Healthy, Nuclear Medicine Undergraduate Medical Education
Conditions
Keywords
Artificial intelligence, interactive teaching, nuclear medicine, undergraduate education, medical student
Brief summary
This single-center randomized controlled trial will enroll 85 nuclear medicine undergraduate students. Participants will be randomized into two arms: a three-stage AI multi-interactive teaching intervention group (n=43) and a conventional lecture-based control group (n=42). The study is designed to compare theoretical knowledge, instructor-rated performance, student satisfaction, discussion participation, core concept comprehension, and classroom engagement between the two teaching approaches. Planned evaluations will be conducted after the teaching intervention.
Interventions
Undergraduate students receive nuclear medicine theoretical courses via AI-driven multiple interactive teaching mode.
Undergraduate students receive standard nuclear medicine theoretical courses by conventional lecture-based teaching.
Sponsors
Study design
Eligibility
Inclusion criteria
* Undergraduate students majoring in clinical medicine who take the nuclear medicine theoretical course. * Age ≥18 years old. * Voluntarily agree to participate in this study and provide informed consent. * Complete the full-cycle nuclear medicine teaching activities.
Exclusion criteria
* Students who have previously received systematic nuclear medicine coursework. * Incomplete participation in teaching activities or missing post-intervention assessment data. * Students who refuse to join this research.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Difference in post-test theoretical knowledge scores of nuclear medicine between the two student groups | At the end of the teaching intervention (approximately 4-week teaching period) | Nuclear medicine theoretical knowledge post-test score; examination scale range from 0 (minimum, poorest performance) to 100 (maximum, best performance). Higher scores indicate better theoretical knowledge mastery. The between-group score difference will be compared. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Difference in student classroom engagement scores between AI-driven teaching group and traditional lecture group | At the end of the teaching intervention (approximately 4-week teaching period) | Student classroom engagement is assessed using a validated classroom engagement rating scale. The total scale score ranges from 20 (minimum, poorest classroom engagement) to 100 (maximum, optimal classroom engagement). Higher scores represent better classroom engagement of students. The difference in post-intervention engagement scores between the two groups will be analyzed. |
| Difference in learning satisfaction questionnaire scores between the two groups | At the end of the teaching intervention (approximately 4-week teaching period) | Student learning satisfaction is evaluated with a standardized learning satisfaction questionnaire. The overall questionnaire score ranges from 10 (minimum, lowest learning satisfaction) to 50 (maximum, highest learning satisfaction). Higher scores indicate higher student learning satisfaction with nuclear medicine teaching. Post-intervention satisfaction scores are compared between the AI-driven teaching group and the traditional lecture group. |
| Difference in practical-relevant learning experience scores between the two groups | At the end of the teaching intervention (approximately 4-week teaching period) | Students' practical-relevant learning experience is assessed using a validated practical learning experience scale. The total scale score ranges from 15 (minimum, poorest practical learning experience) to 75 (maximum, optimal practical learning experience). Higher scores represent better practical learning experience and stronger perceived mastery of nuclear medicine practical knowledge. Post-intervention learning experience scores are compared between the AI-driven teaching group and the traditional lecture group. |
Countries
China