Banca de DEFESA: FERNANDA DAYANNE DAMASCENO CUNHA

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : FERNANDA DAYANNE DAMASCENO CUNHA
DATE: 27/07/2023
TIME: 10:00
LOCAL: https://uci.zoom.us/j/98530248147
TITLE:

AN INTERPLAY BETWEEN TASK COMPLEXITY, INDIVIDUAL DIFFERENCES AND SPEECH CONNECTEDNESS IN ADULT BILINGUALS

KEY WORDS:

Speech Connectedness; Task complexity; Working Memory Capacity; Speech Graphs.

PAGES: 100
BIG AREA: Linguística, Letras e Artes
AREA: Linguística
SUBÁREA: Psicolinguística
SUMMARY:

This thesis is situated in the field of applied linguistics and aims to investigate the effects of manipulating task complexity on speech connectivity, measured through attributes of speech graphs. Additionally, it seeks to gain a deeper understanding of the role of individual differences in Working Memory Capacity (WMC) and Theory of Mind (ToM) among participants. For this study, bilingual Brazilians (n=33) who have Portuguese as their first language (L1) and English as their second language (L2) were recruited, all of whom were regular students of the Access E2C English course. Participants who agreed to participate in the research signed a consent form prior to data collection. The protocols used in this study included: L2 oral production based on comic strips, divided into more and less complex tasks; a self-administered Reading Span Test (Oliveira et al., 2021) for WMC measures; and the Faux-Pas Test (Baron-Cohen, O'Riordan, Stone, Jones, & Plaisted, 1999) to assess participants' ToM levels. The data collected during the oral tasks were processed using the computational tool Speech Graphs (Mota et al., 2012, 2016, 2019) for speech graph generation. We conducted descriptive and inferential statistical analyses to address our research questions and hypotheses. Through the descriptive analysis of speech graphs and the attributes LSC (largest strongly connected component), LCC (largest connected component) e RE (repeated edges), we were able to spot tendencies. Namely, individuals tend to present a more connected speech when performing under the non complex condition. Despite finding medium to large effect size measures (Cohen's d) among the speech graph attributes under both complexity conditions, our inferential analysis confirmed that task complexity predicts only the attributes LCC and RE. In regard to our two other research question, we did not find any evidence of the relationship between WMC and ToM in speech connectedness under different task complexity conditions. Our results provide important considerations for future research and a deeper comprehension of the relationship between task complexity, speech connectedness and individual. Further research could aim at exploring the additional variables and refined the techniques used to measure individual differences in WMC and ToM.

COMMITTEE MEMBERS:
Presidente - 1666189 - JANAINA WEISSHEIMER
Interna - 1153427 - MAHAYANA CRISTINA GODOY
Externa à Instituição - MARA PASSOS GUIMARAES - UFMG
Externa à Instituição - NATALIA BEZERRA MOTA - UFRJ