李昱岑,陈航燕,朱广天,包雷

• 1:苏州大学物理科学与技术学院物理教育研究所
• 2:集美大学师范学院
• 3:东南大学生物科学与医学工程学院
• 4:东南大学学习科学研究中心

摘要(Abstract)：

如何有针对性地为就业指导提出建设性意见，提升高校就业率是各高等院校就业指导工作所面临的严峻挑战。本研究采用机器学习算法，以我国东部地区N校物理类专业本科生就业为例，以学业及非学业因素为特征，构建毕业生就业预警模型，获得了较好的就业预警预测效果。模型呈现以大学英语、线性代数、电动力学及热力学统计物理等科目成绩为重要预测指标的学业预警趋势；而政治面貌、民族、性别、生源地等非学业因素的特征重要性指数远低于学业因素。本研究旨在为高校理工科类专业就业指导小组提升就业预警干预工作的有效性提供新思路、新方法、新对策。

关键词(KeyWords)： 人工智能;机器学习;大学生就业;就业指导

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金(项目编号:11904246);; 苏州大学物理科学与技术学院2022年度东吴攀登计划教改类项目(项目编号:NH10840022);; 教育部人文社会科学研究青年项目(项目编号:24YJCZH474)

作者(Author): 李昱岑,陈航燕,朱广天,包雷

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