Different Language Knowledge but Similar Language-Learning Patterns in Bilingual Children Screened on the QUILS: English-Spanish

• In Event: 2-185 - Measuring School Readiness Skills of Dual Language Learners: Development and Validation of Assessment Tools

Integrative Statement

Children learning more than one language must uncover the unique regularities of each language. Just as there is variability in the course of language development for monolingual children (Hart & Risley, 1995; Hoff, 2003; Hurtado, Marchman, & Fernald, 2008), there is variability for Dual Language Learners (DLLs) in the development of each language. Sources of variability include differences in skills used to acquire each language and nonequivalent learning environments for the two languages (Bohman et al., 2010). This paper examines DLLs’ performance on the Quick Interactive Language Screener: English–Spanish (QUILS:ES) to address how we can 1) capture variability when screening DLLs’ language knowledge and 2) compare language-learning patterns across DLLs’ languages.
First, how can screening DLLs capture their language knowledge given that bilingualism lies on a continuum (mostly Spanish—mostly English) and given that developing language knowledge may be distributed unevenly across languages (Hoff et al., 2012)? We reasoned that risk for language impairment is best estimated with Best Scores, computed by summing the best score across languages on each aspect of language. Less than 2% of preschoolers tested on QUILS:ES (N=364) performed “best” on all the vocabulary and syntax subtests in a single language. Most DLLs had vocabulary and syntax knowledge that was distributed between their languages, supporting the strength of this measure for capturing DLLs’ language skill.
Second, how do language-learning patterns compare across DLLs’ two languages and relative to monolinguals? Two QUILS:ES subtests provide an ideal test of this question. One subtest evaluates the process by which children home in on a novel noun’s referent. Do children track multiple possible meanings of words via “cross-situational learning” (Yu & Smith, 2007), or do they track a single hypothesized meaning for each word via a “propose-but-verify” strategy (Trueswell et al., 2013)? DLLs (N=568) were tested on 4, two-trial “fast mapping” items in each language. Trial 1 presented a novel noun with 4 choices including the target nonce object; Trial 2 tested extension of the word to another exemplar. Similar to monolingual children, DLLs’ success on Trial 2 depended on Trial 1 success (Figure 1), supporting the “propose-but-verify” word-learning model in DLLs, in both languages.
Another QUILS:ES subtest examines how DLLs interpret tensed and untensed embedded clauses. In English, preschool-aged children are better able to interpret untensed clauses (e.g., “What did Mom say to buy”) than tensed clauses (e.g., “What did Mom say she bought”). Is this also true for both languages of DLLs, even though Spanish shows more equivalence in form between these classes? DLLs (N=563) were tested on 4 “embedded clause” items in each language (2 tensed, 2 untensed). Complementation type was a significant predictor of performance (Figure 2), indicating that the development of this syntactic understanding is comparable for monolingual children and DLLs, for both of their languages.
In sum, the QUILS:ES can inform questions of linguistic interest and serve as a reliable screener for DLLs. Given that monolingual norms over-identify bilingual children at risk for language difficulties (Paradis, 2005), the QUILS:ES should ameliorate this problem.

Authors

• Aquiles Iglesias, University of Delaware
  Presenting Author

• Jill de Villiers, Smith College
  Non-Presenting Author

• Dani Levine, Temple University
  Non-Presenting Author

• Kathy Hirsh-Pasek, Temple University
  Non-Presenting Author

• Roberta Michnick Golinkoff, Univ of DE
  Non-Presenting Author

• Mary Sweig Wilson, University of Vermont & Laureate Learning Systems
  Non-Presenting Author