The rapid development of big data analytics and Internet of Things (IoT) technologies presents new opportunities for strengthening business Japanese education, particularly in the areas of practical language application, learner engagement, and classroom management. Conventional instruction may provide an insufficient connection between linguistic knowledge, business practices, and intercultural communication. To address these challenges, this study proposes an IoT-enabled, data-driven teaching model structured around three interconnected modules: preparation, learning, and evaluation. The framework establishes a feedback cycle through which information about learners’ needs, instructional activities, and evaluation outcomes can inform subsequent teaching decisions. An associated smart classroom architecture integrates a perception layer for collecting environmental and participation data with a control layer for managing classroom resources and authorized access. The study further introduces quantitative indicators for student distribution, knowledge coverage, learning motivation, instructional goal attainment, and classroom management. Two questionnaire-based analyses are presented to examine students’ learning needs and preferences for blended instruction. The manuscript reports an average 12% improvement in teaching efficiency, although the measurement procedure and comparative data supporting this figure require further documentation. The study identifies opportunities for integrating technological infrastructure with the pedagogical requirements of professionally oriented Japanese-language instruction while emphasizing the need for more rigorous outcome evaluation.
