Within the psycholinguistic literature, there has been a longstanding debate regarding whether we resolve syntactic parsing ambiguities via universal or language-specific biases. The present study investigates attachment biases in the online parsing of ‘relative clause’ (RC) attachment in Italian with respect to pseudorelative (PR) availability. Following the PR account Grillo (2012), languages are assumed to universally prefer local attachment. When languages appear to prefer non-local attachment, this is due (at least partially) to the availability of PRs. Specifically, Grillo and Costa (2014) suggest that whenever a string is ambiguous between a PR and a RC, the parser will prefer the PR parse, resulting in apparent non-local attachment. Although there is growing evidence that PR availability indeed affects offline interpretations, few studies have explored this account from an online perspective. Hence, we conducted a self-paced reading task in Italian. In that task, we directly manipulated PR availability and attachment. Reading times for the critical and postcritical regions along with accuracy to comprehension questions were subjected to mixed-effect regressions. Consistent with the PR account, online results indicated a clear bias for local attachment with true RCs. When PRs were available, we observed a non-local bias. Additionally, the present study provides novel evidence in support of the PR-First Hypothesis, as results indicated that the initial preference for PRs may persist and affect the interpretation of even globally disambiguated items.

Code-switching is a natural phenomenon in which a speaker alternates between two languages. Although code-switching could be a useful tool for foreign language learning (Bhatti et al., 2018; Macaro, 2005), it is unknown what types of code-switches are potentially most useful. To investigate this, we present an experiment in which we compare learning rate and success of learning vocabulary (nouns) and functional categories (determiners) from input containing two types of switches from English into a Swahili-based artificial language: inserting two adjacent words (e.g., Kiti ro is next to the book) or inserting two distant words (e.g., The kiti is next to book ro). Images help participants deduce word meaning. Recall accuracy over successive cycles is used to provide a measure of learning rate for nouns and determiners, allowing us to gauge the effect of code-switching on learning grammar and lexis independently. Data collection (n ≈ 40 per condition) is ongoing.