The Training Method for Digital Data Operation

Author:

Shevtsova I. V.1ORCID

Affiliation:

1. Lomonosov Moscow State University

Abstract

The purpose of study is to develop the training method for operation with digital data. The article discusses the issues of training for mining and analyzing digital data on the example of social networks for higher education programs in the areas of “Management”, “Public administration”, “Human resources” and “Political Science”. The relevance of the study is justified by factors: digital transformation of economy; development of digital data sources; increasing the importance of digital data in management. Universities have a new task - to prepare students for working with digital data in their professional activities. A review of scientific sources has shown that programming skills are required to apply existing data mining methods. While the modern IT and data sources contain tools for working with data, which are available to a wide range of users without the need to write the code. Materials and methods. The study is based on the theoretical materials and the practice of operation with digital data in management processes. The empirical studies were conducted to evaluate the effectiveness of the application of practical data manipulation techniques in higher education training. Results. The method was developed for the practical training in data mining and analysis skills. The implementation of the author’s method in the educational process showed its effectiveness in the formation of practical skills in working with digital data, as well as a high level of assimilation of theoretical foundations due to the presentation of educational materials in an accessible form for non-core IT area. The method doesn’t require a specific complex of the material and technical support for training and labor intensity. The article highlights the areas of application of social network data in Economics and science: marketing research of consumers and competitive advantages of goods or services; formation of a data set for machine learning and usage of artificial intelligence technologies, political research of civil society and political preferences of citizens, scientific research on the organization and management of social media. Training for analytical work on the example of social networks highly motivates students due to the significant role of networks among young people. The use of effective pedagogical technologies such as project-oriented learning, social learning, and collaboration in an electronic educational environment supports the quality of training by the developed method. As a result, students better learn knowledge and practical skills that are also applicable to working with other types of social media and global data platforms. Conclusion. The article reveals: the specifics of teaching materials; development of a workshop in the areas of training; modern pedagogical technologies, scheme, and teaching methods. The advantages and disadvantages of social networks as a data source are considered. The presented method is implemented in teaching the discipline “Informatics” of the basic training cycle at the faculty of public administration of Lomonosov Moscow State University.

Publisher

Plekhanov Russian University of Economics (PRUE)

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference20 articles.

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3