Abstract
This review contributes to the current debate on cross-linguistic influence in third language (L3) acquisition in unbalanced bilingual heritage speaker contexts. It compares findings resulting from the project “Multilingual Development: A Longitudinal Perspective (MEZ)”, with pivotal other studies. Recently, surprisingly little cross-linguistic influence was reported to originate in the heritage languages, there being only minor differences between monolinguals’ and bilingual heritage speakers’ performance in the additional language English. The current aim is to present evidence that argues for the importance of including extralinguistic variables such as socio-economic status or school type in L3 acquisition studies.
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Notes
- 1.
E-LiPS (English LiMA Panel Study), a subproject of the Linguistic Diversity Management in Urban Areas (LiMA) Panel Study (LiPS), conducted at the University of Hamburg from 2009 until 2013 (Linguistic Diversity Management in Urban Areas, 2009–2013, directed by Peter Siemund and Ingrid Gogolin) was the project preceding MEZ. Similar to MEZ, just on a smaller scale but with one additional cohort of students (Vietnamese-German bilinguals), the goal of LiPS was to document the linguistic development of bilingual school children. The study focused on the proficiency in the heritage languages and the proficiency in German, the language of the environment and language of instruction in school. E-LiPS was the extension of this study and focused additionally on foreign language acquisition.
- 2.
As unstandardized effect size measures (e.g., regression coefficients or differences in group means) are difficult to interpret, we only report standardized estimates and indicate polarity and relative size of unstandardized estimates.
- 3.
Hopp et al. (2019, p. 105) report small positive β values for ‘Gender female’ with p-values larger than .05. Maluch and Kempert (2019, p. 878) report small negative estimates for ‘Gender (girls)’ for a multiple regression analysis explaining listening comprehension in English and small positive estimates for explaining reading proficiency. However, none of these reaches statistical significance.
- 4.
Lorenz et al. (2020, p. 198) report a small statistically significant negative estimate for ‘Gender: male’ for a regression model explaining English proficiency based on C-test scores which includes German monolingual, as well as Russian-German and Turkish-German bilinguals. In a second regression model, which is based on the bilingual participants only, this variable was not included as it was not among the relevant predictor variables when fitting the model.
- 5.
Wilden and Porsch (2016, p. 206) report standardized estimates of -.05 and -.06 for ‘Gender’ for multilevel regression analyses assessing listening comprehension and reading comprehension, respectively, acknowledging a very small lead for the female students.
- 6.
Lorenz et al. (2021a) report a statistically significant negative estimate for ‘measurement point’ in a regression analysis predicting the frequency of normalized lexical transfer tokens.
- 7.
Maluch et al. (2016, p. 115) report positive estimates (all statistically significant) for mixed dominant German, mixed dominant non-German, and non-German only students for a regression model predicting English language achievement in school year six (reference group: German monolingual students). In school year eight, only the positive estimate for the mixed dominant German group reaches statistical significance; the other two bilingual groups do not outperform the monolingual German students anymore.
- 8.
This is clearly a simplification and should be investigated in a more differentiated manner, but such a discussion would go beyond the scope of this paper.
- 9.
To quote just one example, Lorenz (2019, pp. 234, 336–337) reports a small statistically significant positive estimate for ‘School type: other’ in a regression analysis predicting the ratio of missing 3rd person singular -s morphemes.
- 10.
Lorenz et al. (2020, pp. 198–199) report a large statistically significant negative estimate for ‘School: other’ in a regression analysis predicting English C-test scores.
- 11.
Lorenz et al. (2019, p. 194) report a very small but significant positive effect size based on an analysis of variance of SES (F(2, 1512) = 88.62, p < .001 η2 = 0.10).
- 12.
Lorenz et al. (2021b, p. 283) report a statistically significant standardized path coefficient of 0.32 for SES contributing to the latent variable ‘background’ in a structural equation model predicting English proficiency based on English C-test scores.
- 13.
Lorenz et al. (2020, p. 213) add in a footnote that “the estimate of the socioeconomic status (HISEI), when included in the regression model, turned out to be extremely small (.004) at a significance level of p = .756”.
- 14.
Lorenz et al. (2020, p. 198) report a statistically significant positive estimate for ‘cognitive ability test’ in a regression analysis predicting English proficiency based on C-test scores.
- 15.
The respective standardized path coefficient is 0.639 (Lorenz et al. 2021b, p. 283).
- 16.
Berthele and Udry (2022, p. 154) report a standardized path coefficient of 0.58 between the latent construct ‘cognition’ and English proficiency based on the Oxford young learners’ placement test in a structural equation model called ‘general cognition model’.
- 17.
For example, Lorenz et al. (2020, p. 198) report a statistically significant negative estimate for the Turkish-German bilinguals in a regression analysis predicting English proficiency based on C-test scores.
- 18.
Lorenz et al. (2021a, p. 805) report a statistically significant negative estimate for the Turkish-German bilinguals in a regression analysis predicting the frequency of normalized lexical transfer tokens.
- 19.
Maluch et al. (2015, p. 81) report a positive estimate of 1.02 (not statistically significant) for the group of Arabic-German bilinguals for a regression model explaining English achievement. As a comparison, the estimates for Chinese-German (6.08), Polish-German (6.80), Turkish-German (5.01) and other bilingual students (3.71) reach statistical significance.
- 20.
Maluch and Kempert (2019, p. 876) report intermediate effects between bilinguals who received heritage language instruction and bilinguals who did not when comparing listening comprehension (d = 0.63) and reading proficiency (d = 0.56) in English.
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Lorenz, E., Feindt, K., Rahbari, S., Siemund, P. (2022). The Influence of Extralinguistic Variables on Cross-Linguistic Influence in Contexts of Bilingual Heritage Speakers: A Summary of Topical Research Findings. In: Brandt, H., Krause, M., Usanova, I. (eds) Language Development in Diverse Settings. Edition ZfE, vol 11. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-35650-7_10
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