Information/Cognitive Processing Perspectives: State of the Art (1989-Present)

1. Information/Cognitive Processing Perspectives: State of the Art (1989-Present) Chapter 7 Tracey and Morrow Pages 166-191 Morrow, L. M., & Tracey, D. H. (2006). Lenses on Reading: An Introduction to Theories and Models. New York, N.Y.: The Guilford Press.Content in this section directly cited from Lenses on Reading unless otherwise noted Benedictine University

2. Information/Cognitive Processing Perspectives: State of the Art In this section, you will examine: • Parallel Distributed Processing Model • Dual-Route Cascaded Model • Double-Deficit Hypothesis • Neuroscience and Education Benedictine University

3. PARALLEL DISTRIBUTED PROCESSING MODEL Benedictine University

4. Parallel Distributed Processing Model • This model is regularly updated: • The Plaut and McClelland (1993) version is currently the prominent version of Parallel Distributed Processing Model • Two central features of the Parallel Distributed Processing Model are: • All cognitive information is stored as a series of connectionsbetween units • These connections between units become stronger and faster with repeated pairings • Connectionism: The conceptualization of storing information in the brain as a series of connections of differing strength Benedictine University

5. Parallel Distributed Processing Model • Please note that a diagram of this model is located on page 165 in Lenses on Reading in Figure 9.1 • This model is a connectionisttheory of reading • Explained in great detail in Adams’ (1990) Beginning to Read, the model suggests that four primary processors are central to the reading process: • The Orthographic Processor • The Meaning Processor • The Context Processor • Phonological Processor Benedictine University

6. 1. The Orthographic Processor • The reading process begins in the orthographic processorwhere print recognition occurs • This processor: • Can be thought of as a storehouse of orthographic knowledge • Holds knowledge about lines, curves, angles, and space, all associated with the information needed for letter (and number) identification • In the case of letter identification, the connections between the units comprising any single letter become stronger with repeated exposure • For example, the association between the straight line and the small curve in the letter b become stronger with repeated exposure to the letter b • The same kind of process occurs for all letters and numbers Benedictine University

7. 1. The Orthographic Processor Cont. • As individuals repeat the practice of print… • They make stronger and faster connections between the separate units within letters and numbers (the lines, curves, angles, and space) • Eventually, they experience letter and number identification as automatic • The concept of Connectionism applies to the strength of: • The associations between letters within a word • The associations of lines, curves, angles, and space within a letter Benedictine University

8. 1. The Orthographic Processor Cont. • Connections between letters form when letter patterns frequently occur together in words: • For example, in the English language, the letter T is frequently followed by the letter Hand rarely followed by the letter Q • According to this model, as a result of the frequency of these two letter occurring together, the connection between the letters Tand H is much stronger and faster than the connection between the letters T and Q Benedictine University

9. Interletter Associational Unit System • This model suggests that, during the reading process, the orthographic processor uses the strength of the connections between letters to: • Activate lettersthat are likely to follow the initially identified letter • Suppress lettersthat are unlikely to follow the initially identified letters • This process, known as the “interletter associational unit system,” assists readers in gradually making more rapid word identification skills • Adams (1990) underscores a critical element of this system: • Letter recognition must be automatic for the system to operate • In its absence, readers are forced to read one letter at a time, greatly slowing the reading process and decreasing the likelihood of adequate comprehension QUIET SQUIRREL QUEEN Benedictine University

10. 2.The Meaning Processor • The meaning processor attaches the meaning (vocabulary) to words identified in the orthographic processor • This processor is the only processor in the model that both receives and delivers information to all of the other processors • As in the previous processor, the meanings of vocabulary words are organized according to connectionist principles • Any individual’s personal experiences determine which associations are made and the strength and speed of those associations • Example: “Let’s Go Swimming” A lake in the country A community pool Two Different Associations by the same person Benedictine University

11. 2. The Meaning ProcessHow Does This Relate To Schema? • This processor also functions to enable likely word meanings to be activated as unlikely word meanings are suppressed • The totality of a person’s knowledge of any topic is his or her schema • The strength and speed of the connections among the units within a schema, or between schemas, are connectionist in nature according to this model • The Parallel Distributed Processing Model suggests that, as individuals progress through life, they acquire an ever greater number of schemas that are organized within and between, by connectionist principles • These schemas are the sources of word meaning as readers engage in the reading process Benedictine University

12. 3. The Phonological Processor • The phonological processor is where the sounds associated with words are processed • In the English language, the smallest unit of sound is known as a phoneme • In this processor, each phoneme is considered a unit • As with the previous processors, the units within the phonological processor are linked according to the rules of Connectionism • i.e., sounds that frequently occur together have stronger and faster connections with each other than sounds that rarely occur together • Based on this construction of connections, this processor activates sounds that are likely to follow each other while suppressing sounds that are unlikely to be adjacent Benedictine University

13. 3. The Phonological Processor Cont. There are two additional benefits offered by this model: • It provides a redundancy system to the orthographic processor known as the alphabetic backup system • This aspect is activated when a person has an auditory familiarity with a word that has never been seen in printed form • In this case, the reader “sounds out” the word and uses the sounds of the word to aid in accessing word identification and meaning • It has a running memory capability • This feature provides an “inner voice” when one is reading, allowing words to be briefly held in working memory and be available for the further processing as they are read Benedictine University

14. 4. Context Processor • The context processor is where the reader constructs and monitors the meanings of phrases, sentences, paragraphs, and full texts during the reading process • When the reading experience is progressing smoothly, the outcome of the context processor is a coherent message to the reader • As with the other processors, the organization of this processor is connectionist in nature, with knowledge of the topic, language, and text all providing units of information for synthesis • Furthermore, like the other processors, the context processer both receives and delivers information to and from the meaning processor The dogs sat quietly. Sat dogs the quietly Benedictine University

15. The Parallel Distributed Processing Model: A Summary • According to this model, successful reading is dependent on a reader’s abilities in four areas: • Automatic Letter Recognition • Accurate Phonemic Processing • Strong Vocabulary Knowledge • The ability to construct meaningful messages during reading Benedictine University

16. The Parallel Distributed Processing Model: A Summary Cont. • The information within and between each of these processors is organized according to connectionist principles • The processors are all interactive and compensatory • This is consistent with work suggesting that when too much internal attention is used in lower level processing (orthographic, meaning, and phonological processors), comprehension in higher-level processing (the context processor) will suffer (LaBergeand Samuels, 1974) Benedictine University

17. In the ClassroomThe Parallel Distributed Processing Model This model suggests that reading is dependent on automatic letter recognition and that, unless letter identification is automatic, the interletter associational unit system will not initiate, greatly impairing reading fluency (Adams, 1990) • Classroom instruction that develops rapid letter identification is essential • Carnine, et al., (2004) offer four guidelines for effective letter instruction: • Initially introduce only the most common sounds associated with each letter • Teach separately letters that are highly similar in sound or print • Teach letters that are most frequent first • Teach lowercase letters before uppercase letters • These authors assert that the pace at which letters are taught should be determined by the students' success rates • Letter instruction should begin with an • Introductory phase based on modeling and student repetition Followed by a • Discriminatory phase in which students' knowledge of newly learned letters is tested against their knowledge of previously learned letters Benedictine University

18. In the ClassroomThe Parallel Distributed Processing Model • This model also indicates that helping students learn to read by using word families (frequent letter combinations such as the -ate family and the -in family) is highly effective because this approach reinforces connections between letters that frequently occur together (Adams, 1990) • There are a wide variety of activities based on word families: • Matching games • Sorting games • Activities that keep the word family ending and change the initial letter • For example, students can create small books containing words and pictures for each of the major and minor word families • When students are taught to read using word families, their knowledge of common letter patterns within words is strengthened Benedictine University

19. DUAL ROUTE CASCADED MODEL Benedictine University

20. Dual-Route Cascaded Model • This model is similar to The Parallel Distributed Processing Model in that both are computer-based models that encode text and output sound • The primary difference between the two models is in the way word identification is conceptualized to be handled by the computer architecture • In the Parallel Distributed Processing Model, all words and non-words are “read” by the computer in a single path that exists for turning print into sound • As described earlier, this path is based on a system in which the principles of Connectionism (connections are weighted according to frequency of pairings) govern relationships Benedictine University

21. Dual-Route Cascaded Model • In contrast, the Dual-Route Cascaded Model computer architecture has two routes for processing text input: • Lexical Route - A path for handling words that are already known to the reader/computer • Non-Lexical Route - A path for handling unknown words and non-words • The Lexical Route: • First, identifies a word as familiar • Second, it processes the words as a whole, immediately providing the reader/computer with the word’s correct meaning and pronunciation • In simple terms, this route can be thought of as a “whole word” or “sight word” approach to reading in which words are automatically recognized rather than broken down according to sound-symbol relationships Benedictine University

22. Dual-Route Cascaded Model • The Non-Lexical Route is based on a letter-to-sound rule procedure • This path is only used for words and letter strings that are unfamiliar to the reader • 144 Grapheme-Phoneme Correspondence Rules govern the computer architecture of the model • These rules are applied to incoming letter strings (words and non-words) as the computer “reads” • The degree to which the computer is able to correctly pronounce the letter strings that are presented is judged to be an indicator of the effectiveness of the model in representing human cognitive processing during reading Benedictine University

23. Dual-Route Cascaded ModelConclusions • This model argues that acquisitionandknowledge of rules is one feature that distinguishes better and poorer readers: • Better readershave a greater grasp of the rules that govern letter-sound relationships • While poorer readers have a weaker grasp of this information Benedictine University

24. Dual-Route Cascaded ModelConclusions • This model differs from the previous model because this approach uses two processing routes and a “rules based” system • The term “cascaded” refers to the speed with which levels of the model within the two routes are activated during the reading process • In this model, information is passed from one level to the next without waiting for full processing C-A-T FR BR D-O-G PH SHH-EEE M-O-M W-O-W Benedictine University

25. In The Classroom: Sight WordsDual-Route Cascaded Model • This model emphasizes the importance of automatic, sight-word recognition • In sight-word reading students do not sound out words • They look at them and pronounce them automatically. • High frequency words (those that occur with the greatest frequency in the English language) are often taught as sight words because there is a great payoff for the reader in knowing very common words • Additionally, high frequency words (e.g. the, this, through, and there) are often phonetically irregular and therefore well suited to sight-word instruction • Carnine, et al., suggest that sight-word instruction begin with lists and then progress to application in paragraphs Benedictine University

26. In The Classroom: Sight WordsDual-Route Cascaded Model Young readers need much practice in reading sight words in text: • Introductory lessons can start when students know four words • When students are able to read each word in 2 seconds or less, new sight words can be added to the list, although it is recommended that word lists do not exceed 15 words • When students can read ~15 sight words on a list at a pace of 2-3 seconds per word, paragraphs that are based on the sight words, combined with easily decodable words, should be provided for students • As they practice known sight words during text reading new sight words can be introduced and practiced in lists • Lists of high-frequency words, as well as other words ideal for teaching by sight, can be found in Fry and colleagues’ (2006) classic book, The Reading Teacher’s Book of Lists Benedictine University

27. DOUBLE-DEFICIT HYPOTHESIS Benedictine University

28. Double-Deficit Hypothesis • The Double-Deficit Hypothesis attempts to explain the cause of reading disabilities (Wolf and Bowers, 1999) • It argues that the Phonological-Core Variable Difference Model, in which a phonological deficit is viewed as the primary cause of reading disability, is incomplete • According to the Double-Deficit Hypothesis, many reading-disabled children also suffer from a deficit in rapid naming skill • Children with this deficit are less ableto rapidly name: • Colors when shown pictures of colored blocks • Objects when shown pictures of objects • Letters and numbers when shown strings of such print Benedictine University

29. Double-Deficit Hypothesis • According to researchers of this theory, reading-disabledchildren fall into one of three categories: • Children for whom phonological deficits are the core of their reading disability • Children for whom naming speed deficits are the core of their reading disability • Children for whom bothphonological deficits and naming speed deficits are problematic • The children who fall into the last category, those with a “double deficit” are also those whose reading impairment is most severe Benedictine University

30. Double-Deficit Hypothesis • Wolf and Bowers acknowledge that many researchers recognize that naming speed is a deficit among disabled readers: • However, they also note that others categorize the naming speed deficit as a subarea of the phonological deficit • In contrast, their Double-Deficit Hypothesisviews naming speed as a distinct and separate entity, uniquely contributing to reading failure • Those who believe in the Double-Deficit Hypothesis argue that educational interventions ideally matched to the different subtypes of disabled readers are needed Benedictine University

31. In The Classroom:RAVE-O ProgramDouble-Deficit Hypothesis • This theory suggests that there are two distinct areas of cognitive deficit in the most disabled dyslexic readers: • Phonological processing • Rapid naming • Wolf, et al.(2000), created and evaluated the RAVE-O Program (Retrieval, Automaticity, Vocabulary, Elaboration, Orthography) specifically to address the needs of readers believed to have double deficits in their cognitive processing • The program’s goal is to increase readers’ speeds in the areas of auditory processing, visual pattern recognition, word identification, and vocabulary Benedictine University

32. NEUROSCIENCE AND EDUCATION Benedictine University

33. Neuroscience and Education • Neuroscience studies cognition, but it is rooted in biology • It is concerned with the study of neurons and cells • Neuroscience is “…the processes by which the brain learns and remembers, from the molecular and cellular levels right through to the brain system” (Goswami, 2004) Benedictine University

34. Neuroscience and Education • The term “cognitive science” is theoretical in nature, and the term “neuroscience” is biological in nature • The term “cognitive neuroscience” refers to the study of higher patterns of brain functioning through brain imaging technology • Patterns of brain activity, which are believed to reflect mental states, mental representations, and learning, can be viewed while utilizing “neuroimaging” • This can be done through Positron Emission Tomography (PET), Functional Magnetic Resonance Imaging (fMRI), and Event-related Potentials (ERPs) Benedictine University

35. Neuroscience and Education • There are reports of several neuroscientific findings related to reading (Goswami, 2004) • For example, Goswami states that neuroimaging has confirmed earlier beliefs that the left side of the brain handles the primary systems involved in the reading process • Specifically, she summarizes work by Pugh, et al. (2001), who found that the occipital, temporal, and parietal areas are largely responsible for processing print Benedictine University

36. Neuroscientific Findings • As reading skill improves it is accompanied by increased activation in the temporal-occipital region of the brain (Shaywitzel al., 2002) • Additionally, children diagnosed with developmental dyslexia showed decreased activity in this region when compared with normally functioning peers • The temporal-parietal junction was to be central to phonological processing, letter-sound recoding, and spelling dysfunction (Simos, et al. (2002) Benedictine University

37. NEUROIMAGINGDYSLEXIC CHILDREN • Dyslexic children showed impaired neuroimaging performance compared to normally developing readers during a task related to rhyming (Simos, et al., 2002) • These authors also demonstrated that, following a remedial intervention, the dyslexic children’s neuroimaged performances improved • Neuroimaging of dyslexic children reveals atypical organization of the right side of the brain consistent with the development of compensation strategies (Heim, Eulitz, and Elbert (2003) cited by Goswami) Benedictine University

38. NEUROIMAGINGDYSLEXIC CHILDREN • Although neuroscience currently has few classroom applications, Goswami(2004) believes that neuroscience will be an important part of the future of research in education • She predicts it will be used increasingly for the early diagnosis of children in need of special education and in the study of the effects of varying interventions on learners of all ages and abilities Benedictine University