【作者】 曾凤彩； 李晓峰； 郝秀兰；

【Author】 ZENG Fengcai;LI Xiaofeng;HAO Xiulan;Beijing Union University;

【机构】 北京联合大学；

【摘要】 随着科技的快速发展和行业需求的不断变化,传统的工程类研究生培养模式缺乏针对性,难以满足学生个体的差异和多样化需求。通过深入分析工程类硕士研究生的培养现状,结合大数据技术的发展,探究工程类研究生的个性化培养模型。拟在培养过程中,建立学生成长数据库、学校管理数据库、导师指导数据库等,利用数据推演方法,实时跟踪学生的学习和发展情况,及时调整研究生个人培养方案,提高工程类研究生的综合素质和创新能力,使其更好地适应工程领域的发展需求,为行业输送更多高质量的专业人才。以培养创新人才为核心,推进研究生个性化培养的进展,同时探索更加有效的工程类研究生个性化培养模式,为提升研究生培养质量提供新路径,以适应现代化建设的需求,培养更多高层次的工程科技领军人才。更多还原

【Abstract】 With the rapid development of technology and the continuous changes in industry demands,the traditional training model for engineering graduate students lacks specificity and is difficult to meet the individual differences and diverse needs of students.Through in-depth analysis of the current situation of master’s degree training for engineering students,combined with the development of big data technology,this paper explores the personalized training model for engineering graduate students.It is proposed to establish student growth databases,school management databases,and mentor guidance databases during the training process,using data-driven methods to track students’ learning and development in real-time,and to adjust graduate individual training plans promptly.This approach aims to enhance the comprehensive quality and innovative capabilities of engineering graduate students,enabling them to better adapt to the development needs of the engineering field and to provide the industry with more high-quality professional talents.With the cultivation of innovative talents as the core,we should promote the progress of personalized training for graduate students.At the same time,exploring more effective personalized training models for engineering graduate students provides a new path for improving the quality of graduate training,so as to meet the needs of modernization construction,and to cultivate more high-level engineering technology leaders.更多还原