This paper examines the distinct yet interconnected roles of large language model AI and human cognitive processes in language understanding and generation. AI processes language as digital signs, while humans use it as analog signs, utilizing their neural networks, an analog medium. This fundamental difference underscores that AI is unlikely to supplant human language use. Humans’ language teaching and learning will probably remain essential, particularly in the context of second language education. However, in an era of ubiquitous AI, the proficiency of English as a second language needs reevaluation. This study proposes a model of integrated proficiency in which humans’ embodied ability and AI-augmented capacity will mutually develop and complement each other.

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The purpose of this study is to investigate the changes of noun phrase complexity and its factors in the process of learning essay writing in English through the analysis of a longitudinal leaner corpus. Since Biber et al. (2011) claimed the importance of the complexity of noun phrases in English writing, there have been many studies conducted to analyze the complexity of noun phrases. Kim (2021) used a longitudinal Korean learner corpus of English to report that the noun phrase complexity alone significantly decreased among five syntactic features. In order to verify Kim’s report, the current study using a 290-thousand-word longitudinal Japanese learner corpus of English calculated the syntactic features by means of Lu’s (2010) Syntactic Complexity Analyzer and conducted generalized linear mixed modeling, showing that contrary to Kim’s result the complexity of noun phrases increased significantly. Once the order of topics was taken into further analysis, the order of topics modulated the effect of the noun phrase complexity even though essay scores increased longitudinally regardless of the topic order differences. It could be concluded that the noun phrase complexity is affected by topic differences greater than the effect of essay score increase.

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English education in Japan is undergoing significant changes, partly due to rapid globalization. New curricula are rolling out in elementary, junior high, and high schools, focusing on agentic, interactive, and deep learning, and universities are adapting. This study, involving 316 first-year university students, explores the negative aspects of learning engagement. It examines how teacher-controlled instruction and psychological needs frustration lead to learners' disengagement and lower achievement in English learning. Using correlation and structural equation modeling (SEM), the study found that teacher-controlled instruction directly and indirectly affects disengagement, negatively affecting their achievement in English learning. The findings suggest the need to address teacher-controlled teaching due to its adverse effects on student motivation, engagement, and achievement.

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[in Japanese]

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