Modeling Input Factors in Second Language Acquisition of the English Article Construction

Abstract

Based on the Competition Model, the current study investigated how cue availability and cue reliability as two important input factors influenced second language (L2) learners' cue learning of the English article construction. Written corpus data of university-level Chinese-L1 learners of English were sampled for a comparison of English majors and non-English majors who demonstrated two levels of L2 competence in English article usage. The path model analysis in structural equation modeling was utilized to investigate the relationship between the input factors and L2 usage (frequency and accuracy of article cue production). The findings contribute novel and scarce empirical evidence that confirms a central claim of the Competition Model, i.e., the changing importance of cue availability and cue reliability in the frequency and accuracy of production. Cue availability was found to determine L2 production frequency regardless of level of L2 competence. Cue reliability was the input factor that differentiated competence levels. When learners stayed at a relatively lower L2 proficiency, cue reliability played an important role in influencing L2 frequency of usage rather than accuracy of usage. When learners developed increased exposure to and stronger competence in the target language, cue reliability played a significant role in determining learners' success of cue learning. The study is methodologically innovative and expands the empirical applicability of the Competition Model to the domain of second language production and construction learning.

Estimating Cue Strengths in Oral Production in a Japanese Learner Corpus

“…In sum, case marking was one of the most reliable cues in native speakers' speech, and this was mirrored in learners' speech, matching the first scenario in Section The Current Study. While this study was not designed to demonstrate the direct relationship between input properties and production or to demonstrate the actual learning process, the results corroborate Zhao and Fan (2021), who showed using statistical modeling that the cue reliability in the input was a reliable predictor of L2 learning.…”

“…Second, by analyzing spontaneous production by learners, the study demonstrates how learners themselves use the cues of word order, case marking, and animacy to express transitive relations, extending the prior work within the framework of the competition model that has focused on comprehension. As far as I know, the recent study by Zhao and Fan (2021) was the first to investigate both the input and production in L2 learning (they used written production data while the current study used oral production data), and as they suggested, "[l]anguage production is perhaps the area that has the most urgent need for more empirical data" (p. 4).…”

“…Lastly, the cue strengths will be adjusted to match the native speakers of the target language over time (MacWhinney, 2005). One of the possible correlates is proficiency (e.g., McDonald and Heilenman, 1991;Sasaki, 1994;Pham and Ebert, 2016;Zhao and Fan, 2021). For example, Sasaki (1994) found that L1-English learners come to rely more on case markers as their proficiency improves.…”

“…While most work in the competition model framework has used data from sentence interpretation experiments, the model addresses both comprehension and production (Bates and Devescovi, 1989;Zhao and Fan, 2021). In addition, calculating cue validity in corpora can offer a more precise picture of the relative importance of cues, which should be informative for experimenters (Bates and MacWhinney, 1989).…”

“…In addition, calculating cue validity in corpora can offer a more precise picture of the relative importance of cues, which should be informative for experimenters (Bates and MacWhinney, 1989). McDonald (1987), McDonald and Heilenman (1991), Kempe and MacWhinney (1998), Chan et al (2009), Tanaka and Shirai (2014), and Zhao and Fan (2021), for example, have used corpus data to estimate cue strengths. The current study follows these studies by using the competition model framework to analyze learner corpus data.…”