The project approach is widely used in organizing the training of IT specialists in universities. Despite the fact that the organized development processes are extremely close to the processes used in commercial IT companies, the analysis of the development process of student projects is not carried out. This article proposes an approach for performing analytics of the development process in a student project, and also discusses options for using the results of analytics in assessing student work.

The work is devoted to the development and implementation of a CMS engine for creating popular science portals on geology with the subsequent implementation of an adaptive version of the popular science portal “History of the Earth: a geological perspective”. The following were selected and implemented as the basic entities of the engine being developed: “main page”, “article”, “gallery”, “video”, “3D-Earth”, “timeline”, “time component” and “3D Exhibit”. As a result of the work done, a popular science portal was created that allows us to study our planet in the context of time intervals, events and artifacts.

One way to evaluate the scientific activity of a scientist is to calculate various indicators based on the number of his publications and their citation. In this case, each co-author of the publication receives the same number of points for it. A similar ranking method leads to an artificial increase in the number of co-authors in our publications. This leads to a distortion of ratings, and to a significant decrease in the quality of thematic search. The method presented in the paper allows us to evaluate the contribution of the author to his published works. Approbation of the method was done on the data of the scientometric system IAS ISTINA.

The relevance of the issues of the analysis of scientific publications is due to the fact that with the of Internet technologies, it became possible to collect data on the publication citation network. Meanwhile, the current approach to the analysis of scientific publications is based on bibliometric indicators that take into account only the number of citations. However, network analysis, which is mainly used in the study of social networks, is becoming increasingly widely used. The author has developed a methodology that allows for an effective analysis of scientific publications based on network analysis methods alternative to bibliometric methods. As criteria for evaluating scientific publications based on network analysis, relevant measures of the centrality of the citation network nodes are established: centrality by degree of connectivity; centrality by proximity to other nodes; centrality by mediation; centrality by authority; centrality by concentration. The author presented the experiment result that allows validating the developed methodology of network analysis of the scientific publications significance. Scientometric databases were used as primary sources of data on publications, which make it possible to track the citation of publications and identify relevant citation networks. The application of the proposed network analysis methodology contributes to the identification of important publications in the development of the scientific direction.

A brief overview of some methods of artificial intelligence in the field of Earth sciences is given. The prospects of using these methods to obtain new knowledge are noted. The results of the authors' first attempts to apply natural language processing methods for processing scientific articles on geology are presented. The possibilities of developing work in this direction are discussed.

This paper considers the questions about the possibility of using data about the students presented in electronic form to build their digital portraits.  A set of characteristics necessary for its construction is proposed, a data model is designated.

Implemented tools for collecting data about students from social networks and other Internet resources. Algorithms for constructing a digital portrait are proposed. The application of machine learning algorithms for these tasks is illustrated. Examples of the use of digital portraits in education are given.