Granularity and the acquisition of grammatical gender: How order-of-acquisition affects what gets learned

Abstract

Why do adult language learners typically fail to acquire second languages with native proficiency? Does prior linguistic experience influence the size of the "units" adults attend to in learning, and if so, how does this influence what gets learned? Here, we examine these questions in relation to grammatical gender, which adult learners almost invariably struggle to master. We present a model of learning that predicts that exposure to smaller units (such as nouns) before exposure to larger linguistic units (such as sentences) can critically impair learning about predictive relations between units: such as that between a noun and its article. This prediction is then confirmed by a study of adult participants learning grammatical gender in an artificial language. Adults learned both nouns and their articles better when they were first heard nouns used in context with their articles prior to hearing the nouns individually, compared with learners who first heard the nouns in isolation, prior to hearing them used in context. In the light of these results, we discuss the role gender appears to play in language, the importance of meaning in artificial grammar learning, and the implications of this work for the structure of L2-training.

Distributional learning of subcategories in an artificial grammar: Category generalization and subcategory restrictions

“…Indeed, some subcategories in natural languages have partially correlated cues to subcategory structure (e.g., Monaghan et al, 2005), and as described earlier, many investigators have found successful subcategorization learning when distributional cues are correlated with phonological, semantic, or morphological cues (e.g., Gerken et al, 1999; Gerken et al, 2005; Gomez & Lakusta, 2004). Some have also suggested that artificial grammar learning in a semantically-empty world significantly impairs syntax learning (e.g., Moeser & Bregman, 1972; though see Arnon & Ramscar, 2012, for evidence that distributional analyses may be impaired if the learner relies on some types of semantic cues). All of this evidence clearly shows that correlated perceptual cues are relevant for categorization when they are present and that learners can utilize correlated cues to induce categories in experimental settings.…”

Towards cognitively plausible data science in language research

“…This sensitivity to order allows it to capture the effect of blocking (Kamin, 1969;Rescorla & Wagner, 1972), and to formulate precise predictions about the consequences of order for human learning (Ramscar et al, 2010;Arnon & Ramscar, 2012;Ellis, 2006a).…”

“…The blocking phenomenon (Kamin, 1969), for example, explains why an association between a cue and an outcome (the conditioned and unconditioned stimuli in traditional learning theory terminology) is impaired if that same outcome had already been paired with another cue: the second cue will not facilitate prediction of the outcome and for that reason the cue will be ignored. Blocking has been used to explain L2 acquisition (Ellis, 2006a), as well as phenomena of early language acquisition such as overgeneralization of irregular plurals (Ramscar & Yarlett, 2007) and difficulties in acquiring grammatical gender in L2 (Arnon & Ramscar, 2012).…”

The cave of shadows: Addressing the human factor with generalized additive mixed models

“…As shown by Marsolek (2008), the association strengths between visual features and object names are subject to continuous updating. Ramscar et al (2010) and Arnon and Ramscar (2012) documented the consequences of within-experiment learning in the domain of language. Kleinschmidt and Jaeger (2015) report and model continuous updating in auditory processing in the context of speakerlistener adaptation.…”