Intelligent Context Generation and Adaptive Training: Construction of an AI-driven Clinical Communication Practice Teaching System for Nursing English
Abstract
contexts, single training methods, and difficulty in meeting individual learning needs. This paper focuses on the construction of an AI-driven
clinical communication practice teaching system for nursing professional English, exploring the application of intelligent context generation
and adaptive training technologies in it. The system takes artificial intelligence technologies such as natural language processing, virtual reality, and machine learning as the core, constructs realistic clinical communication contexts, realizes personalized adaptive training, and improves nursing students' English communication skills in clinical practice.
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[1] Lin Y. A Study on Career-oriented English Vocabulary Teaching Strategies: A case Study of Nursing Profession [J]. World Education
Forum, 2024, 2 (10).
[2] Widanta J R M I, Sitawati R A A, Handayani C N L, et al. The Impact of Task-Based Language Teaching on Nursing Students' English-
Learning Motivation [J]. Theory and Practice in Language Studies, 2024, 14 (10): 3131-3140.
[3] Cheng Z, Luo T. Cross-Cultural Communication Strategies for English Teaching in Sports Management Under the Context of Globalization: Theoretical Exploration and Educational Reflection [J]. Trends in Social Sciences and Humanities Research, 2024, 2 (6).
[4] Liu Y. An analysis of English classroom teaching design for foreign nursing majors in higher vocational schools based on demand analysis [J]. New Explorations in Education and Teaching, 2024, 2 (5).
[5] Ahmed M M S A, Jamshed M, Sarfaraj M, et al. Exploring Diverse Teaching Models for Enhancing Nursing Students' English Language
Proficiency: A Blended Learning Perspective [J]. World Journal of English Language, 2024, 14 (5).
[6] Wu Z, Huang X, Deng W. Exploration and Practice of English Course Teaching of Business Administration Major in Vocational Colleges [J]. International Journal of Mathematics and Systems Science, 2023, 6 (2).
DOI: http://dx.doi.org/10.70711/neet.v3i9.7764
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