Practice of Teaching Management in Colleges and Universities under the Internet Environment

The purpose of the study was to justify the essence of the “Internet immersion” phenomenon and to create a standardized method for its measurement. A comparative analysis of approaches to human behavior on the Internet environment and existing diagnostic methods has revealed a significant variety of categories and definitions used. At the same time, there is no definition that: first, characterizes the degree and quality of user's Internet activity; second, is free from negative and clinical connotations; and, third, describes a wider time range of Internet usage than the actual state of immersion. The authors substantiate the possibility of studying the phenomenon of the Internet immersion through the category of disposition. It consists of the readiness to use technical means and informational resources of the Internet to solve problems in various types of activities and communication. The authors identify traditional components in the structure of the Internet immersion phenomenon. These are, first of all, a cognitive component, represented by digital competence self-assessment; then, an affective component, represented by motivation and emotional and value-based attitude towards the Internet; and a behavioral component, represented by the amount of digital consumption. Based on this definition, it was possible to construct a compact 9-block “Index of the Internet immersion” questionnaire. Its standardization was conducted on the sample of 712 adolescents, aged from 11 to 17. Using the factor analysis, the structure of the questionnaire was identified. The first factor includes questions that relate to the time spent on the Internet and signs of dependence on it. The second factor includes questions that reveal the activity component and emotional attitude to the Internet. The third factor includes questions about experience and self-assessment of digital competence. The advantage of the “Index of the Internet immersion” questionnaire is a fairly high reliability for internal consistency of scales throughout the questionnaire. We also confirmed the sufficient convergent validity of the “Internet environment immersion Index” method with the “Scale of Problematic Internet Usage” by A.A. Gerasimova, A.B. Kholmogorova (adapted version of Generalized Problematic Internet Use Scale (GPIUS) by S. Caplan) and the Internet Addiction Test (IAT, K. Young), modified by V. A. Loskutova. This indicates its validity as an independent tool that does not duplicate other tools for semantically similar phenomena measurement. In the conditions of forced self-isolation that have developed in our country, the method of the Internet immersion diagnostics as an adequate and theoretically justified tool will allow us to study changes in the emotional state and behavior of teenagers on the Internet.

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Probability Models for Assessing Effectiveness of Advertising Channels in the Internet Environment

The Journal of Social Sciences Research ◽

10.32861/jssr.spi5.209.215 ◽

2018 ◽

pp. 209-215

Keyword(s):

Graph Theory ◽

Markov Chains ◽

Markov Processes ◽

The Internet ◽

Probability Models ◽

Method Of Calculation ◽

Internet Environment ◽

The Impact ◽

Theory Of Graphs ◽

Selection Of

Nowadays, marketing specialists simultaneously use several channels to attract visitors to websites. There is a difficulty in assessing not only the efficiency and conversion of each channel separately, but also in their interconnection. The problem occurs when users visit a website from several sources and only after that do the key action. To assess the effectiveness and selection of the most optimal channels, different models of attribution are used. The models are reviewed in the article. However, we propose to use multi-channel attribution, which provides an aggregate assessment of multi-channel sequences, taking into account that they are interdependent. The purpose of the paper is to create an attribution model that comprehensively evaluates multi-channel sequences and shows the effect of each channel on the conversion. The presented model of attribution can be based on the theory of graphs or Markov chains. The first method of calculation is more visual, the second (based on Markov chains) allows for work with a large amount of data. As a result, a model of multi-channel attribution was presented, which is based on Markov processes or graph theory. It allows for maximum comprehensive assessing of the impact of each channel on the conversion. On the basis of the two methods, calculations were carried out, confirming the adequacy of the model used for the tasks assigned.

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