Visual Analysis of Mobile-Assisted Language Education and Discussion on the Role of Mobile LLM Applications in TCSOL

This article utilizes Citespace software to conduct a visual analysis of papers related to "mobile-assisted language education" from the Web of Science SSCI and SCI databases over the past decade (2014-2024), and discusses the role of mobile large language model applications in TCSOL based on the analysis results. The conclusions are as follows. Firstly, China, the United States, Spain, the United Kingdom, and Iran are the leading countries in terms of publication volume. Asian countries, particularly those in East Asia, are enthusiastic about research in this field. What’s more, the keyword co-occurrence and cluster graphs show that the research in this field mainly focus on learning analytics, second language learning in higher education, acceptance of mobile technology in language education, teaching/learning strategies in mobile-assisted language learning and mobile-assisted applications. The potential research hotspots in this field in the future may be research on teaching/learning strategies based on psychological theories, studies on mobile-assisted Chinese as a second language learning, and artificial intelligence applications represented by large language models. Lastly, Mobile LLM applications possess capabilities such as multilingual support, multimodal interaction, language generation, and assessment, making them suitable as auxiliary teachers and language practice partners for L2 Chinese learners. The focus of future research may lie in the optimization of teaching effects, teaching strategies, and the functional improvements of mobile large language model applications in the direction of language education.