摘要
新冠肺炎疫情给旅游经济带来了巨大冲击,疫情下学生的专业认同与职业意向状况日益受到关注。文章以学生群体为调查对象,采用探索性和验证性因子分析、方差分析方法揭示疫情下高职旅游管理专业认同的维度特征、关联结构及特征差异。结果表明:高职旅游管理专业认同包括“专业前景、专业教学、专业意识、专业归属、专业认知”五个基本维度,疫情下学生对“专业前景、专业归属”认可度较低;五个专业认同维度相互联系、密不可分,共同构建了高职旅游管理专业认同的结构特征;家庭经济状况、年级、专业选择、是否经常参加社团或学生会活动、学习成绩、家庭居住地在专业认同的各维度上呈现出显著差异。该研究为后疫情时代的职业教育改革与旅游人才培养提供思考。
The COVID-19 epidemic has brought a huge impact on the tourism economy,and students’major identity and career intentions have received growing attention.This paper makes a survey of higher vocational stu⁃dents,adopts exploratory and confirmatory factor analysis and analysis of variance to reveal the dimension feature,relevant structure and feature differences of tourism management major identity in higher vocational colleges under the epidemic situation.The result shows that:Tourism management major identity in higher vocational colleges cov⁃ers the five dimensions of major prospect,major teaching,major consciousness,major attachment and major cogni⁃tion;under the epidemic,the students’recognition of“major prospect and major attachment”is low;the five di⁃mensions are interconnected and interwoven to jointly construct the structure feature of tourism management major identity in higher vocational colleges;the family finance status,grades,major choice,participating in associations or student union activities,academic performance and places of family residence perform significant differences at all dimensions of major identity.This study provides references for the vocational education reform and tourism talent fostering in the post-pandemic era.
作者
刘宇飞
龙艳玲
王小欢
贺园
刘凯
LIU Yu-fei;LONG Yan-ling;WANG Xiao-huan;HE Yuan;LIU Kuai(Ji'an polytechnic,Ji'an 343006,China;Guangdong Polytechnic of Science and Trade,Guangzhou 510000,China;Yichun early chlydhood Teachers College,Yichun 336000,China)
出处
《经济论坛》
2022年第2期84-93,共10页
Economic Forum
基金
江西省教育科学规划项目“高职旅游管理学生专业认同与创业意向关系研究”(19YB376)阶段性成果
江西省教育科学规划项目“高职院校“政校企社”嵌入式旅游人才培养路径研究”(19YB375)阶段性成果。
关键词
专业认同
新冠肺炎疫情
旅游管理专业
维度特征
统计分析
Major identity
COVID-19 epidemic
Tourism management major
Dimensional features
Statistic analysis
