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Evaluation of the Effectiveness of MED·SMART-AI in Undergraduate Clinical Anesthesia Teaching

Author(s)

Zhen Wu1, Jie Hou2, Lixin Yin1, Wanchao Liu1, Jun Geng1, Laiyou Wen1,*

Affiliation(s)

1Department of Anesthesiology, Jiangyin Hospital Affiliated to Nantong University, Jiangyin, Wuxi, Jiangsu, China 2Department of Science and Education, Jiangyin Hospital Affiliated to Nantong University, Jiangyin, Wuxi, Jiangsu, China *Corresponding Author.

Abstract

This study aimed to assess the impact of MED·SMART-AI on undergraduate clinical anesthesia internship teaching. Sixty undergraduate interns at Jiangyin Hospital Affiliated to Nantong University were divided into two groups. One group (n=30, February-April 2024) received traditional instruction, while the other (n=30, May-July 2024) was taught using the MED·SMART-AI method. The evaluation included theoretical knowledge, practical skills, case analysis performance, student learning initiative, and self-evaluation components, such as learning ability, communication skills, and self-confidence. Interns utilizing MED·SMART-AI demonstrated significantly higher scores in theoretical examinations, skills assessments, and case analysis compared to those receiving traditional instruction. Furthermore, the MED·SMART-AI group exhibited notable improvements in learning initiative (information, self-management, and learning cooperation abilities), alongside enhanced self-evaluations of learning ability, doctor-patient communication, literature retrieval, scientific research innovation, and self-confidence. These findings indicate that integrating MED·SMART-AI into undergraduate clinical anesthesia education effectively improves academic outcomes and fosters a more proactive and self-assured learning approach.

Keywords

MED·SMART-AI; Clinical-Anesthesia; Undergraduate Teaching; Educational Effectiveness; Learning Initiative

References

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