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Word recognition is a manner of reading based upon 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 (ie. reading). Word recognition functions primarily on automaticity. Phonetics and word analysis, on the other hand, 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. 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 flashcards Nevertheless, ease in word recognition, as in fluency, enables the proficiency that fosters comprehension of the text being read.

The intrinsic value of word recognition may be obvious due to the prevalence of literacy in modern society. However, its role in the areas of literacy learning, second-language learning, and developmental delays in reading may be less conspicuous. 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. Furthermore, a better understanding of the processes involved in word recognition may enable more specific treatments for individuals with reading disabilities.

Several theories have been put forth proposing the mechanisms by which words are recognized in isolation, yet with both speed and accuracy. While these theories originally suggested a system that recognized words as whole units (ex. Bouma shape), over time, the theories became more focussed on the significance of individual letters and letter-shape recognition (ex. Serial letter recognition and parallel letter recognition).

Bouma Shape
Bouma shape, named after the Dutch psychologist Herman Bouma, refers to the overall outline, or shape, of a word. Herman Bouma discussed the role of “global word shape” in his word recognition experiment conducted in 1973. 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. 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 uppercase, or with alternating upper and lower case letters, supports the bouma theory. It was put forth that a novel bouma shape created by changing the lower-case letters to capitals 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 which letters had been shown to them if they were presented for a short period of time within a word, rather than a mix of random letters. Furthermore, multiple studies have demonstrated that misspelled words with similar bouma shape are less likely to be noticed than misspelled words that have a non-matching bouma shape.

Though these effects have been consistently replicated, many of the reasons for them have been contested. Some have suggested that the reduced reading of uppercase words is due to practice effects. People with practice become faster at reading uppercase words, and this counters the importance of the bouma. Also, the effect of word superiority might result from familiarity with phonetic combinations of letters, rather than the outline of the word, according to McClelland & Johnson.

Parallel processing vs. Serial processing
Currently, the most consensus on models of word recognition lies in the model of Parallel Letter Recognition. In this model, all letters within a group are perceived simultaneously and this information is used for word recognition. In contrast, the serial recognition model proposed that letters are recognized individually, one by one, before being integrated for word recognition. However, this model was rejected because it cannot explain the Word Superiority Effect, which states readers can identify letters more quickly and accurately in the context of a word rather than isolation. The serial recognition model would predict that single letters are identified faster and more accurately than many letters together, as with a word. In fact, according to this model, letters presented in a word would impede individual letter recognition because each letter is attended to one at a time, and in order.

Neural Networks of Word Recognition
A more modern approach to word recognition has been based on recent research on neuron function. The visual aspects of a word, such as horizontal and vertical lines or curves, are suspected 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. Those words with characters that match the visual representation of the word one is observing, receive excitatory signals. As the mind processes the appearance of the word further, 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 simultaneous weakening of associations with irrelevant ones, eventually activates the correct word as part of word recognition in the neural network.

Word Recognition and the Brain
Using PET scans and Event-Related Potentials, researchers have located two, separate areas in the fusiform gyrus that respond specifically to strings of letters. A region of the posterior fusiform gyrus responds to words and non-words, regardless of their semantic context. Conversely, the anterior fusiform gyrus is affected by the semantic context, and whether letter combinations are words or pseudowords (letter combinations that mimic phonetic conventions, in novel combinations. Ex. shing). This role of the anterior fusiform gyrus may correlate to higher processing of the word’s concept and meaning. Both of 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 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 200ms, the integration of different kinds of information occurs.

The accuracy with which words are recognized is dependent on the area of the retina receiving stimulation. Reading in English selectively trains specific regions of the left hemi-retina for processing of 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 is developed in the corresponding left cerebral hemisphere.

Saccadic Eye Movements, Fixations and Word Recognition
Eyes make brief, unnoticeable movements called saccades approximately three to four times per second. Saccades are separated by fixations, which are moments when the eyes are not moving. During saccades, visual sensitivity is diminished, which is termed 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.

Frequency Effects
The frequency effect suggests that words which appear the most in printed language are easier to recognize than words which appear less frequently. 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, and has played a role in the development of many theories such as the bouma shape.

The neighborhood frequency effect is that word recognition is poorer (ie, slower and less accurate) if the target has an orthographic neighbor that is higher in frequency than itself. Orthographic neighbors are words of all the same length that can be created by changing one letter of that word.

Interletter spacing
Serif fonts, ie: fonts with small appendages at the end of strokes, hinder lexical access. Word recognition is quicker on average by 8ms with Sans-Serif fonts. These fonts have significantly more interletter spacing, which is in line with studies in which responses to words with increased interletter spacing were faster, regardless of word frequency and length. This demonstrates an inverse relationship between fixation duration and small increases in interletter spacing. This is most likely due to a reduction in lateral inhibition in the neural network. 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 centre of words.

Tools and Measurements
Both positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) are used to study activation of various parts of the brain while participants perform reading-based tasks. However, magnetoencephalography (MEG) and electroencephalography (EEG) provide more accurate temporal measurement, by recording event related potentials each millisecond. Though identifying where the electrical responses occur can be easier with MEG, 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 event-related potentials with eye movement monitoring, researchers are able to correlate fixations during readings with word recognition in the brain during 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, or less common, words induce longer fixations, and smaller, less important words, may not be fixated on at all while reading a sentence.

Learning and Word Recognition
According to the Literacy Information and Communication System (LINCS) website, the role of word recognition results in differences between the habits of adults and children learning how to read. For non-literate adults learning to read, many rely more on word recognition than on phonics and word analysis. Poor readers with pre-existing knowledge concerning the target words can recognize words and make fewer errors than poor readers with no prior knowledge. Instead of blending sounds of individual letters, adult learners are more likely to recognize words automatically. 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. However, practice and improved proficiency tend to lead to a more efficient use of combining reading ability and background knowledge for effective word recognition.

The role of frequency effect has been greatly incorporated into the learning process. While the word analysis approach is extremely beneficial, many words defy regular grammatical structures, and are most easily incorporated into the lexical memory by automatic word recognition. To facilitate this, many educational sources 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 flashcards, word-tracing, reading aloud, picturing the word, and other forms of practice that improve the association of the visual text with word recall.

Role of Technology in Word Recognition
Improvements in technology have greatly contributed to advances in understanding and research in word recognition. New word recognition capabilities have made computer-based learning programs more effective and reliable. Improved technology has enabled eye-tracking, to monitor individuals’ saccadic eye movements while they read. This has furthered understanding of how certain patterns of eye movement increase word recognition and processing. Furthermore, changes can simultaneously be 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 focusses when an individual is reading, and where the boundaries of attention lie. With this additional information, researchers have proposed new models of word recognition, which can be programmed into computers. As a result, computers can now mimic how a human would perceive and react to language and novel words. 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 and 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.

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 efficacious 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. And ultimately, the development of word recognition may facilitate the breakthrough between “learning to read” and “reading to learn.”

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