This educational reform study aims to explore whether a full English course built on the DeepSeek artificial intelligence platform can improve orthopedic nurses' professional English competence. It will also examine nurses' satisfaction with AI-assisted teaching. The main questions it seeks to answer include:

Will the DeepSeek-based full English course improve orthopedic nurses' professional English test scores?

Will nurses' transcultural nursing self-efficacy and nurse-patient therapeutic interaction ability improve after the course training?

What are nurses' experiences when using the DeepSeek AI platform for learning?

Researchers will compare the English proficiency changes of the same group of orthopedic nurses before and after the training to observe the course effects.

Participants will:

Attend an 11-week full English course based on the DeepSeek platform, approximately 1-2 hours per week

Complete a professional English written test and an oral proficiency assessment before and after the training

Complete the Transcultural Self-Efficacy Tool (TSET-CV) and the Nurse-Patient Therapeutic Interaction Scale (NuPTIS) before and after the training

Complete a teaching satisfaction and AI learning experience questionnaire after the course

This educational reform study aims to explore whether a full English course built on the DeepSeek artificial intelligence platform can improve orthopedic nurses' professional English competence and international service capabilities.

Background: With the advancement of the "Belt and Road" Initiative, international exchange and cooperation in orthopedic nursing have become increasingly frequent, placing higher demands on nurses' professional English proficiency. However, orthopedic nurses currently generally lack adequate professional English competence. Traditional nursing English education suffers from a single course structure, disconnection between teaching content and clinical practice, and a lack of personalized learning pathways. DeepSeek, as a leading domestic AI model, possesses powerful natural language processing, intelligent speech recognition, and personalized recommendation capabilities, yet its application in nursing English education remains unexplored.

Objective: This study aims to construct a DeepSeek-based full English course system for orthopedic nurses, explore effective pathways for AI-empowered nursing English teaching, and verify its practical effects on improving orthopedic nurses' professional English competence, transcultural nursing self-efficacy, and nurse-patient therapeutic interaction ability.

Study Design: A quasi-experimental study with a one-group pretest-posttest design will be adopted. Sixty registered orthopedic nurses will be recruited to participate in an 11-week blended online and offline full English course based on the DeepSeek platform. The effectiveness of the course intervention will be evaluated by comparing changes in nurses' professional English test scores, oral proficiency assessment results, Transcultural Self-Efficacy Tool (TSET-CV) scores, and Nurse-Patient Therapeutic Interaction Scale (NuPTIS) scores before and after the training.

Intervention: The full English course built on the DeepSeek platform spans 11 weeks and is divided into six modules:

Weeks 1-2 (Basic English for Orthopedic Nursing): Learning anatomical terms such as bones, muscles, and joints, as well as basic doctor-patient consultation dialogues Weeks 3-4 (Trauma Orthopedic Nursing): Learning English abbreviations for fracture classification and English instructions for orthosis use Weeks 5-6 (Joint Replacement and Nursing): Learning English preoperative education and postoperative complication prevention knowledge for hip and knee replacement surgeries Weeks 7-8 (Spinal Disorders and Nursing): Learning English expressions for common spinal diseases and reading English literature Weeks 9-10 (Common Orthopedic Nursing and Orthoses): Learning English instructions for the use of cervical collars, lumbar supports, crutches, and other orthoses Week 11 (Clinical Cross-cultural Communication): Comprehensive training in cross-cultural communication skills, completing a full-process simulated dialogue test from admission consultation to discharge instructions

Outcome Measures: The following indicators will be measured before and after the training:

Professional English written test score (self-developed test, total score 100) Oral proficiency assessment score (including fluency, accuracy, and terminology mastery, rated by the AI system) Transcultural Self-Efficacy Tool (TSET-CV, 30 items, covering three dimensions: cognitive, practical, and affective) Nurse-Patient Therapeutic Interaction Scale (NuPTIS, 20 items, covering four dimensions: emotional support, empathic communication, patient-centered care, and supportive communication process) Self-rated English ability and learning needs survey

Post-training data collection: teaching satisfaction questionnaire, AI learning experience questionnaire, and DeepSeek backend learning behavior data Statistical Analysis: SPSS 26.0 software will be used. Paired sample t-tests or Wilcoxon signed-rank tests will be employed to compare indicators before and after the training. Effect sizes will be reported as Cohen's d or r values. The significance level is set at α = 0.05.

Expected Outcomes: Develop a complete full English course system for orthopedic nurses (including a course syllabus, 11 sets of courseware, a specialized vocabulary bank, and AI scenario scripts), produce one teaching reform research report, publish one paper in a core journal, and achieve a participant satisfaction rate of ≥ 95%.

Inclusion Criteria:

• ① On-duty nurses in the orthopedics department ② Obtained the nurse professional qualification certificate ③ Obtained the patient's informed consent and signed the informed consent form ④ The research was approved by the ethics committee of this hospital.

Exclusion Criteria:

• Nurses who have not completed 1/2 of the course content

Nature of the Study: This is an educational reform study rather than a clinical drug or device trial. The data collected consist primarily of nurses' English test scores, scale assessments, and teaching satisfaction feedback, which do not involve patient health information or clinical efficacy data.

Data Sensitivity: The research data include participants' individual learning performance, English proficiency assessments, and questionnaire feedback, which contain information that could indirectly identify individuals (e.g., employee ID, study code, platform usage records). Although data have been anonymized, there remains a potential risk of re-identification within a small institutional setting.

Informed Consent Limitations: The informed consent form for this study did not include authorization for sharing data to public repositories. Participants only consented to the use of their data for analysis and publication of this study.