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Mean Length of Utterance (MLU). A measure of language ability. A Measure of Language Ability. www.stfx.ca/people/jlayes. Mean Length of Utterance (MLU). MLU is a way to score a child’s language ability
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Mean Length of Utterance (MLU) • A measure of language ability A Measure of Language Ability www.stfx.ca/people/jlayes
Mean Length of Utterance (MLU) • MLU is a way to score a child’s language ability • When scoring for MLU, researchers count the number of morphemes in the child’s utterances • It has been found that as age increases, so does the average number of morphemes used by the child
Morphemes • Smallest element of meaning in speech E.g.: “Walk the dog” contains 3 morphemes “The dog walked” contains 4 morphemes -The suffix “-ed” adds meaning • Remember: Morphemes and words are not the same thing
Morphemes • Free Morphemes: • These are words on their own: • E.g. “Dog”, “Walk”, “Sit”, “House” • Bound Morphemes: • Prefixes and Suffixes • These are not words on their own: • E.g. “re-”, “un-”, “pre-”, “-ed”, “-s”, “-ing”, “-ly”
Using MLU to Assess Language Ability • Shouldn’t be used as the only measure, but does correlate with other language measures • Rice, Redmond, & Hoffman (2006) • Showed MLU correlated positively with: • Developmental Sentence Scoring (DSS) • Index of Productive Syntax (IPSyn) • MLU in Words (rather than Morphemes)
MLU and Age • Miller & Chapman (1981) • Found a positive correlation of r=.88 between age and MLU • Lots of research provides us with the average MLU for children at each age • E.g. - At 30 months, you can expect an MLU of 2.54 - At 60 months, expect MLU of 5.36 • Can be a diagnostic tool for Language Impairment, but researchers caution it shouldn’t be the only one
Children’s Understanding of Morphemes • Berko, 1958 e.g. • Used nonsense words and pictures • Found that children aged 4-7 correctly knew how to pluralize by adding an s or z sound. • Correctly understood the use of the d sound for past tense • Understood the use of -ing
Scoring a Child for MLU • Ideally: • Observe and record interaction for 30-60 mins where dialogue is likely, e.g. Playing with dolls with mom • Pick out 100 utterances made by the child that are completely intelligible • Transcribe the interaction (write out what was said) ->
Scoring a Child for MLU • What to count as a morpheme: • Free Morphemes: (“truck” = 1) • -s (used as plural- “girls” = 2) • -ed (“jumped” = 2) • -ing (“dancing” = 2) • -s (used as possessive –”mom’s car” = 3) • Contractions (“she’s” = 2) • There are exceptions (see next slide)
Scoring a Child for MLU • Exceptions/What not to count as a morpheme: • Unintentional repetitions (“He he is there”=3) • Compound words (“doghouse” =1) • “Does”, “Let’s”, “don’t”, “won’t” each = 1 • Reduplications (“Choo, choo” =1) • Proper Names (“Mickey Mouse” =1) • Irregular plurals (“pants” =1) • Catenatives (“gonna” =1) • Fillers (“umm” =0)
Example Utterances • Some Examples: • Mommy’s going downstairs” • Mommy =1 • -’s =1 • go =1 • -ing= 1 • downstairs =1 • Total Morphemes= 5
Example Utterances • “The truck, umm, the truck went vroom, vroom” • The = 1 • truck = 1 • umm = 0 (filler) • the = 0 (repetition) • truck = 0 (repetition) • went = 1 • vroom = 1 • vroom = 0 (reduplication) • Total Morphemes = 4
Scoring a Child for MLU • Once the morphemes have been counted for each utterance: • Add up all the morphemes • Divide by the number of utterances • Ideally 100 • Now have the child’s Mean Length of Utterance score
Example MLU Calculation • 1) “Mommy’s going downstairs” = 5 Morphemes • 2) “The truck, umm, the truck went vroom vroom” = 4 Morphemes Total = 9 Morphemes • 9 Morphemes divided by 2 utterances = 4.5 • MLU (in this very short transcript)= 4.5
Part I: Data Collection • As we watch the videos, try to write down everything the child says • You will then be given transcripts of portions of the videos • You will be given the last ten statements of her speech in each video
Part II: Calculate MLU • For each transcript: • Count up the morphemes for each utterance • Then, add them up, and divide by 10 • This gives you an MLU score for each of the two transcripts
Part III: Data Analysis • Open the linked SPSS Data File • Save to Desktop, Open SPSS, Open File • Run a Dependent (paired-samples) t-test in SPSS • to see if MLU scores changed significantly in participants from 30 mths(2.5 years old) to 36 mths(3 years old) • Did the children’s language complexity increase in the space of 6 months? • Each participant has been tested twice.
Note about t-tests: • Independent t-test: Compares two groups of different people • E.g. Comparing the marks from one lab section to another • Dependent t-test: Compares people to themselves at different times. • E.g. Comparing each student’s 260 midterm mark to their exam mark. • The t-test determines if two sets of scores are different from one another. When the Significance Level is less than 0.05, this tells us that there is only a 5% or less probability that the difference you found was not real. There is a 95% or more probability that this difference is real and would be found again and again. • Reporting results: t(df)= insert t-value, p___0.05. • The ‘p’ stands for “probability”. If it is less than 0.05, insert the “<“ symbol, “>” if greater.