基于深度学习算法的青少年思想、行为与成长规律动态研究

IF 0.5 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING International Journal of Data Warehousing and Mining Pub Date : 2024-01-31 DOI:10.4018/ijdwm.333518
Qi Fu
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引用次数: 0

摘要

青年的成长和发展关系到国家和民族的命运,新时期青年的培养意义重大。青年时期是人生的特殊阶段,这一时期青年的思想道德观念还具有很强的可塑性。在对他们进行教育的过程中,要把握他们思想道德成长的特点和规律,做到有的放矢。青少年思想道德成长的特点是多变性、主体性、实践性、层次性;青少年思想道德成长的规律是引导超越规律、教化内化规律、知志行相互促进规律、循序渐进规律。随着经济全球化、互联网、大数据的深入发展,青年的思想、行为、心理不断发生变化,这对青年思想政治教育提出了巨大的挑战。
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Dynamic Research on Youth Thought, Behavior, and Growth Law Based on Deep Learning Algorithm
The growth and development of youth is related to the destiny of the country and the nation, and the cultivation of young people in the new era is of great significance. Youth is a special stage in life, and the ideological and moral concepts of young people during this period are still very malleable. In the process of educating them, it is necessary to grasp the characteristics and laws of their ideological and moral growth to be targeted. The characteristics of young people's ideological and moral growth are variability, subjectivity, practicality, and hierarchy; the laws of their ideological and moral growth include the law of guiding transcendence, the law of edification and internalization, the law of mutual promotion of knowledge, will and action, and the law of gradual progression. With the intensification of economic globalization, the Internet, and big data, the thoughts, behaviors, and psychology of young people are constantly changing, which poses a huge challenge to youth ideological and political education.
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来源期刊
International Journal of Data Warehousing and Mining
International Journal of Data Warehousing and Mining COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
2.40
自引率
0.00%
发文量
20
审稿时长
>12 weeks
期刊介绍: The International Journal of Data Warehousing and Mining (IJDWM) disseminates the latest international research findings in the areas of data management and analyzation. IJDWM provides a forum for state-of-the-art developments and research, as well as current innovative activities focusing on the integration between the fields of data warehousing and data mining. Emphasizing applicability to real world problems, this journal meets the needs of both academic researchers and practicing IT professionals.The journal is devoted to the publications of high quality papers on theoretical developments and practical applications in data warehousing and data mining. Original research papers, state-of-the-art reviews, and technical notes are invited for publications. The journal accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to papers focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving
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