产业转型升级背景下智慧公路专业群人才培养模式研究——以福建船政交通职业学院为例
Research on Talent Development Models for Smart Highway Professional Groups Amidst Industrial Transformation and Upgrading:A Case Study of Fujian Chuanzheng Communications College
黄颖 1李琳 1吴恺云1
作者信息
- 1. 福建船政交通职业学院 土木工程学院,福建 福州 350007
- 折叠
摘要
在交通行业转型升级大背景下,打破原有专业壁垒,形成交叉融合型的专业群人才培养架构是智慧公路专业群构建重要举措.以福建船政交通职业学院智慧公路专业群为例,对智慧公路专业群人才培养模式与改革进行了实践探索.首先,对智慧公路行业现状进行分析,归纳行业发展面临的客观问题;其次,针对这些问题以及发展需求,构建了智慧公路专业群组群架构;最后,从专业群人才培养模式、课程体系、教学模式、评价体系和师资队伍等方面,进行了智慧公路专业群人才培养模式改革研究,为行业的发展提供高素质技术技能人才支撑,同时为行业转型升级大背景下专业转型指明了方向.
Abstract
Amidst the backdrop of transformation and upgrading within the transportation industry,it is necessary to break down exist-ing professional barriers and establishing a cross-integrated talent training framework for professional groups stands as a pivotal measure in cultivating a proficient Smart Highway Professional Group.This paper takes the Smart Transportation Professional Group of Fujian Chuanzheng Communications College as a case study to delve into practical explorations of talent cultivation models and reforms within the Smart Highway Professional Group domain.Firstly,an analysis of the current state of the smart highway industry is conducted,identify-ing objective challenges faced by industry development.Subsequently,in response to these challenges and development imperatives,a structured professional group framework for smart highway is outlined.Finally,research is conducted into reforming the talent cultivation model within the smart highway professional group,focusing on aspects such as talent cultivation modes,curriculum systems,teaching methodologies,evaluation frameworks,and faculty composition.This endeavor aims to furnish the industry with high-caliber technical and skilled personnel while charting a course for professional transformation in the context of industry transformation and upgrading.
关键词
产业转型升级/人才培养模式/创新跨界/项目制/校企合作Key words
industrial transformation and upgrading/talent development models/cross-disciplinary innovation/project-based learn-ing/industry-academia collaboration引用本文复制引用
出版年
2024
NETL
NSTL
万方数据