Flashcards
Language 1 - Word Recognition
Cards in this deck (34)
- 1Words- Have sounds & meanings
- 2Tasks used to examine word recognition- Reading task
- Naming task
- Lexical decision task - 3Reading task- Researchers measure time spent to read each word, often using eye trackers
- If people spend longer at looking at a word - recognition of the word difficult
- If people spend little time looking at a word (or even skip the word) - recognition of the word is easy - 4Naming task- Participants read words aloud
- The time between the appearance of the word on the screen and the start of the sound of the participants speaking the word is measured - 5Lexical decision tasks 1- Measure the time that participants take to decide whether or not a string of letters represents a word
eg. Table > YES
Toble > NO
- To make the task more difficult - the letter strings that are not words do follow typical arrangements from the language
eg. Tobly (typical)
Zjuybb (non-typical) - 6Lexical decision tasks 2- Often used in conjunction with SEMANTIC PRIMING
- If the target word is preceded by a word that is semantically related - lexical decision is made FASTER (Meyer & Schvaneveldt, 1971) - 7Semantic PrimingThe observation that a response to a target is faster when it is preceded by a semantically related prime compared to an unrelated prime.
Eg. Target - dog
Semantically related prime - cat
Unrelated prime - car - 8Meyer & Schvaneveldt (1971)
- 9Factors Influencing Word Recognition1) Word Length
2) Word Frequency
3) Presentation Context
4) Neighborhood effects - 10Word length- Words that are shorter (Fewer letters) are recognised FASTER
- SHORT WORDS = RECOGNISED FASTER - 11Word frequency 1- Words that are more common (high frequency) are recognised faster than words that are less common (low frequency)
Eg. The girl saw the cat jumping on the tree (high frequency)
The girl saw the yak jumping on the tree (low frequency) - 12Word frequency 2A variation of the lexical decision task is the CATEGORY DECISION TASK
- High frequency words are categorised FASTER than low frequency words - 13Category Decision TaskParticipants decide as quickly as possible whether a
word belongs to a category - 14Presentation Context- Similar to semantic priming
- Words that can be predicted by the presentation context are recognised FASTER
- Participants read an incomplete sentence
"The skiers were buried alive a sudden..."
Recognized word
- "Avalanche" (predictable)
- "Inflation" (unpredictable) - 15Presentation Context - Tulving and Gold (1963)- Found that the number of context words preceding the target word affected the response time
- If the target word - PREDICTABLE from context - participants response time is FASTER as more context is given
- If the target word - UNPREDICTABLE from context - participants response time is SLOWER as more context is given - 16Neighborhood Effects- Orthography Neighborhood
- Phonological Neighborhood - 17Orthography Neighborhood- Orthography - information about the spelling of words based on vision
- Is the number of words that can be formed by changing one letter of a word
eg. Tank = tasks, rank, sank, etc. - 18Andrews (!989,1992)For LOW frequency words, recognition is FASTER if the words have MANY ORTHOGRAPHIC neighbors
- 19Phonological Neighborhood- Phonology - information about the sound of words based on audition
- Is the number of words that can be formed by changing one phoneme (one unit of sound) of a word
eg. Cheap = Chip, Chop, Cheese, etc.
- Orthographic neighbors can be phonological neighbors & vice-versa - 20Yates (2005)Recognition is faster for words with many phonological neighbors
- 21MODELS of Word Recognition1) Logogen Model
2) Interactive Activation Model
3) Dual-Route Model - 22Logogen Model 1 (Morton, 1969)- Each word has a word recognition unit that receives AUDITORY & VISUAL info
- When auditory & visual info matches the word of the unit = activation in the unit INCREASES until a threshold is reached
- Threshold reached = Word recognised
- When auditory & visual info DOES NOT sufficiently match the word of the unit = activation DOES NOT reach the threshold & word NOT recognised
- 23Logogen Model 2- Can account for word-frequency effects - High freq. have units w/ lower thresholds & are therefore recognised FASTER
- Presentation context & priming can temporarily lower thresholds
- Words that can PREDICT from the context and words that are semantic related to the preceding word = recognised FASTER - 24Word-Superiority Effect- Letters are recognised FASTER when presented INSIDE of words than presented in ISOLATION or presented inside non-words (Reicher, 1969; Wheeler, 1970)
- Logogen model - CANNOT account for Word-Superiority Effect
- Interactive Activation Model - CAN account for Word-Superiority Effect - 25Interactive Activation Model 1 (McClelland & Rumelhardt, 1981, 1982)- Proposes that word recognition operates like a network with layers, which contain nodes and excitatory and inhibitory connections between the nodes
- When a person sees the word 'work' (bottom layer), feature nodes (lines and shaped) in the second layer become more or less activated through excitatory and inhibitory connections
- Feature nodes = increase or decrease activation of letter nodes (again through excitatory & inhibitory connections) in the third layer
- 26Interactive Activation Model 2- Word = work - increases activation in the feature node 'O' - INCREASES activation in all the letter nodes which have the same shape (Eg. o, b, p, q, g); Decreases activation in all letter which DO NOT have the same shape (a, c, e, f, h, etc)
- ^^ Letter nodes then increase or decrease activation in all the word nodes that HAVE or DO NOT HAVE these letters - 27Interactive Activation Model 3- Although very influential - CANNOT explain some effects due to its rigidity
- Beside features, letters, and words, the model also has a slot coding system
- To distinguish words with the same letters (eg. limes, miles, slime, smile) - the order of the letter also MATTERS
- We often do not notice when words have letter are out of order (eg. typos)
- Recent versions of the model (Spatial Coding Model; Davis, 2019) do not code letter position as rigidly - 28Dual Route Model 1 (Coltheart et al., 2001)- Argues that there are 2 pathways between seeing the word (input) and understanding the meaning of the word (output) of word recognition
- 2 pathways:
1) Direct or Lexical route
2) Indirect or Phonological route
- 29Direct or Lexical Route- Connecting the visually presented word to its meaning
- Route is used for FAMILIAR WORDS - 30Indirect or Phonological route- Phonological rules are used to convert graphemes (letters & groups of letters) onto phonemes (sounds)
- The sounds are then put together and the meaning of the resulting word is finally searched
- Route is used for UNFAMILIAR WORDS & NON-WORDS - 31Dual Route Model 2- 2 routes - develop independently when children learn to read
- Problems with each route can occur and lead to specific reading difficulties:
1) Developmental surface dyslexia
2) Developmental phonological dyslexia - 32Developmental Surface Dyslexia- The direct/lexical route - UNAVAILABLE
- Only indirect/phonological route - can be USED (i.e. reading words letter-by-letter)
- Surface dyslexics - have difficulties reading words with an IRREGULAR PRONOUNCIATION (eg. yacht) and often confuse homophones (eg. for, four, fore) - 33Developmental Phonological Dyslexia-The indirect/phonological route - UNAVAILABLE
- Only direct/lexical route - can be USED (i.e. recognising full words)
- Phonological dyslexics - have difficulties reading UNFAMILIAR words and non-words - particularly problematic for children who are learning to read - most written words will be unfamiliar for them - 34Summary- Three tasks used to examine word recog. :
- Reading task, Naming task, and lexical decision task
- Four factors influencing word recog.:
- Word length, word frequency, presentation context, & neighborhood effects
- 3 models of word recog.:
- Logogen Model, Interactive Activation Model, Dual Route model
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- undergraduate Cognitive psychology Flashcards on Language 1 - Word Recognition, created by Izati Saim on 12/01/2022.
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- Izati Saim
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