ClinicalTrials.gov
public full text
Public Domain
AI-driven Multiple Interactive Teaching Model on Nuclear Medicine Students' Theoretical Knowledge and Practical Skills
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.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Development and Validation of an E-learning Module on Systemic Anticancer Therapy and Its Effectiveness on the Knowledge Attitude and Practice of Nurses in Administering Systemic Anticancer Agents at a Specialized Cancer Centres in Oman.#369843
- Diverse patients’ attitudes towards Artificial Intelligence (AI) in diagnosis#686543
- Diverse Patients’ Attitudes Towards Artificial Intelligence (AI) in Diagnosis#309806
- Effect of Guided Imagery and Progressive Muscle Relaxation as a Means to Improve the Psychological Well-being and the Quality of Life for Patients With Breast and Prostate Cancer#907339
- Developing metacognitive knowledge for effective AI-supported study behaviors in undergraduate biology: recommendations for instructors.#610243
Record · ID 900186
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive