(Kemp & Klee,1997)
Of respondents*:
• 85% of SLPs said they use LSA
• Those who don‟t sample said they don‟t have
enough time
• 59% of the 85% transcribe children‟s language in
real-time while children produce the sample
• 78% of the 85% use 50-utterance samples or less
• Only 8% of SLPs who used LSA used computers to
assist with transcription and analysis
• Presumed by researchers that SLPs working with
school-age children use LSA even less
That‟s key
Brown (1973)
MLU and stages of development
Is longitudinal vs. a 50-utterance
sample a fair comparison?
And it can be very technical,
difficult, and time-consuming!
Steps in Our Study of LSA
If SLPs are going to use 50 utterances, we should
get more out of them! Robust Sampling
Study
If we back away from longitudinal studies, we‟ll
need to find better calculation methods.
Normative Study
Which calculations are important? Correlational
Study
How do kids with & without language impairment
compare? Comparative Study
Can we reduce the time required to collect,
transcribe and analyze samples? Timed Study
Study #1: Robust Sampling
Can we change the quality of samples?


22 students each collected a language sample
from a child ( = 51.36 months, SD = 12.14)
Small group of student trainers



Prepared handout on collecting sample emphasizing
narrative elicitation Handout.doc
Trained same 22 students via role-playing in
elicitation techniques
Six months after 1st sample, same 22 students
each collected a second language sample from
a different child ( = 57.81, SD = 13.2)
Trained Conversational
Strategies for Collecting


Turnabouts = Comment + Cue for child
to talk
Process Questions





How did…
What happened…
Tell me…
I wonder what you…
Why did…


More than one-word “why” questions
Not appropriate for kids below 4.5 yrs
Trained Conversational
Strategies for Collecting

Use narrative elicitations instead of
yes/no questions


Build on what the child says or on what you
know
Begin with…



Your mom says you…. That sounds like fun. Tell
me what happened.
I know that you…. Tell me what happened.
Did you ever…. Tell me what you did.
Study #1: Robust Sampling
Can we change the quality of samples?

Results

Significant difference




Increase in child MLU, t = 3.05; p < 0.001
Decrease in the mean number of yes/no questions
asked by adult, t = 4.35; p < 0.001
Decrease in the mean number of one-word child
responses, t = 3.46; p < 0.001
No significant difference


Mean number of child clauses per sentence, t =
.84; p > .05
Mean number of child utterances per turn, t =
-.96; p > .05
Study #1: Robust Sampling
Can we change the quality of samples?

Results

Significant difference




Increase in child MLU, t = -3.05; p < 0.01
Decrease in the mean number of yes/no questions
asked by adult, t = 4.35; p < 0.001
Decrease in the mean number of one-word child
responses, t = 3.46; p < 0.001
No significant difference


Mean number of child clauses per sentence, t =
.84; p > .05
Mean number of child utterances per turn, t =
-.96; p > .05
Study #2: Normative
Study

175 50-utterance samples of
children 30-89 months


Used the more narrative techniques
taught previously
Analyzed in several ways


Guidelines for analysis
Collapsed ages into 36, 48, 60, 72,
and 84 mos. (6 mos below - 5 mos above)
Based on 175 50-utterance samples from 3-7 year-olds
Quantitative
MLU
Clauses/Sentence
Words/Clause
Noun Phrases/Sentence
Total number of words
Words/Sentence
Noun Phrases/Clause
Elements/Noun phrase
Words/Verb Phrase
Qualitative
Elements of Verb
Phrase
Sentence structure
Prepositional and
Infinitive Phrases
Prepositions
Embedding &
Conjoining
Subordinating Pronouns
Conjunctions
Based on 175 50-utterance samples from 3-7 year-olds
Quantitative
MLU
Clauses/Sentence
Words/Clause
Noun Phrases/Sentence
Total number of words
Words/Sentence
Noun Phrases/Clause
Elements/Noun phrase
Words/Verb Phrase
Qualitative
Elements of Verb
Phrase
Sentence structure
Prepositional and
Infinitive Phrases
Prepositions
Embedding &
Conjoining
Subordinating Pronouns
Conjunctions
Taken from Brown‟s Rules
for Counting Morphemes

Count as one morpheme







Reoccurrences of a word for emphasis
Ritualized reduplications (choo-choo)
Compound words (railroad, birthday)
Irregular past tense verbs (went)
Diminutives (doggie)
Auxiliary verbs
Irregular plurals (men)
Taken from Brown‟s Rules
for Counting Morphemes

Count as two morphemes





Possessive nouns (noun + „s or s‟)
Plural nouns (noun + s)
Third person singular present tense
verbs (verb + s)
Regular past tense verbs (verb + ed)
Present progressive verbs (verb +
ing)
Taken from Brown‟s Rules
for Counting Morphemes

Do NOT count



Disfluences
Fillers
With mazes, count the most full
form of what the child has said.
Example: So [we went to, to…you
know,] we planned to go to [that place
that we…uh, the,] the circus but [we
could…]it rain ed = 13 morphemes
Run-on sentences
If an utterance contains more than two clauses
joined with and, consider it a run-on sentence
and divide as follows*:
We went to the circus and I saw clowns and there
were elephants and I got this sweet sticky stuff.
We went to the circus and I saw clowns.
[And] there were elephants and I got this sweet
sticky stuff.
* Lee, DSS
Should we do this with other conjunctions too?
What about don‟t, can‟t, and won‟t ? 1 or 2?
When is gonna 1 and when is it 3?
When are gotta, hafta, and wanna 1 or 2?
7
6
5
4
1 SD
MLU
3
1SD
2
1
0
18 mos 24 mos 30 mos 36 mos 42 mos 48 mos 54 mos 60 mos
Count as one morpheme
Each word in proper nouns/names
Additional bound morphemes (Suggested by child samples)
-ful, -ly, -y (adj.), -en, -th, -ish, -ment, -tion, dis-, un-,
re-, -er (comparative), -est (superlative), -er (person
or thing that does some action unless common, such
as teacher)
Count as two morphemes
Wanna, gotta, and hafta
All contractions (don‟t, can‟t, won‟t, I‟d, he‟s, we‟ll, they‟ve)
Count gonna as three morphemes
:
14.00
12.00
10.00
MLU
8.00
Series1
Linear (Series1)
6.00
4.00
2.00
0.00
0
10
20
30
40
50
Age in 12 month intervals
60
70
80
90
14.00
12.00
10.00
5.33
5.48
6.68
7.73
0.77
6.00
1.30
1.12
1.79
2.35
3.19
4.03
4.36
4.89
5.38
-1 StDev
48 mos
60 mos
72 mos
84 mos
Age
MLU
8.00
3.96
MLU
St DevSeries1
Linear (Series1)
4.00
36 mos
2.00
0.00
0
10
20
30
40
50
Age in 12 month intervals
60
70
80
90
9
8
7
6
Brown (1974)
5
Rice et al (2010)
4
Our Study
3
2
1
0
36 mos
48 mos
60 mos
72 mos
84 mos
9
8
7
6
Brown (1974)
5
Rice et al (2010)
4
Our Study
3
2
1
0
36 mos
48 mos
60 mos
72 mos
84 mos
Ritualized reduplications (bye-bye) = 1
All contractions (I‟m, we‟d)
=1
Gonna, wanna, gotta, hafta = 2
Compound words = 1
600
Total Number of Words
500
400
300
Series1
Linear (Series1)
200
100
0
0
10
20
30
40
50
Age in 12 month intervals
60
70
80
90
600
Total Number of Words
500
400
189.67
249.65
261.18
314.94
336.07
TNW
55.36
61.43
65.90
87.41
90.97
StDev Series1
200
134.31
188.22
195.28
227.53
245.10
-1 StDev
36 100
mos
48 mos
60 mos
72 mos
84 mos
Age
300
Linear (Series1)
0
0
10
20
30
40
50
Age in 12 month intervals
60
70
80
90
Clauses/Sentence Guidelines

A clause contains a subject and a verb
Mommy walked but I ran. (2 clauses, 1 sentence)

Count imperatives as clauses
Come here. ([You] come here.)(1 clause , 1 sentence)

Count compound subjects or verbs as a single
clause/sentence
Mommy walked and ran all the way home = 1 clause , 1 sentence (1
subject but 2 verbs)
Bobby and Jim ran fast = 1 clauses , 1 sentence (2 subjects, 1 verb)

Count as a clause when the subject and/or a portion
of the verb is omitted because of ellipsis as long as
some portion of the verb remains: Benefits older child
Who can go with me? I can. = 1 clause , 1 sentence (S + aux. verb, so 1
clause)
What did you do? Ran home. (Main verb, so 1 clause , 1 sentence)
3.00
2.50
Clauses/Sentence
2.00
1.50
Series1
Linear (Series1)
1.00
0.50
0.00
0
10
20
30
40
50
Age in 12 month intervals
60
70
80
90
3.00
2.50
2.00
1.21
1.28
1.43
1.46
0.09
0.13
0.17
0.27
0.27
1.00
1.00
1.08
1.11
1.16
1.19
-1 StDev
36 mos
0.50
48 mos
60 mos
72 mos
84 mos
Age
Clauses/Sentence
1.09
1.50
Cl/Sent
Series1
StDev
Linear (Series1)
0.00
0
10
20
30
40
50
Age in 12 month intervals
60
70
80
90
25
Words/Sentence
20
15
Series1
Linear (Series1)
10
5
0
0
10
20
30
40
50
Age in 12 month intervals
60
70
80
90
25
20
5.82
6.45
7.49
7.86
Wds/Sen
0.74
1.31
1.31
2.12
2.06
StDev
3.87
4.51
5.14
5.37
5.80
-1 StDev
365 mos
48 mos
60 mos
72 mos
84 mos
Age
Words/Sentence
4.62
15
10
0
0
10
20
30
40
50
Age in 12 month intervals
60
70
80
90
Series1
Linear (Series1)
9.00
8.00
7.00
Words/Clause
6.00
5.00
Series1
4.00
Linear (Series1)
3.00
2.00
1.00
0.00
0
10
20
30
40
50
Age in 12 month intervals
60
70
80
90
9.00
8.00
7.00
6.00
Words/Clause
4.23
5.00
4.78
5.00
5.17
5.34
Wds/Cl
Series1
4.00
0.58
StDevLinear (Series1)
0.70
0.82
0.71
0.64
4.08
4.18
4.46
4.70
-1 StDev
48 mos
60 mos
72 mos
84 mos
Age
3.00
3.65
2.00
361.00mos
0.00
0
10
20
30
40
50
Age in 12 month intervals
60
70
80
90
Verb Phrase Guidelines

Verb Phrases = The verb and everything
related that follows. Examples:




The dog has been eating my candy. (5 words)
Why is mommy sleeping in the sun? (5 words)
Conjoining: They went home and I played by
myself. (2 verb phrases; 2 and 3 words
respectively)
Embedding: I know what you did at school
today. (2 verb phrases: “know what you did at
school today” and “did at school today”; 7 and 4
words respectively)
Verb Phrase Guidelines

Ellipsis: Count as a verb phrase but only
the words in the verb portion not other
omitted but related items.
Who can eat this last piece of pizza?
I can. Count as 2 words: I can (eat).
Do NOT count additional phrases also implied by
ellipsis I can (eat)(the last piece of pizza).

Compound verbs: Count as two verb
phrases
Mommy chased the dog and caught it.
I‟m going to go too. (1 verb phrase, 5 words)
Is she coming with us? (1 verb phrase, 4 words)
What do you want? (1 verb phrase, 2 words)
What do you want?
You do want .
9.00
8.00
Words/Verb phrase
7.00
6.00
5.00
Series1
4.00
Linear (Series1)
3.00
2.00
1.00
0.00
0
10
20
30
40
50
Age in 12-month Intervalss
60
70
80
90
9.00
8.00
7.00
Words/Verb phrase
3.21
0.37
2.84
6.00
3.89
4.02
4.21
4.78
0.61
0.64
0.69
1.19
Wds/VP
5.00
4.00
StDev Series1
Linear (Series1)
3.00
2.00
36 mos
3.28
3.38
3.52
3.59
-1 StDev
48 mos
60 mos
72 mos
84 mos
Age
1.00
0.00
0
10
20
30
40
50
Age in 12-month Intervalss
60
70
80
90
5.00
4.50
4.00
Noun phrases/Sentence
3.50
3.00
2.50
Series1
Linear (Series1)
2.00
1.50
1.00
0.50
0.00
0
10
20
30
40
50
Age in 12-month Intervals
60
70
80
90
5.00
4.50
4.00
Noun phrases/Sentence
3.50
3.00
1.97
2.23
2.33
2.42
3.03
0.63
0.60
0.45
0.94
1.60
1.73
1.98
2.09
-1 StDev
48 mos
60 mos
72 mos
84 mos
Age
10
30
2.50
0.51
NP/Sen
StDevSeries1
Linear (Series1)
2.00
1.46
1.50
1.00
36 mos
0.50
0.00
0
20
40
50
Age in 12-month Intervals
60
70
80
90
5.00
4.50
4.00
Noun phrases/Clause
3.50
3.00
2.50
Series1
Linear (Series1)
2.00
1.50
1.00
0.50
0.00
0
10
20
30
40
50
Age in 12 month intervals
60
70
80
90
5.00
4.50
4.00
Noun phrases/Clause
3.50
3.00
2.50
Series1
Linear (Series1)
2.00
1.50
1.00
0.50
0.00
0
10
20
30
40
50
Age in 12 month intervals
60
70
80
90
Category
Element
Determiner =
Quantifier + Article + Possessive
pronoun + Demonstrative +
Numerical term
Adjective =
Possessive Noun + Ordinal +
Adverb + Adjective + Descriptor
Noun =
Pronoun + Noun
Modifier =
Prep. Phrase + Adjectival +
Adverbial + Embedded clause
Initiator
Initiator
Only, a few of, just, at least, nearly
Quantifier
Article
Possessive pronoun
Demonstrative
Numerical term
All, both, half, no, one-tenth, some
A, the, an
My, your, his, her, its, our, their
This, that, these, those
One, two, thirty, one thousand
Possessive Noun
Ordinal
Adverb
Adjective
Descriptor
Mommy‟s, boys‟, children‟s, Juan‟s
First, next, last, next to, second, final
Really, very
Blue, big, fat, married, challenging
Shopping (center), baseball (game)
Dog, house, girl, couples, dish, cow
Prep. Phrase
Adjectival
Adverbial
Embedded clause
On TV, in the window, at the event
Next door, loved by all, beloved
Here, there
That lives next door, who you know
4.00
3.50
Elements/Noun phrase
3.00
2.50
2.00
Series1
Linear (Series1)
1.50
1.00
0.50
0.00
0
10
20
30
40
50
Age in 12-month intervals
60
70
80
90
4.00
3.50
Elements/Noun phrase
3.00
2.50
1.84
2.07
2.16
2.24
2.40
Elem/NP
2.00
Series1
0.46
0.39
0.37
0.42
0.27
StDev
1.38
1.00
1.68
1.79
1.82
2.13
-1 StDev
360.50mos
48 mos
60 mos
72 mos
84 mos
Age
1.50
0.00
0
10
20
30
40
50
Age in 12-month intervals
60
70
80
90
Linear (Series1)
We‟re really talking about probability. If 70%
of kids use a language feature within 50
utterances, we can safely assume more than
70% have that feature.
Even some language development studies use
the 70% criterion for mastery, although
admittedly not most.
It's nearly impossible to get many language
features displayed by 90% of the children, the
usual level for mastery, in just 50 utterances.
2-element
ENPs
3-element
ENPs
4-element
ENPs
36 m
48 m
60 m
72 m
84 m
*
*
*
*
*
*
*
*
*
*
3 year olds‟ predominate 3-word forms
Article + Adjective + Noun (e.g., a
bad boy, a big circle, a bouncy
noodle)
Article + Descriptor + Noun (e.g., the
Grinch movie, a seal thing)
4 year olds‟ predominate 3-word forms
Article + Adjective + Noun (the big dragon,
a hard game, a blue one, a pink phone,
an easy book)
Article + Descriptor + Noun (the octopus
name, a customer thing, the beach water,
a shark mouth)
Article + Noun + Prepositional phrase (a
picture of a doll, a list of vegetables, the
guy with the hat on)
5 year olds‟ predominate 3-word forms
Article + Adjective + Noun (a pink coat, a
little daughter, a good cat, the coolest
playground)
Article + Descriptor + Noun (the pumpkin
patch, the party stuff, the goat sound,
the brake station)
Article + Noun + Prepositional phrase (a
house for your little daughter, a picture
of Damien)
6-7 year olds‟ predominate 4-word forms
Article + Adjective + Adjective + Noun (a little
furry spot)
Article + Adjective + Descriptor + Noun (a big
kid room, the little baby chicks)
Article + Adjective + Noun + Prepositional phrase
(a big cloud of dust, a red mark on his stomach)
Article + Adjective + Noun + Embedded clause
(the new one I like)
Article + Adjective + Noun + Adverb (a little
heart right here)
36
m
48 m
60 m
72 m
84 m
Initiator
*
Quantifier
Article
*
*
*
*
*
*
Possessive Pronoun
Demonstrative
Numerical Term
Possessive Noun
Ordinal
Adverb
Adjective
Descriptor
Noun/Pronoun
Prepositional phrase
Adjectival
Adverbial
Embedded Clause
*
*
*
36 m
48 m
60 m
72 m
84 m
Uninflected
*
*
*
*
*
Copula (Am/is/are)
*
*
*
*
*
Aux Verb (Am/is/are) + Ving
*
*
Reg. past -ed
*
*
Irreg. past
*
*
*
*
*
*
Will/going to + Verb
Modal Aux + Verb
Do/don‟t/does/doesn‟t + Verb
Did/didn‟t + Verb
3rd Person -s
*
36 m
48 m
60 m
72 m
84 m
Infinitive Phrases
*
*
*
*
*
Prepositional Phrases
*
*
*
*
*
*
*
Adverbs
One auxiliary verb
2+ auxiliary verbs
36 m
In
On
With
48 m
60 m
72 m
84 m
Types of Embedding

Object Noun Phrase Complements

Following words such as know,
remember, forget, feel, think, say
I know what you did.

May omit connecting pronoun
Mommy said (that) we can‟t go.

Relative Clauses are attached to a
noun
I want the kitty (that) I saw yesterday.
36 m
Conjoining
Embedded clause
Type: Object NP comp
Type: Relative Clause
Specific connecter:That
48 m
60 m
72 m
84 m
MLU
Cl/Sen
Wd/Cl
NP/Sen
TNW
Wd/Sen Elm/NP
Wds/VP
In 70% of 36month-olds
Article
Poss. Pronoun
Demonstrative
Adjective
In current child
√
√
√
In 70% of 36month-olds
Uninflected
Copula (Am, is, are)
Aux (Am, is, are) + Ving
Modal + Verb
Do, does, don‟t, doesn‟t
+ Verb
3rd Person -s
Current child
√
√
In 70% of 36month-olds
In current child
Infinitive Phrase
Prepositional
Phrase
1 Auxiliary Verb
√
MLU
Cl/Sen
Wd/Cl
NP/Sen
TNW
Wd/Sen Elm/NP
Wds/VP
In 70% of 60month-olds
Current child
Quantifier
Article
Poss. Pronoun
Demonstrative
Adjective
Descriptor
Prepositional Phrase
√
√
In 70% of 60month-olds
Uninflected
Copula (Am, is, are)
Aux (Am, is, are) + Ving
Regular Past -ed
Irregular Past
Will/going to + Verb
Modal + Verb
Do, does, don‟t, doesn‟t
+ Verb
3rd Person -s
Current child
√
√
√
√
√
√
In 70% of 60month-olds
Infinitive Phrase
Prepositional Phrase
1 Auxiliary Verb
Conjoining
Current child
√
√
√
Embedded Clause
In 70% of 60month-olds
Current child
In
On
√
CASL Subtests



Syntax Construction measures ability to
use sentence formation rules to create new
sentences
Paragraph Comprehension measures the
comprehension of sentence structure
through various spoken narratives
Pragmatic Judgment measures the child‟s
ability to decide and use language that is
appropriate in various social situations
Quantitative Language
Data Analysis

Language samples analyzed for
Words/verb phrase
Clauses/sentence
Words/clause
Total number of words

Noun phrases/sentence
Words/sentence
MLU
Elements/noun phrase
Correlation calculated between
each of these factors and each
CASL subtest
Correlation is NOT
cause and effect…
Cause and effect would look like this:
Cause
Effect
Correlation is NOT
cause and effect…
Cause and effect would look like this:
Cause
Effect
Correlation is NOT
cause and effect…
Cause and effect would look like this:
Cause
Effect
Correlation looks more like:
Factor 1
Factor 2
Correlation is NOT
cause and effect…
Cause and effect would look like this:
Cause
Effect
Correlation looks more like:
Factor 1
Factor 2
Variable
r value
Words/verb phrase
0.5603
Noun phrases/sentence
0.2792
Clauses/sentence
0.8684
Words/sentence
0.8693
Elements/noun phrase
0.1875
Words/clause
0.5985
MLU
0.8883
Total number of words
0.8849
Variable
r value
Words/verb phrase
0.6999
Noun phrases/sentence
0.1696
Clauses/sentence
0.8436
Words/sentence
0.5985
Elements/noun phrase
0.2043
Words/clause
0.6514
MLU
0.9080
Total number of words
0.8794
Variable
r value
Words/verb phrase
0.5713
Noun phrases/sentence
0.5052
Clauses/sentence
0.8848
Words/sentence
0.8642
Elements/noun phrase
0.2821
Words/clause
0.7140
MLU
0.8397
Total number of words
0.8475
Most highly correlated factors
(Variables we obtained with
a correlation higher than .8)
Variable
Pragmatic
Judgment
Syntax
Construction
Paragraph
Comprehension
Clauses/
sentence
0.8684
0.8436
0.8848
Words/
sentence
0.8693
0.5985
0.8642
MLU
0.8883
0.9080
0.8397
Total Number
of Words
0.8849
0.8794
0.8475