For close to a century, experiments using artificial languages (hereafter ALs) have been a staple of psycholinguistic research (Esper, Reference Esper1925). Contemporary AL research has spanned numerous levels of linguistic inquiry, from phonetic learning through syntax (see Culbertson & Schuler, Reference Culbertson and Schuler2019). This approach has also been successfully applied across development, from infants and children (see Saffran & Kirkham, Reference Saffran and Kirkham2018) through older adults (e.g., Schwab, Schuler, Stillman, Newport, Howard & Howard, Reference Schwab, Schuler, Stillman, Newport, Howard and Howard2016), even spanning cross-species comparisons (e.g., Wilson, Slater, Kikuchi, Milne, Marslen-Wilson, Smith & Petkov, Reference Wilson, Slater, Kikuchi, Milne, Marslen-Wilson, Smith and Petkov2013). Given the proliferation of AL methods for investigating issues related to first language acquisition, it is not surprising that research on bilingualism has also embraced this approach. This special themed section comprises four concise review articles describing how AL research has informed questions related to bilingualism and second language learning. The articles also discuss the strengths and limitations of this approach, as well as pointing to future directions for the field.

One of the primary reasons for the longevity of AL experimental designs is that ALs can serve as ‘test tube models’ for natural language acquisition (Morgan-Short, Steinhauer, Sanz & Ullman, Reference Morgan-Short, Steinhauer, Sanz and Ullman2012, p.934; Morgan-Short, Reference Morgan-Short2020). Whereas natural language stimuli are often highly variable and present a challenge with respect to isolating individual features (e.g., de Graaff, Reference De Graaff1997), ALs inherently allow for fine-grained control in stimulus creation thereby permitting precise manipulation of the input features. Further, AL affords experimenters the opportunity to measure learning after a relatively short period of familiarization and is also amenable to longitudinal studies. Moreover, having tight control over the input allows experimenters to tailor the relationship between features of the AL and the languages known by participants. Consequently, as noted by Hayakwa, Ning and Marian (Reference Hayakawa, Ning and Marian2020), this may provide an opportunity to better understand the causal mechanisms that facilitate learning. In turn, this may bear implication for translating AL research towards the understanding of language disorders and delays in bilingual learners.

While there are many benefits to the AL approach, it is worth noting that there are also potential limitations. Notably, one issue inherent to experiments using AL stimuli is determining how well the findings scale up to language phenomena in natural settings. An integral aspect of AL studies is that they represent reductionist approaches for measuring learning that often strip away many of the cues and features that are characteristic of real-world learning environments. Therefore, accounting for naturalistic variability and connecting the laboratory studies with real-world learning outcomes continues to be an important direction for validating the use of AL studies as a proxy for natural language learning (for example, see Ettlinger, Morgan-Short, Faretta-Stutenberg & Wong, Reference Ettlinger, Morgan-Short, Faretta-Stutenberg and Wong2016). As noted below, these validation endeavors may involve both behavioral and neural measures (see Morgan-Short, Reference Morgan-Short2020).

The first contribution of the special themed section by Hayakawa et al. (Reference Hayakawa, Ning and Marian2020) discusses how AL research related to word learning has contributed to our understanding of second language learning and bilingual cognition. The article focuses on two research questions. First, the authors examine linguistic factors that influence second language acquisition in the context of acquiring novel vocabulary. This includes how learning is modulated by features of the artificial words and the degree of similarity to known languages, as well as several other factors. The second issue pertains to the impact of bilingual experience on word learning throughout development and into adulthood. The article closes with a discussion of databases that provide useful resources for conducting AL research on word learning.

The next contribution by Grey (Reference Grey2020) explores how AL research has been used to study grammar learning and processing in bilinguals, with an emphasis on morphosyntactic structures. In addition to exploring these issues in bilinguals, the review also discusses bilingual third language learning, and compares performance to monolingual second language learning. The author makes an important distinction (also mirrored in the article by Morgan-Short) by delineating several types of AL systems and the extent to which they are consistent with natural languages.

The contribution by Morgan-Short (Reference Morgan-Short2020) focuses on the neural mechanisms involved in L2 grammar learning, as informed by research using ALs. As noted, the author delineates different types of ALs, noting that, to date, there have been different levels of validation for meaningful versus non-meaningful ALs. The article then reviews several studies using meaningful ALs to investigate the impact (on learning outcomes) of age of acquisition and type of exposure, as assessed by both behavior and neural measures. Finally, the article discusses how AL research has informed the online learning mechanisms that underlie L2 grammar learning.

Finally, the article by Weiss, Schwob and Lebkuecher (Reference Weiss, Schwob and Lebkuecher2020) focuses on how AL research has contributed to our understanding of statistical learning and bilingualism. Specifically, the authors focus on two questions informed by the AL approach. The first is establishing whether bilingualism impacts statistical learning abilities in early- and late-learning bilinguals. The second question involves determining how learners (of all ages) contend with multiple sets of input statistics, a situation that arguably models a challenge confronting bilingual learners, particularly during the early stages of development (see also Weiss, Poepsel & Gerfen, Reference Weiss, Poepsel, Gerfen and Rebuschat2015).

In sum, artificial language learning experiments have facilitated many new insights into bilingualism and second language learning. The goal of this collection is to serve as both an introduction and reference for how AL research can inform the study of bilingualism. Moreover, this special themed section aspires to facilitate and inspire future research in bilingualism and second language learning using AL paradigms.