Implementation of a Blended Online and Offline Teaching Model
ConditionGenerative Artificial Intelligence
Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18-25
SponsorHengxu Wang
About this trial
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.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Nursing major students;
Four-year undergraduate students.
Disqualifiers
Students who drop out midway;
Students whose absences accumulate to exceed 30% of the total class hours.
Trial design
Design model
Sequential
Treatments tested in this trial
A blended online and offline teaching model for internal medicine nursing practice based on generative artificial intelligence
BehavioralThis study will employ a convergent mixed-methods design. Participants will be convenience-sampled undergraduate nursing students from the 2024 cohort (intervention group) and the 2023 cohort (control group) at Changsha Medical University. The intervention group will experience the new blended model, which includes: 1) Optimizing a GAI-assisted clinical case library with progressive scenarios; 2) Utilizing online resources (Learning Terminal platform, virtual simulation experiments with an AI assistant); 3) Engaging in offline interactive sessions (card-based desktop deduction games and scenario simulations). The control group will receive traditional teaching methods. Quantitative data will include course scores (theoretical knowledge and practical skills) and teaching satisfaction questionnaires. Qualitative data will be collected via semi-structured interviews to explore students' experiences deeply.
Treatment groups
600 Participants
are divided into 1 treatment groupGroup A: Experimental groupExperimental treatment 1 intervention
Trial outcomes
Primary outcomes
1
Course Scores
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.
Time frame
At the end of the 6-month course.2
Teaching Satisfaction Score
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.
Time frame
At the end of the 6-month course.Secondary outcomes
1
Online and Offline Teaching Effect Evaluation
A multidimensional teaching effectiveness score will be calculated based on a digital combined evaluation system. This system incorporates standardized quantitative evaluations from three sources: student self-assessment (using a structured rating scale), teacher and small team self-assessment (using a structured rating scale), and expert supervision group assessment (using a structured observation rubric). These assessments are designed to use a common unit of measure (points on a standardized scale). The scores from these three components will be aggregated using a pre-defined weighting formula to produce a single composite teaching effectiveness score.
Time frame
At the end of the 6-month course.2
Qualitative Interviews
Thematic analysis of semi-structured individual interviews conducted with participants from the experimental group. This qualitative measure will identify, analyze, and report patterns (themes) concerning the perceived effectiveness, learning experiences, strengths, and limitations of the blended teaching model. The results will be presented as a summary of key themes and insights, not as a numerical score.
Time frame
Within one month after completion of the 6-month course.Locations
Sponsors and contacts
Click on the lead sponsor to view all of their trials.
Hengxu Wang
Lead sponsor
Changsha Medical University
Sponsor institution
Source ClinicalTrials.gov
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