This study presents a comprehensive bibliometric analysis of language acquisition research conducted from 2019 to 2024. Using data from Lens.org and visualization tools like VOSviewer, the study examines citation patterns, co-authorship networks, institutional contributions, and keyword trends to map the intellectual landscape of the field. The findings reveal that Second Language Acquisition (SLA), bilingualism, mobile-assisted learning, and artificial intelligence (AI)-driven language instruction are among the most dominant themes. Influential authors, such as Deguine and Barrot, as well as key institutions from the United States, China, and the Philippines, have significantly contributed to knowledge production. The study also highlights emerging research interests, including neurodiversity, self-regulated learning, and sociocultural perspectives on multilingual education. Bibliometric laws such as Lotka’s, Bradford’s, and Zipf’s Laws were applied to analyze author productivity and publication sources. This study serves as a valuable resource for researchers, educators, and policymakers by identifying research gaps, collaboration patterns, and future directions in language acquisition.
Colorada et al. (Sat,) studied this question.