Lang & Comm 3 Flashcards

1
Q

2 countries of highest and lowest literacy rates

A

Latvia 99.9%
Chad

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

How many people are illiterate globally

A

769,000,000 (World Literacy Found., 2012)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

2 types of costs of illiteracy

A

economic - £2BN per year
social - higher chance of depression, substance abuse, suicidal ideation and poor physical health

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

visual word recognition

A

first stage of reading where we transform letters into meaning

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

through which store do we achieve visual word recogniton

A

through our mental lexicon

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

how many words in English speaker’s mental lexicon

A

60,000-70,000

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

grapheme

A

letter groups that correspond to form one phoneme

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

what do graphemes form the bridge between

A

phonology and orthogrpahy

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

how do we test if graphemes are used for visual word recognition?

A

letter detection (Ray, Ziegler and Jacobs, 2000)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

what is this testing and what did it find

A

if graphemes are used for visual word recognition - they ARE as ‘a’ in broad took longer than a in ‘brash’

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

morpheme

A

smallest meaningful unit of language (“un-real” = prefix and root)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

complications of morphemes and examples

A

pseudo-affixes:
de-ter vs de-press
corn-er vs farm-er
se-ed vs look-ed

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

how do we test if morphemes are used for visual word recognition?

A

primed lexical decision (Lima and Pollastek, 1983)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

what is this testing and what did it find

A

with no morphemes used, priming expectedly was strongest with most overlap (3>2>1)

with morphemes, priming was strongest with the morpheme option no matter how much overlap it had (2>1=3)

morphemes are access units in visual word recognition

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

what is this testing and what did it find

A

had to say it words were real/non-real:
CORNER = pseudo-suffix = greater priming
BROTHEL = no pseudo suffix = priming is comparable

suffixes + pseudo suffixes are used in early word recognition

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

how do we test if letters are processed in parallel or serially to one another?

A

word naming (DV = rt + accuracy) (Weekes 1997)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

what is this testing and what did it find

A

word length effects in reading:
HF words all comparable
LF words weak connection
non-words needed serial grapheme-phoneme conversion

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

why is grapheme-phoneme conversion necessary for non-words

A

they aren’t stored in our mental lexicon, have to serially letter-by letter

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

are letters processed in parallel or serially? And what is paid attention to

A

MOSTLY parallel
first > last letters > middle letters
consonants

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

activating a whole set of words coded in a similar way

A

Coltheart’s N: orthographic neighbourhood

21
Q

how do we test if words with shared letters are all activated when searching for a target?

A

form-based priming/orthographic priming (Evett and Humphrys 1981)

22
Q

what is this testing

A

if we activate all similar words when searching for a target

23
Q

orthogrpahic neighbourhoods: explain results

A

real and non-real primes that share letters as target = faster identification

WORDS that share letters are negatively connected in lexicon (inhibit similar words)

NON-WORDS that share letters don’t inhibit

24
Q

how do we test if there are feedback connections between letters and words?

A

letter detection (Reicher 1969)

25
what does this letter detection task (Reicher 1969) test?
if there are feedback systems between words and letters
26
explain results of Reicher's study
letters detected better in words than non-words letters in words are detected better by letters on their own = there is a feedback systems of words-letters (word superiority effect)
27
give 3 extra phenomena with word recognition (FAS)
Frequency effect – HF words recognised faster Age of Acquisition effect – words learned younger = recognised faster Semantic priming effect – primed by dog rather than school eg – faster in saying CAT
28
2 ways different models of word recognition differ
series/parallel access one way/interactive relationship between letters and words
29
list these top to bottom
Forster's search model Morton's logogen model R&M Interactive Activation model
30
what model is this
Forster's search model:
31
list 4 steps in Forster's search model (RASA)
Recognise units of a word Access a unit in correct bin (parallel) Search frequency ranked bin for target word (serial) Access master file for meaning
32
which model is this
Morton's logogen model
33
why is Morton's logogen model parallel
information about letters is being sent to all logogens at once
34
why is Morton's logogen model not interactive
information only feeds forward from letters to words
35
what type of word is a logogen threshold high for
low frequency words
36
what can logogen thresholds depend on
frequency and prior exposure
37
what happens when activation passes logogen threshold
logogen fires and word is recognised
38
logogen
word detector
39
is Morton's logogen model top-down or bottom-up
bottom-up, from letters to words only
40
which model is this
R&M Interactive Activation Model
41
what makes R&M IAC Model the same as logogen model
Parallel activation of all words that contain letters recognised
42
what makes R&M IAC Model different to logogen
between level connections - feedback means activation of word goes back to letters (word superiority effect)
43
what effect according to the R&M IAC Model creates feedback (bottom-up and top-down processing)
word superiority effect
44
what is the difference between thresholds in logogen and R&M IAC Models?
logogen thresholds vary HF words have higher resting levels of activation - not thresholds - in R&M IAC Model
45
how well does each model of word recognition explain frequency effect (HF = faster)
:) SM - bins ranked by frequency :) LM - Lower activation threshold :) R&M IAC - higher resting levels of activation
46
how well does each model of word recognition explain word length effect (no clear effect)
:) SM - words rnaked by freq. (length = insig.) :) LM & R&M IAC - letters processed in parallel (length = insig)
47
how well does each model of word recognition explain form priming (loup/LOUD)
:) SM - possible if prime and target in same bin and prime hasn't been reached yet when target appears :) LM & R&M IAC - primes activates letters from target
48
how well does each model of word recognition explain morpheme units
:) SM - only if the access unit = morphemes :( LM & R&M IAC - predict more priming for more shared letter overlap
49
how well does each model of word recognition explain word superiority effect
:( SM & LM - no interaction between letters-words :) R&M IAC - interactivity predicts effects