Language priming in the wild: Using a mobile-app for online data-collection

Syntactic priming paradigms are widely used to investigate language production, yet they are almost exclusively implemented in controlled laboratory settings. This limits scalability, inclusivity, and the study of language behavior in everyday contexts. Here, we present and validate a smartphone-based method for measuring syntactic priming. Our mobile application implements a picture description task commonly used in laboratory studies and incorporates automated speech transcription and syntactic classification. Using our app, we collected data on the production of active and passive sentence structures and evaluated short-term, cumulative, and long-term (across sessions) priming effects. To assess methodological validity, we compared the patterns observed in app-collected data with those obtained previously using an equivalent laboratory paradigm. Results demonstrate that the mobile app reliably elicits short-term syntactic priming, with increased production of passive structures following passive primes, replicating well-established laboratory effects. Within-session analyses further revealed cumulative priming, indicating gradual learning of infrequent syntactic structures. Long-term priming over a one-week interval was not observed in the app data, in contrast to laboratory findings. However, a follow-up experiment with a 24-hour interval between sessions yielded significant long-term priming effects, suggesting that retention of syntactic learning may decay more rapidly in uncontrolled, real-world environments. Together, these findings establish the mobile application as a valid and scalable method for studying syntactic priming outside the laboratory. The approach enables large-scale data collection in naturalistic settings and provides a flexible methodological framework for investigating individual differences in large diverse samples, and potential intervention applications in language research.