A Longitudinal Study in the L2 Acquisition of the French TAM System
Abstract
:1. Introduction
2. The French, English and Spanish TAM Systems
- 1.
- Je ne peux pas y aller avec toi, je dois rendre ce rapport demain.No puedo ir contigo, tengo que entregar este informe mañana.‘I cannot go with you, I have to turn in this report tomorrow’.
- Je voudrais bien y aller avec toi, mais ce n’est pas possible.Me gustaría ir contigo, pero no puedo.‘I would like to go with you, but I can’t’.
- Tu aurais dû me le dire, je t’aurais aidé.Me lo tendrías que haber dicho, te hubiera ayudado.‘You should have told me, I would have helped you’.
- 2.
- Elle a échoué à ses examens parce qu’elle était malade.Suspendió sus exámenes porque estaba enferma.‘She failed her exams because she was sick’.
- Je suis triste qu’elle soit malade.Me apena que esté enferma.‘I’m sad that she is sick’.
- Il est dommage vous n’ayez pas pu venir avec nous.Es una lástima que no pudiera venir con nosotros.‘It’s a pity that you couldn’t come with us’.
- 3.
- Elle pense que c’est-IndPrespossible/*ce soit-SubjPrespossible.‘She thinks it’s possible’
- Elle ne pense pas que c’est-IndPresvrai/ce soit-SubjPresvrai.‘She does not think it’s true’
- Pense-t-elle que c’est intéressant-IndPres/ce soit-SubjPresintéressant?‘Does she think it’s interesting?’
- 4.
- Paul cherche un traducteur qui sait-IndPres/sache-SubjPres/saurait-CondPresl’arabe.‘Paul is looking for a translator who knows Arabic’.
- Lisa aimerait travailler avec des collègues qui la respectent-IndPres- SubjPres/respecteraient-CondPres.‘Lisa would like to work with colleagues who respect her’.
- 5.
- They insist that all the students sign up for a counselor.
- They insist that this student sign up for a counselor
- 6.
- The customer is demanding that the stores return his money.
- The customer demanded that the store return his money
- 7.
- We insist that he be the one to make the call.
- The customer demanded that his money be returned.
- 8.
- We insist that he not make the telephone call.
- *We insist that he do/does make the telephone call.
- 9.
- Estaba caminado sola, no sé por qué.Elle marchait seule, je ne sais pas pourquoi.‘She was walking by herself, I don’t know why’.
- Estoy pensando en este nuevo proyecto.Je suis en train de réfléchir à ce nouveau projet.‘I’m thinking about this new project’.
- Estaba cocinando la cena.Il préparait/était en train de préparer le dîner.‘He was cooking dinner’.
- 10.
- Quand je vivais à Nice, je jouais au tennis en été.Cuando vivía en Nice, jugaba al tenis durante el verano.‘When I lived in Nice, I would play tennis in the summer’.
- 11.
- Lo han vendido.Ils l’ont vendu.‘They have sold it’.
- Han empezado a construir la casa nueva.Ils ont commencé à construire la nouvelle maison.‘They have started to build the new house’.
- Hace much tiempo que lo conozco.Je le connais depuis longtemps.‘I have known him for a long time’.
- 12.
- Sophie est sortie-pc avec ses amis hier soir.Sophie went out with her friends last night.
- Sophie sort-IndPres avec ses amis de temps en temps.Sophie has been going out with her friends once in a while.
3. Literature Review of French TAM Studies
4. Learnability Issues and Research Questions
5. Materials and Methods
5.1. Participants
5.2. Classroom Setting and Materials
5.3. Procedure and Tasks
6. Results
7. Discussion
- 13.
- Une âme sœur est-IndPresquelqu’un qu’on aime-IndPres, et qui nous aide-IndPresàdevenir- InfPresla meilleure personne qu’on puisse- SubjPresêtre-InfPres.A soulmate is someone we love and who helps us to become the best person we can be’.
- 14.
- Donc la mort de Renée n’est-IndPrespas inutile parce qu’elle a- IndPresun but, la mort deRenée permet- IndPresque Paloma vive-SubjPres.‘So Renée’s death is not useless because it has a goal, Renée’s death allows Paloma to live’.
- 15.
- Tandis que tous les policiers déshumanisent-IndPresles juifs, un policier écoute- IndPresSarah et la laisse-IndPress’échapper-InfPresdu camp.‘While all the policemen dehumanize Jews, one policeman listens to Sarah and lets herflee the camp’.
- 16.
- Les concierges qui ont- IndPresdu courage et de la sympathie pour les familles juives etceux qui ont- IndPrespeur des policiers et qui sont-indpres coupables de dénoncer-InfPresles familles.‘Building managers who are brave and feel for the Jewish families, and those who areafraid of the policemen and who are capable of denouncing families’.
- 17.
- Quand elle est arrivée, elle a demandé de voir M. Lamarc, elle a dû attendre seulement quelquesminutes pour lui *apparaître-Infet *mener-Infelle à son bureau (essay 5, L1 English group)‘When she arrived, she asked to see Mr. Lamarc, she only had to wait a few minutes forhim to appear and show her to his office’
- 18.
- Si Julia n’avait pas trouvé-pqple secret de la famille de son mari, sa vie n’aurait sansdoute pas été touchée-CondPast.‘If Julia had not found her husband’s family, it would probably not have changed her life’.
- 19.
- Parce que leur famille avait déménagé-pqpdans l’appartement de Sarah il y a plusieursannées, Julia avait trouvé-pqple lien vers les deux familles.‘Because her family had moved into Sarah’s apartment several years ago, Julia had foundthe connection between the two families’.
- 20.
- Peut-être que si l’Holocauste n’a pas eu lieu-*pc/pqp, Sarah aurait vécu-CondPastune longuevie innocente.‘Maybe, if the Holocaust had not taken place, Sarah would have lived a long, innocentlife’.
- 21.
- Dans cette partie, on apprendra-futune chose secrète de chaque personnage et Jeannotrévèlera- futson vrai nom.‘In this part, we will learn a secret about each character and Jeannot will reveal his realname’.
- 22.
- Dans mon film, je vais changer-FutProle rôle de Marcel Langer un peu, et l’acteur quipeut-IndPrescompléter-InfPresce personnage est-IndPresGerard Butler.‘In my movie, I’m going to change the role of Marcel Langer a bit, and the actor who cancomplete this character is Gerard Butler’.
- 23.
- Par contre, le petit frère de Sarah n’avait pas été trouvé-pqp, car il s’était caché-pqpet Sarah nousracontera-futles malheurs et sentiments qu’elle a ressentis-pcdurant plus d’un mois.‘On the other hand, Sarah’s little brother was not found because he hid and Sarah will tellus about the misfortunes and feelings she experienced for over a month’.
- 24.
- Quand sa famille a été soudainement arrêtée-pc pour la déportation, Sarah a verrouillé-pcson petitfrère Michel dans le placard de sorte qu’il serait-*CondPressûr et caché jusqu’à ce qu’elle puisse-SubjPresretourner-InfPresle sauver-InfPres.‘When her family was suddenly arrested to be deported, Sarah locked up her little brotherMichel in the closet so that he would be safe and hidden until she could come back andsave him’.
- 25.
- J’ai bien aimé-pcle livre, mais pour l’adapter-InfPrespour le cinéma il faut-IndPresque jechangerais-*CondPres/SubjPresplusieurs parties de l’histoire.‘I liked the book, but to turn it into a movie, I need to change several parts of the story’.
- 26.
- Renée est-IndPresune veuve et concierge qui a travaillé-*pc/IndPresdans l’appartement depuis27 ans, mais elle cache-IndPresqu’elle aime- IndPresla philosophie, Ia litterature, la gastronomieet la musique classique parce qu’elle croit- IndPresque les residents ne voudraient-CondPrespascela.‘Renée is a widow and building manager who has been working for 27 years, but she hides that she likes philosophy, literature, gastronomy, and classical music because shethinks that the residents would not like it’.
- 27.
- François avait toujours imaginé-pqpque ses parents sportifs se sont rencontrés-*pc/pqpau bordde la piscine ou au stade et qu’il avait-imp un frère, jusqu’un jour il a appris-pcla vérité.‘François had always imagined that his athletic parents had met by the pool or thestadium and that he had a brother until he learned the truth one day’.
8. Conclusions
Funding
Conflicts of Interest
Appendix A. Essays’ Topics [Translated from French]
- Essay 1. Oscar et la dame rose
- Essay 2. Un secret
- Essay 3. L’élégance de l’hérisson
- Essay 4. Elle s’appelait Sarah
- Essay 5. Adaptation of Les enfants de la liberté
- Essay 6. Choose one of the following movies: Il y a longtemps que je t’aime (Claudel 2008), Les choristes (Barratier 2004), La vie rêvée des anges (Zonca 1998). Take notes as you watch it, then write a 4–6 page short story.
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1 | As a marked mood necessary to express various modalities (i.e., the speaker’s attitude towards the utterance), the subjunctive is considered as a benchmark in the L2 acquisition of French. |
2 | |
3 | Izquierdo and Kihlstedt (2019) focuses even more narrowly on imparfait in written narratives by Hispanophone learners (n = 94). |
4 | Recasts are defined as a corrective reformulation of an erroneous utterance during a natural interaction, they are thus a form of implicit negative feedback e.g., (Spada 1997). |
5 | Un secret, novel by Philippe Grimbert (2007) and movie by Claude Miller (2007); Elle s’appelait Sarah, novel by Tatiana de Rosnay (2010) and movie by Gilles Paquet-Brenner (2010); Les enfants de la liberté, novel by Marc Lévy (2008), no film adaptation; Oscar et la dame en rose, novel and film by Eric Emmanuel Schmitt (2009); L’élégance du hérisson, novel by Muriel Barbéry (2009) and film by Mona Achache (2009). |
6 | The abbreviations used for the forms are as follows: IndPres (indicative present), PC (passé composé), IMP (imparfait), InfPres (infinitive present), PartPres (present participle), CondPres (conditional present), SubjPres (subjunctive present), PQP (plus-que-parfait), FutPro (future proche, near future), InfPast (infinitive past), CondPast (conditional past), PresProg (present progressive), SubjPast (past subjunctive), PS (passé simple), IMPProg (imparfait progressive), PastPart (past participle), FutProg (future progressive). |
7 | The forms were chosen because they were either frequent (i.e., indicative present, infinitive present, passé composé, imparfait, future) or provided a temporality and/or mood contrast (i.e., subjunctive present, plus-que-parfait, present participle, conditional present). |
8 | A General Linear Mixed Model (GLMM) was used to test for significant differences in mean error percentage for the fixed effects of groups, essays, and their interaction. Subject intercept was used as a random effect. A separate GLMM was conducted for each error type. |
9 | The appropriate verbal forms would be: Quand elle est arrivée, elle a demandé de voir M. Lamarc, elle a dû attendre seulement quelques minutes pour qu’il apparaisse-SubjPres et la mène-SubjPres à son bureau. |
10 | The Sonoran Mexican Spanish of our participants does not differ from European Spanish in its use of past aspectual distinctions or indicative-subjunctive alternation (Carvalho 2018, personal communication). |
11 | The 160 subjunctive tokens were used with the following triggers: de sorte que (n = 1), afin que (n = 2), après que (n = 1)—although it is followed by the indicative in prescriptive grammars, French native speakers use it with the subjunctive—bien que (n = 26), avant que (n = 6), pour que (n = 14), jusqu’à ce que (n = 17), que (n = 20), falloir (n = 6), aimer (n = 3), souhaiter (n = 1), vouloir (n = 34), ne pas croire (n = 1), le fait que (n = 2), noun/adjective que (n = 23), superlative (n = 3). |
L1 English n = 9 | Heritage French n = 4 | Heritage Spanish n = 3 | |
---|---|---|---|
gender | F (n = 7), M (n = 2) | F (n = 4) | F (n = 2), M (n = 1) |
age | 21 (20–22) | 22 (20–24) | 21.7 (20–23) |
college status | undergraduate | ||
college major | French (n = 5) | French (n = 2) | French (n = 3) |
age of onset | 15–17 | 0 | 15–17 |
L2 setting | instructed | home/instructed | instructed |
Francophone stay | no (n = 6) yes (n = 4) 6 weeks to a year | yes (n = 4) 4–12 years | no (n = 3) |
motivation | very to extremely motivated |
L1 English (n = 9) | Essay 1 | Essay 2 | Essay 3 | Essay 4 | Essay 5 | Essay 6 | Total Average |
---|---|---|---|---|---|---|---|
words | 8681 | 8704 | 8346 | 8859 | 9326 | 16,126 | 60,042 |
verbal tokens | 1289 | 1274 | 1277 | 1126 | 1193 | 2800 | 8959 |
IndPres | 815 | 691 | 827 | 527 | 626 | 1161 | 4647 |
IndPres % | 63.22% | 54.24% | 64.76% | 46.8% | 52.47% | 41.46 | 52% |
Errors | 36–4.41% | 9–1.30% | 9–1.08% | 16–3.03% | 8–1.27% | 44–3.78% | 122–2.65% |
PC | 110 | 197 | 114 | 223 | 104 | 673 | 1421 |
PC % | 8.53% | 15.46% | 8.92% | 19.8% | 8.71% | 24.03% | 15.9% |
Errors | 21–19.09% | 18–9.13% | 7–6.14% | 10–4.48% | 3–2.88% | 46–6.83% | 105–7.4% |
IMP | 97 | 186 | 82 | 143 | 39 | 322 | 869 |
IMP % | 7.52% | 14.6% | 6.42% | 12.7% | 3.26% | 11.5% | 9.7% |
Errors | 8–8.24% | 9–4.83% | 3–3.65% | 10–6.99% | 1–2.56% | 14–4.34% | 45–5.2% |
InfPres | 205 | 141 | 195 | 160 | 190 | 405 | 1296 |
InfPres % | 15.9% | 11.06% | 15.37% | 14.21% | 15.92% | 14.46% | 14.5% |
Errors | 27–13.17% | 9–6.38% | 11–5.64% | 14–8.75% | 11 -5.78% | 23–5.67% | 95–7.3% |
PartPres | 16 | 14 | 11 | 15 | 17 | 25 | 98 |
PartPres % | 1.24% | 1.18% | 0.86% | 1.33% | 1.42% | 0.003% | 1.09% |
Errors | 2–12.5% | 2–14.28% | 0–0% | 4–26.67% | 1–5.88% | 0–0% | 9–9.2% |
CondPres | 13 | 9 | 7 | 16 | 70 | 43 | 158 |
CondPres % | 1.01% | 0.71% | 0.55% | 1.42% | 5.86% | 1.53% | 1.76% |
Errors | 3–23.1% | 5–55.6% | 0–0% | 10–62.5% | 5–7.14% | 8–18.6% | 31–19.6% |
SubjPres | 12 | 13 | 18 | 7 | 24 | 14 | 88 |
SubjPres % | 0.93% | 1.02% | 1.41% | 0.62% | 2.0% | 0.5% | 0.98% |
Errors | 3–25% | 1–7.69% | 0–0% | 0–0% | 0–0% | 14–100% | 18–20.4% |
PQP | 4 | 3 | 3 | 15 | 0 | 49 | 74 |
PQP % | 0.31% | 0.23% | 0.23% | 1.33% | 0.0% | 1.75% | 0.82% |
Errors | 0–0% | 0–0% | 0–0% | 0–0% | 0–0% | 6–12.2% | 6–8.1% |
Future | 4 | 3 | 8 | 6 | 107 | 58 | 186 |
Future % | 0.31% | 0.23% | 0.63% | 0.53% | 8.96% | 2.07% | 2.07% |
Errors | 0–0% | 0–0% | 1–12.5% | 0–0% | 0–0% | 0–0% | 1–0.53% |
FutPro | 7 | 3 | 1 | 1 | 3 | 11 | 26 |
FutPro % | 0.54% | 0.23% | 0.078% | 0.089% | 0.25% | 0.39% | 0.29% |
Errors | 0–0% | 0–0% | 0–0% | 1–100% | 0–0% | 1–9.1% | 2–7.7% |
InfPast | 3 | 2 | 4 | 7 | 9 | 10 | 35 |
InfPast % | 0.23% | 0.15% | 0.31% | 0.62% | 0.75% | 0.35% | 0.39% |
Errors | 1–33.3% | 0–0% | 0–0% | 0–0% | 1–11.1% | 0–0% | 2–5.7% |
CondPast | 1 | 9 | 4 | 3 | 0 | 4 | 21 |
CondPast % | 0.07% | 0.71% | 0.31% | 0.26% | 0.0% | 0.14% | 0.23% |
PresProg | 1 | 1 | 0 | 0 | 1 | 3 | 6 |
PresProg % | 0.07% | 0.078% | 0.0% | 0.0% | 0.084% | 0.11% | 0.067% |
SubjPast | 1 | 1 | 0 | 2 | 0 | 6 | 10 |
SubjPast % | 0.07% | 0.078% | 0.0% | 0.18% | 0.0% | 0.21% | 0.11% |
Errors | 0–0% | 0–0% | 0–0% | 0–0% | 0–0% | 1–16.7% | 1–10% |
PS | 0 | 1 | 0 | 0 | 0 | 3 | 4 |
PS % | 0.0% | 0.078% | 0.0% | 0.0% | 0.0% | 0.11% | 0.044% |
Errors | 0–0% | 0–0% | 0–0% | 0–0% | 0–0% | 2–66.7% | 2–50% |
IMPProg | 0 | 0 | 2 | 0 | 0 | 0 | 2 |
IMPProg % | 0.0% | 0.0% | 0.15% | 0.0% | 0.0% | 0.0% | 0.022% |
Errors | 0–0% | 0–0% | 1–50% | 0–0% | 0–0% | 0–0% | 1–50% |
PastPart | 0 | 0 | 1 | 1 | 2 | 1 | 5 |
PastPart % | 0.0% | 0.0% | 0.078% | 0.089% | 0.16% | 0.03% | 0.056% |
FutProg | 0 | 0 | 0 | 0 | 1 | 0 | 1 |
FutProg % | 0.0% | 0.0% | 0.0% | 0.0% | 0.084% | 0.0% | 0.011% |
Imperative | 0 | 0 | 0 | 0 | 0 | 12 | 12 |
Imperative % | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.43% | 0.133% |
HL French (n = 4) | Essay 1 | Essay 2 | Essay 3 | Essay 4 | Essay 5 | Essay 6 | Total Average |
---|---|---|---|---|---|---|---|
words | 4872 | 5043 | 5532 | 5296 | 5071 | 9617 | 35,431 |
verbal token | 891 | 850 | 850 | 738 | 704 | 1703 | 5736 |
IndPres | 539 | 428 | 458 | 217 | 376 | 601 | 2619 |
IndPres % | 60.5% | 50.3% | 53.9% | 29.4% | 53.4% | 35.3% | 45.6% |
Errors | 4–0.74% | 6–1.4% | 2–0.43% | 1–0.46% | 2–0.53% | 25–4.2% | 40–1.5% |
PC | 62 | 109 | 60 | 134 | 63 | 239 | 667 |
PC % | 6.9% | 12.8% | 7.1% | 18.2% | 8.95% | 14.0% | 11.6% |
Errors | 2–3.2% | 5–4.6% | 3–5% | 5–3.73% | 2–3.2% | 15–6.3% | 32–4.8% |
IMP | 73 | 143 | 108 | 152 | 22 | 319 | 817 |
IMP % | 8.2% | 16.8% | 12.7% | 20.6% | 3.12% | 18.7% | 14.2% |
Errors | 1–1.4% | 6–4.2% | 7–6.5% | 17–11.2% | 2–9.1% | 11–3.4% | 44–5.4% |
InfPres | 180 | 128 | 171 | 158 | 152 | 407 | 1196 |
InfPres % | 20.2% | 15.1% | 20.1% | 21.4% | 21.59% | 23.9% | 20.85% |
Errors | 0–0% | 0–0% | 2–1.2% | 0–0% | 7–4.6% | 1–0.24% | 10–0.83% |
PartPres | 4 | 12 | 14 | 10 | 10 | 18 | 68 |
PartPres % | 0.44% | 1.41% | 1.64% | 1.35% | 1.42% | 1.1% | 1.18% |
Errors | 1–25% | 0–0% | 0–0% | 0–0% | 1 | 0–0% | 2–2.9% |
CondPres | 8 | 6 | 7 | 7 | 7 | 3 | 38 |
CondPres % | 0.89% | 0.71% | 0.82% | 0.95% | 0.99% | 0.01% | 0.66% |
Errors | 0–0% | 0–0% | 2–28.6% | 3–42.8% | 0–0% | 0–0% | 5–13.2% |
SubjPres | 7 | 5 | 6 | 4 | 7 | 20 | 49 |
SubjPres % | 0.78% | 0.58% | 0.71% | 0.54% | 0.99% | 1.17% | 0.08% |
PQP | 6 | 5 | 1 | 25 | 5 | 19 | 61 |
PQP % | 0.67% | 0.58% | 0.11% | 3.38% | 0.71% | 1.1% | 1.06% |
Errors | 0–0% | 0–0% | 0–0% | 2–8% | 0–0% | 0–0% | 2–3.3% |
Future | 4 | 9 | 19 | 9 | 51 | 12 | 104 |
Future % | 0.44% | 1.05% | 2.22% | 1.22% | 7.24% | 0.07% | 1.81% |
Errors | 0–0% | 1–11.1% | 0–0% | 1–11.1% | 0–0% | 2–16.7% | 4–3.8% |
FutPro | 2 | 0 | 1 | 2 | 4 | 8 | 17 |
FutPro % | 0.22% | 0.0% | 0.11% | 0.27% | 0.56% | 0.04% | 0.29% |
Errors | 0–0% | 0–0% | 0–0% | 1–50% | 0–0% | 0–0% | 1–5.9% |
InfPast | 0 | 1 | 3 | 2 | 2 | 2 | 10 |
InfPast % | 0.0% | 0.11% | 0.35% | 0.27% | 0.28% | 0.01% | 0.17% |
CondPast | 0 | 0 | 0 | 3 | 0 | 5 | 8 |
CondPast % | 0.0% | 0.0% | 0.0% | 0.41% | 0.0% | 0.02% | 0.13% |
SubjPast | 0 | 0 | 0 | 2 | 0 | 1 | 3 |
SubjPast % | 0.0% | 0.0% | 0.0% | 0.27% | 0.0% | 0.005% | 0.05% |
PS | 4 | 4 | 1 | 11 | 3 | 27 | 50 |
PS % | 0.44% | 0.47% | 0.11% | 1.49% | 0.42% | 1.58% | 0.87% |
Errors | 0–0% | 0–0% | 0–0% | 1–9.1% | 0–0% | 1–3.7% | 2–4% |
PastPart | 1 | 0 | 0 | 2 | 1 | 6 | 10 |
PastPart % | 0.11% | 0.0% | 0.0% | 0.27% | 0.14% | 0.03% | 0.17% |
Errors | 1–100% | 0–0% | 0–0% | 2–100% | 1–100% | 6–100% | 10–100% |
Imperative | 1 | 0 | 0 | 0 | 1 | 16 | 18 |
Imp. % | 0.11% | 0.0% | 0.0% | 0.0% | 0.14% | 0.09% | 0.32% |
ImpProg | 0 | 0 | 1 | 0 | 0 | 0 | 1 |
ImpProg % | 0.0% | 0.0% | 0.11% | 0.0% | 0.0% | 0.0% | 0.017% |
HL Spanish (n = 3) | Essay 1 | Essay 2 | Essay 3 | Essay 4 | Essay 5 | Essay 6 | Total/Average |
---|---|---|---|---|---|---|---|
word | 2849 | 3230 | 2946 | 3052 | 2815 | 5300 | 20,192 |
word average | 949.67 | 1076.67 | 982 | 1017.33 | 938.33 | 1766.67 | 6730.67 |
verbal token | 521 | 496 | 460 | 428 | 431 | 1041 | 3377 |
IndPres | 320 | 240 | 246 | 178 | 240 | 387 | 1611 |
IndPres % | 61.4% | 48.38% | 53.48% | 41.59% | 55.68% | 37.17% | 47.7% |
Errors | 10–3.1% | 7–2.9% | 2–.81% | 5–2.8% | 4–1.7% | 12–3.1% | 40–2.5% |
PC | 40 | 75 | 51 | 109 | 28 | 256 | 559 |
PC % | 7.78% | 15.12% | 11.16% | 25.46% | 6.49% | 24.61% | 16.6% |
Errors | 5–12.5% | 0–0% | 2–3.9% | 5–4.6% | 1–3.6% | 13–5.1% | 26–4.6% |
IMP | 21 | 64 | 64 | 31 | 2 | 109 | 291 |
IMP % | 4.03% | 12.9% | 13.91% | 7.24% | 0.46% | 10.47% | 8.62% |
Errors | 1–4.76% | 4–6.25% | 19–29.7% | 3–9.7% | 0–0% | 5–4.6% | 32- 10.9% |
InfPres | 112 | 91 | 76 | 78 | 72 | 197 | 626 |
InfPres % | 21.5% | 18.34% | 16.52% | 16.22% | 16.71% | 3.58% | 18.53% |
Errors | 8–7.1% | 9–9.9% | 4–5.3% | 3–3.8% | 0–0% | 2–1.0% | 26–4.2% |
PartPres | 3 | 3 | 3 | 5 | 3 | 6 | 23 |
PartPres % | 0.57% | .60% | 0.65% | 1.16% | 0.69% | 0.57% | 0.68% |
Errors | 0–0% | 0–0% | 1–33.3 | 0–0% | 0–0% | 0–0% | 1–4.3% |
CondPres | 3 | 3 | 3 | 2 | 13 | 19 | 43 |
CondPres % | 0.57% | .60% | 0.65% | 0.46% | 3.02% | 1.82% | 1.27% |
Errors | 0–0% | 1–33.3% | 2–66.7% | 1–50% | 0–0% | 3–15.8% | 7–16.3% |
SubjPres | 4 | 5 | 3 | 5 | 8 | 16 | 41 |
SubjPres % | 0.76% | 1.0% | 0.65% | 1.16% | 1.86% | 1.53% | 1.21% |
Errors | 1–25% | 1–20% | 0–0% | 0–0% | 0–0% | 2–12.5 | 4–9.7% |
PQP | 2 | 7 | 3 | 8 | 0–0% | 12 | 32 |
PQP % | 0.38% | 1.41% | 0.65% | 1.86 | 0.0% | 1.15% | 0.94% |
Future | 3 | 2 | 7 | 3 | 57 | 15 | 87 |
Future % | 0.57% | 0.40% | 1.52% | 0.7% | 13.22% | 1.44% | 2.57% |
Errors | 2–66.7% | 1–50% | 0–0% | 1–66.7% | 0–0% | 2–13.3% | 6–6.9% |
FutPro | 9 | 2 | 1 | 2 | 3 | 8 | 25 |
FutPro % | 1.72% | 0.40% | 0.21% | 0.46% | 0.69% | 0.77% | 0.74% |
Errors | 2 | 0–0% | 0–0% | 0–0% | 0–0% | 0–0% | 2–8.0% |
InfPast | 3 | 2 | 0 | 5 | 3 | 7 | 20 |
InfPast % | 0.57% | 0.40% | 0.0% | 1.16% | 0.69% | 0.67% | 0.59% |
CondPast | 0 | 0 | 0 | 1 | 0 | 3 | 4 |
CondPast % | 0.0% | 0.0% | 0.0% | 0.23% | 0.0% | 0.29% | 0.12% |
PresProg | 0 | 0 | 1 | 0 | 1 | 0 | 2 |
PresProg % | 0.0% | 0.0% | 0.21% | 0.0% | 0.23% | 0.0% | 0.06% |
SubjPast | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
SubjPast % | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.09 | 0.03% |
Imperative | 1 | 0 | 0 | 0 | 1 | 1 | 3 |
Imperative % | 0.19% | 0.0% | 0.0% | 0.0% | 0.23% | 0.09 | 0.89% |
Past participle | 0 | 2 | 0 | 1 | 0 | 0 | 3 |
Past participle % | 0.0% | 0.40% | 0.0% | 0.23% | 0.0% | 0.0% | 0.89% |
InfPresProg | 0 | 0 | 2 | 0 | 0 | 0 | 2 |
InfPresProg % | 0.0% | 0.0% | 0.43% | 0.0% | 0.0% | 0.0% | 0.06% |
ImpProg | 0 | 0 | 0 | 0 | 0 | 3 | 3 |
ImpProg % | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.29% | 0.89% |
RecentPast | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
RecentPast % | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.09 | 0.03% |
L1 English | HL French | HL Spanish | ||||
---|---|---|---|---|---|---|
Erroneous Tokens | Percentage | Erroneous Tokens | Percentage | Erroneous Tokens | Percentage | |
IndPres | 122 | 2.65% | 40 | 1.5% | 40 | 2.5% |
PC | 105 | 7.4% | 32 | 4.8% | 26 | 4.6% |
IMP | 45 | 5.2% | 44 | 5.4% | 32 | 10.9% |
InfPres | 95 | 7.3% | 10 | 0.83% | 26 | 4.2% |
PartPres | 9 | 9.2% | 68 | 1.18% | 1 | 4.3% |
CondPres | 31 | 19.6% | 5 | 13.2% | 7 | 16.3% |
SubjPres | 18 | 20.4% | 0 | 0% | 4 | 9.7% |
PQP | 6 | 8.1% | 2 | 3.3% | 0 | 0% |
Future | 1 | 0.53% | 4 | 3.8% | 6 | 6.9% |
PastPart | 5 | 0.56% | 10 | 100% | 0 | 0% |
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Ayoun, D. A Longitudinal Study in the L2 Acquisition of the French TAM System. Languages 2020, 5, 42. https://doi.org/10.3390/languages5040042
Ayoun D. A Longitudinal Study in the L2 Acquisition of the French TAM System. Languages. 2020; 5(4):42. https://doi.org/10.3390/languages5040042
Chicago/Turabian StyleAyoun, Dalila. 2020. "A Longitudinal Study in the L2 Acquisition of the French TAM System" Languages 5, no. 4: 42. https://doi.org/10.3390/languages5040042
APA StyleAyoun, D. (2020). A Longitudinal Study in the L2 Acquisition of the French TAM System. Languages, 5(4), 42. https://doi.org/10.3390/languages5040042