Reading and word recognition

Main Body

3. Word Recognition Skills: One of Two Essential Components of Reading Comprehension

Maria S. Murray

Abstract

After acknowledging the contributions of recent scientific discoveries in reading that have led to new understandings of reading processes and reading instruction, this chapter focuses on word recognition, one of the two essential components in the Simple View of Reading. The next chapter focuses on the other essential component, language comprehension. The Simple View of Reading is a model, or a representation, of how skillful reading comprehension develops. Although the Report of the National Reading Panel (NRP; National Institute of Child Health and Human Development [NICHD], 2000) concluded that the best reading instruction incorporates explicit instruction in five areas (phonemic awareness, phonics, fluency, vocabulary, and comprehension), its purpose was to review hundreds of research studies to let instructors know the most effective evidence-based methods for teaching each. These five areas are featured in the Simple View of Reading in such a way that we can see how the subskills ultimately contribute to two essential components for skillful reading comprehension. Children require many skills and elements to gain word recognition (e.g., phoneme awareness, phonics), and many skills and elements to gain language comprehension (e.g., vocabulary). Ultimately, the ability to read words (word recognition) and understand those words (language comprehension) lead to skillful reading comprehension. Both this chapter and the next chapter present the skills, elements, and components of reading using the framework of the Simple View of Reading, and in this particular chapter, the focus is on elements that contribute to automatic word recognition. An explanation of each element’s importance is provided, along with recommendations of research-based instructional activities for each.

Learning Objectives

After reading this chapter, readers will be able to

  1. identify the underlying elements of word recognition;
  2. identify research-based instructional activities to teach phonological awareness, decoding, and sight recognition of irregular sight words;
  3. discuss how the underlying elements of word recognition lead to successful reading comprehension.

Introduction

Throughout history, many seemingly logical beliefs have been debunked through research and science. Alchemists once believed lead could be turned into gold. Physicians once assumed the flushed red skin that occurred during a fever was due to an abundance of blood, and so the “cure” was to remove the excess using leeches (Worsley, 2011). People believed that the earth was flat, that the sun orbited the earth, and until the discovery of microorganisms such as bacteria and viruses, they believed that epidemics and plagues were caused by bad air (Byrne, 2012). One by one, these misconceptions were dispelled as a result of scientific discovery. The same can be said for misconceptions in education, particularly in how children learn to read and how they should be taught to read.1

In just the last few decades there has been a massive shift in what is known about the processes of learning to read. Hundreds of scientific studies have provided us with valuable knowledge regarding what occurs in our brains as we read. For example, we now know there are specific areas in the brain that process the sounds in our spoken words, dispelling prior beliefs that reading is a visual activity requiring memorization (Rayner, Foorman, Perfetti, Pesetsky, & Seidenberg, 2001). Also, we now know how the reading processes of students who learn to read with ease differ from those who find learning to read difficult. For example, we have learned that irregular eye movements do not cause reading difficulty. Many clever experiments (see Rayner et al., 2001) have shown that skilled readers’ eye movements during reading are smoother than struggling readers’ because they are able to read with such ease that they do not have to continually stop to figure out letters and words. Perhaps most valuable to future teachers is the fact that a multitude of studies have converged, showing us which instruction is most effective in helping people learn to read. For instance, we now know that phonics instruction that is systematic (i.e., phonics elements are taught in an organized sequence that progresses from the simplest patterns to those that are more complex) and explicit (i.e., the teacher explicitly points out what is being taught as opposed to allowing students to figure it out on their own) is most effective for teaching students to read words (NRP, 2000).

As you will learn, word recognition, or the ability to read words accurately and automatically, is a complex, multifaceted process that teachers must understand in order to provide effective instruction. Fortunately, we now know a great deal about how to teach word recognition due to important discoveries from current research. In this chapter, you will learn what research has shown to be the necessary elements for teaching the underlying skills and elements that lead to accurate and automatic word recognition, which is one of the two essential components that leads to skillful reading comprehension. In this textbook, reading comprehension is defined as “the process of simultaneously extracting and constructing meaning through interaction and involvement with written language” (Snow, 2002, p. xiii), as well as the “capacities, abilities, knowledge, and experiences” one brings to the reading situation (p. 11).

Learning to Read Words Is a Complex Process

It used to be a widely held belief by prominent literacy theorists, such as Goodman (1967), that learning to read, like learning to talk, is a natural process. It was thought that since children learn language and how to speak just by virtue of being spoken to, reading to and with children should naturally lead to learning to read, or recognize, words. Now we know it is not natural, even though it seems that some children “pick up reading” like a bird learns to fly. The human brain is wired from birth for speech, but this is not the case for reading the printed word. This is because what we read—our alphabetic script—is an invention, only available to humankind for the last 3,800 years (Dehaene, 2009). As a result, our brains have had to accommodate a new pathway to translate the squiggles that are our letters into the sounds of our spoken words that they symbolize. This seemingly simple task is, in actuality, a complex feat.

The alphabet is an amazing invention that allows us to represent both old and new words and ideas with just a few symbols. Despite its efficiency and simplicity, the alphabet is actually the root cause of reading difficulties for many people. The letters that make up our alphabet represent phonemes—individual speech sounds—or according to Dehaene, “atoms” of spoken words (as opposed to other scripts like Chinese whereby the characters represent larger units of speech such as syllables or whole words). Individual speech sounds in spoken words (phonemes) are difficult to notice for approximately 25% to 40% of children (Adams, Foorman, Lundberg, & Beeler, 1998). In fact, for some children, the ability to notice, or become aware of the individual sounds in spoken words (phoneme awareness) proves to be one of the most difficult academic tasks they will ever encounter. If we were to ask, “How many sounds do you hear when I say ‘gum’?” some children may answer that they hear only one, because when we say the word “gum,” the sounds of /g/ /u/ and /m/ are seamless. (Note the / / marks denote the sound made by a letter.) This means that the sounds are coarticulated; they overlap and melt into each other, forming an enveloped, single unit—the spoken word “gum.” There are no crisp boundaries between the sounds when we say the word “gum.” The /g/ sound folds into the /u/ sound, which then folds into the /m/ sound, with no breaks in between.

So why the difficulty and where does much of it begin? Our speech consists of whole words, but we write those words by breaking them down into their phonemes and representing each phoneme with letters. To read and write using our alphabetic script, children must first be able to notice and disconnect each of the sounds in spoken words. They must blend the individual sounds together to make a whole word (read). And they must segment the individual sounds to represent each with alphabetic letters (spell and write). This is the first stumbling block for so many in their literacy journeys—a difficulty in phoneme awareness simply because their brains happen to be wired in such a way as to make the sounds hard to notice. Research, through the use of brain imaging and various clever experiments, has shown how the brain must “teach itself” to accommodate this alphabet by creating a pathway between multiple areas (Dehaene, 2009).

Instruction incorporating phoneme awareness is likely to facilitate successful reading (Adams et al., 1998; Snow, Burns, & Griffin, 1998), and it is for this reason that it is a focus in early school experiences. For some children, phoneme awareness, along with exposure to additional fundamentals, such as how to hold a book, the concept of a word or sentence, or knowledge of the alphabet, may be learned before formal schooling begins. In addition to having such print experiences, oral experiences such as being talked to and read to within a literacy rich environment help to set the stage for reading. Children lacking these literacy experiences prior to starting school must rely heavily on their teachers to provide them.

The Simple View of Reading and the Strands of Early Literacy Development

Teachers of reading share the goal of helping students develop skillful reading comprehension. As mentioned previously, the Simple View of Reading (Gough & Tunmer, 1986) is a research-supported representation of how reading comprehension develops. It characterizes skillful reading comprehension as a combination of two separate but equally important components—word recognition skills and language comprehension ability. In other words, to unlock comprehension of text, two keys are required—being able to read the words on the page and understanding what the words and language mean within the texts children are reading (Davis, 2006). If a student cannot recognize words on the page accurately and automatically, fluency will be affected, and in turn, reading comprehension will suffer. Likewise, if a student has poor understanding of the meaning of the words, reading comprehension will suffer. Students who have success with reading comprehension are those who are skilled in both word recognition and language comprehension.

Ch 3 Figure 1

Figure 1. Strands of early literacy development. Reprinted from Connecting early language and literacy to later reading (dis)abilities: Evidence, theory, and practice, by H. S. Scarborough, in S. B. Newman & D. K. Dickinson (Eds.), 2002, Handbook of early literacy research, p. 98, Copyright 2002, New York, NY: Guilford Press. Reprinted with permission.

These two essential components of the Simple View of Reading are represented by an illustration by Scarborough (2002). In her illustration, seen in Figure 1, twisting ropes represent the underlying skills and elements that come together to form two necessary braids that represent the two essential components of reading comprehension. Although the model itself is called “simple” because it points out that reading comprehension is comprised of reading words and understanding the language of the words, in truth the two components are quite complex. Examination of Scarborough’s rope model reveals how multifaceted each is. For either of the two essential components to develop successfully, students need to be taught the elements necessary for automatic word recognition (i.e., phonological awareness, decoding, sight recognition of frequent/familiar words), and strategic language comprehension (i.e., background knowledge, vocabulary, verbal reasoning, literacy knowledge). The sections below will describe the importance of the three elements that lead to accurate word recognition and provide evidence-based instructional methods for each element. Chapter 4 in this textbook will cover the elements leading to strategic language comprehension.

Word Recognition

Word recognition is the act of seeing a word and recognizing its pronunciation immediately and without any conscious effort. If reading words requires conscious, effortful decoding, little attention is left for comprehension of a text to occur. Since reading comprehension is the ultimate goal in teaching children to read, a critical early objective is to ensure that they are able to read words with instant, automatic recognition (Garnett, 2011). What does automatic word recognition look like? Consider your own reading as an example. Assuming you are a skilled reader, it is likely that as you are looking at the words on this page, you cannot avoid reading them. It is impossible to suppress reading the words that you look at on a page. Because you have learned to instantly recognize so many words to the point of automaticity, a mere glance with no conscious effort is all it takes for word recognition to take place. Despite this word recognition that results from a mere glance at print, it is critical to understand that you have not simply recognized what the words look like as wholes, or familiar shapes. Even though we read so many words automatically and instantaneously, our brains still process every letter in the words subconsciously. This is evident when we spot misspellings. For example, when quickly glancing at the words in the familiar sentences, “Jack be nimble, Jack be quick. Jack jamped over the canbleslick,” you likely spotted a problem with a few of the individual letters. Yes, you instantly recognized the words, yet at the same time you noticed the individual letters within the words that are not correct.

To teach students word recognition so that they can achieve this automaticity, students require instruction in: phonological awareness, decoding, and sight recognition of high frequency words (e.g., “said,” “put”). Each of these elements is defined and their importance is described below, along with effective methods of instruction for each.

Phonological Awareness

One of the critical requirements for decoding, and ultimately word recognition, is phonological awareness (Snow et al., 1998). Phonological awareness is a broad term encompassing an awareness of various-sized units of sounds in spoken words such as rhymes (whole words), syllables (large parts of words), and phonemes (individual sounds). Hearing “cat” and “mat,” and being aware that they rhyme, is a form of phonological awareness, and rhyming is usually the easiest and earliest form that children acquire. Likewise, being able to break the spoken word “teacher” into two syllables is a form of phonological awareness that is more sophisticated. Phoneme awareness, as mentioned previously, is an awareness of the smallest individual units of sound in a spoken word—its phonemes; phoneme awareness is the most advanced level of phonological awareness. Upon hearing the word “sleigh,” children will be aware that there are three separate speech sounds—/s/ /l/ /ā/—despite the fact that they may have no idea what the word looks like in its printed form and despite the fact that they would likely have difficulty reading it.

Because the terms sound similar, phonological awareness is often confused with phoneme awareness. Teachers should know the difference because awareness of larger units of sound—such as rhymes and syllables—develops before awareness of individual phonemes, and instructional activities meant to develop one awareness may not be suitable for another. Teachers should also understand and remember that neither phonological awareness nor its most advanced form—phoneme awareness—has anything whatsoever to do with print or letters. The activities that are used to teach them are entirely auditory. To help remember this, simply picture that they can be performed by students if their eyes are closed. Adults can teach phonological awareness activities to a child in a car seat during a drive. The child can be told, “Say ‘cowboy.’ Now say ‘cowboy’ without saying ‘cow.’” Adults can teach phoneme awareness activities as well by asking, “What sound do you hear at the beginning of ‘sssun,’ ‘sssail,’ and ‘ssssoup’?” or, “In the word ‘snack,’ how many sounds do you hear?” or by saying, “Tell me the sounds you hear in ‘lap.’” Notice that the words would not be printed anywhere; only spoken words are required. Engaging in these game-like tasks with spoken words helps children develop the awareness of phonemes, which, along with additional instruction, will facilitate future word recognition.

Why phonological awareness is important

An abundance of research emerged in the 1970s documenting the importance of phoneme awareness (the most sophisticated form of phonological awareness) for learning to read and write (International Reading Association, 1998). Failing to develop this awareness of the sounds in spoken words leads to difficulties learning the relationship between speech and print that is necessary for learning to read (Snow et al., 1998). This difficulty can sometimes be linked to specific underlying causes, such as a lack of instructional experiences to help children develop phoneme awareness, or neurobiological differences that make developing an awareness of phonemes more difficult for some children (Rayner et al., 2001). Phoneme awareness facilitates the essential connection that is “reading”: the sequences of individual sounds in spoken words match up to sequences of printed letters on a page. To illustrate the connection between phoneme awareness and reading, picture the steps that children must perform as they are beginning to read and spell words. First, they must accurately sound out the letters, one at a time, holding them in memory, and then blend them together correctly to form a word. Conversely, when beginning to spell words, they must segment a spoken word (even if it is not audible they are still “hearing the word” in their minds) into its phonemes and then represent each phoneme with its corresponding letter(s). Therefore, both reading and spelling are dependent on the ability to segment and blend phonemes, as well as match the sounds to letters, and as stated previously, some students have great difficulty developing these skills. The good news is that these important skills can be effectively taught, which leads to a discussion about the most effective ways to teach phonological (and phoneme) awareness.

Phonological awareness instruction

The National Reading Panel (NRP, 2000) report synthesized 52 experimental studies that featured instructional activities involving both phonological awareness (e.g., categorizing words similar in either initial sound or rhyme) and phoneme awareness (e.g., segmenting or blending phonemes). In this section, both will be discussed.

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Figure 2. Oddity task featuring rhymes (top row) and initial sounds (bottom row). Used with permission from Microsoft.

Figure 3. Sample of an Elkonin Box featuring the word “fan.” The picture of the word eases the memory load for students as they concentrate on segmenting the individual sounds. Used with permission from Microsoft.

Figure 3. Sample of an Elkonin Box featuring the word “fan.” The picture of the word eases the memory load for students as they concentrate on segmenting the individual sounds. Used with permission from Microsoft.

A scientifically based study by Bradley and Bryant (1983) featured an activity that teaches phonological awareness and remains popular today. The activity is sorting or categorizing pictures by either rhyme or initial sound (Bradley & Bryant, 1983). As shown in Figure 2, sets of cards are shown to children that feature pictures of words that rhyme or have the same initial sound. Typically one picture does not match the others in the group, and the students must decide which the “odd” one is. For instance, pictures of a fan, can, man, and pig are identified to be sure the students know what they are. The teacher slowly pronounces each word to make sure the students clearly hear the sounds and has them point to the word that does not rhyme (match the others). This is often referred to as an “oddity task,” and it can also be done with pictures featuring the same initial sound as in key, clock, cat, and scissors (see Blachman, Ball, Black, & Tangel, 2000 for reproducible examples).

Evidence-based activities to promote phoneme awareness typically have students segment spoken words into phonemes or have them blend phonemes together to create words. In fact, the NRP (2000) identified segmenting and blending activities as the most effective when teaching phoneme awareness. This makes sense, considering that segmenting and blending are the very acts performed when spelling (segmenting a word into its individual sounds) and reading (blending letter sounds together to create a word). The NRP noted that if segmenting and blending activities eventually incorporate the use of letters, thereby allowing students to make the connection between sounds in spoken words and their corresponding letters, there is even greater benefit to reading and spelling. Making connections between sounds and their corresponding letters is the beginning of phonics instruction, which will be described in more detail below.

An activity that incorporates both segmenting and blending was first developed by a Russian psychologist named Elkonin (1963), and thus, it is often referred to as “Elkonin Boxes.” Children are shown a picture representing a three- or four-phoneme picture (such as “fan” or “lamp”) and told to move a chip for each phoneme into a series of boxes below the picture. For example, if the word is “fan,” they would say /fffff/ while moving a chip into the first box, then say /aaaaa/ while moving a chip into the second box, and so on. Both Elkonin boxes (see Figure 3) and a similar activity called “Say It and Move It” are used in the published phonological awareness training manual, Road to the Code by Blachman et al. (2000). In each activity children must listen to a word and move a corresponding chip to indicate the segmented sounds they hear, and they must also blend the sounds together to say the entire word.

Decoding

Another critical component for word recognition is the ability to decode words. When teaching children to accurately decode words, they must understand the alphabetic principle and know letter-sound correspondences. When students make the connection that letters signify the sounds that we say, they are said to understand the purpose of the alphabetic code, or the “alphabetic principle.” Letter-sound correspondences are known when students can provide the correct sound for letters and letter combinations. Students can then be taught to decode, which means to blend the letter sounds together to read words. Decoding is a deliberate act in which readers must “consciously and deliberately apply their knowledge of the mapping system to produce a plausible pronunciation of a word they do not instantly recognize” (Beck & Juel, 1995, p. 9). Once a word is accurately decoded a few times, it is likely to become recognized without conscious deliberation, leading to efficient word recognition.

The instructional practices teachers use to teach students how letters (e.g., i, r, x) and letter clusters (e.g., sh, oa, igh) correspond to the sounds of speech in English is called phonics (not to be confused with phoneme awareness). For example, a teacher may provide a phonics lesson on how “p” and “h” combine to make /f/ in “phone,” and “graph.” After all, the alphabet is a code that symbolizes speech sounds, and once students are taught which sound(s) each of the symbols (letters) represents, they can successfully decode written words, or “crack the code.”

Why decoding is important

Similar to phonological awareness, neither understanding the alphabetic principle nor knowledge of letter-sound correspondences come naturally. Some children are able to gain insights about the connections between speech and print on their own just from exposure and rich literacy experiences, while many others require instruction. Such instruction results in dramatic improvement in word recognition (Boyer & Ehri, 2011). Students who understand the alphabetic principle and have been taught letter-sound correspondences, through the use of phonological awareness and letter-sound instruction, are well-prepared to begin decoding simple words such as “cat” and “big” accurately and independently. These students will have high initial accuracy in decoding, which in itself is important since it increases the likelihood that children will willingly engage in reading, and as a result, word recognition will progress. Also, providing students effective instruction in letter-sound correspondences and how to use those correspondences to decode is important because the resulting benefits to word recognition lead to benefits in reading comprehension (Brady, 2011).

Decoding instruction

Teaching children letter-sound correspondences and how to decode may seem remarkably simple and straightforward. Yet teaching them well enough and early enough so that children can begin to read and comprehend books independently is influenced by the kind of instruction that is provided. There are many programs and methods available for teaching students to decode, but extensive evidence exists that instruction that is both systematic and explicit is more effective than instruction that is not (Brady, 2011; NRP, 2000).

As mentioned previously, systematic instruction features a logical sequence of letters and letter combinations beginning with those that are the most common and useful, and ending with those that are less so. For example, knowing the letter “s” is more useful in reading and spelling than knowing “j” because it appears in more words. Explicit instruction is direct; the teacher is straightforward in pointing out the connections between letters and sounds and how to use them to decode words and does not leave it to the students to figure out the connections on their own from texts. The notable findings of the NRP (2000) regarding systematic and explicit phonics instruction include that its influence on reading is most substantial when it is introduced in kindergarten and first grade, it is effective in both preventing and remediating reading difficulties, it is effective in improving both the ability to decode words as well as reading comprehension in younger children, and it is helpful to children from all socioeconomic levels. It is worth noting here that effective phonics instruction in the early grades is important so that difficulties with decoding do not persist for students in later grades. When this happens, it is often noticeable when students in middle school or high school struggle to decode unfamiliar, multisyllabic words.

When providing instruction in letter-sound correspondences, we should avoid presenting them in alphabetical order. Instead, it is more effective to begin with high utility letters such as “a, m, t, i, s, d, r, f, o, g, l” so that students can begin to decode dozens of words featuring these common letters (e.g., mat, fit, rag, lot). Another reason to avoid teaching letter-sound correspondences in alphabetical order is to prevent letter-sound confusion. Letter confusion occurs in similarly shaped letters (e.g., b/d, p/q, g/p) because in day-to-day life, changing the direction or orientation of an object such as a purse or a vacuum does not change its identity—it remains a purse or a vacuum. Some children do not understand that for certain letters, their position in space can change their identity. It may take a while for children to understand that changing the direction of letter b will make it into letter d, and that these symbols are not only called different things but also have different sounds. Until students gain experience with print—both reading and writing—confusions are typical and are not due to “seeing letters backward.” Nor are confusions a “sign” of dyslexia, which is a type of reading problem that causes difficulty with reading and spelling words (International Dyslexia Association, 2015). Students with dyslexia may reverse letters more often when they read or spell because they have fewer experiences with print—not because they see letters backward. To reduce the likelihood of confusion, teach the /d/ sound for “d” to the point that the students know it consistently, before introducing letter “b.”

To introduce the alphabetic principle, the Elkonin Boxes or “Say It and Move It” activities described above can be adapted to include letters on some of the chips. For example, the letter “n” can be printed on a chip and when students are directed to segment the words “nut,” “man,” or “snap,” they can move the “n” chip to represent which sound (e.g., the first, second, or last) is /n/. As letter-sound correspondences are taught, children should begin to decode by blending them together to form real words (Blachman & Tangel, 2008).

For many students, blending letter sounds together is difficult. Some may experience letter-by-letter distortion when sounding out words one letter at a time. For example, they may read “mat” as muh-a-tuh, adding the “uh” sound to the end of consonant sounds. To prevent this, letter sounds should be taught in such a way to make sure the student does not add the “uh” sound (e.g., “m” should be learned as /mmmm/ not /muh/, “r” should be learned as /rrrr/ not /ruh/). To teach students how to blend letter sounds together to read words, it is helpful to model (see Blachman & Murray, 2012). Begin with two letter words such as “at.” Write the two letters of the word separated by a long line: a_______t. Point to the “a” and demonstrate stretching out the short /a/ sound—/aaaa/ as you move your finger to the “t” to smoothly connect the /a/ to the /t/. Repeat this a few times, decreasing the length of the line/time between the two sounds until you pronounce it together: /at/. Gradually move on to three letter words such as “sad” by teaching how to blend the initial consonant with the vowel sound (/sa/) then adding the final consonant. It is helpful at first to use continuous sounds in the initial position (e.g., /s/, /m/, /l/) because they can be stretched and held longer than a “stop consonant” (e.g., /b/, /t/, /g/).

An excellent activity featured in many scientifically-based research studies that teaches students to decode a word thoroughly and accurately by paying attention to all of the sounds in words rather than guessing based on the initial sounds is word building using a pocket chart with letter cards (see examples in Blachman & Tangel). Have students begin by building a word such as “pan” using letter cards p, a, and n. (These can be made using index cards cut into four 3″ x 1.25″ sections. It is helpful to draw attention to the vowels by making them red as they are often difficult to remember and easily confused). Next, have them change just one sound in “pan” to make a new word: “pat.” The sequence of words may continue with just one letter changing at a time: panpatratsatsitsiptiptaprap. The student will begin to understand that they must listen carefully to which sound has changed (which helps their phoneme awareness) and that all sounds in a word are important. As new phonics elements are taught, the letter sequences change accordingly. For example, a sequence featuring consonant blends and silent-e may look like this: slim—slime—slide—glide—glade—blade—blame—shame—sham. Many decoding programs that feature strategies based on scientifically-based research include word building and provide samples ranging from easy, beginning sequences to those that are more advanced (Beck & Beck, 2013; Blachman & Tangel, 2008).

A final important point to mention with regard to decoding is that teachers must consider what makes words (or texts) decodable in order to allow for adequate practice of new decoding skills. When letters in a word conform to common letter-sound correspondences, the word is decodable because it can be sounded out, as opposed to words containing “rule breaker” letters and sounds that are in words like “colonel” and “of.” The letter-sound correspondences and phonics elements that have been learned must be considered. For example, even though the letters in the word “shake” conform to common pronunciations, if a student has not yet learned the sound that “sh” makes, or the phonics rule for a long vowel when there is a silent “e,” this particular word is not decodable for that child. Teachers should refrain from giving children texts featuring “ship” or “shut” to practice decoding skills until they have been taught the sound of /sh/. Children who have only been taught the sounds of /s/ and /h/ may decode “shut” /s/ /h/ /u/ /t/, which would not lead to high initial accuracy and may lead to confusion.

Sight Word Recognition

The third critical component for successful word recognition is sight word recognition. A small percentage of words cannot be identified by deliberately sounding them out, yet they appear frequently in print. They are “exceptions” because some of their letters do not follow common letter-sound correspondences. Examples of such words are “once,” “put,” and “does.” (Notice that in the word “put,” however, that only the vowel makes an exception sound, unlike the sound it would make in similar words such as “gut,” “rut,” or “but.”) As a result of the irregularities, exception words must be memorized; sounding them out will not work.

Since these exception words must often be memorized as a visual unit (i.e., by sight), they are frequently called “sight words,” and this leads to confusion among teachers. This is because words that occur frequently in print, even those that are decodable (e.g., “in,” “will,” and “can”), are also often called “sight words.” Of course it is important for these decodable, highly frequent words to be learned early (preferably by attending to their sounds rather than just by memorization), right along with the others that are not decodable because they appear so frequently in the texts that will be read. For the purposes of this chapter, sight words are familiar, high frequency words that must be memorized because they have irregular spellings and cannot be perfectly decoded.

Why sight word recognition is important

One third of beginning readers’ texts are mostly comprised of familiar, high frequency words such as “the” and “of,” and almost half of the words in print are comprised of the 100 most common words (Fry, Kress, & Fountoukidis, 2000). It is no wonder that these words need to be learned to the point of automaticity so that smooth, fluent word recognition and reading can take place.

Interestingly, skilled readers who decode well tend to become skilled sight word “recognizers,” meaning that they learn irregular sight words more readily than those who decode with difficulty (Gough & Walsh, 1991). This reason is because as they begin learning to read, they are taught to be aware of phonemes, they learn letter-sound correspondences, and they put it all together to begin decoding while practicing reading books. While reading a lot of books, they are repeatedly exposed to irregularly spelled, highly frequent sight words, and as a result of this repetition, they learn sight words to automaticity. Therefore, irregularly spelled sight words can be learned from wide, independent reading of books. However, children who struggle learning to decode do not spend a lot of time practicing reading books, and therefore, do not encounter irregularly spelled sight words as often. These students will need more deliberate instruction and additional practice opportunities.

Sight word recognition instruction

Teachers should notice that the majority of letters in many irregularly spelled words do in fact follow regular sound-symbol pronunciations (e.g., in the word “from” only the “o” is irregular), and as a result attending to the letters and sounds can often lead to correct pronunciation. That is why it is still helpful to teach students to notice all letters in words to anchor them in memory, rather than to encourage “guess reading” or “looking at the first letter,” which are both highly unreliable strategies as anyone who has worked with young readers will attest. Interestingly, Tunmer and Chapman (2002) discovered that beginning readers who read unknown words by “sounding them out” outperformed children who employed strategies such as guessing, looking at the pictures, rereading the sentence on measures of word reading and reading comprehension, at the end of their first year in school and at the middle of their third year in school.

Other than developing sight word recognition from wide, independent reading of books or from exposure on classroom word walls, instruction in learning sight words is similar to instruction used to learn letter-sound correspondences. Sources of irregularly spelled sight words can vary. For instance, they can be preselected from the text that will be used for that day’s reading instruction. Lists of irregularly spelled sight words can be found in reading programs or on the Internet (search for Fry lists or Dolch lists). When using such lists, determine which words are irregularly spelled because they will also feature highly frequent words that can be decoded, such as “up,” and “got.” These do not necessarily need deliberate instructional time because the students will be able to read them using their knowledge of letters and sounds.

Regardless of the source, sight words can be practiced using flash cards or word lists, making sure to review those that have been previously taught to solidify deep learning. Gradual introduction of new words into the card piles or lists should include introduction such as pointing out features that may help learning and memorization (e.g., “where” and “there” both have a tall letter “h” which can be thought of as an arrow or road sign pointing to where or there). Sets of words that share patterns can be taught together (e.g., “would,” “could,” and “should”). Games such as Go Fish, Bingo, or Concentration featuring cards with these words can build repetition and exposure, and using peer-based learning, students can do speed drills with one another and record scores.

Any activity requiring the students to spell the words aloud is also helpful. I invented an activity that I call “Can You Match It?” in which peers work together to practice a handful of sight words. An envelope or flap is taped across the top of a small dry erase board. One student chooses a card, tells the partner what the word is, and then places the card inside the envelope or flap so that it is not visible. The student with the dry erase board writes the word on the section of board that is not covered by the envelope, then opens the envelope to see if their spelling matches the word on the card. The ultimate goal in all of these activities is to provide a lot of repetition and practice so that highly frequent, irregularly spelled sight words become words students can recognize with just a glance.

Word Recognition Summary

As seen in the above section, in order for students to achieve automatic and effortless word recognition, three important underlying elements—phonological awareness, letter-sound correspondences for decoding, and sight recognition of irregularly spelled familiar words—must be taught to the point that they too are automatic. Word recognition, the act of seeing a word and recognizing its pronunciation without conscious effort, is one of the two critical components in the Simple View of Reading that must be achieved to enable successful reading comprehension. The other component is language comprehension, which will be discussed in Chapter 4. Both interact to form the skilled process that is reading comprehension. Because they are so crucial to reading, reading comprehension is likened to a two-lock box, with both “key” components needed to open it (Davis, 2006).

The two essential components in the Simple View of Reading, automatic word recognition and strategic language comprehension, contribute to the ultimate goal of teaching reading: skilled reading comprehension. According to Garnett (2011), fluent execution of the underlying elements as discussed in this chapter involves “teaching…accompanied by supported and properly framed interactive practice” (p. 311). When word recognition becomes effortless and automatic, conscious effort is no longer needed to read the words, and instead it can be devoted to comprehension of the text. Accuracy and effortlessness, or fluency, in reading words serves to clear the way for successful reading comprehension.

It is easy to see how success in the three elements that lead to automatic word recognition are prerequisite to reading comprehension. Learning to decode and to automatically read irregularly spelled sight words can prevent the development of reading problems. Students who are successful in developing effortless word recognition have an easier time reading, and this serves as a motivator to young readers, who then proceed to read a lot. Students who struggle with word recognition find reading laborious, and this serves as a barrier to young readers, who then may be offered fewer opportunities to read connected text or avoid reading as much as possible because it is difficult. Stanovich (1986) calls this disparity the “Matthew Effects” of reading, where the rich get richer—good readers read more and become even better readers and poor readers lose out. Stanovich (1986) also points out an astonishing quote from Nagy and Anderson (1984, p. 328): “the least motivated children in the middle grades might read 100,000 words a year while the average children at this level might read 1,000,000. The figure for the voracious middle grade reader might be 10,000,000 or even as high as 50,000,000.” Imagine the differences in word and world knowledge that result from reading 100,000 words a year versus millions! As teachers, it is worthwhile to keep these numbers in mind to remind us of the importance of employing evidence-based instructional practices to ensure that all students learn phoneme awareness, decoding, and sight word recognition—the elements necessary for learning how to succeed in word recognition.

Summary

In order for students to comprehend text while reading, it is vital that they be able to read the words on the page. Teachers who are aware of the importance of the essential, fundamental elements which lead to successful word recognition—phonological awareness, decoding, and sight recognition of irregular words—are apt to make sure to teach their students each of these so that their word reading becomes automatic, accurate, and effortless. Today’s teachers are fortunate to have available to them a well-established bank of research and instructional activities that they can access in order to facilitate word recognition in their classrooms.

The Simple View of Reading’s two essential components, automatic word recognition and strategic language comprehension, combine to allow for skilled reading comprehension. Students who can both recognize the words on the page and understand the language of the words and sentences are much more likely to enjoy the resulting advantage of comprehending the meaning of the texts that they read.

Questions and Activities

  1. List the two main components of the simple view of reading, and explain their importance in developing reading comprehension.
  2. Explain the underlying elements of word recognition. How does each contribute to successful reading comprehension?
  3. Discuss instructional activities that are helpful for teaching phonological awareness, decoding, and sight recognition of irregularly spelled, highly frequent words.
  4. View the following video showing a student named Nathan who has difficulty with word recognition: https://www.youtube.com/watch?v=lpx7yoBUnKk (Rsogren, 2008). Which of the underlying elements of word recognition (e.g., phonological awareness, letter-sound correspondences, decoding) do you believe may be at the root of this student’s difficulties? How might you develop a new instructional plan to address these difficulties?

References

Adams, M. J., Foorman, B. R., Lundberg, I., & Beeler, T. (1998). The elusive phoneme: Why phonemic awareness is so important and how to help children develop it. American Educator, 22, 18-29. Retrieved from http://literacyconnects.org/img/2013/03/the-elusive-phoneme.pdf

Beck, I. L., & Beck, M. E. (2013). Making sense of phonics: The hows and whys (2nd ed.). New York, NY: Guilford Press.

Beck, I. L., & Juel, C. (1995). The role of decoding in learning to read. American Educator, 19, 8-25. Retrieved from http://www.scholastic.com/Dodea/Module_2/resources/dodea_m2_pa_roledecod.pdf

Blachman, B. A., Ball, E. W., Black, R., & Tangel, D. M. (2000). Road to the code: A phonological awareness program for young children. Baltimore, MD: Paul H. Brookes Publishing Co.

Blachman, B. A., & Murray, M. S. (2012). Teaching tutorial: Decoding instruction. Charlottesville, VA: Division for Learning Disabilities. Retrieved from http://teachingld.org/tutorials

Blachman, B. A., & Tangel, D. M. (2008). Road to reading: A program for preventing and remediating reading difficulties. Baltimore: Brookes Publishing.

Boyer, N., & Ehri, L. (2011). Contribution of phonemic segmentation instruction with letters and articulation pictures to word reading and spelling in beginners. Scientific Studies of Reading, 15, 440-470. doi:10.1080/10888438.2010.520778

Bradley, L., & Bryant, P. E. (1983). Categorizing sounds and learning to read: A causal connection. Nature, 303, 419-421. doi:10.1038/301419a0

Brady, S. (2011). Efficacy of phonics teaching for reading outcomes: Indicators from post-NRP research. In S. A. Brady, D. Braze, & C. A. Fowler (Eds.), Explaining individual differences in reading: Theory and evidence (pp. 69–96). New York, NY: Psychology Press.

Byrne, J. P. (2012). Encyclopedia of the Black Death. Santa Barbara, CA: ABC-CLIO.

Davis, M. (2006). Reading instruction: The two keys. Charlottesville, VA: Core Knowledge Foundation.

Dehaene, S. (2009). Reading in the brain. New York, NY: Penguin Books.

Elkonin, D. B. (1963). The psychology of mastering the elements of reading. In B. Simon & J. Simon (Eds.), Educational psychology in the U.S.S.R. (pp. 165-179). London, England: Routledge & Kegan Paul.

Fry, E., Kress, J., & Fountoukidis, D. (2000). The reading teacher’s book of lists (4th ed.). Paramus, NJ: Prentice-Hall.

Garnett, K. (2011). Fluency in learning to read: Conceptions, misconceptions, learning disabilities, and instructional moves. In J. R. Birsh (Ed.), Multisensory teaching of basic language skills (p. 293-320). Baltimore, MD: Brookes Publishing.

Goodman, K. (1967). Reading: A psycholinguistic guessing game. Journal of the Reading Specialist, 6, 126-135. doi:10.1080/19388076709556976

Gough, P. B., & Tunmer, W. E. (1986). Decoding, reading, and reading disability. Remedial and Special Education, 7, 6-10. doi:10.1177/074193258600700104

Gough, P. B., & Walsh, M. (1991). Chinese, Phoenicians, and the orthographic cipher of English. In S. Brady & D. Shankweiler (Eds.), Phonological processes in literacy (pp. 199-209). Hillsdale, NJ: Erlbaum.

International Dyslexia Association. (2015). Definition of dyslexia. Retrieved from http://eida.org/definition-of-dyslexia/

International Reading Association. (1998). Phonemic awareness and the teaching of reading: A position statement from the board of directors of the International Reading Association. Retrieved from http://www.reading.org/Libraries/position-statements-and-resolutions/ps1025_phonemic.pdf

Nagy, W., & Anderson, R. C. (1984). How many words are there in printed school English? Reading Research Quarterly, 19, 304-330. doi:10.2307/747823

National Institute of Child Health and Human Development. (2000). Report of the National Reading Panel: Teaching children to read: An evidence-based assessment of the scientific research literature on reading and its implications for reading instruction: Reports of the subgroups. (NIH Publication No. 00-4754). Washington, DC: U.S. Government Printing Office. Retrieved from http://www.nichd.nih.gov/publications/pubs/nrp/documents/report.pdf

Rayner, K., Foorman, B. R., Perfetti, C. A., Pesetsky, D., & Seidenberg, M. S. (2001). How psychological science informs the teaching of reading. Psychological Science in the Public Interest, 2, 31-74.

Scarborough, H. S. (2002). Connecting early language and literacy to later reading (dis)abilities: Evidence, theory, and practice. In S. B. Neuman & D. K. Dickinson (Eds.), Handbook of early literacy research (pp. 97-110). New York, NY: Guilford Press.

Snow, C. E. (Chair). (2002). Reading for understanding: Toward an R & D program in reading comprehension. Santa Monica, CA: Rand. Retrieved from http://www.prgs.edu/content/dam/rand/pubs/monograph_reports/2005/MR1465.pdf

Snow, C. E., Burns, M. S., & Griffin, P. (Eds.). (1998). Preventing reading difficulties in young children. Washington, DC: National Academy Press.

Rsogren, N. (2008, June 13). Misunderstood minds chapter 2 [Video file]. Available from https://www.youtube.com/watch?v=lpx7yoBUnKk

Stanovich, K. E. (1986). Matthew effects in reading: Some consequences of individual differences in the acquisition of literacy. Reading Research Quarterly, 21, 360–407. doi:10.1598/RRQ.21.4.1

Tunmer, W. E., & Chapman, J. W. (2002). The relation of beginning readers’ reported word identification strategies to reading achievement, reading-related skills, and academic self-perceptions. Reading and Writing: An Interdisciplinary Journal, 15, 341-358. doi:10.1023/A:1015219229515

Worsley, L. (2011). If walls could talk: An intimate history of the home. New York, NY: Bloomsbury.

Endnotes

1: For detailed information on scientifically-based research in education, see Chapter 2 by Munger in this volume. Return

From Wikipedia, the free encyclopedia

Word recognition, according to Literacy Information and Communication System (LINCS) is «the ability of a reader to recognize written words correctly and virtually effortlessly». It is sometimes referred to as «isolated word recognition» because it involves a reader’s ability to recognize words individually from a list without needing similar words for contextual help.[1] LINCS continues to say that «rapid and effortless word recognition is the main component of fluent reading» and explains that these skills can be improved by «practic[ing] with flashcards, lists, and word grids».

In her 1990 review of the science of learning to read, psychologist Marilyn Jager Adams wrote that «the single immutable and nonoptional fact about skilful reading is that it involves relatively complete processing of the individual letters of print.»[2] The article «The Science of Word Recognition» says that «evidence from the last 20 years of work in cognitive psychology indicates that we use the letters within a word to recognize a word». Over time, other theories have been put forth proposing the mechanisms by which words are recognized in isolation, yet with both speed and accuracy.[3] These theories focus more on the significance of individual letters and letter-shape recognition (ex. serial letter recognition and parallel letter recognition). Other factors such as saccadic eye movements and the linear relationship between letters also affect the way we recognize words.[4]

An article in ScienceDaily suggests that «early word recognition is key to lifelong reading skills».[5] There are different ways to develop these skills. For example, creating flash cards for words that appear at a high frequency is considered a tool for overcoming dyslexia.[6] It has been argued that prosody, the patterns of rhythm and sound used in poetry, can improve word recognition.[7]

Word recognition is a manner of reading based upon the immediate perception of what word a familiar grouping of letters represents. This process exists in opposition to phonetics and word analysis, as a different method of recognizing and verbalizing visual language (i.e. reading).[8] Word recognition functions primarily on automaticity. On the other hand, phonetics and word analysis rely on the basis of cognitively applying learned grammatical rules for the blending of letters, sounds, graphemes, and morphemes.

Word recognition is measured as a matter of speed, such that a word with a high level of recognition is read faster than a novel one.[3] This manner of testing suggests that comprehension of the meaning of the words being read is not required, but rather the ability to recognize them in a way that allows proper pronunciation. Therefore, context is unimportant, and word recognition is often assessed with words presented in isolation in formats such as flash cards[8] Nevertheless, ease in word recognition, as in fluency, enables proficiency that fosters comprehension of the text being read.[9]

The intrinsic value of word recognition may be obvious due to the prevalence of literacy in modern society. However, its role may be less conspicuous in the areas of literacy learning, second-language learning, and developmental delays in reading. As word recognition is better understood, more reliable and efficient forms of teaching may be discovered for both children and adult learners of first-language literacy. Such information may also benefit second-language learners with acquisition of novel words and letter characters.[10] Furthermore, a better understanding of the processes involved in word recognition may enable more specific treatments for individuals with reading disabilities.

Theories[edit]

Bouma shape[edit]

Bouma shape, named after the Dutch vision researcher Herman Bouma, refers to the overall outline, or shape, of a word.[11] Herman Bouma discussed the role of «global word shape» in his word recognition experiment conducted in 1973.[12] Theories of bouma shape became popular in word recognition, suggesting people recognize words from the shape the letters make in a group relative to each other.[3] This contrasts the idea that letters are read individually. Instead, via prior exposure, people become familiar with outlines, and thereby recognize them the next time they are presented with the same word, or bouma.

The slower pace with which people read words written entirely in upper-case, or with alternating upper- and lower-case letters, supports the bouma theory.[3] The theory holds that a novel bouma shape created by changing the lower-case letters to upper-case hinders a person’s recall ability. James Cattell also supported this theory through his study, which gave evidence for an effect he called word superiority. This referred to the improved ability of people to deduce letters if the letters were presented within a word, rather than a mix of random letters. Furthermore, multiple studies have demonstrated that readers are less likely to notice misspelled words with a similar bouma shape than misspelled words with a different bouma shape.

Though these effects have been consistently replicated, many of their findings have been contested. Some have suggested that the reading ability of upper-case words is due to the amount of practice a person has with them. People who practice become faster at reading upper-case words, countering the importance of the bouma. Additionally, the word superiority effect might result from familiarity with phonetic combinations of letters, rather than the outlines of words, according to psychologists James McClelland and James Johnson.[13]

Parallel recognition vs. serial recognition[edit]

Parallel letter recognition is the most widely accepted model of word recognition by psychologists today.[3] In this model, all letters within a group are perceived simultaneously for word recognition. In contrast, the serial recognition model proposes that letters are recognized individually, one by one, before being integrated for word recognition. It predicts that single letters are identified faster and more accurately than many letters together, as in a word. However, this model was rejected because it cannot explain the word superiority effect, which states that readers can identify letters more quickly and accurately in the context of a word rather than in isolation.

Neural networks[edit]

A more modern approach to word recognition has been based on recent research on neuron functioning.[3] The visual aspects of a word, such as horizontal and vertical lines or curves, are thought to activate word-recognizing receptors. From those receptors, neural signals are sent to either excite or inhibit connections to other words in a person’s memory. The words with characters that match the visual representation of the observed word receive excitatory signals. As the mind further processes the appearance of the word, inhibitory signals simultaneously reduce activation to words in one’s memory with a dissimilar appearance. This neural strengthening of connections to relevant letters and words, as well as the simultaneous weakening of associations with irrelevant ones, eventually activates the correct word as part of word recognition in the neural network.

Physiological background[edit]

The brain[edit]

Using positron emission tomography (PET) scans and event-related potentials, researchers have located two separate areas in the fusiform gyrus that respond specifically to strings of letters. The posterior fusiform gyrus responds to words and non-words, regardless of their semantic context.[14] The anterior fusiform gyrus is affected by the semantic context, and whether letter combinations are words or pseudowords (novel letter combinations that mimic phonetic conventions, ex. shing). This role of the anterior fusiform gyrus may correlate to higher processing of the word’s concept and meaning. Both these regions are distinct from areas that respond to other types of complex stimuli, such as faces or colored patterns, and are part of a functionally specialized ventral pathway. Within 100 milliseconds (ms) of fixating on a word, an area of the left inferotemporal cortex processes its surface structure. Semantic information begins to be processed after 150 ms and shows widely distributed cortical network activation. After 200 ms, the integration of the different kinds of information occurs.[15]

The accuracy with which readers recognize words depends on the area of the retina that is stimulated.[16] Reading in English selectively trains specific regions of the left hemiretina for processing this type of visual information, making this part of the visual field optimal for word recognition. As words drift from this optimal area, word recognition accuracy declines. Because of this training, effective neural organization develops in the corresponding left cerebral hemisphere.[16]

Saccadic eye movements and fixations[edit]

Eyes make brief, unnoticeable movements called saccades approximately three to four times per second.[17] Saccades are separated by fixations, which are moments when the eyes are not moving. During saccades, visual sensitivity is diminished, which is called saccadic suppression. This ensures that the majority of the intake of visual information occurs during fixations. Lexical processing does, however, continue during saccades. The timing and accuracy of word recognition relies on where in the word the eye is currently fixating. Recognition is fastest and most accurate when fixating in the middle of the word. This is due to a decrease in visual acuity that results as letters are situated farther from the fixated location and become harder to see.[18]

Frequency effects[edit]

The word frequency effect suggests that words that appear the most in printed language are easier to recognize than words that appear less frequently.[19] Recognition of these words is faster and more accurate than other words. The word frequency effect is one of the most robust and most commonly reported effects in contemporary literature on word recognition. It has played a role in the development of many theories, such as the bouma shape. Furthermore, the neighborhood frequency effect states that word recognition is slower and less accurate when the target has an orthographic neighbor that is higher in frequency than itself. Orthographic neighbors are words of all the same length that differ by only one letter of that word.[19]

Real world applications[edit]

Inter-letter spacing[edit]

Serif fonts, i.e.: fonts with small appendages at the end of strokes, hinder lexical access. Word recognition is quicker with sans-serif fonts by an average of 8 ms.[20] These fonts have significantly more inter-letter spacing, and studies have shown that responses to words with increased inter-letter spacing were faster, regardless of word frequency and length.[21] This demonstrates an inverse relationship between fixation duration and small increases in inter-letter spacing,[22] most likely due to a reduction in lateral inhibition in the neural network.[20] When letters are farther apart, it is more likely that individuals will focus their fixations at the beginning of words, whereas default letter spacing on word processing software encourages fixation at the center of words.[22]

Tools and measurements[edit]

Both PET and functional magnetic resonance imaging (fMRI) are used to study the activation of various parts of the brain while participants perform reading-based tasks.[23] However, magnetoencephalography (MEG) and electroencephalography (EEG) provide a more accurate temporal measurement by recording event-related potentials each millisecond. Though identifying where the electrical responses occur can be easier with an MEG, an EEG is a more pervasive form of research in word recognition. Event-related potentials help measure both the strength and the latency of brain activity in certain areas during readings. Furthermore, by combining the usefulness of the event-related potentials with eye movement monitoring, researchers are able to correlate fixations during readings with word recognition in the brain in real-time. Since saccades and fixations are indicative of word recognition, electrooculography (EOG) is used to measure eye movements and the amount of time required for lexical access to target words. This has been demonstrated by studies in which longer, less common words induce longer fixations, and smaller, less important words may not be fixated on at all while reading a sentence.

Learning[edit]

According to the LINCS website, the role of word recognition results in differences between the habits of adults and the habits of children learning how to read.[8] For non-literate adults learning to read, many rely more on word recognition than on phonics and word analysis. Poor readers with prior knowledge concerning the target words can recognize words and make fewer errors than poor readers with no prior knowledge.[24] Instead of blending sounds of individual letters, adult learners are more likely to recognize words automatically.[8] However, this can lead to errors when a similarly spelled, yet different word, is mistaken for one the reader is familiar with. Errors such as these are considered to be due to the learner’s experiences and exposure. Younger and newer learners tend to focus more on the implications from the text and rely less on background knowledge or experience. Poor readers with prior knowledge utilize the semantic aspects of the word, whereas proficient readers rely on only graphic information for word recognition.[24] However, practice and improved proficiency tend to lead to a more efficient use of combining reading ability and background knowledge for effective word recognition.[8]

The role of the frequency effect has been greatly incorporated into the learning process.[8] While the word analysis approach is extremely beneficial, many words defy regular grammatical structures and are more easily incorporated into the lexical memory by automatic word recognition. To facilitate this, many educational experts highlight the importance of repetition in word exposure. This utilizes the frequency effect by increasing the reader’s familiarity with the target word, and thereby improving both future speed and accuracy in reading. This repetition can be in the form of flash cards, word-tracing, reading aloud, picturing the word, and other forms of practice that improve the association of the visual text with word recall.[25]

Role of technology[edit]

Improvements in technology have greatly contributed to advances in the understanding and research in word recognition. New word recognition capabilities have made computer-based learning programs more effective and reliable.[8] Improved technology has enabled eye-tracking, which monitors individuals’ saccadic eye movements while they read. This has furthered understanding of how certain patterns of eye movement increases word recognition and processing. Furthermore, changes can be simultaneously made to text just outside the reader’s area of focus without the reader being made aware. This has provided more information on where the eye focuses when an individual is reading and where the boundaries of attention lie.

With this additional information, researchers have proposed new models of word recognition that can be programmed into computers. As a result, computers can now mimic how a human would perceive and react to language and novel words.[8] This technology has advanced to the point where models of literacy learning can be digitally demonstrated. For example, a computer can now mimic a child’s learning progress and induce general language rules when exposed to a list of words with only a limited number of explanations. Nevertheless, as no universal model has yet been agreed upon, the generalizability of word recognition models and its simulations may be limited.[26]

Despite this lack of consensus regarding parameters in simulation designs, any progress in the area of word recognition is helpful to future research regarding which learning styles may be most successful in classrooms. Correlations also exist between reading ability, spoken language development, and learning disabilities. Therefore, advances in any one of these areas may assist understanding in inter-related subjects.[27] Ultimately, the development of word recognition may facilitate the breakthrough between «learning to read» and «reading to learn».[28]

References[edit]

  1. ^ «Assessment Strategies and Reading Profiles».
  2. ^ Adams, Marilyn Jager (1990). Beginning to read : thinking and learning about print. Cambridge: MIT Press. p. 105. ISBN 978-0-262-51076-9.
  3. ^ a b c d e f (Larsen, 2004)
  4. ^ «The Science of Word Recognition». Microsoft.
  5. ^ «Early Word Recognition Is Key To Lifelong Reading Skills Says New Study». www.sciencedaily.com. Retrieved 2017-01-09.
  6. ^ «Flash Card Word Recognition Skills for Dyslexia».
  7. ^ ftp://128.46.154.21/harper/muri/Chen_PDSR_SP04.pdf
  8. ^ a b c d e f g h (Kruidenier, 2002)
  9. ^ (Luckner & Urbach, 2012)
  10. ^ (Everson, 2011)
  11. ^ (Ranum, 1998)
  12. ^ (Bouma & Bouwhuis, 1979)
  13. ^ (McClelland & Johnston, 1977)
  14. ^ (Nobre, Truett & McCarthy, 1994)
  15. ^ (Hauk, Davis, Ford, Pulvermuller & Marslen-Wilson, 2006)
  16. ^ a b (Mishkin, Mortimer, Forgays & Donald, 1952)
  17. ^ (Irwin, 1998)
  18. ^ (Nazir, Heller & Sussman, 1992
  19. ^ a b (Grainger, 1990)
  20. ^ a b (Moret-Tatay & Perea, 2011)
  21. ^ (Pereaa, Moret-Tataya & Gomezc, 2011)
  22. ^ a b (Perea & Gomez 2012)
  23. ^ (Sereno & Rayner, 2003)
  24. ^ a b (Priebe, Keenan & Miller, 2010)
  25. ^ (Literacy Information and Communication System)
  26. ^ (Davis & Mermelstein, 1980)
  27. ^ (Scarborough, 2009)
  28. ^ (Campbell, Kelly, Mullis, Martin & Sainsbury, 2001, p.6)

Citations[edit]

  • Bouma, H., & Bouwhuis, D. (1979). Visual word recognition of three-letter words as derived from the recognition of the constituent letters» Perception & Psychophysics 25(1), 12-22. Retrieved from http://alexandria.tue.nl/repository/freearticles/734512.pdf
  • Campbell, J. R., Kelly, D. L., Mullis, I. V. S., Martin, M. O., & Sainsbury, M. (2001). Framework and specifications for pirls assessment 2001 . (2nd ed., p. 6). Chestnut Hill, MA, USA: International Study Center, Lynch School of Education, Boston College. Retrieved from http://timssandpirls.bc.edu/pirls2001i/pdf/PIRLS_frame2.pdf
  • Davis, S. B.; Mermelstein, P. (1980). «Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences». IEEE Transactions on Acoustics, Speech, and Signal Processing. 28 (4): 357–366. CiteSeerX 10.1.1.462.5073. doi:10.1109/tassp.1980.1163420.
  • Everson, M. E. (2011). «Word recognition among learners of Chinese as a foreign language: Investigating the relationship between naming and knowing». The Modern Language Journal. 82 (2): 194–204. doi:10.1111/j.1540-4781.1998.tb01192.x.
  • Grainger, J (1990). «Word frequency and neighborhood frequency effects in lexical decision and naming» (PDF). Journal of Memory and Language. 29 (2): 228–244. doi:10.1016/0749-596x(90)90074-a.
  • Hauk, O.; Davis, M. H.; Ford, M.; Pulvermuller, F.; Marslen-Wilson, W. D. (2006). «The time course of visual word recognition as revealed by linear regression analysis of erp data» (PDF). NeuroImage. 30 (4): 1383–1400. doi:10.1016/j.neuroimage.2005.11.048. PMID 16460964. S2CID 17367093.
  • Irwin, D (1998). «Lexical processing during saccadic eye movements». Cognitive Psychology. 36 (1): 1–27. doi:10.1006/cogp.1998.0682. PMID 9679075. S2CID 25066325.
  • Kruidenier, K. (2002). Research-based principles for adult basic education reading instruction (Contract no. ED-01-PO-1037). Retrieved from National Institute for Literacy website: http://lincs.ed.gov/publications/pdf/adult_ed_02.pdf
  • Larsen, K. (2004, July). The science of word recognition. Advanced Reading Technology, Microsoft Corporation, Retrieved from http://www.microsoft.com/typography/ctfonts/wordrecognition.aspx
  • Literacy Information and Communication System. (n.d.). Print skills (alphabetics). Retrieved from http://lincs.ed.gov/readingprofiles/MC_Word_Recognition.htm
  • Luckner, J. L.; Urbach, J. (2012). «Reading fluency and students who are deaf or hard of hearing: Synthesis of the research». Communication Disorders Quarterly. 33 (4): 230–241. doi:10.1177/1525740111412582. S2CID 145617612.
  • McClelland, J. L.; Johnston, J. C. (1977). «The role of familiar units in perception of words and nonwords» (PDF). Perception & Psychophysics. 22 (3): 249–261. doi:10.3758/bf03199687. S2CID 144497014.
  • Mishkin, Mortimer; Forgays; Donald (1952). «Word recognition as a function or retinal locus». Journal of Experimental Psychology. 43 (1): 43–48. doi:10.1037/h0061361. PMID 14907990.
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Word Recognition

J. Zevin, in Encyclopedia of Neuroscience, 2009

Summary

Behavioral research has established a number of key phenomena in word recognition: Many factors that influence the efficiency of computing meaning from sound – and both meaning and sound from text – have been discovered. Sophisticated computational models have provided mechanistic explanations for these findings while, largely in parallel, research in cognitive neuroscience and neuropsychology has revealed gross aspects of the neuroanatomy of word recognition and has begun to explore finer-grained detail of how these processes are accomplished in the brain. Although serious controversies remain, these multiple different avenues of research together have provided important insights about the word recognition and about many broader issues in the study of cognition.

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Word Recognition, Cognitive Psychology of

M.A. Moreno, G.C. van Orden, in International Encyclopedia of the Social & Behavioral Sciences, 2001

Word recognition refers to a component process of language. Word recognition transforms written and spoken forms of words into linguistic representations. Historically, word recognition also referred to lexical decision performance. In lexical decision, participants judge whether individually presented letter-strings actually spell words (with respect to a target language). Linear statistical methods were applied to ‘word’ response time data to isolate component effects and thereby individuate word recognition. Component effects would be revealed in additive interactions among factors that affect ‘word’ response times. But empirical evidence has not resolved the nature of word recognition. The effort is frustrated by ubiquitous, nonadditive, interactions among word factors. Recurrent connectionist models are conducive to nonadditive interactions. Recurrent connectionist models are nonlinear dynamical systems in which each component interacts directly or indirectly with every other component. Because the models are nonlinear, small changes in parameters that control the interaction may induce large or qualitative changes (nonadditive interactions) in the performance of a model. Consequently, empirical tests of nonlinear dynamical systems focus on the stability of the interaction among system components (not component effects). Conventional methods are inadequate for this task. Advances in nonlinear modeling await advances in methodology before cognitive experiments may adequately test recurrent connectionist models.

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Assessment in Schools – Oracy

A.L. Bailey, in International Encyclopedia of Education (Third Edition), 2010

Lexical skills

Word recognition, a receptive skill, and word use, an expressive skill, are key components of oral-language development and proficiency. A student’s lexicon, or store of known words can be measured it terms of its breadth and depth. Breadth of word knowledge is the number of different words known, whereas depth includes semantic connections between words. Lexical skills also include student knowledge of derivational morphology (e.g., the variety of affixes that can be added to known words to create additional words with different parts of speech, such as chemic‘al’ (adjective) and chemist‘ry’ (noun)).

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Reading Interventions

Laurice M. Joseph, in Encyclopedia of Applied Psychology, 2004

4 Whole Word Interventions

Whole word recognition or “look–say” approaches are effective especially for teaching words with irregular sound and spelling patterns. In look–say approaches, children practice reading words as a whole until they achieve fluency and the words become a part of their sight vocabularies. For instance, words that are printed on index cards can be read as a whole within a specified time period. Research has shown that whole word methods may produce immediate word recognition achievement effects, whereas phonic approaches may produce more long-term generalized effects, especially when students encounter words unknown to them.

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Handwriting Recognition, Automatic

S. Srihari, in Encyclopedia of Language & Linguistics (Second Edition), 2006

Word Recognition

A word recognition algorithm attempts to associate the word image to choices in a lexicon. Typically, a ranking is produced. This is done either by the analytic approach of recognizing the individual characters or by the holistic approach of dealing with the entire word image. The latter approach is useful in the case of touching printed characters and handwriting. A higher level of performance is observed by combining the results of both approaches. There exist several different approaches to word recognition using a limited vocabulary.

Analytic word recognition based on determining presegmentation points followed by determining an optimal path through a state transition diagram is shown in Figure 4. In the holistic approach, the word image is represented by a fixed size vector, for example by imposing a fixed grid on the word image (Figure 5). Other holistic features are the upper and lower profiles of word images, which are represented as a series of vectors describing the global contour of the word image and bypass the segmentation phase. Word recognition involves preprocessing, a possible segmentation phase that could be avoided if global word features are used, recognition, and postprocessing. Performance of the methods is a function of the size of the lexicon.

Figure 4. Analytic word recognition: (A) word with presegmentation points shown and (B) corresponding state transition diagram.

Figure 5. Holistic word recognition: a word is represented in an 8 × 4 grid and a feature vector is extracted.

When dealing with large lexicon sizes, performance can be improved by using a dynamic lexicon. For example, the lexicon is represented as a tree and the results of recognizing the first few characters are used to eliminate possible paths in the tree. In another method, word images are oversegmented such that after segmentation no adjacent characters remain touching. Instead of passing on combinations of segments to a generic recognizer, a lexicon is brought into play early in the process. A combination of adjacent segments is compared to only those character choices that are possible at the position in the word being considered. The approach can be viewed as a process of accounting for all the segments generated by a given lexicon entry. Lexicon entries are ordered according to the goodness of match. Dynamic programming is used to string the potential character candidates into word candidates, combine heuristics to disqualify certain groups of primitive segments from being evaluated if they are too complex to represent a single character, and take into account compatibility between consecutive character candidates.

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Language and Communication in Non-Alzheimer’s Dementias

Monique M. Cherrier, … D. Frank Benson, in Handbook of Neurolinguistics, 1998

31-1.3.4 Reading and Writing

Subtle word recognition deficits may occur in VaD patients (Kontiola et al., 1990), and prominent alexia can occur with lesions in the left angular gyrus. Kertesz and Clydesdale (1994) found that VaD patients had more dysgraphia than AD patients. The VaD group had greater difficulty writing letters presented individually in dictation, had significantly poorer copying of words in sentences, and obtained little benefit from the opportunity to copy previously dictated material. These language and speech findings likely reflect focal neurological motor signs found in VaD patients along with heterogeneity of these signs resulting in contradictory results between studies.

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Computational Models of Normal and Impaired Language in the Brain

Anthony E. Harris, Steven L. Small, in Handbook of Neurolinguistics, 1998

23-3.1 Feedforward Architecture

To model word recognition and naming, Seidenberg and McClelland (1989) constructed a parallel distributed processing model of the mechanisms by which orthographic representations are mapped to phonological ones. The model provides putative mechanisms for the two major aspects of acquisition of word-recognition skills. The first aspect that must be learned is spelling/sound correspondences, or the systematic correspondences between the written and spoken forms of language. The second aspect concerns the distribution of letter patterns in the lexicon, or the distribution of permissible letter combinations making up the written words in the language. One key feature of each of these aspects of word recognition is their inconsistency. The spelling/sound correspondences are not always followed, and the cues as to phonological, syllabic, and semantic information contained in the orthographic representations are not always reliable. Such a system is termed quasi-regular, where the relations among entities are statistical rather than categorical. Hence, connectionist models, which can encode statistical relations between representational units in its connection strengths, are particularly appropriate for investigating the word-recognition domain.

Several supervised learning models have examined issues of abnormal development and effects of brain damage on normal adults (Brown, in press). In one example, Small et al. (1995) presented a model accounting for category-specific naming deficits without assuming explicit categorical knowledge in the brain. Category-specific losses of semantic memory generally arise after temporal lobe damage (Hart & Gordon, 1992), and have involved selective loss of categories such as concrete objects, inanimate objects, animate objects, animals, and fruits and vegetables (Hart, Berndt, & Caramazza, 1985; Hart & Gordon, 1992; Sartori & Job, 1988; Warrington, 1981a; Warrington & McCarthy, 1983; Warrington & Shallice, 1984a). In normals, processing of superordinate categorical information can be slower than for object-level information (Collins & Quillian, 1969). A common account of these findings is that categorical information is explicitly encoded in the brain, with the agnosias corresponding to loss of this information. However, cortical imaging studies and direct cortical stimulation studies have met with difficulty in finding explicit, localized categorical information (Gordon et al., 1990; Ojemann, Ojemann, Lettich, & Berger, 1989; Small, Noll, Perfetti, Xu, & Schneider, 1994). The authors presented an alternative formulation, in which distributed categorical information was coded implicitly in featural information. A feedforward backprop net was trained to match input feature vectors with objects on its outputs. After training, the input feature space and the emergent hidden unit representations were analyzed. They found that the input feature vectors implicitly contained categorical information, due to the statistical structure found in natural clustering of features. In addition, using principal components analysis on the hidden unit representations, it was found that many of the higher principal components encoded for intuitive categories. The result of the study was to demonstrate that categorical information could exist in a distributed fashion without explicit encoding, in contrast to standard information processing accounts.

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The Neuroscience of Reading

U. Goswami, in International Encyclopedia of Education (Third Edition), 2010

Developmental Differences in the Time Course of Neural Activation

If basic word-recognition processes are delayed in developmental dyslexia, this will delay access to semantics and, therefore, affect reading comprehension. Similarly, cognitive processes such as grapheme–phoneme conversion might take longer in developmental dyslexia. EEG and MSI technologies can help us to study these questions.

One of very few longitudinal neuroimaging studies of children learning to read used MSI to gain information about developmental differences in the time course of neural activation. Simos and his colleagues studied 33 English-speaking children – 16 of whom were thought to be at high risk of developing dyslexia. The researchers compared brain activation in a letter-sound task (the child saw a letter and had to provide its sound) and a simple nonword-reading task (recoding nonwords like ‘lan’ to sound). Both tasks were administered at the end of kindergarten and again at the end of the first grade (see Simos et al., 2005). In kindergarten, the high-risk group were significantly slower to show neural activity in response to both letters and nonwords in the occipitotemporal region (requiring, on average, 320 ms compared to 210 ms for those not at risk). The high-risk group also showed atypical activation in the left inferior frontal gyrus when performing the letter-sound task. For this task, the onset of activity actually increased developmentally – from 603 ms in kindergarten to 786 ms in the first grade. The typically developing readers did not show a processing-time increase.

When Simos and his colleagues compared the onset of activity of the three core neural networks for reading, they found that low-risk children showed early activity in the left occipitotemporal regions. This was followed by activity in the temporoparietal regions, predominantly in the left hemisphere, and then by bilateral activity in the inferior frontal regions. In contrast, high-risk children showed little differentiation in terms of the time course of activation between the occipitotemporal and temporoparietal regions. High-risk children who were also nonresponsive to a phonological remediation package being administered during the study (N = 3) were distinct in showing earlier onset of activity in the inferior frontal gyrus compared to the temporoparietal regions. Simos and colleagues commented that the increased inferior frontal activation probably reflected the role of compensatory articulatory processes. This may indicate that children with phonological difficulties rely more heavily on networks for articulation when phonological processing is required.

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Juggling Two Languages in One Mind

Judith F. Kroll, … Jorge R. Valdes Kroff, in Psychology of Learning and Motivation, 2012

2.1.1 Bilingual Word Recognition

Studies of bilingual word recognition have asked whether words or lexical features associated with the language not in use are activated when recognizing a word in one language alone out of context (e.g., Dijkstra, 2005; Kroll et al., 2006). The research strategy has been to exploit the presence of similar features in each language to determine whether the two languages can be processed independently in a selective manner. Many languages contain translation equivalents that are cognates, with similar orthography and/or phonology in both languages (e.g., in Dutch and English, the word hotel is spelled identically and pronounced similarly although the phonology is almost never precisely the same). But the same languages often also include words that are false friends or interlexical homographs, with similar orthography and/or phonology but different meanings (e.g., the word room appears in both Dutch and English but means cream in Dutch). Both cognates and homographs are at least momentarily ambiguous with respect to language membership when presented out of context, so it is possible to compare word-recognition performance for these special words relative to words that unambiguously belong to one language or the other. The results of a now impressive number of studies show that bilinguals process language-ambiguous words differently than language-unambiguous words and that monolinguals are insensitive to these differences. The monolingual comparison is critical to rule out the contribution of correlated lexical features that might otherwise differentiate the two types of words.

To illustrate, when bilinguals perform a visual lexical decision task in which they have to decide whether a letter string is a real word, they are faster when the letter string is a cognate translation than an unambiguous control word (e.g., Dijkstra, Van Jaarsveld, & Ten Brinke, 1998). When the letter string is an interlexical homograph, bilinguals are typically slower relative to control words but response speed and accuracy also depends on the mix of conditions (e.g., De Groot, Delmaar, & Lupker, 2000; Von Studnitz & Green, 2002). The data for both the processing of cognates and interlingual homographs suggest that the bilingual is activating information about the other language. For cognates, the convergence of lexical form and meaning produces facilitation. For homographs, there is interference generated by the conflict in meaning across the two languages unless the task can exploit the presence of cross-language tokens (e.g., see Dijkstra et al., 1998, Experiment 3). The difference across these conditions is not only apparent in behavioral data but also in electrophysiological studies that map out the early time course of these processes in the brain (e.g., Midgley, Holcomb, & Grainger, 2009) and in fMRI studies that identify brain activity (e.g., Van Heuven, Schriefers, Dijkstra, & Hagoort, 2008).

One might wonder whether the lexical decision task or other binary decision tasks which do not require the phonology of the word to be specified, encourage the engagement of the language not in use. But similar results are obtained when the task is changed to simple word naming, where there is generally facilitation for cognates and interference for interlexical homographs (e.g., Jared & Szucs, 2002; Schwartz, Kroll, & Diaz, 2007). In word naming, the phonology of the target language must be specified to enable the bilingual to produce the word in the intended language but the results are largely the same as those for lexical decision. Likewise, one might ask whether the activation of the language not in use only occurs when the bilingual is recognizing words in the L2. For all but the most proficient and balanced bilinguals, the processing of L2 is typically slower than the processing of L1, so perhaps it is not surprising to see effects of the more dominant and skilled L1 on the less dominant and slower L2. Although it is easier to find effects of the L1 on the L2 than the reverse, there is solid evidence that once individuals are relatively proficient in the L2, there are similar effects of the L2 on the L1, even in experiments in which the bilingual is unaware of the relevance of L2 and in which the L2 is not explicitly engaged (e.g., Van Hell & Dijkstra, 2002; Van Wijnendaele & Brysbaert, 2002).

Perhaps the most surprising result of all is that the parallel activation of the bilingual’s two languages is not eliminated when language-ambiguous words are placed in sentence context (e.g., Duyck, Van Assche, Drieghe, & Hartsuiker 2007; Libben & Titone, 2009; Schwartz & Kroll, 2006; Van Hell & De Groot, 2008). One might think that the out-of-context nature of word-recognition paradigms would increase cross-language ambiguity in the absence of syntactic, semantic, or pragmatic information that might otherwise bias lexical access towards the target language. To the contrary, the evidence on word recognition in sentence context shows that it is very difficult to eliminate the parallel activation of the two languages even in the presence of multiple cues to the language in use. Most of the experiments that have investigated this issue have examined cognate effects. The question is whether the cognate facilitation typically observed in out-of-context word recognition is reduced or eliminated in sentence context. The finding is that the cognate effect disappears only when the sentence context is highly constrained semantically (e.g., Schwartz & Kroll, 2006; Van Hell & De Groot, 2008; but see Van Assche, Dreighe, Duyck, Welvaert, & Hartsuiker, 2011). In low-constraint sentence contexts, the cognate effects are as robust as in the out-of-context word-recognition studies. What is notable is that in these low-constraint sentences, the language of the sentence is blocked so that the bilingual is fully engaged in processing in one language alone. Furthermore, like the earlier results on out-of-context word recognition, there is evidence that the activation of both languages can be seen even when the sentence is processed in the more dominant L1 (e.g., Van Assche, Duyck, Hartsuiker, & Diependaele, 2009). The results suggest that bilinguals are not able to easily exploit the language of the sentence context to selectively process the target language.

The parallel activation of the two languages appears to be a feature of the system itself rather than a consequence of particular experimental conditions. Cross-language interactions are observed both within and outside of sentence context and for both the L1 and the L2. Additional support for the idea that the high level of interaction between the bilingual’s two languages reflects the design of the system rather than a strategy imposed by experimental conditions comes from studies that have examined these issues in bilinguals for whom there is less obvious cross-language ambiguity. Languages such as Dutch and English share the same writing system and the opportunity for ambiguity is high when a word is presented in print. But many languages differ in the form of their lexical representation and again, in theory, these differences might be expected to function as cues to allow bilinguals to separate their two languages more easily. Studies on cross-script bilinguals who speak Chinese and English or Hebrew and English show the same sort of interactions that have been reported for same-script bilinguals (e.g., Gollan, Forster, & Frost, 1997; Jiang, 1999; Thierry & Wu, 2007; Wu & Thierry, 2010). Because the orthographic representation of a word’s written form is not shared, the cross-script results suggest that the activation of overlapping phonology may be sufficient to engage the language not in use. But a recent study of deaf readers who are bilingual in American Sign Language (ASL) and written English (Morford et al., 2011) shows that when they read in English alone, the translations of the ASL signs are activated. In this context, there is neither orthographic nor phonological overlap across the two languages. The finding that ASL is active when deaf readers process written English suggests that cross-language interactions are a common feature when more than one language is used and although structural differences across languages may modulate the form of possible transfer, they do not determine its presence or absence.

The studies we have reviewed show that there is parallel activation of the bilingual’s two languages even under circumstances that, in theory, should allow processing to be restricted selectively to one language alone. The examples we discussed were drawn from the literature on visual word recognition. It is beyond the scope of this chapter to review this work in greater detail but we note that evidence for language nonselectivity has also been reported for spoken word recognition in and out of sentence context (e.g., Chambers & Cooke, 2009; Marian & Spivey, 2003). There is a suggestion in the research on spoken recognition that it may be possible to more easily enable selective access when listening to speech than when reading printed text (e.g., Ju & Luce, 2004; Weber & Cutler, 2004), but the majority of studies suggest the same sort of cross-language interactions observed in the visual domain. A recent paper by Lagrou, Hartsuiker, and Duyck (2011) shows that even when words are spoken in accented speech that should provide a cue to the listener, there is evidence for nonselective access.

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Word Recognition, Written

D. Balota, M. Yap, in Encyclopedia of Language & Linguistics (Second Edition), 2006

Word Recognition: the Future

The study of visual word recognition will continue to be a vital area of research in experimental psychology and psycholinguistics, with a number of important challenges. For example, we believe that future models will take into consideration the manner in which attention and task constraints influence the lexical processing system. As one can see from the models described above, most models assume a relatively passive lexical system that responds to stimulus input. However, a more comprehensive model will most likely include an attentional system that modulates the weights on specific pathways depending upon the goals of a given task. In addition, there will be some constraints provided from the in vivo studies of the human brain while it is engaged in lexical processing, via neuroimaging techniques. As noted above, multiple models may be able to accommodate the same set of findings. It is likely that understanding patterns of neural activity in circumscribed brain areas will provide an important next step in this literature (e.g., Binder et al., 2003).

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For people who have been reading and writing for years, it’s unthinkable to imagine a time when they could not recognize letters or words. However, as children learn to read they must begin to connect the symbols they see on the page with the letters they have heard and spoken.

One of the key aspects of teaching reading is teaching word recognition, both by sight and sound. There are a number of strategies that teachers can employ to get students to recognize words.

What Is Word Recognition in Reading?

When a reader with years of experience reads a page, he doesn’t stop and read every word and wonder what it means. What experienced readers do that allows them to read quickly and efficiently is called word recognition.

The more fluent a reader is in word recognition, the easier it will be for him or her to comprehend complex text and challenging abstract concepts. On the contrary, slow word recognition means constant reading and analysis of words and sentences. When readers struggle with word recognition, their memory and their comprehension skills are quickly drained from spending so much time on analysis.

Learning Word Recognition

The best way to gain word recognition is repeated and consistent exposure to the same words over and over. This is simple for avid readers, but it is something critical for children who are just beginning to read or who are given the opportunity to look at books regularly.

Despite the fact that the English language is vast and rich and contains a tremendous vocabulary, the fact is that only around 100 words comprise about 50 percent of the words that all people read in English each day.

This means that constant exposure to the words that most people need to read to navigate their lives is not difficult to orchestrate. These words are around and available. When a child begins to remember that the letters «a-n-d» spell the word «and,» she will immediately recognize it and move on to the next word. There is no more sounding out, no more analysis. Their word recognition propels them forward as they read.

How to Teach Contextual Word Recognition Activities

Understanding word recognition is simple. Being able to teach word recognition is hard. This is a particular challenge for teachers who have a classroom where students are at varying levels of experience and competence with the material. The most consistent and successful way for children to learn word recognition is to expose them over and over to text that contains these words, particularly text that is not especially challenging to comprehend.

The more children are exposed to books with the same words in them, the sooner they will recognize the shape and size of a word rather than needing to read it.

Use More Clues

Context clues are when readers rely on the ancillary content of a sentence or a page to guess at what word might be suggested. In this way, the context can help the reader to anticipate the word. Another great way to help students recognize words is to provide syntactic clues or word order clues.

Often the structure of a sentence will help a student to guess whether the word that is next is a verb, a noun or an adjective. Outside the realm of words, pictures or illustrations can help to bridge a connection between the picture of the word and the spelling of the word. This association may be especially helpful for students who are highly visual. Contextual word recognition activities are among the most valuable.

What Are Some Good Word Recognition Strategies?

Science has shown that the human brain is hardwired for speech, but the same is not said of reading or writing. The facts of this are that the language, English, is an invention, as are all languages. This means that the brain must extend itself and create a new neural pathway that helps to translate the marks you are seeing on the paper and connect them to the sounds you use when you speak. This is a tremendous feat for the human brain.

When you look at things from this perspective, it makes sense that learning to read can be hard for some people. This is in part because when you write words, you break them down into smaller blocks called phonemes. These blocks are essentially the ‘atoms» of words. Unlike languages like Chinese, where a character can stand for a whole word or an entire syllable, the English language has an alphabet where words are broken down to individual sounds, and the sounds are rearranged.

This means that in order to read and write in the language, young readers must be able to identify and separate the different sounds in the words and recognize them as the symbols they see written out on the page. This means that teaching word recognition strategy will likely involve not only extensive reading on the part of the child but extensive speaking and mirroring the speech by associating it with the written word.

What Are Some Word Recognition Activities for Young Readers?

Begin by helping students sound out the words they are seeing. Whether or not they get the word quickly is not the issue. Having them work through each sound while looking at the word that is made up of those sounds creates a connection.

Once they have sounded out what the letters in «pat» do, they will be able to read that word. They will, with repetition, be able to understand when they see that word again that those sounds are made by those shapes.

Help the student identify the word «chunks.» This is especially useful with older readers who are working on understanding compound words. By sounding out the chunks and then putting them together, the student will start to be able to recognize and identify specific word «families.» This word recognition activity for middle schoolers will help them to identify words that they already know, and then put those words in context and see if they are able to make sense of the sentence.

Asking a student what a particular word looks like or reminds them of can often be a good jumping off point for identifying the word they are faced with. If there’s a letter in it that reminds them of another word, start there. See if making that letter sound and indicating which part of the word it shows up it helps to create a moment of recognition for the student.

What Are Word Recognition Strategies for Diverse Learning Levels?

As difficult as it is for the average student to learn how to read words with instant, automatic recognition, it is even more challenging for students with special needs. Kids with special needs who struggle to learn word recognition might see letters in reverse position and may mix up the sounds of letters that look similar, such as «d» and «b» or may struggle to place sound chunks together.

This is why it is important for teachers to have word recognition activities for preschoolers at the ready just in case there is a need to work on basic skills with students.

Phonological Awareness

Phonological awareness is one of the most critical aspects of true word recognition. Phonological awareness means being able to identify and be aware of sounds as they are found in different words and applying that phonetic knowledge when you encounter an unfamiliar word. Word recognition games around phonemes are popular and can be done as a parent or a teacher.

One example is asking children to identify the sounds at the beginning of several words that start with the same letter. Then ask the children to identify the sounds at the end of several words that end in the same letter. This will strengthen their understanding of these letters and their spoken counterparts. This will help them to recognize the letters as functioning entities next time that they encounter them.

What Is the Difference Between Word Recognition and Word Identification?

Word recognition describes the cognitive act of remembering or recognizing a familiar word that has been seen before. Word identification, on the other hand, is the process of decoding the meaning of the word through its phonetic sounds. In other words, sounding a word out. These are two methods by which students internalize new vocabulary words.

Even the most seasoned reader occasionally encounters a word that he or she has never seen before. In the case of an exceptionally long or oddly spelled word, the reader does not resort to word recognition. They have simply never seen this word before. The process that then takes over is called word identification. This means that the reader will slowly sound out the word, recognizing the phonemes he or she has seen before, and thus be able to read the word.

Reading comprehension is, of course, the ultimate goal. Both word recognition and word identifications are strategies and skills that when honed, can help increase overall comprehension. The more words a reader is able to instantly recognize and process, the faster he or she will be able to comprehend what is being read. This means that the occasions where a word needs to be sounded out, identified, processed and understood is far rarer. The result is that comprehension isn’t slowed down by constant reflection and analysis.

Word recognition activities are not designed simply to increase the vocabulary of the student. If this is a byproduct of word recognition that is wonderful, and it is part of the reason why avid readers have such large vocabularies. However, the goal of word recognition is the improvement of reading comprehension. Whether someone is reading the directions on a dangerous household chemical, or reading a bedtime story, the ability to immediately recognize and subconsciously process every word helps.

Fluency is achieved when a reader has sufficient word recognition to be able to comprehend everything he or she is reading. This means that the reader isn’t slowing down every third word to figure out what the word is, and thus forgetting what came before. This type of difficulty can lead to reading sentences over and over and over again with no clear comprehension. Increased recognition leads to increased speed and facility with language. This, in turn, leads to increased comprehension and ultimately, fluency.

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This article is an excerpt from the LD@school learning module Technology for All: Supporting Students with LDs by Integrating Technology into Classroom Instruction. Click here to access this module.

The act of reading simultaneously draws on many different processes: a reader must decode words, know what they mean, understand words when they are strung together in sentences, understand the use of pronouns, make connections between ideas using relationship markers, create mental pictures, make inferences, sum up information, and so forth.

The right technological tools can make a significant difference to students who struggle with word recognition as well as reading comprehension.

Word Recognition

The ability to read develops over many years. At the primary level, students learn word recognition, a skill that often poses a great challenge to students with LDs. Difficulties with word recognition, in turn, tend to cause problems with the other processes required for effective reading.

It is important to note, however, that difficulties with word recognition only affect processes related to written language. If a student with this challenge were to hear a story read to them, the processes required for comprehension of this verbal text would not be impaired.

There are many technological tools that can support students with difficulties in word recognition.

Click here to access the Reading Rockets webpage about their recommended literacy apps.

Reading Comprehension

Later on, comprehension becomes the key focus of reading instruction. Educators must support students in the following ways:

  • Provide students with a variety of reading material and media
  • Develop their understanding of literary devices
  • Model comprehension strategies

Primary students reading on a bench

The following sections present technological tools that support these reading goals.

Text-to-speech

Text-to-speech software can read aloud digital or printed text; this is beneficial as students are more likely to understand text when unfamiliar words are read to them (MacArthur, Ferreti, Okolo, & Cavalier, 2001). Text-to-speech can have a positive effect on: decoding and word recognition (Raskind & Higgins, 1999), reading fluency, and reading comprehension (Izzo, Yurick, & McArrell, 2009; Montali & Lewandowski, 1996; Stodden, Roberts, Takahishi, Park, & Stodden, 2012). Text-to-speech software can be especially helpful for students who retain more information through listening than reading. This software can assist students with monitoring and revising their typed work, as hearing the text read aloud may assist students in catching grammatical errors that may have otherwise gone unnoticed (Raskind & Higgins, 1995; Rao, Dowrick, Yuen, & Boisvert, 2009; Zhang, 2000). After reviewing the literature, Strangman and Dalton (2005) reported that the use of text-to-speech software can improve students’ sight reading and decoding abilities. In addition, text-to-speech software can improve the reading comprehension of individuals with specific deficits in phonological processing (difficulty hearing letter-sounds) as students can learn to decode new words when they are highlighted as they are read aloud (Fasting & Halaas Lyster, 2005; Holmes & Silvestri, 2009).

Examples of Text-to-Speech Software:

  • Read&Write (for Google Chrome, Windows PCs, iPad, Macs)
  • Balabolka
  • Kurzweil 3000 – firefly

Click here to access the handout When I use Text-to-Speech (PDF).

Digital Texts

Twenty-first century readers must be able to comprehend many different types of texts, such as comic strips, fairy tales, news, informational documents, and many more. Some texts are similar in digital and print forms, but others are available only through the use of technology. For example, tweeting and blogging are texts that now play a role in many of our daily lives.

Click here to access the article Tweeting and Blogging in the Classroom: Leveling the Playing Field for Students with Learning Disabilities.

Digital texts greatly facilitate the task of differentiating instruction. Students are able to use accessibility functions to customize their settings (font size, spacing, colour contrast, bolding, etc.), which frees up cognitive load for comprehension.

Furthermore, most digital texts include features that help students to better understand the texts. For example, many sites have a menu or table of contents that remains visible on the screen, which helps readers understand the structure and main ideas of the text.

Finally, hyperlinked text helps students compensate for a weak vocabulary and access further information on concepts for which they have little prior knowledge.

Visual Learning Software

Visual learning software, such as graphic organizers and mind maps, is another indispensable tool to develop students’ reading comprehension skills. It can be used to illustrate different text structures (narrative, descriptive, argumentative, etc.), and it helps students identify the most important elements of the text they are reading, as well as see an overview of the entire text.

In a different setting, when students “read to learn”, visual learning software helps to reduce the burden on working memory and to display the ideas in a different way to better draw connections between elements of the text by categorizing them or by linking supporting evidence to key concepts.

Click here to access the article All Students can Read to Learn Science!.

Educators can also model the use of visual learning software to demonstrate relationships among characters in a novel. These relationships, often implicit in novels, become explicit and visual when visual learning software is used, which helps students better understand these subtle connections as they read.

Explicit Instruction of Reading Strategies

Even when students use technology to compensate for an area of weakness, it is crucial that they be able to exercise their other reading skills in order to comprehend the text. Therefore, educators should explicitly teach reading strategies to all students.

Image of the PDF

Click here to access the PDF of the SQ3R reading comprehension strategy.

Reading is a difficult task that draws on many cognitive processes at once, but with access to individualized instructional strategies and assistive technology, students with learning disabilities can improve their skills in both word recognition and reading comprehension. Educators in the primary grades should focus on the improvement of word recognition, which may help to prevent future problems with the processes required for effective reading. In later grades, when comprehension becomes the key focus of reading, weak reading skills can be supplemented by assistive technology such as text-to-speech, digital texts, and visual learning software. Regardless of the intervention used, all students should be explicitly taught reading strategies that encourage them to utilize contextual cues, focus on metacognition, ask questions, make connections, and expand on what they have learned.

Additional Resources

Click here to access the answer to the question How can assistive technology be used in the classroom to support the acquisition of reading skills by students with LDs?.

Click here to access the resource Reading Rockets – Assistive Technology for Kids with Learning Disabilities: An Overview.

References:

Fasting, R. B., & Halaas Lyster, S. (2005). The effects of computer technology in assisting the development of literacy in young struggling readers and spellers. European Journal of Special Needs Education, 20(1), 21-40. doi:10.1080/0885625042000319061

Holmes, A., & Silvestri, R. (2009). Text-to-voice technology in adult aboriginal sample with reading difficulties: Examination of the efficacy. Toronto, ON: Aboriginal Office of the Ministry of Education and Ministry of Training, Colleges, and Universities.

Izzo, M., Yurick, A., & McArrell, B. (2009). Supported eText: Effects of text-to-speech on access and achievement for high school students with disabilities. Journal of Special Education Technology, 24, 9-20.

MacArthur, C. A., Ferretti, R. P., Okolo, C. M., & Cavalier, A. R. (2001). Technology applications for students with literacy problems: A critical review. The Elementary School Journal, 101(3), 273-301. doi:10.1086/499669

Montali, J., & Lewandowski, L.  J. (1996). Bimodal reading: Benefits of a talking computer for average and less skilled readers. Journal of Learning Disabilities, 29, 271-279. doi:10.1177/002221949602900305

Rao, K., Dowrick, P., Yuen, J., & Boisvert, P. (2009). Writing in a multimedia environment: Pilot outcomes for high school students in special education. Journal of Special Education Technology, 24, 27-38.

Raskind, M. & Higgins, E. (1995). Effects of speech synthesis on the proofreading efficiency of postsecondary students with learning disabilities, Learning Disability Quarterly, 18, 141-158. doi:10.2307/1511201

Raskind, M. & Higgins, E. (1999). Speaking to read: The effects of speech recognition technology on the reading and spelling performance of children with learning disabilities. Annals of Dyslexia, 49,  251-281. doi:10.1007/s11881-999-0026-9

Stodden, R. A., Roberts, K. D., Takahishi, K., Park, H. J., & Stodden, N. J. (2012). The use of text-to-speech software to improve reading skills of high school struggling readers. Procedia Computer Science, 14, 359-362. doi:10.1016/j.procs.2012.10.041

Strangman, N., & Dalton, B. (2005). Using technology to support struggling readers: A review of the research. In D. Edyburn, K. Higgins, & R. Boone (Eds.), Handbook of special education technology research and practice (pp. 325-334). Whitefish Bay, WI: Knowledge by Design, Inc.

Zhang, Y. (2000). Technology and the writing skills of students with learning disabilities. Journal of Research on Computing in Education, 32, 467-478.

Presentation on theme: «CHAPTER 5: Reading: Word Recognition»— Presentation transcript:

1

CHAPTER 5: Reading: Word Recognition
Strategies for Teaching Learners with Special Needs Tenth Edition Edward A. Polloway James R. Patton Loretta Serna Jenevie W. Bailey Developed by:

2

Literacy Development Stages
Emergent Pretends to read Identify some letters 5-20 high frequency words Beginning Match spoken words to written text Uses beginning, middle, and end sound to decode word Reads orally Fluent 100 words per minute high frequency words Reads with expression

3

Key Components of Reading
Vocabulary development Structural analysis Contextual analysis Fluency Comprehension Phonemic awareness Some students may present with problems in one or more of these areas.

4

Reading in the Curriculum
Decoding-Based Programs Skills-based “bottom-up,” part to whole Teach sound-symbol correspondence Focus on sequence of skills Holistic Approach Whole Language emphasis Whole to part Read “real” books and stories they write Print rich environment

5

Approaches to Reading Instruction
Students with disabilities often require intensive, direct instruction to learn to read. This intensive level of instruction is not provided in a classroom from a PURE whole language philosophy. Polloway, Patton, & Serna recommend using a balanced approach incorporating both decoding-based program and the holistic approach for students with disabilities.

6

Balanced Literacy Phonemic Awareness
Understanding the relationship between sounds and symbols Discriminate between words and sounds Identify sounds within words Manipulate the sounds in words Identify phonemes Isolate sounds

7

Balanced Literacy Word Recognition Vocabulary Teaching
Whole word recognition Think ‘sight words’ Vocabulary Teaching Word meanings are taught directly Comprehension Strategies Modeling Predicting, questioning, clarifying

8

Balanced Literacy Self Monitoring Extensive Reading
Teaching students to read and reread as necessary Extensive Reading Exposure, Exposure Exposure!

9

Reading Assessment Primary purpose: Instructional Planning
Classroom-Based Assessment Informal Reading Inventories Curriculum-Based Measurement Formal Instruments Achievement tests Reading tests Phonological awareness

10

Use of Assessment Data Inform instruction
Screening, eligibility, and diagnostics Monitoring of progress Analyzing student’s strengths and weaknesses Whole class profile

11

Formative Assessments
Informal Reading Inventories Independent Reading Level Instructional Level Frustration Level Curriculum-based Measurement Oral Reading Scoring System Checklist of Comprehension Skills Reading Assessment Summary Class Profile of Word Analysis Skills

12

Phonological Awareness
Definition: awareness of the phonological structure of words. Working toward automaticity Children with learning disabilities: must be taught explicitly, often an issue. Auditory segmenting (breaking words into component parts) Auditory blending (recombining words from smaller parts) Letter-sound correspondence

13

Phonetic Analysis Definition: a strategy for attacking unknown words by focusing on the letter-sound relationships and how to blend sounds into words, and to break words into sounds. Builds on phonological awareness Understanding of the alphabetic code Should be one part of a reading instruction program, not all of it.

14

Sight-Word Vocabulary
Sight-words: important, high-frequency words, some are phonetically irregular Working toward automaticity Children with learning disabilities: must be taught explicitly, often an issue. Fernald Method Repeated Readings Unison Readings Edmark Reading Program Teaching Phonetic Analysis Skills Vocabulary Instruction

15

Functional Reading A level of literacy necessary for information and protection Protection Level Teach as sight words Examples Danger Flammable Doctor No Trespassing Advanced Level: To fill out applications, pass a driver’s test, follow simple directions at work

16

Structural Analysis This group of skills enable students to use larger segments of words for decoding cues. Directly influences fluency Examples Syllabication Root words Compound words Prefixes/suffixes Contractions/ plurals

17

Contextual Analysis The identification of an unknown word based on its use in a sentence or passage. Uses contextual cues to guess or anticipate words as a strategy to support reading and comprehension Syntactic cues (structures) Semantic cues (meaning) May be problematic for older students Examples John had a little red (wagon): for younger students CRUSCH: for older students

18

Phonemic Awareness and Word-Recognition Curricular programs
Lindamood Program for Reading, Spelling, and Speech Phonological Awareness Training for Reading Reading Mastery Program Corrective Reading Program (CRP) Spalding Method Wilson Reading System Edmark Reading Program

19

Peer-Mediated Strategies
Useful in meeting student’s individual reading needs when students exhibit a variety of reading levels Helpful for many children, but not all To support comprehension Example PALS

20

Middle and Secondary Level
Problem areas Many not reading at grade level Less motivated Need instruction in both decoding and comprehension Decoding Myths for Older students

21

Middle and Secondary Level Word Identification
Identify/Decode unfamiliar words accurately, effortlessly, and rapidly Provide explicit, systematic instruction Word Identification skills Work identification strategy Overt word parts strategy Making long words Corrective Reading Program (CRP)

22

Lesson Plans Reading Standards: Foundational Skills (K–5) Know and apply grade-level phonics and word analysis skills in decoding words. a. Demonstrate basic knowledge of one-to-one letter-sound correspondences by producing the primary sound or many of the most frequent sounds for each consonant. b. Associate the long and short sounds with common spellings (graphemes) for the five major vowels. c. Read common high-frequency words by sight (e.g., the, of, to, you, she, my, is, are, do, does). d. Distinguish between similarly spelled words by identifying the sounds of the letters that differ.

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