A Study Protocol for Implementing a Blended Online and Offline Teaching Model Based on Generative Artificial Intelligence in the Practical Teaching of Internal Medicine Nursing: a Mixed-methods Study
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 600
- 主要终点
- Course Scores
研究概览
简要总结
This study aims to design, implement, and evaluate a blended online and offline teaching model for Internal Medicine Nursing, integrating generative artificial intelligence (GAI), a virtual simulation platform, card-based exercises, and scenario simulation. The objective is to address key limitations of traditional teaching, including low student engagement, insufficient cultivation of clinical thinking, limited personalized learning, and a disconnect between theory and practice.
A mixed-methods approach will be used. All undergraduate nursing students from the 2024 cohort at Changsha Medical University will be enrolled via convenience sampling as the experimental group to receive the new blended model. The 2023 cohort will serve as the control group, receiving traditional teaching. Quantitative data (course grades, satisfaction questionnaires) and qualitative data (semi-structured interviews) will be collected to comprehensively evaluate the model's effectiveness.
Expected outcomes include improved student mastery of theoretical knowledge, enhanced practical skills and clinical thinking, increased learning interest, and higher teaching satisfaction. The study intends to provide a replicable, scalable innovative solution for nursing education reform, ultimately contributing to the training of high-quality applied nursing talents.
Key problems addressed:
Overcoming single-method teaching and poor interaction through GAI and gamification.
Enhancing clinical thinking and decision-making via dynamic GAI cases and card-based exercises.
Providing personalized learning paths and instant feedback using GAI technology.
Bridging the theory-practice gap with high-fidelity virtual and scenario simulations.
Implementing a multi-dimensional evaluation system beyond final exams to assess comprehensive student abilities.
详细描述
This study protocol describes the development, implementation, and evaluation of a blended online and offline teaching model integrated with generative artificial intelligence (GAI) for practical teaching in Internal Medicine Nursing. The model combines a GAI-optimized clinical case library, a virtual simulation platform, card-based desktop exercises, and scenario simulation teaching.
The clinical case library will be developed using GAI to generate progressive, multi-stage cases reflecting real clinical progression (e.g., from COPD to Cor Pulmonale), each containing 2-3 stages designed to train clinical reasoning and decision-making. Online teaching resources will include a Learning Terminal-based course covering nine internal medicine systems, with electronic courseware, assessments, and discussion forums. The existing virtual simulation platform will be enhanced with a GAI-based Q&A assistant to support knowledge acquisition and operational training. Dedicated online learning groups will facilitate communication.
Offline teaching will incorporate card-based desktop exercises and high-fidelity scenario simulations. The card game includes five card types: Patient Information, Nursing Goal, Nursing Intervention, Emergency Situation, and Assessment & Feedback. Scenarios are derived from the GAI case library and involve standardized patients and high-fidelity simulators to replicate clinical environments.
The model will be implemented using a mixed-methods design. The experimental group (2024 undergraduate nursing cohort) will receive the blended model, while the control group (2023 cohort) will receive traditional teaching. Evaluation includes quantitative metrics (theory and practical exam scores, teaching satisfaction surveys) and qualitative methods (semi-structured interviews with the experimental group). Course scores are weighted 60% for theory and 40% for practical skills, the latter comprising case analysis, emergency drills, virtual simulation performance, and online course results. A multidimensional evaluation mechanism involving students, teachers, and expert supervisors will be established.
The teaching team consists of 8 full-time instructors, 4 clinical teachers, and 4 training center staff. Lessons learned from the mixed-methods evaluation will be used to refine and promote the teaching model.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Sequential
- 主要目的
- Other
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 25 Years（Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Nursing major students;
- •Four-year undergraduate students.
排除标准
- •Students who drop out midway;
- •Students whose absences accumulate to exceed 30% of the total class hours.
结局指标
主要结局
Course Scores
时间窗: At the end of the 6-month course.
The total course score is a composite measure evaluating overall academic performance. It comprises two components: a theoretical knowledge score (assessed via a closed-book examination, scored out of 100 points) and a practical skill assessment score (evaluated through case analysis, emergency drill simulations, virtual simulation performance, and online course participation, each contributing 20% to the practical score, which is also scaled to 100 points). The final total course score is calculated by weighting the theoretical score at 60% and the practical score at 40%, resulting in a composite value out of 100.
Teaching Satisfaction Score
时间窗: At the end of the 6-month course.
Teaching satisfaction will be measured using a validated evaluation questionnaire developed based on a review of relevant literature, research group discussions, and consultation with nursing education experts. The questionnaire produces a quantitative satisfaction score.
次要结局
- Online and Offline Teaching Effect Evaluation(At the end of the 6-month course.)
- Qualitative Interviews(Within one month after completion of the 6-month course.)
研究者
Hengxu Wang
Staff Nurse
Changsha Medical University