Language Profile LEAP-Q

To gain more insight into the participants’ language profiles, all of them filled out an adapted version of the Language Experience and Proficiency Questionnaire (Marian et al., 2007). Generally, the 89 minority-language-speaking bilinguals showed a significant effect of language, F (2, 264) = 377.80, p < 0.001, ηp2 = 0.741, on the proficiency self-evaluation, in that the mean score of the L1 Uyghur (M = 8.97, SD = 1.18) was higher than the L2 Chinese (M = 7.83, SD = 1.33). The preference for language use was significantly different between the two languages, F (2, 264) = 271.46, p < 0.001, ηp2 = 0.673, with the average preference for using L1 (M = 49.30%, SD = 15.90) being larger than L2 (M = 43.80%, SD = 14.00). There was also a significant difference, F (2, 264) = 253.74, p < 0.001, ηp2 = 0.658, in the frequency of language exposure in that the L1 Uyghur (M = 48.66%, SD = 14.53) was more exposed to it than the L2 Chinese (M = 40.51%, SD = 12.64).

Self-evaluated language proficiency and language use preference (see Table 1) were taken into consideration as indices to assess the overall relative language strength of Uyghur (L1) and Chinese (L2). The reason for including self-reported preference in the calculation of language dominance is that this factor was suggested by previous studies as being part of the individual differences that represented bilingual language dominance (Silva-Corvalán and Treffers-Daller, 2015; Caffarra et al., 2016). Our dominance measure shares similarities with the four criteria (i.e., language history, use, proficiency and attitude) that are part of the Bilingual Language Profile (BLP; Birdsong et al., 2012), a standardised language dominance profile measure. The element of language use preference in our measure is an index for personal language attitude towards one language in actual use, which can be viewed as an adaptation of language use and attitude from the BLP. The language proficiency criterion in the BLP was adopted in our measure to represent the participants’ language skills as well. Our measure only excludes the dimension of language history because the target bilinguals acquire the same L1 and L2 (Uyghur and Chinese languages) from the same region and the homogeneity of bilinguals has limited the variation in the dimension of language history. Therefore, it is a reliable approach to use language proficiency and language use preference as the dominance measure. Language proficiency was self-rated on an 11-point scale from the score of 0 to 10 for each literacy skill and for each language. Language use preference was scaled in percentages to indicate the use frequency of L1, L2 and L3 in the following scenarios: reading a book, having a conversation and writing a letter. The sum of the preference percentages for different languages in each scenario should equal 100%. For instance, when reading a book, a bilingual might prefer to read 55% of the time in L1, 35% of the time in L2 and the remaining 10% in L3. Given that both language proficiency and language use preference are the two dimensions that we used to evaluate language dominance, the scale had to be unified by transforming the language use percentage into a score on the same scale as proficiency. In the first step, the three proficiency scores (L1, L2 and L3) for each literacy skill were added. For instance, if one participant evaluates the score of his/her reading skill as 10 for L1, 8 for L2 and 5 for L3, the sum score for reading would be 23. In the second step, the overall score for each literacy skill was multiplied by the percentage of language use preference, yielding a separate score for each language. For instance, in case the same individual reported the following language use preferences, L1 (55%), L2 (35%) and L3 (10%), when reading a book, these percentages of language use preference in the reading scenario were transformed into scores of 12.65 (23^*0.55) for L1, 8.05 (23^*0.35) for L2 and 2.3 for L3 (23^*0.10). Thus, based on this method, there were three transformed scores for each language that indicated the language use preference for reading books, engaging in conversation and writing letters. Additionally, four proficiency scores (two productive and two receptive skills) existed for each language. In total, each participant was assigned seven scores for each language. The strength of each language could be represented by a composite score, that is, the sum of all seven scores. To measure each participant’s language dominance, the first step was to obtain an index of dominance by subtracting the composite score for Chinese from the score for Uyghur. The second step was to convert the index of dominance into a z-score, which was used as the final dominance score. The above measurement of language dominance followed the operationalisation proposed in a previous study by Treffers-Daller and Korybski (2015). In the present study, the final dominance score (z-score) varied from −2.37 to 2.59, with a mean of 0. As a continuous scale, the closer to or higher than +1 the final dominance score is, the more L1-dominant the bilingual is; the closer to or lower than −1 it is, the more L2-dominant the bilingual is.

Mean scores and standard deviations (in parenthesis) for language experience background information of bilingual participants.