Digital transformation of education and science puts forward new requirements for training of graduate and doctoral students, in particular for development of informational and analytical competence. It is described in international documents governing scientific field. Analysis of digital systems and consideration of their services allows us to say that their existing list and functionality can be used to develop informational and research competence of postgraduate and doctoral students. It is confirmed that important role in development of informational and research competencies of postgraduate and doctoral students is given to digital technologies, in particular, to digital open systems. Their use contributes to improving and expanding opportunities in research, presentation of research results and image of the researcher and institution. Digital society requirements to informational and research competence of postgraduate and doctoral students are defined and described. They include: readiness and ability to carry out research activities; ability to search and select necessary information and data, their transformation, storage and transmission using digital technologies; ability to critically evaluate found information (check their accuracy, timeliness, expediency); ability to perform scientific research (organization, planning, conducting) with use of digital technologies. Course of experimental work is presented; the obtained results are given and their interpretation is carried out. Fisher's angular transformation was applied in order to confirm reliability of obtained results of experimental study. Experimental verification of the proposed methodological system of using digital systems in postgraduate and doctoral students training, aimed at the development of information and research competence confirmed its effectiveness and pedagogical feasibility.
The objective of the article is constructing of the two-factor model on the basis of the statistical material of the Webometric Rating of Universities, which analytically describes the status of Ukrainian higher educational institutions in terms of Webometrics indicators, provides an opportunity for its quantitative and qualitative analysis and forecasting of development trends of market educational services and marketing research in this area. The statistical analysis of the data of the Webometric Rating of Universities was conducted using the professional statistical information processing program STATGRAPHICS Centurion XV.I. Analytical relations are obtained using the Pade approximation technique. Mathematical editor Maple has been used to visualize the results of research and illustrate a qualitative picture of the rating of Ukrainian universities in the Internet space using the Webometric Indicators system. A two-factor model of the state and forecast of academic representation of Ukrainian universities according to Webometric rating is constructed. Using the proposed model, an analytical expression is obtained that allows for quantitative and qualitative assessments of the world ranking of higher educational institutions of Ukraine in the Web-indicators system Webometrix in order to increase their academic presence on the Internet, to strengthen the international authority and raise the national science school as a whole for a qualitatively new degree of development. The scientific novelty of the work is in the inclusion in the model of the time factor, the availability of which makes it possible, firstly, to extend the statistical material used in time and, secondly, to predict the trends and prospects of presentation in the Internet space of Ukrainian universities as advanced research centers. The main results of the work can be useful as a methodological material during the educational process in higher educational institutions, in the training and improvement of the skills of management personnel, in developing programs for reforming the educational process in higher education in order to bring it closer to European requirements and achieve the level of the best world universities. The presented methodology and data analysis algorithm can be generalized to evaluate rating systems of other nature: when evaluating students' educational and community work, financial analysis, in particular, to assess the probability of default of non-lending organizations, to determine the reliability of commercial banks, to conduct sociological tests, and surveys, medical and biological research and other areas of public administration.
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