Research on Optimization Path of Neurosurgery Clinical Teaching Management Mode Integrating Artificial Intelligence and PBL Teaching Method
- VernacularTitle:人工智能融合PBL教学法神经外科临床教学管理模式优化路径研究
- Author:
Yang LI
1
;
Sijia ZHANG
;
Lihan ZHANG
;
Haicheng YANG
;
Jinquan CAI
;
Xiangqi MENG
;
Chuanlu JIANG
Author Information
1. 哈尔滨医科大学附属第二医院 黑龙江 哈尔滨 150086
- Publication Type:Journal Article
- Keywords:
Artificial Intelligence;
Problem-Based Learning;
neurosurgery;
clinical teaching;
medical education management
- From:
Chinese Hospital Management
2025;45(8):70-72,76
- CountryChina
- Language:Chinese
-
Abstract:
Objective In the clinical teaching of neurosurgery,the traditional Problem-Based Learning(PBL)teaching model faces systematic challenges such as the disconnection between the training cycle of specialized talents and technological iteration,the limitation of practical opportunities due to hospital infections,and the inefficient allocation of teaching resources.It provides a new path for teaching reform based on the deep integration of Artificial Intelligence and PBL,but it still needs to address issues such as differences in intern participation,insufficient technical adaptability of instructors,and fragmented resource allocation.Based on these problems,a collaborative mechanism of"technology development-talent cultivation"and a multi-dimensional optimization path of"intern participation-instructor training-hospital resource input"are proposed.On this basis,through collaborative strategies such as strengthening the incentive mechanism for autonomous learning,establishing a standardized instructor training system,and building a dynamic resource allocation platform,the management of neurosurgery clinical teaching is promoted towards intelligence,personalization,and systematization.
