Lab 10: Auditory Sentence Processing
[For this lab, you will be a subject in a PC-based experiment of auditory sentence processing. The experiment is a gating experiment that runs under the Windows program E-prime. This handout describes the nature of the experiment and the questions you need to answer for the lab. Your TA will give you separate instructions on how to start E-prime, run the experiment, and save your data.]
In English, some sentences are temporarily structurally ambiguous. For example, the active sentence given in (a) and the passive sentence given in (b) are syntactically ambiguous until one has read the verb inflection (the inflection -ing in the active and the inflection –ed in the passive)
a. The girl was pushing the boy.
b. The girl was pushed by the boy.
In this experiment, we explore whether adults can predict whether a sentence is active or passive prior to hearing the verbal inflection (i.e., prior to the point of syntactic disambiguation). In the experiment, you will listen to sentence fragments that are either taken from an active sentence or a passive sentence. Sentences are either truncated after the was (as shown in example c) or after the verb stem (as shown in example d). Your job is to guess how the sentence ends. In other words, you must decide whether the sentence fragment was taken from an active sentence or a passive sentence.
c. Was termination: The girl was ….
d. Verb stem termination: The girl was push ….
The goals of this lab are 1) to investigate whether
non-syntactic factors affect sentence processing, 2) to understand how
psycholinguistic experiments are designed such that one can systematically test
hypotheses and 3) to understand some key statistical concepts such as null
hypothesis, main effect, interaction, and significance level
One common way of designing experiments is to have a factorial design in each factor is orthogonal to the others. In this experiment , there are 96 trials. The two main factors are (1) passive/active and (2) terminates after aux/terminates after verb stem. These two factors are crossed (orthogonal), yielding distinct sentence types. A third factor is verb. Each of the 6 verbs appear in each sentence condition an equal number of times. There are two sets of noun phrases (NPs) that are always paired with each another. Specifically, the man is always paired with the woman and the boy is always paired with the girl. Each NP appears as the subject (i.e., first NP) and object (i.e., second NP) of each sentence type an equal number of times. Each NP appears as the subject (the first NP) with each verb in each sentence condition an equal number of times.
Based on the above description, answer the following questions:
1. How many sentence types are there?
2. How many examples of each sentence type do subjects do?
3: How many times do the subjects hear a given verb in a sentence type
4: How many times does man appear as the subject (first NP) of the following sentence type "The man was VERB(ing the woman).
5: How many times does man appear as the subject (first NP) in the following sentence: "The man was PUSH(ing the woman).
Using the Analysis of Variance (ANOVA) table given at the end of this handout, answer the following questions
6a. How many subjects do we have data from?
6b. What 3 factors are analyzed in this ANOVA?
6c. How many levels are there for each of the 3 factors?
7a. On average, what percentage of the time did these subjects guess correctly for actives?
7b. On average, what percentage of the time did they guess correctly for passives?
7c. What is the null hypothesis with respect to the factor active/passive?
7d. How likely was the difference in performance on actives and passives due to chance along? (Hint: look for the p value)
7e. How confident can we feel in rejecting the null hypothesis?
8a. On average, what percentage of the time did these subjects guess correctly for sentences that were truncated after the auxiliary?
8b. On average, what percentage of the time did these subjects guess correctly for sentences that were truncated after the verb stem?
8c. What is the null hypothesis with respect to the point at which the sentences were truncated?
8d. How likely was the difference on was truncations and verb stem truncations due to chance alone?
8e. How confident can we feel in rejecting the null hypothesis?
9a. On average, which verb(s) did subjects do the worst on?_______ What percentage of the time did they guess correctly for this/these verb(s)?
9b. On average, which verb(s) did subjects do the best on?_______ What percentage of the time did they guess correctly for this/these verb(s)?
9c. What is the null hypothesis with respect to the verbs used in the sentences?
9d. How likely was the difference among the verbs due to chance alone?
9e. How confident can we feel in rejecting the null hypothesis?
10. There was a significant interaction between the choice of verb and performance on active versus. passive sentences (F(5, 105) = 3.465, p = .006). Your TA will explain what is meant by an interaction, but intuitively, in this case, it means that the particular verb used in a sentence affected the pattern of response for actives and passives. Using the ANOVA table, can you find any verbs that displayed a different pattern from the other verbs. (HINT: look to see if the difference in percentage correct for actives and passives was approximately same for all 6 verbs or if the difference was a lot greater or lesser for some verb than others.)
11. The same sets pictures were used for push and shove and for touch and tickle. Given this, the difference in performance between push and shove and between touch and tickle could not be due to the pictures per se.
What might account for the difference between push and shove?
What might account for the difference between touch and tickle?
12. Are any of the other interactions among the 3 factors significant?
SOURCE: grand mean
verb
psvact auxstem N MEAN SD
SE
528 0.6608 0.3302 0.0144
SOURCE: verb
verb
psvact auxstem N MEAN SD
SE
tickle
88 0.6250 0.3515 0.0375
touch
88 0.6903 0.3216 0.0343
push
88 0.6712 0.3498 0.0373
sniff
88 0.6903 0.2984 0.0318
kiss
88 0.6659 0.3228 0.0344
shove
88 0.6222 0.3362 0.0358
SOURCE: psvact
verb
psvact auxstem N MEAN SD
SE
Act
264
0.7396
0.3012
0.0185
Pass
264
0.5820
0.3395
0.0209
SOURCE: verb psvact
verb
psvact auxstem N MEAN SD
SE
tickle
Act
44 0.7102 0.3321 0.0501
tickle
Pass
44 0.5398 0.3533 0.0533
touch
Act
44 0.7159 0.2727 0.0411
touch
Pass
44 0.6648
0.3655 0.0551
push
Act
44
0.6799
0.3752
0.0566
push
Pass
44 0.6625 0.3266 0.0492
sniff
Act
44 0.7955 0.2487 0.0375
sniff
Pass
44 0.5852 0.3095 0.0467
kiss
Act
44
0.7920
0.2715
0.0409
kiss
Pass
44 0.5398 0.3232 0.0487
shove
Act
44 0.7443 0.2878 0.0434
shove
Pass
44 0.5000 0.3396 0.0512
SOURCE: auxstem
verb
psvact auxstem N MEAN SD
SE
Stem
264
0.8330
0.2595
0.0160
Aux
264
0.4886
0.3027
0.0186
SOURCE: verb auxstem
verb
psvact auxstem N MEAN SD
SE
tickle Stem 44 0.7727 0.3135 0.0473
tickle Aux 44 0.4773 0.3272 0.0493
touch
Stem
44 0.8977 0.1732 0.0261
touch
Aux
44 0.4830 0.3021 0.0455
push
Stem
44 0.8652 0.2343 0.0353
push
Aux
44
0.4773
0.3402
0.0513
sniff
Stem
44 0.8523 0.2244 0.0338
sniff
Aux
44 0.5284 0.2761 0.0416
kiss
Stem
44 0.8261 0.2693 0.0406
kiss
Aux
44
0.5057
0.2928
0.0441
shove
Stem
44 0.7841 0.3062 0.0462
shove
Aux
44 0.4602 0.2850 0.0430
SOURCE: psvact auxstem
verb
psvact auxstem N MEAN SD
SE
Act Stem 132 0.8922 0.2202 0.0192
Act Aux 132 0.5871 0.2946 0.0256
Pass Stem 132 0.7739 0.2822 0.0246
Pass Aux 132 0.3902 0.2785 0.0242
SOURCE: verb psvact auxstem
verb
psvact auxstem N MEAN SD
SE
tickle
Act
Stem
22
0.8182
0.3379
0.0720
tickle Act Aux 22 0.6023 0.2954 0.0630
tickle
Pass Stem 22 0.7273 0.2877 0.0613
tickle
Pass Aux 22 0.3523 0.3149 0.0671
touch
Act
Stem
22
0.8864
0.1490
0.0318
touch
Act Aux 22 0.5455 0.2632 0.0561
touch
Pass Stem 22 0.9091 0.1974 0.0421
touch
Pass Aux 22 0.4205 0.3308 0.0705
push
Act
Stem
22
0.8485
0.2668
0.0569
push
Act
Aux
22
0.5114
0.3970
0.0846
push
Pass Stem 22 0.8818 0.2015 0.0430
push
Pass Aux 22 0.4432 0.2774 0.0592
sniff
Act
Stem
22
0.9318
0.1376
0.0293
sniff
Act
Aux
22 0.6591 0.2622 0.0559
sniff
Pass Stem 22 0.7727 0.2662 0.0568
sniff
Pass Aux 22 0.3977 0.2270 0.0484
kiss
Act
Stem
22
0.9364
0.1787
0.0381
kiss
Act
Aux
22
0.6477 0.2745 0.0585
kiss
Pass Stem 22 0.7159 0.3017 0.0643
kiss
Pass Aux 22 0.3636 0.2406 0.0513
shove
Act
Stem
22
0.9318
0.1756
0.0374
shove
Act
Aux
22
0.5568
0.2551 0.0544
shove
Pass Stem 22 0.6364 0.3398 0.0724
shove
Pass Aux 22 0.3636 0.2858 0.0609
FACTOR : subj verb psvact auxstem correct
LEVELS :
22 6 2 2 528
TYPE
:
RANDOM
WITHIN
WITHIN
WITHIN DATA
SOURCE
SS
df
MS F p
===============================================================
mean
230.5736
1
230.5736 2080.267 0.000 ***
s/
2.3276
21
0.1108
verb
0.4096
5
0.0819
1.838 0.112
vs/
4.6807 105
0.0446
psvact
3.2802
1
3.2802
7.081 0.015 *
ps/ 9.7283 21
0.4633
vp
1.1088
5
0.2218
3.465 0.006 **
vps/
6.7200 105
0.0640
auxstem 15.6550 1
15.6550 196.395 0.000 ***
as/
1.6739
21
0.0797
va
0.2344
5
0.0469
1.265 0.284
vas/
3.8906 105
0.0371
pa
0.2042
1
0.2042
1.886 0.184
pas/
2.2737
21
0.1083
vpa
0.2490
5 0.0498 1.043 0.396
vpas/
5.0145 105
0.0478