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Second language acquisition (SLA) has seen a rapid increase in meta-research, such as systematic reviews and meta-analyses. This line of work has important implications, as it provides comprehensive overviews, establishes consensus, and identifies gaps in the literature on a given topic, both methodologically and substantively. However, the manual processes involved in meta-research can be resource intensive and, perhaps more importantly, prone to human errors. In this chapter, we provide an overview of artificial intelligence (AI) tools that have the potential to streamline meta-research processes, specifically in the context of literature screening. We discuss the strengths and weaknesses of these tools and share our experience using them. We conclude by recognizing that these AI tools are not a substitute for human expertise and judgements but offer exciting opportunities for researchers engaging in meta-research. Our overall goal is to help improve the efficiency, reproducibility, and transparency of meta-research in SLA.
Quan et al. (Tue,) studied this question.