Use of Duolingo Applications in Second Language Learning: A Bibliometric Analysis

Abstract

Purpose: Research on second language acquisition has progressively evolved alongside advances in digital technology, which provides various interactive learning applications. One widely used application is Duolingo, which offers a gamified approach to learning a second language. This study aimed to identify research clusters, map research developments, and analyze the density of research topics concerning the use of the Duolingo application in second-language learning. Methods: This study constitutes quantitative literature research employing a bibliometric approach. Primary data were sourced from the Google Scholar database for the period 2016–2025 and analyzed using VOSviewer software to identify research trends, conduct keyword co-occurrence analysis, and generate network, overlay, and density visualizations. Findings: The findings identified five research clusters, revealing an evolution from descriptive-assistive approaches (2016–2017) toward the exploration of motivational mechanisms (2018–2022), causal impact testing (2018–2024), and multidimensional integrative models (2023–2024). Gaming and Duolingo occupy the highest-density zones, whereas second language acquisition modeling (SLAM) algorithms are in a very low-density zone, representing a potential area for future scientific breakthroughs. Research implications: This study provides implications for educators to utilize Duolingo as a learning medium in second language instruction and for researchers to avoid repetitive descriptive studies and shift toward cross-disciplinary innovation in developing adaptive gamification system prototypes. Originality: The novelty of this study lies in its systematic bibliometric mapping of Duolingo research developments in second language learning, which identifies thematic gaps between saturated and underexplored topics and provides a roadmap for future interdisciplinary research.