大学生学业倦怠:表现、成因及大数据干预策略  

Academic Burnout of College Students:Performance,Causes and Big Data Intervention Strategies

作　　者：宋超[1] SONG Chao(Student Office,Ningbo University of Technology,Ningbo 315211,China)

机构地区：[1]宁波工程学院学生处,浙江宁波315211

出　　处：《宁波教育学院学报》2024年第6期104-107,120,共5页Journal of Ningbo Institute of Education

基　　金：2022年浙江省哲学社会科学规划“高校思想政治工作”专项课题“数据驱动的大学生学业倦怠精准干预研究”(22GXSZ077YBM)。

摘　　要：大学生学业倦怠的主要表现有生理耗竭与心理疲劳、学习动机丧失与学习兴趣减退、行为上的懈怠与逃避、情绪消极与人际关系紧张、认知偏差与自我效能感降低、学业失败与自我否定等。诱发大学生学业倦怠的因素有个体心理因素、外部环境因素、教育评价因素及社会文化因素,大数据技术在大学生学业倦怠干预中可以发挥重要作用,具有精准识别学业倦怠、动态监测学业变化、制定个性化干预策略、多方参与协同干预、效果评估与反馈调整等功能。The main manifestations of college students’academic burnout include physical exhaustion and mental fatigue,loss of learning motivation and decline in interest,behavioral slackening and avoidance,negative emotions and interpersonal tension,cognitive bias and reduced self-efficacy,academic failure and self-denial,etc.The factors inducing college students’academic burnout are deeply analyzed and summarized into individual psychological factors,external environmental factors,educational evaluation factors,and socio-cultural factors.Big data technology plays an important role in intervening in college students’academic burnout,which can be used for precise identification of academic burnout,dynamic monitoring of academic changes,personalized intervention strategy formulation,multi-party participation and collaborative intervention,as well as effect evaluation and feedback adjustment.

关 键 词：大学生 学业倦怠 大数据 

分 类 号：G645[文化科学—高等教育学]