Top-Down Processing of Gender in Natural Second Language Acquisition Setting

TY - ABST

T1 - Top-Down Processing of Gender in Natural Second Language Acquisition Setting

AU - Tse, Alice Ping Ping

AU - Aguirrezabal Zabaleta, Manex

N1 - Conference code: 1

PY - 2018

Y1 - 2018

N2 - For speakers of languages without gender, the grammatical gender agreement places an extra difficulty during the course of acquisition. However, for words with incongruent genders in the native language and the target language, the case could be worse for learners of languages with gender as their first language. It is well-known that interference can appear in incongruent aspects of language. Our brain constantly influences the bottom-up processes with some updating from certain top-down processes during perception or recognition. Language processing for sure is very much affected by many top-down processes. The influence should be more pronounced for second language learners, as properties from their first language will greatly affect the processing of the second language, as we see in the studies of language transfer and interference. Recent studies by Paolieri et al. (2010, 2018) found significant difference between the response times of the two types of stimuli (congruent vs. incongruent) as the incongruity posed an extra processing load to the learners and resulted in a longer response time. They concluded that there should be a direct nonsemantic lexical route in the mental lexicon connecting the two languages at some specific grammatical level, being grammatical gender in this case. The current study aims to check whether results drawn from a formal experimental setup can be extrapolated to a more casual learning setting, and with a bigger dataset. We will employ the data presented for the Duolingo Shared Task on Second Language Acquisition Modeling (SLAM) (Settles et al., 2018). The dataset contains information about some simple exercises encoded in a format similar to the CONLL-U format. We will check if the students of our interest, namely Italian learners of Spanish, need significantly more time for the gender-incongruent trials.

AB - For speakers of languages without gender, the grammatical gender agreement places an extra difficulty during the course of acquisition. However, for words with incongruent genders in the native language and the target language, the case could be worse for learners of languages with gender as their first language. It is well-known that interference can appear in incongruent aspects of language. Our brain constantly influences the bottom-up processes with some updating from certain top-down processes during perception or recognition. Language processing for sure is very much affected by many top-down processes. The influence should be more pronounced for second language learners, as properties from their first language will greatly affect the processing of the second language, as we see in the studies of language transfer and interference. Recent studies by Paolieri et al. (2010, 2018) found significant difference between the response times of the two types of stimuli (congruent vs. incongruent) as the incongruity posed an extra processing load to the learners and resulted in a longer response time. They concluded that there should be a direct nonsemantic lexical route in the mental lexicon connecting the two languages at some specific grammatical level, being grammatical gender in this case. The current study aims to check whether results drawn from a formal experimental setup can be extrapolated to a more casual learning setting, and with a bigger dataset. We will employ the data presented for the Duolingo Shared Task on Second Language Acquisition Modeling (SLAM) (Settles et al., 2018). The dataset contains information about some simple exercises encoded in a format similar to the CONLL-U format. We will check if the students of our interest, namely Italian learners of Spanish, need significantly more time for the gender-incongruent trials.

M3 - Conference abstract for conference

T2 - International Conference on Predictive Processing

Y2 - 20 June 2018 through 22 June 2018

ER -