Publikationsdatenbank

Insights from social network analysis in second language acquisition (2021)

Art

Vortrag

Autoren

Paradowski, Michal B.

Jarynowski, Andrzej (WE 16)

Ochab, Jeremi

Chen, Chih-Chun

Czopek, Karolina

Jelińska, Magdalena

Cierpich, Agnieszka

Kongress

Linguists’ Day of the Belgian Society of Linguistics

Brüssel, 22.10.2021

Quelle

Linguists’ day of the Belgian Society of Linguistics : Vrije Universiteit Brussel, 22 October 2021 : book of abstracts — Thomas Hoelbeek, Laura Rosseel (Hrsg.)

Brüssel, 2021 — S. 43

Sprache

Englisch

Verweise

URL (Volltext): https://sites.uclouvain.be/bkl-cbl/?smd_process_download=1&download_id=%2037263

Kontakt

Institut für Veterinär-Epidemiologie und Biometrie

Königsweg 67
14163 Berlin
+49 30 838 56034
epi@vetmed.fu-berlin.de

Abstract / Zusammenfassung

Social networks play a vital role in the attainment of individuals. Using computational social network analysis (SNA), we investigate the influence of peer interaction dynamics and social graph topology on measurable outcomes in two intensive language courses: a 5-week course of German for Erasmus+
exchange students in Baden-Württemberg (n=40), and a 4-week summer course of the Polish language and culture in Warsaw (n=181). Unlike studies focusing on the micro-level of individual participants’ egocentric networks, thus presenting an emic view only, we show how and why peer learner networks can be examined in their entirety, complementing an etic perspective (Paradowski et al., 2021a, b).
We find among others i) that the best predictor of (both self-reported and independently measured) progress is reciprocal interactions between students in the language being acquired, ii) that outgoing interactions in the TL are a stronger predictor than incoming interactions, iii) a clear negative relationship
between performance and interactions with same-L 1 speakers, iv) (in the German course) a significantly underperforming English native-speaker dominated cluster, and v) that more intense interactions take place between students of different levels of proficiency. vi) Analyses of the various standard centrality measures vis-à-vis performance in turn reveal that the influence of the network is strongest in the domains of pronunciation and lexis, where the simplest measure of degree centrality in TL positively correlates with progress, while betweenness in total communication is significantly anticorrelated. vii) This mirrors the influence direction—on global TL progress—of closeness centrality (ease of access to other students). Combined with the detrimental impact on SLA of a high in-degree, this suggests that viii) for language acquisition via social interaction, the structural properties of the network matter more than processes such as information flow.