactic and vocabulary skills, but not speech at 3.5 to 4 years old, and vocabulary and phonological awareness, but not syntax at age 5 (Scarborough, 1989,

1990, 1991a, 1991b; Scarborough, Dolorich, & Hager, 1991). Further, this suggests that the models used for prediction are dependent upon the age from which the prediction is measured or trying to be made. Thus, it would make sense that we consider the developmental patterns of reading and language skills both individually and collectively, in order to gain a more accurate representation of consistencies and inconsistencies derived from previous models.

Third, phonological awareness in kindergartners is not better predicted by phonological versus non-phonological assessments at younger ages. The phonological model suggests that kindergartners phonological deficits can be predicted by weaknesses indicated in phonological development overall, as opposed to other early language skills.

However, several studies indicate that phonological awareness and speech are not better predictors of future awareness abilities, in comparison to the non-phonological language measures assessed (Bryant, Bradley, Maclean, & Crossland, 1989; Bryant, Maclean,

26 Bradley, & Crossland, 1990; Carroll, Snowling, Hulme, & Stevenson, 2003; Lonigan,

Dyer & Anthony, 2000; Scarborough, 1989, 1990).

Fourth, preschoolers with non-phonological language impairments are at the same risk of developing reading disorders, as those who exhibit impairments with phonological skills. For example, preschoolers who are found to have impairments with any or all aspects of oral language have been found to develop reading disabilities at some point.

The continuity and causal links for preschool language development and later reading achievement have been questioned under the phonological model, simply because studies have shown that even if recovery is made from early language difficulties, the risk for reading difficulties still remains elevated; especially in older children (Fey et al., 1995;

Rescorala, 2002; Scarborough & Dobrich, 1990; Stothard, Sowling, Bishop, Chipchase,

& Kaplan, 1998).

Finally, according to the phonological model, late emergence of reading difficulty is unexpected and challenging to account for. However, a study done by Leach,

Scarborough, and Rescorla (2003) found a group of children indicating grade-appropriate achievement in spelling, decoding, and text comprehension, but just two years later, were found to have late emerging difficulties with word recognition. The evidence provided suggests that there are a number of inconsistencies with predictions drawn from the phonological model collectively. Thus, these research contributions suggest that there are a number of skills that underwrite reading difficulties, above and beyond an individual’s phonological abilities.

A More Encompassing Perspective Model: The Simple View Model of Reading

27 While phonological models of reading were being questioned the “Simple View of Reading” was simultaneously being adopted as a conceptual framework for explaining reading comprehension. The simple view of reading incorporated concerns from the field regarding the influence of language. This new model of reading comprehension (Gough

& Tunmer, 1986; Hoover and Gough, 1990) suggested that reading comprehension abilities were the result of reading and language skills.

Although there are a number of influences on one’s comprehension ability, currently the theoretical underpinnings of the simple view model lay the groundwork for comprehension abilities. The simple view model of reading (Gough & Tunmer, 1986;

Hoover & Gough, 1990) suggested that reading I equaled the product of decoding (D) and language comprehension (C) (R = D x C). More simply stated, proficient reading comprehension was the product of two factors: decoding and language comprehension.

Decoding refers to the ability to read printed words in isolation in a fluent manner, without the assistance of context; while language comprehension refers to the ability to understand spoken language. Tunmer and Chapman (2012) suggested that the process of extracting details and constructing meaning from the text would be impaired if an individual struggled to recognize age appropriate words (decoding) and/or had trouble understanding the language being read (language comprehension). Their view held that neither component alone was sufficient, but instead both components were required for skilled reading. Thus, one could not have strong decoding skills and poor language comprehension skills, or vice versa, and still become a skilled reader.

Though there are a number of other reading skills and processes that influence comprehension, research studies have confirmed that these two components account for a 28 large proportion (45-85%) of the variance in reading comprehension and make significant unique contributions to reading comprehension overall (Aaron, Joshi, & Williams, 1999;

Catts, Hogan & Adolf, 2005; Cutting & Scarborough, 2006; Dreyer & Katz, 1992;

Hoover & Gough, 1990; Kendeou, van den Broek, Whtie, & Lynch, 2009). More importantly, the contribution of these two components is developmental, such that decoding accounts for a large proportion of the variance in younger ages, but around the fourth or fifth grade language comprehension begins to account for nearly all of the variance while decoding accounts for very little. This is due to the idea that in the early years, children are consumed with phonemic and word recognition skills when learning to read. However, as children grow they begin to move into more difficult text; thus, their reading skills began to shift from decoding and word recognition to those requiring vocabulary knowledge and deeper comprehension skills. As a result, students must rely more heavily on higher level language skills (Catts et al., 2005; Francis, Fletcher, Catts &

Tomblin, 2005; Gough, Hoover, & Peterson, 1996).

Concerns regarding the simple view of reading model. The simple view model was gaining in popularity, but research developments and discoveries questioned the adequacy of the model. The simple view model received criticism for several reasons: (1)

There was too much ambiguity for how decoding was conceptualized. The conceptualization of this construct influenced how it was measured (word versus non- word reading), which was thought to have an influence on the amount of variance accounted for by the combination of decoding and language comprehension within the model (Braze, Tabor, Shankweiler, & Mencl, 2007; Kirby & Savage, 2008). (2) The model was questioned for its simplicity, such that decoding and language comprehension 29 alone could not explain all of the variance in reading comprehension. There was concern that relevant reading factors (i.e., phonological awareness, vocabulary, and fluency) were not included in the model, but were found to be highly correlated and predictive of reading comprehension abilities (Adlof, et al., 2006; Johnston & Kirby, 2006; Joshi &

Aaron, 2000). (3) The language comprehension construct was often criticized for its breadth and required a more accurate definition. The sources of variance within this larger composite also needed to be more accurately identified as studies were finding evidence for specific language weaknesses in children with reading comprehension difficulties (Carlisle, 1995, 2000; Deacon, Kieffer, & Laroche, 2014; Nagy, Berninger,

Abbott, Vaughan, & Vermeulen, 2003; Nagy et al., 2006; Nation & Snowling, 1998b;

Nation et al., 2007). (4) Finally, that the simple view model has been criticized for claiming that reading comprehension is the product of decoding and linguistic comprehension at any developmental point, but has provided very little evidence for how these relationships change with age and practice (Chen & Vellutino, 1997; Joshi &

Aaron, 2000; Savage, 2006).

Conceptualization of decoding. The role of decoding for one’s reading comprehension is still a controversial issue. One aim of the original model was to investigate whether there was a connection between decoding skill and reading ability.

However, the definition of decoding was not clearly defined, as there are a number of ways in which it is measured within reading research as a whole.

Many believe that the ability to decode is the core of reading ability, while others consider it a byproduct, with no real causal influence in the process (Gough and Tunmer,

1986). In the original model as well as other studies supporting the simple view decoding 30 has typically been measured with word recognition in terms of accuracy (Aaron, Joshi, &

Williams, 1999; Catts, Adlof, Hogan, & Weismer, 2005; Dreyer & Katz, 1992; Lovett,

1987). However, others have measured decoding by nonword decoding (Hoover &

Gough, 1990; Joshi & Aaron, 2000).

The ambiguity of what comprised decoding, and how it was measured, may have contributed to confusion in the interpretation and evaluation of the model (Kirby &

Savage, 2008). In addition to defining decoding within the model used, it is as equally important to consider the measures that are being used, and how they map onto the construct under study. When choosing assessments of word recognition, it is important to consider the differences among regular, irregular, and sight words as each could provide very different outcomes. Regular words (i.e., cat, outside, yellow, interesting, may, etc.) have common phoneme-grapheme relationships, and can be sounded out when decoded.

These words are generally decodable because they conform to phonetic rules. Irregular words (i.e., was, come, give, of, etc.) on the other hand, often have uncommon phoneme- grapheme relationships and cannot be sounded out. Thus, these are usually not decodable because they do not conform to the usual phonetic rules. Sight words (the, and, this, when, etc.) are words that just can be recognized automatically. It has been suggested that more complete assessments of word recognition improve the extent to which the simple view model may account for variance in reading comprehension ability (Braze et al.,

2007; Johnston & Kirby, 2006).

The potential role of vocabulary and fluency. Vocabulary and fluency were found to be highly correlated and predictive of reading comprehension abilities, yet were not included in the original simple view model. 31 Vocabulary. There has been a great deal of evidence suggesting a strong relationship between vocabulary and reading comprehension (Carroll, 1993; Thorndike,

1973). Vocabulary refers to the knowledge of lexical meanings (orthographic and phonological) of words and the semantic representations connected to these meanings

(Aarnoutse, Van Leeuwe, Voeten, & Oud, 2001; Perfetti, & Hart, 2001; Verhoeven & van Leeuwe, 2008). Verhoeven and Perfetti (2011) explain that words are the carriers of meaning and therefore closely tied to the skills necessary for knowledge construction and adequate comprehension. A review of the literature by Tannenbaum, Torgesen, and

Wagner (2006) revealed that the correlational relationship between vocabulary and reading comprehension varied between .3 and .8. More importantly, it has been found that as children age and become more fluent with basic reading skills, they shift their focus to more advanced reading skills, thus strengthening the magnitude of this relationship (Torgesen, Wagner, Rashotte, Burgess, & Hecht, 1997).

The strong correlation between vocabulary knowledge and comprehension suggests that vocabulary is largely influential in explaining children’s reading comprehension skills. Anderson and Freebody (1981) proposed three hypotheses that could account for the correlations between vocabulary and comprehension. The first is called the instrumentalist hypothesis, and it posits a causal relationship between vocabulary knowledge and comprehension, such that the more knowledge that an individual has for the word meanings within the text, the better their ability to comprehend the text. Hypothesis two is the knowledge hypothesis, and it posits that vocabulary is a reflection of knowledge base, and that world knowledge (rather than word knowledge) accounts for the relationship between vocabulary and comprehension. 32 Finally, hypothesis three is the aptitude hypothesis, and it posits that large vocabularies are the result of having high intelligence or verbal aptitude. Although a strong relationship between vocabulary and reading ability dates back to the early days of research on reading, the relationship between these skills are still somewhat unknown, along with the mechanisms in which vocabulary learning takes place, and the instruction that facilitates such learning (Cain, Oakhill, & Lemmon, 2004). The views vary when it comes to describing the relationship between vocabulary and reading comprehension.

However, they do not stray too far from the original hypothesis of Anderson and

Freebody (1981). Instead, research has offered support to these views so they could be refined and expanded.

Furthermore, a great deal of research has investigated the influence that vocabulary has on an individual’s overall reading ability, and has determined that vocabulary serves as a strong predictor of one’s overall reading ability (Biemiller &

Slonim, 2001; Cunningham & Stanovich, 1998; Wagner et al., 1997). There is a significant amount of evidence to support the instrumentalist hypothesis, which suggests that the better one’s knowledge is for the meanings of words in the text, the better their ability to comprehend the text. Studies have suggested that the size of one’s vocabulary is related to reading comprehension ability (Biemiller, 2005, Ouellette, 2006). Gathercole

(1998) adds that larger vocabulary sizes in children may be attributed to having more efficient memories for word learning. Interestingly, children who know fewer words or have poor vocabularies actually learn fewer words from context, despite the fact that they have the greatest room for improvement (Shefelbine, 1990). One reason that children with smaller vocabularies may struggle is that they have to learn more words and also 33 their understanding of the words, they already know is not as developed as children with richer vocabularies.

Nation (2009) suggests that the causal relationship between vocabulary and reading comprehension could be the result of individual differences, such that individual differences in reading ability are responsible for the individual differences in vocabulary knowledge. According to this view children gain meaning of new words through reading and other related strategies. Children who are better readers overall, typically tend to have more exposure to print, allowing them to develop larger vocabularies, unlike poor readers who have far less exposure to print exposure, often hindering their ability to develop rich vocabulary knowledge (Cunningham & Stanovich, 1991, 1997; Cain &

Oakhill, 2007; Nagy & Anderson, 1984; Nagy & Scott, 2000). Very similarly then, the same approach of individual difference is used to explain reading comprehension skills, suggesting the causal relationship could be bidirectional. Thus, individual differences in vocabulary knowledge are responsible for individual difference in reading comprehension. Therefore, children’s reading comprehension abilities will be compromised if they have limited vocabulary knowledge or difficulty accessing the meaning of words in an efficient manner (Beck, Perfetti, & McKeown, 1982; Daneman &

Green, 1986). Moreover, vocabulary enables comprehension, but reading comprehension also enables one to have the ability to infer additional meaning from the text. Both of these views have received empirical support in the literature, as vocabulary has been shown to predict growth in reading comprehension, just as reading comprehension has been shown to predict growth in vocabulary knowledge (de Jong & van der Leij, 2002;

Muter, Hulme, Snowling, & Stevenson, 2004; Seigneuric & Ehrlich, 2005). 34 There is consistent evidence that a lack of understanding for word knowledge does have the potential to impede the ability to derive meaning from connected text.

Therefore, it is clear that there is some sort of connection for many children between vocabulary, and the ability to construct meaning from text. Across a developmental age span, it has been evidenced that children with better vocabulary knowledge tend to have more advanced reading skills in relation to their peers who have less-developed vocabulary knowledge. Consequently, better readers will then develop larger and better vocabularies over time and poor readers will not (Cunningham & Stanovich, 1997; Nagy

& Scott, 2000). However, there is also research suggesting that the relationship between vocabulary and reading comprehension may not be directly causal; such that, a child with limited vocabulary knowledge does not necessarily imply comprehension difficulties

(Freebody & Anderson, 1983).

Many researchers are interested in discovering the contributions that lead to individual differences in children’s vocabulary abilities. Some suggest that vocabulary performance is the result of exposure and amount of reading, more than it is from oral language skills. This is largely due to the idea that children who read more, are able to build better vocabularies because they are able to derive deeper meaning from the context of what they are reading. However, there is also evidence to suggest that children with better language skills generally demonstrate superior performance on vocabulary learning tasks (Cain, Oakhill, & Lemmon, 2004). Vocabulary is also one of the best predictors of overall verbal intelligence, with correlations near .80 (Anderson & Freebody, 1981;

Sternberg & Powell, 1983).

35 As mentioned previously a plethora of research has been done to assess the simple view model of reading (Gough & Tunmer, 1986; Hoover & Gough, 1990). Given that the model supports only two components in overall reading ability, language comprehension and decoding, many were left wondering why vocabulary was not included given its influence on comprehension abilities. Just as researchers questioned the inclusion of a fluency component in the simple view model, a number of people questioned the role that vocabulary may be able to attribute to the model. So researchers began investigating vocabulary as a component of simple view, in order to see if it would account for additional variance in comprehension skills. Some researchers maintained that vocabulary and language comprehension together were a measure of oral language ability while others contended it was a component that should stand alone, and could account for its own unique variance in comprehension abilities. The outcomes were mixed, with some studies showing that vocabulary predicted unique variance (Braze, Tabor,

Shankweiler, & Mencl, 2007; Ouellette & Beers, 2010), while others suggested that vocabulary did not stand on its own (Harlaar, et al., 2010). Harlaar and colleagues (2010) actually found a correlation of .93 among language comprehension and vocabulary suggesting redundancy within each domain. More importantly, oral vocabulary was found not to predict reading comprehension beyond measures of phonological awareness, decoding, irregular word reading ability, and language comprehension in first graders, but does after accounting for these variables in the sixth grade (Ouellette and Beers, 2009).

Thus, unique effects of vocabulary were often observed in samples that consisted of older children, suggesting that age may be a consideration when determining the unique effects that vocabulary may offer on comprehension. One study in particular proposed another 36 important implication for the simple view model. They investigated to see if vocabulary shared its association with reading comprehension via word-level reading, comprehension-level processes, or both. They assessed 8 and 9 year-old children and found that vocabulary was actually important for both aspects of reading (Ricketts,

Nation, & Bishop, 2007). A number of studies supporting the simple view use word recognition as a measure of the decoding. Therefore, this study suggests that vocabulary may relate to the decoding factor as well. Again, these skills are developmental in nature so age may be a contributing factor in these findings.

Vocabulary by many is considered an essential component to reading comprehension, but often is missing from reading instruction. Children with disabilities often have limited vocabularies, simply due to deficits with vocabulary learning or perhaps poor memory or recall. It is difficult to understand the text when little knowledge about the words or text exists. Thus, a number of interventions and instructional programs have sought to integrate and specifically focus on building and improving vocabulary knowledge. Key vocabulary and concepts are taught across all educational content areas so that students can learn and understand text. Therefore, vocabulary instruction is a necessary part of comprehension instruction because understanding text is significantly correlated with vocabulary development.

Promoting acquisition of vocabulary serves a variety of purposes that facilitate good comprehension. Some students fail to recognize that they do not understand certain words or concepts as they are reading. Teaching students to monitor their understanding of difficult words allows them to gain a deeper knowledge of important words. Students can then figure out enough information about words to use fix-up strategies as a means 37 for repairing comprehension. Teaching words around a concept or theme assists students in making connections between new words, existing knowledge, and concepts being taught. These strategies are more effective for learning and remembering words and text and allow students the opportunity to conceptualize text in multiple ways. Finally, increasing students’ knowledge of and interest in words leads to improvements across multiple genres. The outcome for improvements in vocabulary will ultimately lead to better comprehension.

The role of vocabulary in reading comprehension proved to be significantly important as well. Since the early days of reading research, a relationship between vocabulary and comprehension has been acknowledged (Cain, Oakhill, & Lemmon,

2004; Ouellette, 2006), and vocabulary knowledge has become known as one of the best predictors of reading comprehension (Beck & McKeown, 1991; Cain & Oakhill, 2011;

Torgesen, Wagner, Rashotte, Burgess, & Hecht, 1997). In fact, a review of the literature by Tannenbaum, Torgesen, and Wagner (2006) revealed that the relationship between vocabulary and reading comprehension varied between .3 and .8. The strong correlation between vocabulary knowledge and comprehension suggests that vocabulary is largely influential in explaining children’s reading comprehension skills. Vocabulary has been argued to influence comprehension, both independently, and via other processes and/or components.

Vocabulary has been found to be a unique contributor to reading comprehension, independent of phonological decoding and oral language. Many have argued that vocabulary is a unique component that accounted for additional variance independent of decoding and language comprehension. Verhoeven and van Leeuwe (2008) included 38 vocabulary, in addition to decoding and language comprehension, in a cross-lagged model and found that both vocabulary and language comprehension influenced later reading comprehension. Additionally, others have found that vocabulary predicted reading comprehension, independent of language comprehension, word recognition, irregular word decoding, and phonological awareness for older students, but not for younger students (Ouellette & Beers, 2009).

Within the simple view model the disagreement is not whether vocabulary stands alone as its own construct, but rather whether it is a component of decoding or that of language comprehension. Wilson and Anderson (1986) argue that having an enriched vocabulary facilitates word recognition skills, which can also influence the retrieval of background information (a necessary skill for reading comprehension (Graesser, Singer,

& Trabasso, 1994). Others have argued that it is an element of language (Braze, Tabor,

Shankweiler, & Mencl, 2007; Kendeou, Van den Broek, White, & Lynch, 2009; Kirby &

Savage, 2008; Ouellette, 2006; Ouellette & Beers, 2010; Ricketts, Nation, & Bishop,

2007; Tumner & Chapman, 2012). More recent research has indicated that cooperatively, decoding measured by phonological decoding and word recognition and oral language abilities, measured by language comprehension and vocabulary, accounted for all of the variance in reading comprehension (Harlaar et al., 2010). In fact, these researchers found substantial correlations among their factors: .96 between phonological decoding and word recognition, and .93 between language comprehension and vocabulary, thus suggesting redundancy within each domain. In summary, although a great deal of research has investigated the contribution of vocabulary in the simple view model, none have been able to account for unique variance at large. 39 Fluency. Over time, a great deal of research indicated moderate to high correlations between reading fluency and reading comprehension (Fuchs, Fuchs, &

Maxwell, 1988; Fuchs, Fuchs, Hosp, & Jenkins, 2001; Joshi & Aaron, 2000; Klauda &

Guthrie, 2008; Pinnell et al., 1995; NAEP et al., 2010). Fluency is also commonly used as a predictor of comprehension in young readers (Miller & Schwanenflugel, 2006). Thus, the importance of word reading fluency has become increasingly important (Fuchs et al.,

2001; Wolf, 2001). Reading comprehension demands a considerable amount of cognitive resources, and evidence suggests that when you are able to become a faster and more automatic reader, you are able to free up resources that can be used for other processes

(LaBerge & Samuels, 1974; Perfetti, 1985). Conversely, though, a lack of fluency can also impede reading comprehension. Accuracy does not always equal good fluency. Thus researchers began to question the role of fluency, and felt it was important to capture word reading fluency, as well as accuracy, to see if they could account for additional variance in reading comprehension abilities above and beyond those already accounted for in the simple view model (Fuchs, Fuchs, Hosp, & Jenkins, 2001; Wolf 2001).

Attention is given to the Simple View Model because it stressed the importance of only decoding and linguistic comprehension for reading comprehension abilities, however, several studies have found correlations between fluency and reading comprehension skills (Fuchs, Fuchs, & Maxwell, 1988; Joshi & Aaron, 2000; Shinn,

Good, Knutson, Tilly, & Collins, 1992), but fluency was not an included component in the simple view model. Thus researchers began to investigate whether or not adding fluency would account for additional variance, above and beyond that which it may share with linguistic comprehension and word recognition. Overall, the reviews were mixed, 40 and while some studies suggested that it did account for unique additional variance, others found that it did not account for unique variance, at least not above and beyond what is shared with decoding and listening comprehension.

Joshi and Aaron (2000) used letter naming speed as an indicator of fluency to demonstrate that letter naming speed accounted for 10% unique variance in fourth grade reading comprehension, after controlling for nonword reading accuracy and listening comprehension. Furthermore, they indicated that letter-naming speed was a proxy for word reading. Additionally, Aaron, Joshi and Williams (1999) studies third, fourth and sixth grade students, and found that when combined word recognition and listening comprehension accounted for 65% of the variance in reading comprehension. The word recognition factor accounted for 50% of the variance, and comprehension accounted for

15% when all three grades were combined. Thus parallel with these theories that word recognition becomes less influential as children age and comprehension becomes more important, they too found that in the third grade only word recognition accounted for variance in reading comprehension. In the fourth graders, language comprehension and word recognition were important, and in the sixth graders, the same two factors of word recognition and language comprehension were present; however, the influence of nonword reading decreased, and speeded word reading skills increased, providing evidence that fluency may also be contributing.

Adlof, Catts, and Little (2005) conducted a similar study where they investigated whether or not adding fluency as a factor to the simple view model would predict unique variance for reading comprehension. They conducted a rigorous analyses using SEM looking at the influence of fluency from multiple angles and ages. Their results suggested 41 that fluency provided little unique contribution to reading comprehension. Additionally, they found fluency and word recognition to be highly in the second grade that it encouraged them to combine both variables into one factor. It remained highly correlated in the fourth and eighth grade, but the two constructs were separated into separate constructs. Yet still after controlling for word recognition and listening comprehension, fluency still did not account for any unique variance in reading comprehension in either concurrent or predictive models. The developmental results of their study then align with many other studies, such that word recognition accounts for all the variance in early grades, and tails off later as listening comprehension picks up, which begins to account for an increasing amount of variance as children age.

It appears as if there is still no real agreement for the skills that contribute to fluency, nor have we arrived at an orderly understanding for the role of fluency on comprehension. Like many other reading skills and processes, this is most likely dependent upon the research theory or question at hand, and the type of measures and analysis used to assess the outcomes of the information being studied. Essentially, this overall relates to the definition of fluency that is stated outright at the beginning of a study. Despite these efforts, the more important question is: what role does fluency have when considering reading comprehension? What we do know is although reading fluency was not given considerable attention in the past, it is now a skill that is recognized by many as an important contributor to reading outcomes and other skills directly related to reading. We also know that word reading fluency is necessary for successful oral reading fluency skills (Fuchs, Fuchs, Hosp, & Jenkins, 2001; Wolf, 2001).

In the early stages of reading the majority of cognitive resources are attributed to the 42 process of word recognition. However, as children age and their word recognition skills became faster and more automatic, many more cognitive resources become available to be used for reading comprehension (LaBerge & Samuels, 1974; Perfetti, 1985). Without good fluency skills reading becomes increasingly difficult, and cognitive resources must be split among activities, often resulting in poor comprehension outcomes.

The robustness of the language comprehension construct. Finally, one of the biggest critiques was that language comprehension was essentially taken to represent “all of verbal ability” (Kirby & Savage, 2008). The robustness of the language comprehension facet still required attention, considering many wanted to know what specific aspects of language comprehension were causative to the source of variances found to influence reading comprehension. Many were demonstrating that language comprehension, as measured by language comprehension ability, could be comprised of several components: working memory (Gathercole & Baddeley, 1990), vocabulary

(Beck, McKewon, & Kucan, 2002; Tunmer & Chapman, 2012), morphology (Nunes &

Bryant, 2006), semantics (Nation et al., 2007; Nation & Snowling, 1998), and syntactic knowledge (Catts & Kamhi, 2005). An overwhelming amount of research has demonstrated that being able to understand spoken language relies on a number of of the aforementioned factors. To date, studies have yet to further explore the construct of language comprehension within the simple view model, thus this remains a topic open for review.

Broad language skills contribution. Children with poor comprehension abilities actually do very poorly on tasks measuring their semantic skills. In fact, Nation and

Snowling (1998) found that these children actually are slower and less accurate at making 43 semantic judgments, and are able to produce fewer examples in semantic fluency tasks.

Despite having adequate phonological decoding skills, children with poor comprehension, have difficulty recognizing low-frequency and exception words, than predicted from their basic decoding skills (Nation & Snowling, 1998). Thus, word recognition was most compromised when reading words that require a significant level of semantic support. Underlying semantic skills may constrain both the comprehension and development of skilled word recognition. This suggests that children with comprehension difficulties have trouble processing aspects of language with regards to meaning. Some of this work aligns with the “three-cornered” model of Plaut and colleagues (Plaut,

McClelland, Seidenberg, & Patson, 1996), which provides a framework for considering the relationships between word recognition development, semantic skills, and phonological skills. Considering this relationship, these findings demonstrate that variations in semantic skills also contribute to the development of skilled word recognition.

Only recently has morphological awareness begun to receive more attention from those studying language and literacy. English texts stem from meaningful units of morphemes, like affixes and roots (Nagy & Anderson, 1984), which become more difficult as children age, and are required to read and comprehend more sophisticated texts for a variety of academic purposes (Nagy & Townsend, 2012). Morphemes contribute unique aspects of meaning to words, which require a great deal of language knowledge and interpretation. Morphological tasks require readers to integrate semantic, phonological, and syntactic information (Kuo & Anderson, 2006). Also, morphological awareness requires the manipulation of minimal units of meaning in language. As 44 children learn to read, they move from the use of grapheme-phoneme correspondences to larger sound-spelling units and morphemic units in decoding and encoding words

(Deacon, 2012). Studies have demonstrated a correlation between morphology and reading comprehension, but the underlying mechanisms of the relationship are still quite unclear, and remain up for further investigation (Carlisle, 1995; Deacon, Kieffer, &

Laroche, 2014; Deacon & Kirby, 2004; Deacon, Parrila & Kirby, 2008).

Further, there is evidence demonstrating that morphological knowledge predicts unique variance in vocabulary (Carlisle, 2007; Mahony, Singson, & Mann, 2000). In fact, several studies suggest that there is a relationship between morphological awareness and vocabulary size (Carlisle, 2000; McBride-Chang et al., 2005; Nagy, Berninger, & Abbott,

2006). The relationship between morphological knowledge, vocabulary, and reading comprehension is relatively unclear. However, studies have found, that after controlling for vocabulary, morphological awareness still uniquely predicts reading comprehension

(Carlisle, 1995, 2000; Nagy, Berninger, Abbott, Vaughan, & Vermeulen, 2003; Nagy et al., 2006). Morphological awareness may impact reading comprehension both indirectly through word reading skills, and directly through language systems that morphological awareness impacts the development of reading comprehension (Deacon, Kieffer, &

Laroche, 2014). A study conducted by Kieffer and Box (2013) found that morphological awareness made indirect contributions to comprehension, via vocabulary and fluency, but also made direct, unique contributions to reading comprehension, after controlling for these indirect contributions. Deacon and Kirby (2004) investigated the longitudinal relationship between morphology skills and reading ability and found that morphological awareness was a significant predictor of word accuracy and speed, pseudoword reading 45 accuracy, text reading speed, and comprehension after controlling for phonological skills.

They also found that morphological awareness explained variance in reading comprehension after controlling for word reading. Likewise, a study by Foorman (2012), found that morphological awareness predicted reading comprehension, specifically after controlling for vocabulary, word reading efficiency, and phonological awareness. Thus, the variation in research and findings suggest that morphological knowledge has both direct and indirect or mediating effects on language and reading components.

Semantic language skills refer to how well one understands the meanings of words, phrases and sentences, and using words appropriately when we speak. Semantic skills require individuals to be able to listen to or read a word, and then comprehend the meanings within a particular arrangement. Children that have semantic difficulties can have a very tough time understanding the meaning of words and sentences. Written and spoken language comprehension is dependent upon one’s knowledge of individual word meanings and their ability to deduce meaning from the word arrangement (McGregor,

2004). Nation and Snowling (1998b) found that semantic fluency differed in those with good reading comprehension and those with poor comprehension. More recent work by

Nation, Snowling, and Clarke (2007) demonstrated that poor comprehenders knowledge of new words was relatively week and they presented difficulty consolidating the meanings of newly acquired items. Furthermore, they recalled these items significantly less than good comprehenders too. These results suggest that children’s poor comprehension difficulties may have more to do with semantic than phonological learning when it comes to vocabulary development.

46 Children may fail to understand what they read for a variety of reasons, but the most common reason for comprehension failure is from word level difficulties. Perfetti

(1985) suggests that many younger children, especially poor readers, struggle with comprehension because their word level reading is slow or inefficient. Understanding the role of syntax is a much less researched area within reading comprehension. Research has shown that those with poor comprehension display weaknesses with syntactic comprehension, while others do not (Cain & Oakhill, 2006; Nation et al., 2004). One study found that syntactic knowledge did not predict concurrent reading comprehension skills in 7 and 8 year olds, after controlling for IQ, vocabulary, and word reading abilities. However, what they did find was that it explained significant variance in these children’s comprehension abilities 1 year later (Oakhill, Cain, & Bryant, 2003). Further, others have suggested that failure with syntactic development could be the result of limited reading experience. Nation, Snowling, and Clark (2005) demonstrated that those with poor comprehension are less able to derive the past tense of irregular verbs. They suggest that this may be due to the fact that these are components of language that are learned and practiced through reading.

The relationship between language comprehension skills and reading comprehension has come a long way over the years. As we continue to refine the construct of what constitutes language comprehension, we will be able to better understand the role of the individual and broad components of language on reading comprehension skills. The simple view model of reading has proven to be a strong theoretical foundation that we can continue to build from. Researchers have spent an exhaustive amount of time trying to deduce and conceptualize the processes and skills 47 that surmise “reading comprehension,” so we not only have a uniform definition now, but we are also able to understand the integration of skills and processes more thoroughly. As the evidence for understanding the relationship between language and reading continues to grow, we should also focus more effort and attention to the construct of “language comprehension” and work to deduce its complexity just as we have reading comprehension.

Considering the above, it is clear that understanding the relationship between reading and language is a complex issue. As the research on language and reading continues to expand, it has become more clear that the majority of children identified as having reading difficulties, also have been identified as having underlying language difficulties. More entirely, studies have also shown that language abilities in younger children have been able to predict reading comprehension abilities in older children. Thus although our understanding of the relationship between reading and language has evolved drastically, the most recent research indicates the need to investigate the influence and impact of reading and language over time, using large-scale, longitudinal research

(Oulette & Beers, 2010).

Currently we know that reading comprehension has a strong relationship with other components of reading (i.e., phonological skills, decoding, word recognition, vocabulary, fluency and language comprehension). Although it appears as if comprehension is correlated with multiple aspects of reading, a great amount of research supported the Gough and Tunmer (1986) Simple View Model of Reading.

The American Speech-Language-Hearing Association (2012) reported that 83% of the SLPs who work in schools are servicing children with language disorders. A 48 language disorder is impaired comprehension and/or use of spoken, written, and/or other symbol systems, and can manifest itself solely as an expressive disorder, a receptive disorder, or a mixture receptive/expressive disorder. Moreover, it may involve the form of language (i.e., phonology, morphology, and syntax), the content of language

(semantics), and/or the function of language (pragmatics) in any combination (ASHA,

1993). In schools, children who have fluent oral language skills are the more successful learners (Fey, Catts, & Larrivee, 1995).

Developmental aspects within the simple view framework. It is interesting to note that the multitude of research using the simple view model of reading revealed that age was an important contribution to the model. In fact, several studies have indicated that the contribution and variance accounted for by decoding and language comprehension on reading comprehension are mostly likely, age dependent. For example, Catts and Kamhi

(2012) suggest that in accordance with the simple view of reading, measures of word recognition accounted for more unique variance in reading comprehension in early elementary. However, language comprehension explained more unique variance in the later school grades overall. Thus perhaps another notable finding was the number of children with word reading problems decreased with age, while the number of children with language comprehension difficulties increased with age.

The relationship between language skills and reading comprehension skills can also be considered developmental in nature. As children get older, the overall goal of reading is essentially to be able to extract meaning from what is read. Thus, reading comprehension becomes the primary goal, and many of the beginning reading skills subsequently become secondary reading skills. However, phonological and word 49 identification skills are less influential in general, which is supported by a body of research suggesting decoding is important in the primary years, but as children grow older, their reading comprehension skills become more dependent on their language skills instead. Also, studies have found that children’s decoding skills become less correlated with reading comprehension abilities, while the strength between language comprehension and reading comprehension grows stronger with time.

Because reading and language are both developmental the language skills that contribute to literacy development can change over time, thus placing children at risk for failure at different stages (Whitehurst & Fischel, 2000). Catts and Kamhi (2005) compared the preschool development of children who developed later reading disabilities with those of children that became normal achieving readers. What they found was that different language skills predicted future reading at different preschool ages, such that syntactic and speech production abilities (not vocabulary) at ages 2.5 and 3 years old, syntactic and vocabulary skills (not speech) from 3.5-4 years old, and vocabulary and phonological awareness (not syntax) at age 5. Thus, this suggests that there is evidence that phonological skills are not the only contributor to later reading difficulties. In fact, evidence has suggested that preschoolers who have impairments in any or all aspects of oral language have been found to develop reading disabilities at some point. More importantly, it is not uncommon for some children, who have indicated impairment in the preschool age, to show improvement or disappearance of their deficits by kindergarten.

However, these children have been found to remain at risk for future reading difficulties at older ages (Fey et al., 1995; Rescorla, 2002; Scarborough & Dobrich, 1990; Stothard et al, 1998). 50 Furthermore, a number of research studies investigating the influence of vocabulary and fluency as additional components of the Simple View Model, found a plethora of evidence where decoding explained more variance in reading comprehension at younger age or grade level, while language comprehension explained more variance in reading comprehension at older ages or grade levels. This suggests that there is an age- dependent relationship between reading and language, thus meriting a deeper investigation of this relationship and how the relationship between these constructs change over time.

Thus far, results from studies investigating the simple view model of reading have suggested that the relationship between decoding and language comprehension decreases with age, while the relationship between language comprehension and reading comprehension increases with age. This shift has been said to occur around the 4th or 5th grade. Given the developmental relationship between reading and language, it would be of interest to examine children from longitudinal perspective how these relationships change with age and practice.

Cognitive Models of Reading Comprehension

The simple view model of reading has been discussed frequently because it is the basis of our most present day understanding. However, cognitive models of reading comprehension suggest the simple view model does not include additional elements thought to influence comprehension abilities.

Readers use a variety of processes when they maneuver through text. The various processes involved in reading comprehension are complex, and consist of multiple components. A variety of cognitive models have been developed to lend support to the 51 various skills and processes thought to impact comprehension (van den Broek, Young,

Tzeng, & Linderholm, 1999; Cromley and Azevedo, 2007; Graesser et al., 1994; Kintsch,

1998; Kintsch & Van Dijk, 1978; Kintsch & Rawson, 2005). They all stem from the same idea that comprehension is dependent upon some sort of construction. While these models may differ in their components, they all share the idea that inference and knowledge representation are two key components underlying each model. More importantly it is implied that language skills are largely influential in these abilities, but the influence that individual lower level language skills has on higher level language skills, has yet to be explored in great detail.

Kintsch and van Dijk (1978) model for text comprehension and production does not discuss a conventional schema for expository text. Their model indicates that readers are better able to comprehend through the formation of macrostructures. Macrostructure formations occur when a reader has awareness for the text structure from which macrorules are applied (thus resulting in the formation of the macrostructure). Also, research carried out by Taylor (1982) investigated the effects of the hierarchical summarization strategy instruction on text structure. Results from this study suggest that hierarchical summarization strategy enhanced student’s recall through a verbalized macrostructure. Furthermore, results suggest that text structure strategy instruction is an important component in the development of Kintsch and van Dijk’s (1978) original model of macrostructure formation.

The Landscape Model (van den Broek et al., 1999) describes how readers construct memory representations from what they read. Memory and attentional resources are the interactive processes for comprehension in this model. These two 52 processes together yield an integrated theoretical description of the processes that are involved. Interactions between forward and backward inferences take place in order to make sense of the text. More importantly, this model can be used to implement assumptions about how the reader proceeds through the text. Readers also differ in various aspects of processing, in addition to the retrieval of information from mental representation under the Landscape Model.

Kintsch and Rawson (2005) conclude that comprehension is not a composition of the sum of activity, but rather arises from a coordinated operation as a system. Thus it seems plausible that it is not practical to explain these processes as separate entities.

Instead, the processes occur in coordination with one another, and the meaning is further described, not with the meanings of words, but rather the constructions or schemas that are created as an attempt to explain the whole message.

The Kintsch situation model (1998), suggests that text comprehension involves processing at different levels (Coiro & Dobler, 2007; Joffe, Cain, & Maric, 2007;

McGrew & Wendling, 2010). In particular, this model suggests that the reader builds a semantic network of ideas as they attempt to determine the meaning of text. The reader employs language and visual skills to decode words and combine words and phrases that form meaning. References, links, and syntactic relationships are formed, revised, and revisited throughout the reading process, as a means for constructing and maintaining coherence. The situation model develops as the reader integrates background knowledge with the information provided by the text. Multiple levels of processing are involved, and strategies are both implicit and explicit during the construction of the situation model.

53 Kintsch and Rawson (2005) suggest that comprehension is more than the sum of these processes, but rather the holistic coordination and involvement of these processes for reading comprehension. The Kintsch (1998) situation model is most often referenced because it stresses the importance of understanding comprehension through the examination of processes of a coordinated operation, rather than examining component processes in isolation. Van Dijk and Kintsch (1983) explain that situation models are necessary in order to explain language processing. These models are needed in order to integrate information across sentences, explain similarities in comprehension performance across cognitive modalities, account for the effects of domain expertise on comprehension, explain translation, and to explain how people integrate information from multiple sources (Zwaan & Radvansky, 1998).

The cognitive models described have informed our understanding that comprehension requires a dynamic interaction of a variety of cognitive processes. Studies have also indicated there are multiple cognitive processes contributing to comprehension overall, but just as there is no single cognitive contribution, researchers too have found that there is no single unique model for explaining reading comprehension entirely.

Higher Level Comprehension Skills

Inference and integration. Often times in a reading piece, authors do not explain every detail you need to know in order to understand the text. Therefore, in order to be successful at reading comprehension, one must be able to construct meaningfully based representations by using inferences to extend the meaning of unknown text. In order to do this, a reader must be able to establish links between sentences in order to integrate meanings into a coherent order. Then, they must be able to generate inferences using 54 knowledge they already know, or knowledge they gained from the text to fill in the missing details. Thus, prior knowledge can largely influence one’s ability to comprehend meaningful text.

Inference and integration skills are another developmental skill that improves over time. These are skills important for reading comprehension because they are necessary for building coherence. When adequate causal relations are missing, readers slow down and try to reactivate what is missing by using the text, or retrieving information from background knowledge (van den Broek & Thurlow, 1990). Children as young as 6 are able to make inferences, but the accuracy of inference making is most apparent between the ages of 6 and 15, and then also between teenagers and adults (Barnes, Dennis, &

Haefele-Kalvaitis, 1996; Casteel, 1993). Studies conducted by Oakhill (1982, 1984) suggest that those with poor comprehension were less likely to be able to make inferences, even though the knowledge was well within their grasp. Cain and Oakhill

(2009) suggest this is not likely attributed to memory abilities because their recall of literal information is good, and even when given text to reference, their inference making abilities are still poor. Moreover, this suggests that one’s ability to understand text fully is influenced by one’s ability to make inferences from text that is not always specified.

Cain, Oakhill, Barnes, and Bryant (2001) have validated these assumptions by demonstrating that children with poor comprehension skills actually have deficits in making inferences as well as monitoring their comprehension.

Comprehension monitoring. Readers must be able to make inferences and integrate them to make text coherent, but this is only possible if they are able to monitor their understanding of the text. Comprehension monitoring usually assesses a readers 55 abilities to detect inconsistencies in the text, such as contradictory sentences, scrambled sentences, or statements that conflict with world knowledge (Cain, Oakhill, & Bryant,

2004). Children with comprehension difficulties are said to be poor at detecting internal consistencies in the text (Ehrlich, 1996; Ehrlich, Remond, & Tardieu, 1999). Rubman and

Waters (2000) have argued that effective comprehension monitoring requires the ability to integrate propositions in order to be able to construct a coherent representation of the text. Comprehension monitoring is said to make an important contribution to reading comprehension and develops around the same time that fluency skills are developed

(Baker, 1984; Markman & Gorin, 1981).

Pressley (1998) explains that skilled readers use conscious comprehension processes. Readers use prior knowledge for what is to be expected, while reading allows the reader to monitor their current predictions. They select information that is relative to their personal interests or goals. These individuals monitor their understanding by jumping to and from relative pieces of information and gain further clarification for the information that is confusing or difficult to understand. Additionally, they construct summaries to reinforce why information may or may not make sense. Individuals are able to evaluate the text difficulty, as well as monitor their current understanding of the text.

Overall, these readers are active prior to the reading activity, during the reading process, and after they have finished reading.

There is very little research investigating the causal relationship between comprehension monitoring and reading comprehension. Strategies to improve comprehension monitoring have been taught to children, but have lacked support for effectiveness. However, Cain and Oakhill (1999) assessed children’s ability to monitor 56 their comprehension using inconsistency in a detection task and found that it was not only related to current comprehension abilities, but that it also predicted future comprehension abilities above and beyond accounting for word reading ability, vocabulary, and verbal

IQ. Thus causal relationships for comprehension monitoring on reading comprehension have been demonstrated in children that have the ability to monitor their comprehension.

Knowledge about text structure. Understanding text structure is another area that is associated with comprehension performance. Knowledge about text structure and expectation is useful in helping the reader to retrieve background information and schema necessary for building coherent, meaning-based representations. Researchers have found that knowledge about text structure and expectations about what should be derived from the text are related to both age and reading comprehension (Myers & Paris, 1978; Paris &

Jacobs, 1984).

Narratives are the most common type of text structure and exist in a variety of children’s literacy experiences (i.e., books, children’s text, television programs, movies, etc). Paris and Paris (2003) suggest that narrative comprehension is a foundational skill for later reading comprehension abilities because it involves all of the processes we have previously discussed that are necessary for building coherent representational models

(i.e., identifying key points, making inferences, monitoring understanding, and understanding causal relations). Although, narrative comprehension is an important precursor to reading comprehension, it is often overlooked. Furthermore, it is not known whether narrative comprehension skills develop independently from other skills like phonological skills or vocabulary, or whether they are all interrelated (Lynch, van den

Broek, Kremer, Kendeou, White, & Lorch, 2008). 57 A variety of research has demonstrated that children with poor comprehension abilities have difficulty structuring stories, explaining expectations that are offered by the text, and information provided by different text types (Cain, 2003, 1996; Cain & Oakhill,

1996). Perfetti (1994) suggested that comprehension failure due to not understanding text structure may arise due to inadequate reading experience. Not only do children have difficulty structuring their own stories, but they have exhibited difficulty with overall knowledge of story structure.

A longitudinal study conducted by Cain and Oakhill (1999) found that early measures of story structure knowledge measured in children around 7-8 years of age were predictors of comprehension in children between the ages of 13 and 14. Although knowledge about the organization of narrative text has been said to increase throughout middle childhood (Stein & Glenn, 1982), results indicate that text structure knowledge is influential and predictive even in younger children. Furthermore, findings suggested that there is a causal relationship between knowledge about text structure and effective reading comprehension (Cain & Oakhill, 1999).

Other Critical Components of Reading Comprehension Development

Memory. One final aspect that has been said to influence reading comprehension is memory. Memory serves as an important role in nearly all processes of language and reading we have discussed. As mentioned previously, reading is both dynamic and interactive, requiring an integration of multiple skills, processes and resources. Correct interpretation and the integration of text, rely heavily upon memory storage and recall skills. Memory plays a significant role in this process as readers are called to access several sources of information (i.e., semantic word knowledge, background knowledge, 58 knowledge about text structure, memory based representations, relevant topic specific knowledge, etc.).

Memory also plays a significant role in sight-word and vocabulary acquisition.

Phonological short-term memory and verbal working memory capacity are two components of memory that are actively involved in word learning. Phonological short- term memory relates to the passive storage of verbal information, and verbal working memory capacity involves simultaneous storage and processing of verbal information.

Researchers have suggested that children with good phonological short-term memory are better able to accurately represent the sound structure of a new word, which may allow for better storage and accessibility for new words later on (Gathercole, Hitch, Service, &

Martin, 1997). Verbal working memory is also thought to play a role in vocabulary acquisition as Daneman (1987) and Daneman and Green (1986) found that vocabulary knowledge was related to working memory capacity. Cain, Oakhill, and Bryant (2004) further established that working memory explained unique variance in reading comprehension between the ages of 8 and 11 years, above and beyond contributions made by word reading and verbal ability.

Cain and Oakhill (2009) indicate that reading and language comprehension are strongly associated with memory, and require simultaneous processing and storage of information (working memory), while less strongly associated with simple measures of storage (short-term memory). In fact, working memory measures have been shown to be associated with measures of reading and language comprehension in both children and adults (Cain, Oakhill, & Bryant, 2004). Furthermore, those with poor comprehension have been found to consistently exhibit weaknesses in working memory, but deficits in 59 their short-term memory retrieval abilities were less common (Cain, 2006; Cain, Oakhill

& Lemmon, 2004; Nation, Adams, Bowyer-Crane, & Snowling, 1999). Working memory skills are important for higher-level comprehension skills like comprehension monitoring, inference and integration, and construction of coherent representations, even though they are not able to fully explain performance on these tasks (Cain, Oakhill, & Bryant, 2004;

Oakhill, Cain, & Bryant, 2003). It has been demonstrated that young children and those with poor comprehension fail to make inferences necessary for text comprehension, even when they possess the necessary knowledge (Cain, Oakhill, Barnes, & Bryant, 2001).

Having a general understanding for different types of knowledge is important for processes associated with the successful comprehension skills previously discussed. In fact, the ability to generate inferences relies on specific topic knowledge and background knowledge (Cain & Oakhill, 2009). Although, background knowledge is more of a long- term memory retrieval process, it is yet another area where inadequacies could lead to comprehension failures. Although very few studies have been able to demonstrate that general knowledge and memory are able to fully explain individual differences in reading comprehension abilities, it does not necessarily mean that memory and knowledge are not important contributors for other processes that account for comprehension ability.

Although the definition and etiology of reading comprehension remains a topic of intense debate (Leslie & Caldwell, 2000; Paris and Hamilton, 2009) reading comprehension can be broadly defined as the process of constructing meaning by coordinating a number of complex processes (Cain, Oakhill, & Bryant, 2004; Fuchs,

Fuchs, Hosp, & Jenkins, 2001; Paris, Wasik, & Turner,1991; Paris, 2005; Perfetti &

Hogaboam, 1975). Finally, a decent amount of research has revealed that those with poor 60 comprehension either lack the ability to perform many of these tasks we have discussed related to good comprehension abilities, or complete them with significantly less skill in comparison to those with good comprehension. Although many of these skills have shown to be influential for successful comprehension, the generation of strategies to teach and improve these skills has shown to be significantly ineffective at generalization.

More importantly, this suggests a lot more research needs to be done to understand the influence of these constructs and the processes that underlie these constructs.

Motivation. Wigfield (1994) suggested early on that there may be specific aspects of reading motivation that are unique to reading. More specifically, motivation was considered to be a crucial aspect of reading engagement because it is an effortful activity that involves choice (Wigfield, Guthrie, Tonks, & Pen, 2004). In recent years, research emphasizing composition and context of motivation is considering it to be an important mechanism contributing to individual differences in reading comprehension abilities. A great deal of research has been done relating reading motivation to reading ability and comprehension (Andreassen, 2010; Gotfried, 1985, 1990; Guthrie, Hoa,

Wigfield, Tonks, Humenick, & Littles, 2007; Paris, 2005; Taboada, Tonks, Wigfield, &

Guthrie, 2009). Additional findings suggest that a child’s self-concept about reading can directly relate to performance on reading comprehension tasks (Chapman, Tunmer, &

Prochnow, 2000). More importantly, this body of research offers insight beyond cognitive processes thought to contribute to reading comprehension.

Reading comprehension is yet one of the most contentious constructs within the field of literacy research today. There are a variety of definitions and very little agreement on these definitions, perhaps because the boundaries are so broad and poorly 61 marked (Paris and Hamilton, 2009). Comprehension is difficult to define, isolate, and measure because it is highly interactive, such that readers use a variety of skills and processes when encountering text. (Paris, Carpeneter, Paris, Hamilton, 2005). It has been defined as the ability to remember text (Cain et al, 2004; Graesser & Clark, 1985;

Trabasso, Secco, & van den Broek, 1984), to extract the main ideas from text (Trabasso

& van den Broek, 1985; to build coherence within the text (Graesser, Singer, & Trabasso

1994; Kintsch & van Dijk, 1978), and to apply the information in a text.

A vast amount of former research regarding reading comprehension has found evidence suggesting that lower level comprehension skills (i.e., decoding, word identification, vocabulary, fluency, and language ability) have a strong influence on comprehension abilities. Cognitive theories of comprehension suggest the reader constructs a mental representation, and connects it in meaningful ways by integrating prior knowledge (Kintsch, 1988, 1998; van den Broek, 1994). Yet more recent research suggests reading comprehension is additionally influenced by higher-level comprehension skills (i.e., inference making, comprehension monitoring, and text structure knowledge) (Cain, 2003, 1996; Cain et al., 2001; Cain & Oakhill, 1999, 1996,

2009; Myers & Paris, 1978; Oakhill, 1984, 1982; Paris & Jacobs, 1984).

Despite the differences in the way various researchers and fields attempt to explain the construct of reading comprehension, one thing that remains is the stability of the simple view model. This widely accepted model has served as the theoretical foundation for reading instruction within education in addition to ongoing research identifying processes and components used to better explain reading comprehension.

Despite its influence, the simple view model has not been found to explain all of the 62 variance in reading comprehension. However, simple view studies have undeniably acknowledged that decoding and language comprehension account for a large proportion of the variance in reading comprehension (Adlof, et al., 2006; Braze et al., 2007; Catts et al., 2005; Hoover & Gough, 1990; Joshi & Aaron, 2000; Kershaw & Shatschneider,

2012; Young-Suk et al., 2011). Previous studies have identified the importance for investigating some of the lower and higher level comprehension skills previously discussed within the simple view model of reading framework (Carlisle, 1995; Deacon,

Kieffer, & Laroche, 2014; Deacon & Kirby, 2004; Deacon, Parrila, & Kirby, 2008).

Studies have also found age to be an influential component within the simple view model, such that decoding becomes less influential while language comprehension becomes more influential in older children (Adlof et al., 2006; Catts et al., 2005; Florit &

Cain, 2011; Francis et al., 2005; Gough et al., 1996; Kershaw & Schatschneider, 2012) meriting further investigation of these underrepresented in the literature. These identifiable gaps in the literature are what led to this study.

Study Rationale

The simple view model of reading is widely accepted across the disciplines of education and psychology. For the past three decades, it has shaped reading research and teaching perspectives. However, the extent to which the simple view model of reading applies to the developmental transition between late childhood and early adolescence is not well understood. The aims laid out in this dissertation supplement the narrow research base for the simple view model of reading for older populations of participants—youth in late childhood and early adolescence. These youth are underrepresented in the existing research base of the simple view model. Youth in late childhood and early adolescence 63 are important for better understanding the developmental influence for the simple view reading components of decoding and language comprehension as well as their change over time (Catts et al., 2005; Francis et al., 2005; Gough et al., 1996). This has important implications for the design and implementation of reading curriculums as well as reading intervention selection and reading outcomes.

Studies assessing the simple view of reading model found that fifty percent to ninety-nine percent of the variance in reading comprehension was accounted for by decoding and language comprehension suggesting that other elements of reading (i.e., vocabulary and fluency) be considered as a component within the model (Adlof et al,

2006; Braze et al., 2007; Catts et al., 2005; Hoover & Gough, 1990; Joshi & Aaron, 2000;

Kershaw & Shatschneider, 2012; Young-Suk et al., 2011). High correlations (r = .3 - .8) and predictive abilities between vocabulary and reading comprehension indicated a need for further investigation (Beck & McKeown, 1991; Cain & Oakhill, 2011; Tannenbaum et al., 2006; Torgesen et al., 1997). Unique effects for vocabulary found in older samples of participants, but not younger also suggested a developmental influence for vocabulary over time (Braze et al., 2007; Ouellette & Beers, 2010). Thus, this led to the following aims for this study:

Specific Aim 1. First, examine the correlation between decoding, language

comprehension, vocabulary and reading comprehension in late childhood and

reading comprehension in early adolescence.

Specific Aim 2. Next, investigate the unique and combined contribution for the

simple view variables (language comprehension and decoding) on reading

comprehension during late childhood and early adolescence. 64 Specific Aim 3. Finally, examine whether or not vocabulary adds a unique contribution to the simple view model during late childhood or early adolescence.

65 Chapter 3: Methods

The specific aims of the current study were designed to build upon existing empirical research, investigating the relationship between language and reading skills during late childhood as well as during early adolescence. Participants in the current study were drawn from the Western Reserve Reading Project (WRRP) an ongoing 15- year longitudinal twin study comprised of 436 identical and fraternal same-sex twin pairs from Ohio, Kentucky, and Pennsylvania. The research protocols have been replicated and modified over the course of several years to include a wide-range of language, reading, math, cognitive, and Attention Deficit Hyperactivity Disorder (ADHD) assessments.

Additionally, the dataset includes a variety of child, parent, and teacher information, including questionnaires measuring: demographics, socioeconomic status (SES), academic performance, reading, math motivation, child feelings, and behavior. These measures are designed to capture elements of the child home and school environment, and the overarching impact these elements have on achievement.

The participants in the WRRP study were assessed over consecutive years, beginning in kindergarten or first grade and ending in the final years of high school education. However, for the current study, only the specific time points pertaining to late childhood and early adolescence, age range of 9-13 years, were used. Although, the parent study had a longitudinal design, in order to maximize sample size, the current study focused on analyzing late childhood and early adolescence time points cross-

66 sectionally. Though, many of the subjects overlap between time points, due to attrition, sample migration, and sample refreshment the overlap in participants between time points is not exact.

Participants

The Western Reserve Reading and Math Project (WRRMP) is a multisite longitudinal twin study involving a total of 436 families with twin siblings, 57% of which are female and 43% male (Hart, Petrill, Thompson, & Plomin, 2009), assessed across nine home visits, and one lab visit using fMRI imaging. Recruiting was conducted through school nominations, Ohio State Birth Records, the Twinsburg Twin Days festival, word-of-mouth, media advertisements, and Mothers of Twins Clubs. All participants agreed to voluntarily participate. Ninety-one percent of the sample was

White, five percent was African American, and two percent was Asian. Participants were initially assessed in kindergarten or the first grade, and were assessed annually thereafter.

The data used for this study included subjects who were assessed during late childhood (n

= 582, Mage = 9.81 years, SDage = .98; Mgrade = 3.73, SDgrade = 1.05) and early adolescence

(n = 530, Mage = 12.21 years, SDage = 1.19; Mgrade = 6.04, SDgrade = 1.24).

Opportunity mapping using Geographic Information Systems (GIS) revealed specific statistics for zip codes in order to capture additional demographic variables, and to measure the neighborhood environments where the participants reside. Data was overlaid onto zip codes of the families using census data, and 358 families were successfully mapped. In terms of college attainment, nearly eighty percent of the sample lives in areas where 15-50% of individuals are persons with degrees. It was further discovered that fourteen percent of the sample live in areas where over 50% of the 67 individuals are persons with college degrees, while merely five percent are in areas where less than 15% of individuals are persons with college degrees.

In terms of poverty, nearly ninety-seven percent of the sample was considered to live in areas with very little poverty, with only three percent of the sample living in areas considered to be in highly impoverished (20-40%). Moreover, vacancy rate was used as another indicator of poverty. Nearly eighty-seven percent of the families reside in areas where there is less than one percent vacancy rating, thus further illustrating the study sample typically resides in neighborhoods with little poverty. Finally, the median home value for sixty-nine percent of the sample was between $100,000 and $180,000 dollars.

Twenty-two percent of the sample lived in homes with a value less than 100,000, while nine percent lived in homes valued over 180,000 dollars.

Coupled with the above statistics, demographic information was also collected from family questionnaire responses. Parents and trained research staff provided reports on a variety of socioeconomic risk indicators in the first home visit, including paternal education level. It was observed that 18% of parents in the study sample held high school diplomas or less, while 82% held some college or higher form of education. Overall the maternal education level was 12% for high school or less and 88% for some college or higher education. Paternal employment status was 95% for those with a full-time job and

5% were unemployed or held a part-time job. In terms of marital status, 91% of the sample was married or cohabitated with a partner, while 9% were single. Finally, 93% of the sample lived in a detached home while 7% reported living in subsidized housing, apartment, or a townhouse.

68 Data Collection Procedures

The participants were assessed annually around the same date. For the first nine visits, the subjects were administered the research battery in their homes. Because the sample was comprised of twins, each twin was paired with a different tester, and was assessed in separate areas of the home to minimize distractions or possibly hearing each other’s responses. Staggered starts were used to ensure that if the participants were in a smaller home and closer to one another, that there was not an instance where they were on the same test so that answers could be heard and repeated. A battery of reading, math, language, cognitive, and attention measures were administered. Similar or identical assessments were used year after year in order to maintain consistency. Typically, the entire testing battery usually took approximately three hours to complete. If a participant went over three hours, we discontinued testing to adhere to the timing indicated in the consent.

Constructs and Measurement

Phonological awareness. Phonological skills were assessed using Elision subtest from the Comprehensive Test of Phonological Processing (CTOPP; Wagner, Torgesen, &

Rashotte, 1999). The Elision subtest assessed phonemic analysis and synthesis by requiring the participants to remove phonological segments from spoken words and blend remaining phonemes to form other words. There are 20 items, but testing is stopped following three consecutive errors.

Reliability over time was estimated by the test-retest method, and ranged from .70 to .97 for individual subtests and .78 to .95 for composite scores. Measurement reliability is improved by using more than a single subtest to report composite scores. Validity 69 information is offered in the form of: a) a detailed discussion of the rationale used in selecting items and subtest format, b) conventional item analysis and response theory modeling, and c) logistic regression and delta scores to detect bias. Little or no bias in the groups investigated was reported. Item discrimination and item difficulty statistics reach acceptable levels. Criterion-related validity is reported between concurrent measures, such as the Lindamood Auditory Conception Test, and predictive measures, such as the

Woodcock Reading Mastery Test – R (Word Attack and Word Identification subtests).

Finally, construct validity is reported in the form of confirmatory factor analysis and studies of age group differentiation.

Decoding. Decoding was assessed using the Word Attack subtest of the

Woodcock Reading Mastery Tests-Revised (WRMT-R; Woodcock, 1998). The Word

Attack subtest was used to assess the participants decoding skills and strategies. This subtest requires participants to apply sound-letter correspondence rules to decode unfamiliar words. The participant was asked to read aloud an increasingly complex set of stimulus words. Nonsense words were used to eliminate the chance of having participants be able to recognize or know how to pronounce the words in advance. There are 45 total stimulus items, but testing is stopped following six consecutive errors. The internal consistence reliability. Internal consistency reliability coefficients (r11) of the WRMT-R obtained by split-half reliability for the first through the third grades ranged from .91 to

.98 (M = .94; Woodcock, 1987). The description of reliability was not changed in the

Normative Update edition and was based on the 1987 norms (Woodcock, 1998).

Vocabulary. Vocabulary was assessed using the CELF-4 Word Classes subtest.

The Understanding Spoken Paragraphs subtest of the Clinical Evaluation of Language 70 Fundamentals (CELF-4; Semel, Wiig, & Secord, 2003) was administered to all children at every wave unless the child chose to skip the subtest or asked to stop during testing.

The CELF-4 Word Classes subtest includes both a receptive task and an expressive task.

For the receptive task, the subject was asked to select two words from a choice of 4 words that he or she thinks “go together” the best. For the expressive task, the subject was asked to explain why the two words that he or she selected go together. The Word

Classes expressive task is designed to assess whether a student understands and can express the relationship between two words. On the receptive task, if a student selects an incorrect pair of words, it is assumed that he or she does not understand the relationship between the correct pair (target pair) of words. Therefore, he or she cannot correctly express the relationship. Thus, if a student receives a 0 score (incorrect response) on the receptive task, then he or she receives a 0 score on the expressive task as well.

Evidence of test-retest stability was estimated using Pearson’s product-moment coefficient. The correlation between the test and retest for Word Classes was .90, suggesting adequate stability across time. Reliability for the Word Classes was based on the results of two analyses: coefficient alpha and split-half method. Reliability coefficients were examined using Cronbach’s coefficient alpha. The average across ages

5 to 21 for Word Classes was .88. The reliability based on split-half was correct using

Spearman-Brown formula for the full subtest. The average split-half coefficient across ages 5 to 21 for Word Classes was .83.

Further, content validity, criterion prediction validity, and construct identification validity for the CELF-4 Word Classes subtest were assessed. The content validity was assessed based on literature reviews, expert panel review of content, and clinician 71 feedback from expert populations with a thorough understanding of language among diverse populations to review item content for potential bias. The criterion prediction validity suggests high correlations with the CELF-3. Construct identification validity was done using factor analysis research. These studies strongly supported the concept of the general language factor. The models also reflected that cognitive processes, like working memory on language performance increase as a function of age.

Language comprehension. Language comprehension was assessed using the

CELF-4 Understanding Spoken Paragraphs (USP) subtest. The Understanding Spoken

Paragraphs subtest of the Clinical Evaluation of Language Fundamentals (CELF-4;

Semel, Wiig, & Secord, 2003) was administered to all children at every wave unless the three-hour time limit was reached prior to administration of this particular subtest.

Subjects were read three short stories aloud by the examiner that corresponded to their age, and then asked five questions about each story. Evidence of test-retest stability was estimated using Pearson’s product-moment coefficient. The correlation between the test and retest for USP was .78, suggesting adequate stability across time. Reliability for the

USP was based on the results of two analyses: coefficient alpha and split-half method.

Reliability coefficients were examined using Cronbach’s coefficient alpha. The average across ages 5 to 21 for USP was .69. The reliability based on split-half was correct using

Spearman-Brown formula for the full subtest. The average split-half coefficient across ages 5 to 21 for USP was .73. The reliability coefficients for USP are generally lower than the other subtests due to the subtest length (15 items total) and the range of scoring was only 1’s and 0’s whereas on other subtests there was a wider range of score points.

72 As previously mentioned, content validity, criterion prediction validity, and construct identification validity for the CELF-4 USP subtest were assessed. The content validity was assessed based on literature reviews, expert panel review of content, and clinician feedback from expert populations with a thorough understanding of language among diverse populations to review item content for potential bias. The criterion prediction validity suggests high correlations with the CELF-3. Construct identification validity was done using factor analysis research.

Reading comprehension. Reading comprehension was assessed during the home visit protocol using the Woodcock Reading Mastery Test – Revised (WRMT-R;

Woodcock, 1998). The WRMT-R Passage Comprehension subtest is a cloze-based comprehension assessment. The task requires the child to read a sentence, and be able to correctly identify the missing word using knowledge and understanding presented in prior sentences.

Reliability is the consistency of scores obtained from repeated subject tests, with the same or a similar assessment, and under similar conditions. Reliability for the

WRMT-R was provided from the 1989 revision and were not updated with the new norming sample. Thus the internal consistency of items split-half median was .91 (range

.68-.98) and was also reported for clusters: median =.95 (range .87-.98) and total median=.97 (range .86-.99). No information was available for test-retest reliability or inter-rater reliability.

Moreover, content validity of the WRMT-R was developed with contributions from outside experts (i.e., experienced teachers and curriculum specialists) and contained questions that were comprehensive in both content and difficulty. Classic item techniques 73 were used in the early stages of item development and Rasch modeling was used during later stages. Concurrent validity was the relative effectiveness of the test when compared with an independent criterion measure. Passage comprehension for the WRMT-R correlated significantly with the WJ reading tests at Grades 1, 3, 5, and 8 (.71, .70, .57, and .55 respectively).

Previous studies have indicated that the components in the simple view model of reading are influenced by age. Thus, in order to examine the true relationship between the variables in this study, residual scores were used controlling for the effects of age and sex for all variables.

Analysis Procedure

First, the assumptions of the linear regression model were checked. Next, the correlations were checked for Aim 1. Then multiple linear regressions were ran for late childhood and early adolescence. Finally, the hierarchical model was ran and the order for which the variables were added was developmental in nature and aligned with previous studies (Ouellette & Beers, 2009; Tunmer & Chapman, 2012).

As is standard practice in multiple regression, casewise deletion was performed such that all participants in the current study completed all of the measures. The sample size for each measure varies with sample sizes reported as high as 574 participants and as low as 453 participants. The sample size was the lowest for the CELF-USP measure both in late childhood and early adolescence due to its placement in the protocol. It was the last subtest to be administered and the maximum time allowable for the entire visit was three hours. Therefore, several participants were not assessed on this measure due to time

74 constraints. Thus, the final sample size for late childhood was (n = 464) and the final sample size for adolescence was (n = 435).

75 Chapter 4: Results

First, main assumptions were tested to make sure the data was suitable for analysis. These assumptions deal with outliers, collinearity of data, independent errors, random normal distribution of errors, homoscedasticity & linearity of data, and non-zero variances.

Testing Assumptions for Linear Regression Model

Variable type. The dependent variable (WRMT-PC) measuring reading comprehension is a continuous variable. The independent measures (CELF-USP,

WRMT-WA, and CELF-WC) assessing language comprehension, decoding, and vocabulary are all continuous variables as well.

Normality. All variables are assumed to have normal distributions. If variables are extremely skewed, relationships and significance tests can be impacted; outliers may also influence Type I and Type II errors; and the overall accuracy of the results may be compromised. Normality was examined using skew and kurtosis statistics, histograms, and Q-Plots. Skewness and Kurtosis statistics for normal distributions have an expected kurtosis value of 3 and skewness value of 0. Negative values for skewness indicate data that are skewed to the left, meaning the left tail is long relative to the right tail. Similarly, positive values indicate data are skewed to the right, meaning the right tail is long relative to the left tail. Skewness and Kurtosis statistics for all variables indicated no extreme

76 deviations from normality. Additionally, the histograms for each variable represented approximately normal distributions. Q-Q plots for some of the variables indicated slight deviations from normality, however regression is generally robust to slightly non-normal data.

Standardized residuals. One of the assumptions of regression is that residuals are normally distributed, and a plot of the values of the residuals will approximate a normal curve. This assumption was examined using both a histogram and a normal Q-Q plot of standardized residuals. Both the histogram and the normal Q-Q plot evidenced no non-normality of residuals.

Linearity. The dependent and independent variables require linearity to ensure that the results of the regression analysis will not under- or overestimate the true relationships and increase the risk of Type I and Type II errors. Violation of this assumption threatens the meaning of the parameters estimated in the analysis. Residual plots showing the standardized residuals versus the predicted values are useful for detecting violations in linearity. Standardized residuals and standardized predicted variables were plotted. The residuals were plotted on the vertical axis and were centered around 0. The scatterplot indicated that all independent variables were linearly related to the dependent variable. A scatterplot matrix was also created to examine the dependent variable (WRMT-PC) on each of the independent variables (CELF-USP, WRMT-WA, and CELF-WC). These scatterplots also indicated the assumption of linearity is reasonable- as each of the independent variables (CELF-USP, WRMT-WA, and CELF-

WC) increases, reading comprehension (WRMT-PC) generally increase as well.

77 Independence of Errors. Independence of errors refers to the assumption that errors are independent of one another, such that the participants responded independently.

Violation of this assumption can underestimate standard error or overestimate effect sizes of other variables. Generally, there should not be detectible patterns when data are drawn independently from a population. Boxplots of the residuals were created, showing the median, high and low values, and possible outliers in order to explore violations to independence of errors. The boxplots showed all of the variables at similar levels suggesting that the independence of errors assumption was met.

Homoscedasticity. The assumption of homoscedasticity refers to equal variance of errors across all levels of the independent variables. This assumes that the errors are spread out consistently between all the variables. If this assumption is not met it may weaken the overall analysis or statistical power of the analysis, increase the possibility of a Type I error, or perhaps lead to untrustworthy F-test results. Homoscedasticity was checked using visual examination of a plot of standardized residuals by the regression standardized predicted value. Scatterplots of the residuals with independent variables were used to assess whether or not the residuals were randomly scattered around zero (the horizontal line) providing even distribution. The assumption of homoscedasticity was met.

Collinearity. The assumption of collinearity refers to the assumption that the independent variables are uncorrelated. When collinearity is low, interpretations about the regression coefficients as the effects of the independent variables on the dependent variables can be made. Thus, inferences about the causes and effects of variables can be made more reliably. This assumption is violated when several independent variables 78 correlate at high levels with one another. The more overlap there is between variables the less likely the effects of the variables can be separated. A correlation matrix was examined to see if correlations between the independent variables was low. The highest correlations was .49, suggesting that collinearity was acceptably low and the assumption was met. The data matrix including variance inflation factors (VIF) and Tolerance values were also examined. Tolerance measures the influence of one independent variable on all other independent variables. The VIF is an index of the amount that the variance of each regression coefficient is increased over that with uncorrelated independent variables. The

VIF indicates whether the predictor has a strong linear relationship with the other predictors. Generally, the VIF should be lower than 10 and a Tolerance estimates greater than 0.2. The VIF measures of the study were .782, .629, and .772 respectively, while the

Tolerance estimates were 1.278, 1.591, and 1.295 respectively, suggesting the assumption of minimal collinearity between IV’s had been met.

Aim 1: Examining the Correlation Between Decoding, Language Comprehension,

Vocabulary and Reading Comprehension in Late Childhood and Reading

Comprehension in Early Adolescence.

The descriptive statistics and correlation coefficients among the variables are reported in Table 1 and Table 2 (respectively). In this aim we were interested in the relationship between the simple view variables at two different time points, late childhood and early adolescence.

79 Table 1

Descriptive Statistics

N Min Max Mean Std. Deviation Participant Age Age (Late Childhood) 582 6.50 12.75 9.81 .99 Age (Early Adolescence) 530 8.67 15.25 12.21 1.20 Test Administered CELF-USPa (LC) 502 1 14 9.15 3.08 CELF-USPa (EA) 453 1 15 9.99 2.74 CELF-WCb (LC) 562 2 18 9.89 2.63 CELF-WCb (EA) 523 3 17 10.37 2.61 WRMT-WAc (LC) 574 62 159 107.13 12.87 WRMT-WAc (EA) 528 27 146 102.63 13.54 WRMT-PCd (LC) 538 58 135 106.70 11.06 WRMT-PCd (EA) 491 65 129 103.63 11.32 Note. LC = Late Childhood; EA = Early Adolescence. a Clinical Evaluation of Language Fundamentals – Understanding Spoken Paragraph. b Clinical Evaluation of Language Fundamentals – Word Classes. c Woodcock Reading Mastery Tests – Word Attack. d Woodcock Reading Mastery Tests – Passage Comprehension.

The first sample represents children in late childhood (age M = 9.81, SD = .99), while the second sample represents children during early adolescence (age M =

12.21, SD = 1.20). These two time-points were assessed due to changes in educational and developmental influences on reading comprehension (i.e., instruction, cognitive influences, text structure, etc.). Furthermore, there is very little research specifically looking at this age range within the framework of the simple view model of reading.

Table 1 also breaks down the three simple view variables of decoding (WRMT-

WA), language comprehension (CELF-USP), and reading comprehension (WRMT-PC) as well as a measure of vocabulary (CELF-WC) to assess the role of vocabulary during

80 these age ranges. The CELF-USP was used as a measure of language comprehension.

The mean CELF-USP score during late childhood (M = 9.15, SD = 3.08) was nearly identical to the mean CELF-USP score during early adolescence (M = 9.99, SD = 2.74).

The CELF-WC was used as a measure of vocabulary. The mean CELF-WC score during late childhood (M = 9.89, SD = 2.63) was nearly identical to the mean CELF-USP score during early adolescence (M = 10.37, SD = 2.61). Although it is quite small, the means for both of these subtests show growth from late childhood to early adolescence. The

WRMT-WA was used as a measure of decoding. The mean WRMT-WA score during late childhood (M = 107.13, SD = 12.87) was not statistically different from the mean of the WRMT-WA score during early adolescence (M =102.63, SD = 13.54). The WRMT-

PC was used to assess the subject’s reading comprehension ability. The mean WRMT-PC score during late childhood (M = 106.70, SD = 11.06) was not statistically different from the mean of the WRMT-WA score during early adolescence (M =103.63, SD = 11.32).

81 Table 2

Pearson Correlations Between Measures of Available Data

Variable 1 2 3 4 5 6 7 8

1. CELF-USPa (LC) 1.00

2. CELF-WCb (LC) .486* 1.00

3. WRMT-WAc (LC) .193* .404* 1.00

4. WRMT-PCd (LC) .474* .655* .588* 1.00

5. CELF-USPa (EA) .347* .344* .188* .353* 1.00

6. CELF-WCb (EA) .474* .699* .489* .691* .350* 1.00

7. WRMT-WAc (EA) .191* .407* .805* .580* .176* .499* 1.00

8. WRMT-PCd (EA) .501* .667* .575* .771* .382* .728* .597* 1.00

Note. LC = Late Childhood; EA = Early Adolescence. a Clinical Evaluation of Language Fundamentals – Understanding Spoken Paragraph. b Clinical Evaluation of Language Fundamentals – Word Classes. c Woodcock Reading Mastery Tests – Word Attack. d Woodcock Reading Mastery Tests – Passage Comprehension. *p < .05

Correlations among all variables are presented in Table 2. All of the correlations

indicate positive significant correlations among each of the variables. First, all of the late

childhood variables were correlated amongst each other. Table 2 shows that the two

CELF measures, CELF-USP and CELF-WC were moderately correlated with each other

with a coefficient of (r = .486, p < 0.05). These two measures were also found to

correlate significantly with decoding as measured by WRMT-WA in late childhood.

Decoding (WRMT-WA) has a weak correlation with language comprehension (CELF-

USP) in late childhood (r = .193, p < 0.05), while decoding had a moderate correlation 82 with vocabulary (CELF-WC) in late childhood (r = .404, p < 0.05). Reading

Comprehension (WRMT-PC) was moderately correlated with language comprehension

(CELF-USP; r = .474, p < 0.05) and decoding (WRMT-WA; r = .588, p < 0.05), and was strongly correlated with vocabulary (CELF-WC; r = .655, p < 0.05) in late childhood.

The late childhood measures were all positively correlated with the measures from early adolescence. Language comprehension in early adolescence was moderately correlated language comprehension (CELF-USP; r = .347, p < 0.05), vocabulary (CELF-

WC; r = .474, p < 0.05), decoding (WRMT-WA; r = .191, p < 0.05), and reading comprehension (WRMT-PC; r = .501, p < 0.05) in late childhood. Vocabulary (CELF-

WC) in early adolescence was moderately correlated with late childhood language comprehension (CELF-USP; r = .474, p < 0.05) and late childhood decoding (WRMT-

WA; r = .489, p < 0.05) and strongly correlated with late childhood vocabulary (CELF-

WC; r = .699, p < 0.05) and late childhood reading comprehension (WRMT-PC; r = .691, p < 0.05). Decoding (WRMT-WA) in early adolescence was significantly correlated with language comprehension (CELF-USP; r = .191, p < 0.05), vocabulary (CELF-WC; r =

.407, p < 0.05), decoding (WRMT-WA; r = .805, p < 0.05), and reading comprehension

(WRMT-PC; r = .580, p < 0.05) in late childhood. Reading comprehension in early adolescence was significantly correlated with language comprehension (CELF-USP; r =

.501, p < 0.05), vocabulary (CELF-WC; r = .667, p < 0.05), decoding (WRMT-WA; r =

.575, p < 0.05), and reading comprehension (WRMT-PC; r = .771, p < 0.05) in late childhood.

Finally, the measures in early adolescence were significantly correlated amongst each other. The measures for oral comprehension and vocabulary, respectively CELF- 83 USP and CELF-WC were significantly correlated (r = .350, p < 0.05) in early adolescence. Decoding in early adolescence was significantly, but weakly, correlated with language comprehension (CELF-USP; r = .176, p < 0.05), and moderately correlated with vocabulary (CELF-WC; r = .499, p < 0.05). Finally, reading comprehension demonstrated strong significant correlations with vocabulary (CELF-WC; r = .728, p < 0.05) and moderate correlations with decoding (WRMT-WA; r = .597, p <

0.05). The correlation between reading comprehension (WRMT-RC) and language comprehension (CELF-USP) was significant, but somewhat weak (r = .382, p < 0.05).

Aim 2: Investigating the Unique and Combined Contribution for the Simple View

Variables (Language Comprehension and Decoding) on Reading Comprehension

During Late Childhood and Early Adolescence.

A linear regression was conducted to see how much variance in reading comprehension the simple view variables (language comprehension and decoding) explained during this developmental shift. Two different regressions were ran, one for late childhood and one for early adolescence. The WRMT-R Passage Comprehension residualized score was entered as the dependent variable and the WRMT-R Word Attack residualized score as a measure of decoding and the CELF-4 USP residualized score as a measure of language comprehension were both entered as independent variables. They were entered this way because we were interested in seeing how much total variance was accounted for by these simple view model predictors during the developmental shift from late childhood (Mage = 9.8 years) to early adolescence (Mage = 12.2 years). The results of these analyses are presented in Table 3.

84 Table 3

Simple Regression Analyses for Variables Predicting Reading Comprehension in Late Childhood and Early Adolescence

Late Childhood Early Adolescence Variable B SE B β B SE B β Decoding .438* .028 .524 .548* .038 .538 Language Comp .830* .079 .358 1.004* .129 .287 R2 .485 .427 F 221.84*** 162.28*** Note. B = Unstandardized; β = Standardized. *** p < .001, *p < .05.

Estimates of R2 tell us how much of the variability in the outcome is accounted for by the predictors (decoding and language comprehension). For the first model this study looked at the simple view model predictors during late childhood. As reported in Table 3, the R2 value was .485, which means that decoding and language comprehension account for 48.5% of the variance in reading comprehension ability. The full model was statistically significant (F(2, 471) = 221.839, p <.001), suggesting the model was a good fit for the data. The b-values tell about the relationship between reading comprehension and each simple view predictor. Both predictors had a positive b-value indicating a positive relationship. Thus, as decoding scores increased, reading comprehension scores increased and as language comprehension scores increased, reading comprehension scores increased. During late childhood, decoding, B=.44, p < .05 and language comprehension B=.83, p < .05, were both significant predictors of reading comprehension. Furthermore, the results suggest that decoding (WRMT-WA) had a

85 higher impact than language comprehension (CELF-USP) by comparing the standardized coefficients (beta = .524 versus beta = .358).

Likewise, during early adolescence the R2 was .427 suggesting that 42.7% of the variance in reading comprehension ability is accounted for by decoding and language comprehension. The full model again for early adolescence is statistically significant

(F(2,436) = 162.28, p < .001), suggesting the model was a good fit for the data. During early adolescence, decoding, B=.55, p < .05 and language comprehension B=1.004, p <

.05, were both significant predictors of reading comprehension. Both predictors had a positive b-value indicating a positive relationship. Thus, as decoding scores increased, reading comprehension scores increased and as language comprehension scores increased, reading comprehension scores increased. Furthermore, the results suggest that decoding (WRMT-WA) had a higher impact than language comprehension (CELF-USP) by comparing the standardized coefficients (beta = .538 versus beta = .287).

Aim 3: Examining Whether Vocabulary Adds a Unique Contribution to the Simple

View Model During Late Childhood or Early Adolescence.

In this particular aim we wanted to look at the simple view model and see if vocabulary added a unique contribution to the simple view model. Therefore, a hierarchical multiple regression was ran to see if whether or not adding vocabulary to the simple view model accounted for additional unique variance during these ages. Theory has indicated that phonological awareness is a significant predictor of reading comprehension in early years, so we included this in the model as well. The same regression was ran for the different ages, one for late childhood and one for early adolescence. As was referenced in the introduction, phonological awareness, decoding, 86 language comprehension, and vocabulary in turn become stronger predictors of reading comprehension with development (Adlof et al., 2006; Florit & Cain, 2011; Gough,

Hoover, & Peterson, 1996; Kershaw & Schatschneider, 2012; Snowling, 2000; Torgesen et al., 1997). Thus, these variables were entered in the same stepwise fashion for each model. Phonological awareness was entered in the first step, decoding in the second step, language comprehension in the third step, and vocabulary in the 4th step. This resulted in four different models for each analysis with the addition of a new predictor at each step.

Model 1 refers to the first stage in the hierarchy when only phonological awareness was used as a predictor. Model 2 refers to the next model where phonological awareness and decoding were used as predictors. Model 3 refers to the next model where phonological awareness, decoding, and language comprehension were used as predictors. Model 4 refers to the final model where phonological awareness, decoding, language comprehension, and vocabulary were all used as predictors. Table 4 presents the final regression model for late childhood and early adolescence.

87 Table 4 Hierarchical Regression Analyses for Reading Comprehension in Late Childhood and Early Adolescence.

R2 ∆R2 F β Late Childhood Phonological Awareness .196 .196 113.02** .085* Decoding .386 .190 145.15** .350** Language Comprehension .497 .111 151.79** .194** Vocabulary .591 .094 166.34** .381** Early Adolescence Phonological Awareness .236 .236 134.23** .056 Decoding .366 .130 125.04** .278** Language Comprehension .436 .070 111.23** .144** Vocabulary .609 .173 167.62** .508** Note. *p < .05; **p < .001

Results for the analyses are reported in Table 4. The first column gives the value of R2, which is a measure of how much of the variability in the outcome, reading comprehension is accounted for by the predictors. The regression analysis for late childhood was broken down by the four models. For the Model 1, R2 = .196, which means that phonological awareness accounted for 19.6% of the variation in reading comprehension. For the next model (Model 2), this R2 value increased to .386. This means that phonological awareness and decoding accounted for 38.6% of the variance in reading comprehension in late childhood. The change in R2 (∆R2) is the incremental increase in the model resulting from the addition of a predictor. Thus, in Model 2,

88 decoding accounted for an additional 19% of the variance in reading comprehension. In the next model (Model 3), the R2 again increased to .497. Therefore, phonological awareness, decoding, and language comprehension accounted for 49.7% of the variance in reading comprehension. Language comprehension accounted for an additional 11.1% of the variance in reading comprehension in late childhood. Model 4, which includes all of the predictors, increased to .591. This means that phonological awareness, decoding, language comprehension, and vocabulary together explained 59.1% of the variance in reading comprehension. The ∆R2 is .094, which means that vocabulary explained an additional 9.4% of the variance in reading comprehension in late childhood. The F-ratio represents the ratio of the improvement in prediction that results from fitting the model. If the improvement due to fitting the regression model is much greater than the inaccuracy within the model, then the value of F will be greater than 1 and the exact probability of obtaining the value of F by chance will be calculated. In late childhood all four models were greater than 1 and each model was significant (p < .001). Thus, results from this analysis suggest that the final model including phonological awareness, decoding, language comprehension, and vocabulary significantly improved our ability to predict reading comprehension.

The standardized beta coefficients (β), which represent the individual contribution of each predictor to the model, are reported in the last column of Table 4. These beta values tell about the relationship between reading comprehension and each predictor. All of the beta values in the regression analysis for late childhood have positive values, which indicates each predictor had a positive relationship with reading comprehension.

Thus, as phonological awareness, decoding, language comprehension, and vocabulary 89 skills increase so does reading comprehension. For Model 4, phonological awareness, B =

.12, p < .05, decoding B = .29, p < .001, language comprehension B = .45, p < .001, and vocabulary B = .47, p < .001 were all significant predictors of reading comprehension in late childhood. From the magnitude of the beta values we can see that vocabulary (β =

.381) had the most impact followed by decoding (β = .350), language comprehension (β

= .194), and then phonological awareness (β = .085).

The regression analysis was replicated for early adolescence and was broken down into four models as well. The Model 1 estimates of R2 suggest that phonological awareness accounted for 23.6% of the variation in reading comprehension. For the next model (model 2), this value increased to .366, meaning that phonological awareness and decoding accounted for 36.6% of the variance in reading comprehension in late childhood. In Model 2, decoding accounted for an additional 13% of the variance in reading comprehension. In the next model (Model 3), the R2 again increased to .436.

Therefore, phonological awareness, decoding, and language comprehension accounted for 43.6% of the variance in reading comprehension. Language comprehension accounted for an additional 7% of the variance in reading comprehension in early adolescence.

Model 4, which included all of the predictors, increased to R2 = .609. This means that phonological awareness, decoding, language comprehension, and vocabulary together explained 60.9% of the variance in reading comprehension. The ∆R2 is .173, which means that vocabulary explained an additional 17.3% of the variance in reading comprehension in early adolescence. In early adolescence all four models are greater than 1 and each model is highly significant (p < .001). Thus, these results suggest that the final model,

90 Model 4, significantly improved our ability to predict reading comprehension in early adolescence. The standardized beta coefficients (β), in the last column of Table 4, denote the individual contribution of each predictor to the model. All of the beta values in the regression analysis for early adolescence had positive values, which means that each predictor has a positive relationship with reading comprehension. Thus, as phonological awareness, decoding, language comprehension, and vocabulary skills increased so did reading comprehension. For Model 4, phonological awareness, B = .10, p = .16, decoding

B = .28, p < .001, language comprehension B = .50, p < .001, and vocabulary B = .60, p <

.001 were all significant predictors of reading comprehension with the exception of phonological awareness in early adolescence. From the magnitude of the beta values we can see that vocabulary (β = .508) had the most impact followed by decoding (β = .278), language comprehension (β = .144), and then phonological awareness (β = .056).

91 Chapter 5: Discussion

There are various phonological models of reading comprehension and conceptual and cognitive models of reading comprehension. However, one model in particular, the

Simple View of Reading model (Gough & Tunmer, 1986; Hoover & Gough, 1990) is widely supported throughout the literature and has been adopted as a framework for literacty instruction. The simple view suggests that language comprehension and decoding are the two primary components that account for reading comprehension. Many have assessed this model and have found that these two components do account for a large proportion of variance in reading comprehension abilities (Adlof, Catts, & Little,

2006; Braze, Tabor, Shankweiler, & Mencl, 2007; Catts, Hogan, & Adlof, 2005; Hoover

& Gough, 1990; Joshi & Aaron, 2000; Kershaw & Shatschneider, 2012; Young-Suk,

Wagner, & Foster, 2011). A number of studies have tried to account for the additional variance through measures of vocabulary and fluency and adding additional components to the model (Aaron, Joshi, & Williams, 1999; Braze et al., 2007; Fuchset al., 2001;

Harlaar et al., 2010; Joshi & Aaron, 2000; Ouellette & Beers, 2010; Wolf 2001). Over time, what remains is that decoding and language comprehension still continue to be the primary contributors for reading comprehension ability (Adlof et al., 2006; Aaron, et al.,

1999; Braze et al., 2007; Catts, et al., 2005; Cutting & Scarborough, 2006; Dreyer &

Katz, 1992; Kendeou, et al., 2009; Kershaw & Shatschneider, 2012), but are developmental in nature, meaning their contribution changes over time. Decoding

92 accounts for more variance and predicts reading abilities in younger children more than language comprehension, while language comprehension becomes the primary influence and predictor for comprehension ability in children from around 4th grade on (Adlof et al., 2006; Florit & Cain, 2011; Gough, Hoover, & Peterson, 1996; Kershaw &

Schatschneider, 2012). The change in variance due to age for decoding and language comprehension and the lack of research for children around this developmental shift suggest the need to further assess and understand the relationship between language comprehension and reading comprehension in older children. This study contributed to the literature by looking at differences in the relative influence of the components of the simple view model of reading over time, as well as address weak areas of literature for the specific ages of nine and twelve year-olds.

Aim 1: Correlation Between Study Variables in Late Childhood and Early

Adolescence

The first aim of this study was to explore the relationship between the simple view variables of decoding, language comprehension, and reading comprehension in addition to vocabulary during late childhood and early adolescence time points.

Correlations among the variables were all significant and in a positive direction (see

Table 2).

The repeated measures correlations were all significant and moderately high for vocabulary, decoding, and reading comprehension; yet they were low for language comprehension. The magnitude of these language comprehension correlations are consistent with the literature. High correlations were also found between vocabulary and reading comprehension. Again, this is consistent with previous literature and key 93 assumptions suggesting that individuals who encounter difficulty with decoding will have difficulty understanding what is written. The magnitude of the correlation coefficients among vocabulary, decoding, and reading comprehension measures were greater in early adolescence than late childhood. Previous studies indicate moderate to high correlations between measures of vocabulary and language comprehension. The correlations between these constructs in our study, although significant are lower than previous research suggesting a weak relationship between the two. The type of tests used to measure the components of the model could explain these differences.

Aim 2: Contribution for the Simple View Variables on Reading Comprehension during Late Childhood and Early Adolescence

The analyses in aim 2 of this study intended to explore the current simple view model of reading using measures of language comprehension and decoding to estimate the variability in reading comprehension for two very important time points, late childhood and early adolescence. These two time points are developmentally important, because language and vocabulary are said to become more influential as children age.

During late childhood, decoding, and language comprehension were both significant predictors of reading comprehension, accounting for 48.5% of the variance in reading comprehension ability. During early adolescence, decoding and language comprehension were both significant predictors of reading comprehension but to a lesser degree, accounting for 42.7% of the variance in reading comprehension. Previous studies have also found that decoding and language comprehension explain less variance as children age. Thus, these results suggest that as children age, the simple view model is less

94 effective at predicting reading comprehension abilities as they do when individuals are younger.

Aim 3: What Vocabulary adds to the Simple View Model during Late Childhood and Early Adolescence

Phonological awareness and decoding are said to be important influences on reading comprehension abilities when children are young, but around fourth grade the contribution of these skills decrease, while vocabulary and language comprehension contributions increase. Results from the hierarchical multiple regression suggest that phonological awareness, decoding, language comprehension, and vocabulary accounted for 59.1% of the variance for reading comprehension in late childhood and 60.9% of the variance for reading comprehension abilities in early adolescence. Phonological awareness, decoding, language comprehension, and vocabulary were all significant predictors of reading comprehension in late childhood, but phonological awareness was no longer a significant predictor of reading comprehension by early adolescence. This particular result is not surprising given that phonological skills have developed to a point of automaticity by early adolescence.

Previous studies have suggested that vocabulary is a unique predictor of vocabulary above and beyond that measured by decoding and language comprehension, suggesting that it be included as an additional component in the simple view model

(Braze et al., 2007; Ouellette & Beers, 2010; Tunmer & Chapman, 2012). This study was consistent with that literature suggesting that vocabulary accounted for an additional

9.4% of the variance in reading comprehension in late childhood and 17.3% of the

95 variance in reading comprehension in early adolescence above and beyond that accounted for by decoding and language comprehension.

Use of standardized results suggest that in late childhood, decoding and vocabulary are similarly important predictors of reading comprehension and are dominating the model.

However, by early adolescence the importance of decoding has faded and vocabulary is the most influential component in the model. Thus, in terms of the simple view reading model, it is true that decoding and language comprehension are significant, but they are not doing as good of a job at predicting reading comprehension as vocabulary is when included into the model. These data are consistent with previous studies that have also found unique influence for vocabulary. such that vocabulary is a significant predictor and provides unique influence above and beyond decoding and that as the contribution of language comprehension increases with age, the contribution of decoding decreases.

General Conclusions

This study concludes with some important findings that contribute to the literature. The first, is that consistent with previous literature, decoding and language comprehension do account for a large proportion of the variance in reading comprehension abilities in late childhood and early adolescence. However, there is still a proportion of unexplained variance suggesting that the contribution of these two components cannot entirely explain one’s reading comprehension ability.

The second finding from this study suggests the simple view model of reading may be developmental in nature. Results from this study are similar to previous studies, such that phonological awareness and decoding are better predictors of reading comprehension abilities in late childhood, but that language comprehension and 96 vocabulary are the most influential in predicting reading comprehension during early adolescence.

Finally, there is disagreement as to whether or not vocabulary accounts for unique variance in reading comprehension abilities. This study found that vocabulary made unique contributions to reading comprehension above and beyond that made by decoding and language comprehension. Furthermore, vocabulary accounted for more variance in reading comprehension in early adolescence than late childhood.

Limitations

There are limitations with this work that may have implications on the conclusions that were reached. The literature has addressed some of the concerns with reading comprehension and language comprehension abilities being loaded factors. A number of studies have supported factor analysis using broad factors of reading and language comprehension for looking at the simple view model of reading. This study used single assessments to measure these constructs. Limited measures may have influenced the outcome of this research.

Another potential limitation of the study may have been the measure used to assess language comprehension. The CELF Understanding Spoken Paragraphs measure is a widely used standardized measure of language comprehension. However, the magnitude of the correlation coefficients for language comprehension were the lowest of all the measures both within the repeated measure and across other measures. Weak correlation coefficients may be attributed to measurement error and may be considered a limitation of this study.

97 While there are some distinct limitations to our research, it still offers some important findings to the existing literature. This study looks at a transitional age range that is believed to be an important time where influences on the contributions of reading comprehension are changing.

Directions for Future Research

Given this work, there are some recommendations for future work exploring the simple view model of reading. This study used single measures for each of the constructs

(i.e., phonological awareness, decoding, language comprehension, and reading comprehension). It is recommended that future work investigate these skills as latent factors. Decoding, language comprehension, and reading comprehension are all constructs that involve interrelated skills and processes. Latent factor analyses involving multiple measures will allow for a deeper breakdown and understanding of these broad constructs. Given, that language comprehension is extremely broad, multiple measures of language comprehension should be included aimed at assessing the very specific elements of language like phonological awareness, syntax, morphology, semantics, and pragmatics.

Next, it is recommended that further exploration be given to some of the other factors previously mentioned that influence reading comprehension like motivation, background knowledge, inferencing ability, knowledge of text structure, and memory.

One such model, the Direct and Inferential Mediation (DIME) model proposes to consider the interrelated processes of reading and language. The DIME model, for which very little research exists, stems from the simple view model. Given the research that does exist, studies have found that inference skills play a direct and mediated role in the 98 process of comprehension (Ahmed et al., 2016) and that background knowledge, inference, and vocabulary comprehension strategies have indirect effects via inference on reading comprehension. The DIME model, created by Cromley and Azevedo (2007), is a component-based model subsumed within the SVR framework. The DIME model is similar to the simple view of reading model in that they both suggest reading comprehension is a product of decoding and language comprehension abilities, but each involve different representations for these skills. Within the DIME model decoding is surmised by word reading while language comprehension is composed of vocabulary, background knowledge, and text-processing components (i.e., inference making and reading strategies). The other difference is that the DIME model treats measurable components involved in reading comprehension as a set of interrelated processes, focusing on the components and their relations in a more static model of reading comprehension.

The simple view of reading is a widely accepted view suggesting that reading comprehension is the product of two components: decoding and language comprehension. More specifically stated, reading comprehension cannot occur unless strong decoding and language comprehension skills are present. Educators are often unfamiliar with this theoretical model of reading. Although, its familiarity in the schools is not well known, if incorporated, the theoretical framework for simple view of reading could provide meaningful implications for reading instruction, intervention, and reading outcomes. It could be used to develop reading curriculums and instruction, analyze differences in Response to Intervention (RTI), and explain differences in reading outcomes for students. 99 References

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