The Late(r) Bird Gets the Verb? Effects of Age of Acquisition of English on Adult Heritage Speakers’ Knowledge of Subjunctive Mood in Spanish
Abstract
:1. Introduction
1.1. Subjunctive Mood in Spanish: Purpose Clauses and Adjectival Relative Clauses
1. | Michelei compra | dulces | para que | lai | visitemos/*visitamos |
Michele buy-IND-3ps | sweets | for that | CL-3ps | visit-SUBJ-1ps/*visit-IND-1ps | |
‘Michele buys sweets so that we visit her’ |
2. | Michelei compra | dulces | porque | lai | *visitemos/visitamos |
Michele buy-IND-3ps | sweets | because | CL-3ps | *visit-SUBJ-1ps/visit-IND-1ps | |
‘Michele buys sweets because we visit her’ |
3. | Busco | un robot que | hable/habla | tres idiomas |
look for-IND-1ps | a robot that | speak-SUBJ-3ps/speak-IND-3ps | three languages | |
‘I’m looking for a robot that speaks four languages’ |
1.2. Subjunctive Mood in US Spanish: Stability and Variability
1.3. Age of Acquisition Effects in Heritage Language Inflectional Morphology
1.4. Research Questions and Hypotheses
2. Materials and Methods
2.1. Participants
2.1.1. Age of Acquisition of English
2.1.2. Spanish Proficiency (DELE)
2.2. Procedure
2.2.1. Contextualized Elicited Production Task (CEPT)
4. | Context: Your cousin is a biologist. She needs new binoculars for observing tropical birds. | ||||||||||
You tell the store clerk: | |||||||||||
a. | Busco | unos | binoculares | nuevos | para | que | mi | prima | (OBSERVAR) | ||
Look for-1ps | some | binoculars | new | for | that | my | cousin | (OBSERVE) | |||
‘I am looking for some new binoculars so that my cousin (observe)’ | |||||||||||
Expected Response: | para | que | mi | prima | observe | los pájaros | |||||
for | that | my | cousin | observe-3ps-SUBJ | the birds | ||||||
‘so that my cousin observes the birds’ |
5. | Context: You need a fun movie for your friend. His girlfriend left him yesterday, and now he seems to be very upset. You tell the store clerk: | |||||||||
Busco | una | película | de | humor | porque | ahora | mi | amigo | (ESTAR) | |
Look for-1ps | a | movie | of | humor | because | now | mi | friend | (BE) | |
‘I am looking for a comedy movie because now my friend (be)...’ | ||||||||||
Expected Response: | Porque | ahora | mi | amigo | está | muy triste | ||||
Because | now | my | friend | be-3ps-IND | very sad | |||||
‘because now my friend is very sad’ |
6. | Context: You need a green robot with the ability to speak four languages. You find one with the capacity to function in two languages and another with the capacity to function in three. You say to the store clerk: | ||||||||||||
a. | Busco | Un | robot que | sea | verde | y | que | that | |||||
look for-1ps | A | robot that | is-3ps-SUBJ | green | and | that | (SPEAK) | ||||||
‘I am looking for a robot that is green and that (speaks)...’ | |||||||||||||
Expected Response: | que | sea | verde | y | que | hable | 4 | idiomas | |||||
that | be-3ps-SUBJ | green | and | that | speak-3ps-SUBJ | four | languages | ||||||
‘that is green and speaks four languages’ | |||||||||||||
b. | Mi jefei | quiere | que | lei | traiga | un | robot que | (HABLAR) | |||||
My boss | want-3ps | that | Cl-3ps | bring-1ps-SUBJ | a | robot that | (SPEAK) | ||||||
‘My boss wants me to bring him a robot that (speaks)...’ | |||||||||||||
Expected Response: | que | hable | 4 | idiomas | |||||||||
that | speak-3ps-SUBJ | four | languages | ||||||||||
‘that speaks four languages’ |
7. | Context: You need a remote-control car with the ability to go more than 40 mph. It’s for your grandson. After 5 min, you find one in the toy section. You say to the store clerk: | |
Gracias, pero no necesito ayuda. Ya encontré3 un carrito que (IR) | ||
Thanks, but NEG need-IND-1ps help. Already find-PST-1ps a car that (GO) | ||
‘Thanks, but I do not need help. I already found a car that (goes)...’ | ||
Expected Response: | que va a más de 40 millas por hora | |
that go-3ps-IND at more of 40 miles for hour | ||
‘that goes more than 40 miles per hour’ |
2.2.2. Mood Preference Task (MPT)
8. | Context: Look at the bicycle that we bought for our dad! | |||||
a. | Se | la | compramos para que él | haga | más ejercicio | |
Cl-3ps | Cl-3ps | buy-1ps | for that he do-3ps-SUBJ more exercise | |||
b. | Se | la | compramos para que él | *hace | más ejercicio | |
CL-3ps | Cl-3ps | buy-1ps | for that he *do-3ps-IND more exercise | |||
‘We bought it (the bicycle) for him so that he would exercise more’ |
9. | Context: Look at the big notebook that we bought for our mom! | ||||||
a. | Se | lo | compramos porque ella | necesita | cuadernos para su poesía | ||
Cl-3ps | Cl-3ps | buy-1ps | because she need-3ps-IND | notebooks for her poetry | |||
b. | Se | lo | compramos porque ella | *necesite | cuadernos para su poesía | ||
Cl-3ps | Cl-3ps | buy-1ps because she | *need-3ps-SUBJ notebooks for her poetry | ||||
‘We bought it (the notebook) for her because she needs notebooks for her poetry’ |
10. | Context: We need something sweet for our dad, but we haven’t found anything. | ||||
a. | Buscamos | un postre | que tenga | chocolate y arándanos | |
Look for-1ps | a dessert | that | has-3ps-SUBJ chocolate and blueberries | ||
b. | Buscamos | un postre | que *tiene | chocolate y arándanos | |
Look for-1ps | a dessert | that | *has-3ps-IND chocolate and blueberries | ||
‘We are looking for a dessert that has chocolate and blueberries’ |
11. | Context: We needed something for our dad. We went to a sporting goods store and: | |||||
a. | Encontramos una maleta que | lleva | muchísimos balones de fútbol | |||
Find-1p-pl | a bag | that carry-3ps-IND | lots of | balls of soccer | ||
b. | Encontramos una maleta que | *lleve | muchísimos balones de fútbol | |||
Find-1p-pl | a bag | that *carry-3ps-SUBJ | lots of | balls of soccer | ||
‘We found a bag that carries lots of soccer balls’ |
3. Results
3.1. Contextualized Elicited Production Task (CEPT)
3.1.1. Coding and Data Exclusion
3.1.2. Statistical Model 1: AofAE
3.1.3. Model Results
3.1.4. Statistical Model 2: DELE Proficiency
3.2. Mood Preference Task (MPT)
3.2.1. Coding
3.2.2. Statistical Model 3: AofAE
3.2.3. Model Results
4. Discussion
5. Conclusions
Funding
Conflicts of Interest
Appendix A
Verb | MoodSelection | Condition | ExpectedMood | Regularity |
---|---|---|---|---|
hacer | Lexical | para que | Subjunctive | Irregular |
salir | Lexical | para que | Subjunctive | Irregular |
correr | Lexical | para que | Subjunctive | Regular |
parecer | Lexical | para que | Subjunctive | Irregular |
mover | Lexical | para que | Subjunctive | Regular |
romper | Lexical | para que | Subjunctive | Regular |
llegar | Lexical | para que | Subjunctive | Regular |
tomar | Lexical | para que | Subjunctive | Regular |
tocar | Lexical | para que | Subjunctive | Regular |
ganar | Lexical | para que | Subjunctive | Regular |
observar | Lexical | para que | Subjunctive | Regular |
usar | Lexical | para que | Subjunctive | Regular |
tener | Contextual | −PRE ARC | Subjunctive | Irregular |
decir | Contextual | −PRE ARC | Subjunctive | Irregular |
comprender | Contextual | −PRE ARC | Subjunctive | Regular |
producir | Contextual | −PRE ARC | Subjunctive | Irregular |
dirigir | Contextual | −PRE ARC | Subjunctive | Regular |
elegir | Contextual | −PRE ARC | Subjunctive | Regular |
llamar | Contextual | −PRE ARC | Subjunctive | Regular |
hablar | Contextual | −PRE ARC | Subjunctive | Regular |
aceptar | Contextual | −PRE ARC | Subjunctive | Regular |
explicar | Contextual | −PRE ARC | Subjunctive | Regular |
bajar | Contextual | −PRE ARC | Subjunctive | Regular |
evitar | Contextual | −PRE ARC | Subjunctive | Regular |
ir | Lexical | porque | Indicative | Irregular |
llevar | Lexical | porque | Indicative | Regular |
utilizar | Lexical | porque | Indicative | Regular |
venir | Lexical | porque | Indicative | Irregular |
leer | Lexical | porque | Indicative | Regular |
sacar | Lexical | porque | Indicative | Regular |
seguir | Contextual | +PRE ARC | Indicative | Regular |
estar | Contextual | +PRE ARC | Indicative | Regular |
mirar | Contextual | +PRE ARC | Indicative | Regular |
necesitar | Contextual | +PRE ARC | Indicative | Regular |
recibir | Contextual | +PRE ARC | Indicative | Regular |
decidir | Contextual | +PRE ARC | Indicative | Regular |
Verb | MoodSelection | Condition | ExpectedMood | Regularity |
---|---|---|---|---|
hacer | Lexical | para que | Subjunctive | Irregular |
salir | Lexical | para que | Subjunctive | Irregular |
correr | Lexical | para que | Subjunctive | Regular |
tomar | Lexical | para que | Subjunctive | Regular |
tocar | Lexical | para que | Subjunctive | Regular |
tener | Contextual | −PRE ARC | Subjunctive | Irregular |
decir | Contextual | −PRE ARC | Subjunctive | Irregular |
comprender | Contextual | −PRE ARC | Subjunctive | Regular |
hablar | Contextual | −PRE ARC | Subjunctive | Regular |
aceptar | Contextual | −PRE ARC | Subjunctive | Regular |
ir | Lexical | porque | Indicative | Irregular |
mirar | Lexical | porque | Indicative | Regular |
utilizar | Lexical | porque | Indicative | Regular |
necesitar | Lexical | porque | Indicative | Regular |
seguir | Lexical | porque | Indicative | Regular |
llevar | Contextual | +PRE ARC | Indicative | Regular |
leer | Contextual | +PRE ARC | Indicative | Regular |
venir | Contextual | +PRE ARC | Indicative | Irregular |
estar | Contextual | +PRE ARC | Indicative | Regular |
recibir | Contextual | +PRE ARC | Indicative | Regular |
Appendix B
Model Term | Coefficient | Standard Error | t | Sig. |
Intercept | −2.128 | 0.519 | −4.102 | 0.000 |
AofAGroup = 1 | 0.101 | 0.683 | 0.148 | 0.883 |
AofAGroup = 2 | −0.295 | 0.666 | −0.443 | 0.658 |
AofAGroup = 3 | 1.710 | 0.653 | 2.619 | 0.010 |
AofAGroup = 4 | ||||
MoodSelectType = 1 | −2.594 | 0.798 | −3.250 | 0.001 |
MoodSelectType = 2 | ||||
ExpectedMood = 1 | 6.889 | 0.758 | 9.085 | 0.000 |
ExpectedMood = 2 | ||||
AofAGroup = 1 x MoodSelectType = 1 | −0.174 | 1.059 | −0.165 | 0.869 |
AofAGroup = 1 x MoodSelectType = 2 | ||||
AofAGroup = 2 x MoodSelectType = 1 | 0.098 | 1.121 | 0.087 | 0.931 |
AofAGroup = 2 x MoodSelectType = 2 | ||||
AofAGroup = 3 x MoodSelectType = 1 | −2.308 | 1.327 | −1.739 | 0.082 |
AofAGroup = 3 x MoodSelectType = 2 | ||||
AofAGroup = 4 x MoodSelectType = 1 | ||||
AoAGroup = 4 x MoodSelectType = 2 | ||||
MoodSelectType = 1 x ExpectedMood = 1 | 3.112 | 1.254 | 2.481 | 0.013 |
MoodSelectType = 1 x ExpectedMood = 2 | ||||
MoodSelectType = 2 x ExpectedMood = 1 | ||||
MoodSelectType = 2 x ExpectedMood = 2 | ||||
AofAGroup = 1 x ExpectedMood = 1 | −5.283 | 0.789 | −6.693 | 0.000 |
AofAGroup = 1 x ExpectedMood = 2 | ||||
AofAGroup = 2 x ExpectedMood = 1 | −3.894 | 0.788 | −4.942 | 0.000 |
AofAGroup = 2 x ExpectedMood = 2 | ||||
AofAGroup = 3 x ExpectedMood = 1 | −1.001 | 1.098 | −0.912 | 0.362 |
AofAGroup = 3 x ExpectedMood = 2 | ||||
AofAGroup = 4 x ExpectedMood = 1 | ||||
AofAGroup = 4 x ExpectedMood = 2 | ||||
AofAGroup = 1 x MoodSelectType = 1 x ExpectedMood = 1 | 0.597 | 1.433 | 0.417 | 0.677 |
AofAGroup = 1 x MoodSelectType = 1 x ExpectedMood = 2 | ||||
AofAGroup = 1 MoodSelectType = 2 ExpectedMood = 1 | ||||
AofAGroup = 1 x MoodSelectType = 2 x ExpectedMood = 2 | ||||
AofAGroup = 2 x MoodSelectType = 1 x ExpectedMood = 1 | 0.375 | 1.474 | 0.254 | 0.799 |
AofAGroup = 2 x MoodSelectType = 1 x ExpectedMood = 2 | ||||
AofAGroup = 2 x MoodSelectType = 2 x ExpectedMood = 1 | ||||
AofAGroup = 2 x MoodSelectType = 2 x ExpectedMood = 2 | ||||
AofAGroup = 3 x MoodSelectType = 1 x ExpectedMood = 1 | 2.610 | 2.038 | 1.281 | 0.200 |
AofAGroup = 3 x MoodSelectType = 1 x ExpectedMood = 2 | ||||
AofAGroup = 3 x MoodSelectType = 2 x ExpectedMood = 1 | ||||
AofAGroup = 3 x MoodSelectType = 2 x ExpectedMood = 2 | ||||
AofAGroup = 4 x MoodSelectType = 1 x ExpectedMood = 1 | ||||
AofAGroup = 4 x MoodSelectType = 1 x ExpectedMood = 2 | ||||
AofAGroup = 4 x MoodSelectType = 2 x ExpectedMood = 1 | ||||
AofAGroup = 4 x MoodSelectType = 2 x ExpectedMood = 2 | ||||
|
Model Term | Coefficient | Standard Error | t | Sig. |
Intercept | −2.406 | 0.588 | −4.094 | 0.000 |
Group = 1 | 0.389 | 0.713 | 0.546 | 0.587 |
Group = 2 | ||||
MoodSelectType = 1 | −1.807 | 0.692 | −2.613 | 0.009 |
MoodSelectType = 2 | ||||
ExpectedMood = 1 | 1.462 | 0.489 | 2.989 | 0.004 |
ExpectedMood = 2 | ||||
Group = 1 x MoodSelectType = 1 | −1.404 | 1.047 | −1.341 | 0.180 |
Group = 1 x MoodSelectType = 2 | ||||
Group = 2 x MoodSelectType = 1 | ||||
Group = 2 x MoodSelectType = 2 | ||||
MoodSelectType = 1 x ExpectedMood = 1 | 2.891 | 0.800 | 3.616 | 0.000 |
MoodSelectType = 1 x ExpectedMood = 2 | ||||
MoodSelectType = 2 x ExpectedMood = 1 | ||||
MoodSelectType = 2 x ExpectedMood = 2 | ||||
Group = 1 x ExpectedMood = 1 | 1.569 | 0.511 | 3.067 | 0.002 |
Group = 1 x ExpectedMood = 2 | ||||
Group = 2 x ExpectedMood = 1 | ||||
Group = 2 x ExpectedMood = 2 | ||||
Group = 1 x MoodSelectType = 1 x ExpectedMood = 1 | 1.222 | 1.113 | 1.098 | 0.272 |
Group = 1 x MoodSelectType = 1 x ExpectedMood = 2 | ||||
Group = 1 MoodSelectType = 2 ExpectedMood = 1 | ||||
Group = 1 x MoodSelectType = 2 x ExpectedMood = 2 | ||||
Group = 2 x MoodSelectType = 1 x ExpectedMood = 1 | ||||
AofAGroup = 2 x MoodSelectType = 1 x ExpectedMood = 2 | ||||
AofAGroup = 2 x MoodSelectType = 2 x ExpectedMood = 1 | ||||
AofAGroup = 2 x MoodSelectType = 2 x ExpectedMood = 2 | ||||
|
Model Term | Coefficient | Standard Error | t | Sig. |
Intercept | −3.119 | 0.599 | −5.206 | 0.000 |
AofAGroup = 1 | 1.669 | 0.556 | 3.000 | 0.003 |
AofAGroup = 2 | 1.391 | 0.554 | 2.510 | 0.012 |
AofAGroup = 3 | 0.626 | 0.612 | 1.024 | 0.306 |
AofAGroup = 4 | ||||
MoodSelectType = 1 | −.174 | 0.846 | −0.206 | 0.838 |
MoodSelectType = 2 | ||||
ExpectedMood = 1 | 5.646 | 0.787 | 7.172 | 0.000 |
ExpectedMood = 2 | ||||
AofAGroup = 1 x MoodSelectType = 1 | −0.378 | 0.780 | −0.484 | 0.628 |
AofAGroup = 1 x MoodSelectType = 2 | ||||
AofAGroup = 2 x MoodSelectType = 1 | −0.741 | 0.797 | −0.929 | 0.353 |
AofAGroup = 2 x MoodSelectType = 2 | ||||
AofAGroup = 3 x MoodSelectType = 1 | −0.313 | 0.871 | −0.359 | 0.720 |
AofAGroup = 3 x MoodSelectType = 2 | ||||
AofAGroup = 4 x MoodSelectType = 1 | ||||
AoAGroup = 4 x MoodSelectType = 2 | ||||
MoodSelectType = 1 x ExpectedMood = 1 | 1.673 | 1.279 | 1.308 | 0.194 |
MoodSelectType = 1 x ExpectedMood = 2 | ||||
MoodSelectType = 2 x ExpectedMood = 1 | ||||
MoodSelectType = 2 x ExpectedMood = 2 | ||||
AofAGroup = 1 x ExpectedMood = 1 | −3.978 | 0.694 | −5.735 | 0.000 |
AofAGroup = 1 x ExpectedMood = 2 | ||||
AofAGroup = 2 x ExpectedMood = 1 | −3.713 | 0.687 | −5.403 | 0.000 |
AofAGroup = 2 x ExpectedMood = 2 | ||||
AofAGroup = 3 x ExpectedMood = 1 | −0.590 | 0.807 | −0.731 | 0.465 |
AofAGroup = 3 x ExpectedMood = 2 | ||||
AofAGroup = 4 x ExpectedMood = 1 | ||||
AofAGroup = 4 x ExpectedMood = 2 | ||||
AofAGroup = 1 x MoodSelectType = 1 x ExpectedMood = 1 | 0.067 | 1.179 | 0.057 | 0.955 |
AofAGroup = 1 x MoodSelectType = 1 x ExpectedMood = 2 | ||||
AofAGroup = 1 MoodSelectType = 2 ExpectedMood = 1 | ||||
AofAGroup = 1 x MoodSelectType = 2 x ExpectedMood = 2 | ||||
AofAGroup = 2 x MoodSelectType = 1 x ExpectedMood = 1 | 1.606 | 1.213 | 1.324 | 0.186 |
AofAGroup = 2 x MoodSelectType = 1 x ExpectedMood = 2 | ||||
AofAGroup = 2 x MoodSelectType = 2 x ExpectedMood = 1 | ||||
AofAGroup = 2 x MoodSelectType = 2 x ExpectedMood = 2 | ||||
AofAGroup = 3 x MoodSelectType = 1 x ExpectedMood = 1 | 0.174 | 1.443 | 0.121 | 0.904 |
AofAGroup = 3 x MoodSelectType = 1 x ExpectedMood = 2 | ||||
AofAGroup = 3 x MoodSelectType = 2 x ExpectedMood = 1 | ||||
AofAGroup = 3 x MoodSelectType = 2 x ExpectedMood = 2 | ||||
AofAGroup = 4 x MoodSelectType = 1 x ExpectedMood = 1 | ||||
AofAGroup = 4 x MoodSelectType = 1 x ExpectedMood = 2 | ||||
AofAGroup = 4 x MoodSelectType = 2 x ExpectedMood = 1 | ||||
AofAGroup = 4 x MoodSelectType = 2 x ExpectedMood = 2 | ||||
|
Model Term | Coefficient | Standard Error | t | Sig. |
Intercept | −1.527 | 0.480 | −3.181 | 0.004 |
Group = 1 | −0.117 | 0.411 | −0.285 | 0.776 |
Group = 2 | ||||
MoodSelectType = 1 | −0.408 | 0.684 | −0.596 | 0.557 |
MoodSelectType = 2 | ||||
ExpectedMood = 1 | 1.184 | 0.639 | 1.851 | 0.080 |
ExpectedMood = 2 | ||||
Group = 1 x MoodSelectType = 1 | −0.416 | 0.611 | −0.681 | 0.496 |
Group = 1 x MoodSelectType = 2 | ||||
Group = 2 x MoodSelectType = 1 | ||||
Group = 2 x MoodSelectType = 2 | ||||
MoodSelectType = 1 x ExpectedMood = 1 | 2.165 | 0.934 | 2.318 | 0.031 |
MoodSelectType = 1 x ExpectedMood = 2 | ||||
MoodSelectType = 2 x ExpectedMood = 1 | ||||
MoodSelectType = 2 x ExpectedMood = 2 | ||||
Group = 1 x ExpectedMood = 1 | 1.109 | 0.503 | 2.203 | 0.028 |
Group = 1 x ExpectedMood = 2 | ||||
Group = 2 x ExpectedMood = 1 | ||||
Group = 2 x ExpectedMood = 2 | ||||
Group = 1 x MoodSelectType = 1 x ExpectedMood = 1 | 0.508 | 0.825 | 0.616 | 0.538 |
Group = 1 x MoodSelectType = 1 x ExpectedMood = 2 | ||||
Group = 1 MoodSelectType = 2 ExpectedMood = 1 | ||||
Group = 1 x MoodSelectType = 2 x ExpectedMood = 2 | ||||
Group = 2 x MoodSelectType = 1 x ExpectedMood = 1 | ||||
AofAGroup = 2 x MoodSelectType = 1 x ExpectedMood = 2 | ||||
AofAGroup = 2 x MoodSelectType = 2 x ExpectedMood = 1 | ||||
AofAGroup = 2 x MoodSelectType = 2 x ExpectedMood = 2 | ||||
|
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1 | |
2 | Four of the LCIs were born in the US but then moved to a Spanish-speaking country during very early childhood, specifically, at the ages of (a) 3 weeks old (Participant 61), (b) 2 months old (Participant 11), (c) 2 years old (Participant 75) and (d) 4 years old (Participant 75). Participant 11 and Participant 75 may have been exposed to some English early in childhood. However, given that both of these participants lived with monolingual, Spanish-speaking parents during these short stints in the US, it is unlikely that they received anything more than minimal English exposure at home. |
3 | A reviewer suggests that it would have been better for the sentence fragments in the presuppositional ARC condition, such as (7), to begin with the verb, busco (‘I look for’), as in the -Presupposition items. While doing so would make the items in the presuppositional ARC and non-presuppositional ARC conditions more similar structurally, it is not necessary to have structurally identical items, respectively, in order to show that HSs are sensitive to mood in ARCs. If HSs produce more subjunctive mood in sentences like (6a-b) than in sentences like (7), then it is clear that their production of mood is modulated by the presence or absence of presupposition. |
4 | An odds-ratio (OR), as the name suggests, is simply the ratio between two odds. If a group’s probability of producing subjunctive in Condition A is 80 percent—which can be expressed in odds as ‘4’ (80/20 = 4)—and their predicted probability of producing subjunctive in Condition B is 50 percent—which can be expressed in odds as ‘1’ (50/50 = 1)—then the odds ratio between these two conditions is 4 (4/1 = 4). |
5 | The variable ExpectedMood simply refers to the mood morphology that is expected in a given context, based on what is known about mood selection in monolingual and first-generation immigrant varieties of Spanish. Because para que, for example, obligatorily selects for subjunctive mood in these varieties, the para que condition is coded as ‘1’: SubjunctiveExpected. |
6 | In Section 2.2.1, I presented statistics showing that participants were no more likely to produce subjunctive in the “prime conditions” ((4b) and (6a)) than in the baseline conditions. Despite this finding, it is conceivable that participants, as a result of seeing target subjunctive forms in some experimental sentence fragments, may have produced more subjunctive with para que and in -PRE ARCs than what has been observed in previous studies. A quick comparison with the results of Giancaspro (2019), whose production task did not expose participants to any subjunctive primes, shows that this is not the case. The 12 IntHSs (55.5% with para que and 15.1% in -PRE ARCs) and 17 AdvHSs (88.9% with para que and 66.9% in -PRE ARCs) in Giancaspro (2019) produced very similar rates of subjunctive as compared to the IntHSs (53.5% with para que and 28.0% in -PRE ARCs) and AdvHSs (87.2% with para que and 73.4 in -PRE ARCs) in the present study. |
7 | Interestingly, though, HSs’ DELE proficiency scores were not correlated with the number of college Spanish courses that they had taken: EarlyHSs (r = 0.311, p = 0.224), LateHSs (r = 0.307, p = 0.188), IntHSs (r = 0.369, p = 0.160), AdvHSs (r = 0.259, p = 0.256). |
Condition | MoodSelection | Target Mood | # of Items |
---|---|---|---|
para que | Lexical | Subjunctive | 12 |
porque | Lexical | Indicative | 6 |
−PRE ARC | Contextual | Subjunctive | 12 |
+PRE ARC | Contextual | Indicative | 6 |
Condition | MoodSelection | Target Mood | # of Items |
---|---|---|---|
para que | Lexical | Subjunctive | 5 |
porque | Lexical | Indicative | 5 |
−PRE ARC | Contextual | Subjunctive | 5 |
+PRE ARC | Contextual | Indicative | 5 |
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Giancaspro, D. The Late(r) Bird Gets the Verb? Effects of Age of Acquisition of English on Adult Heritage Speakers’ Knowledge of Subjunctive Mood in Spanish. Languages 2019, 4, 69. https://doi.org/10.3390/languages4030069
Giancaspro D. The Late(r) Bird Gets the Verb? Effects of Age of Acquisition of English on Adult Heritage Speakers’ Knowledge of Subjunctive Mood in Spanish. Languages. 2019; 4(3):69. https://doi.org/10.3390/languages4030069
Chicago/Turabian StyleGiancaspro, David. 2019. "The Late(r) Bird Gets the Verb? Effects of Age of Acquisition of English on Adult Heritage Speakers’ Knowledge of Subjunctive Mood in Spanish" Languages 4, no. 3: 69. https://doi.org/10.3390/languages4030069