3 research outputs found
Spatial-temporal model of engagement of participants of educational activity in the digital educational environment
In the context of the COVID-19 pandemic, the educational process has acquired a virtual character, when the role of technical teaching tools that mediate the real interaction of students with the teacher has sharply increased. The conditions for creating an engagement effect have changed and there is a need to study the phenomenon of engagement and its psychological mechanisms. The main aspects of an engagement manifestation that represent the spatial part of the model are shown: cognitive, emotional, behavioral, activity, motivational, socio-psychological and physical. The novelty of the spatial-temporal model is that it involves all the spatial factors that are included in the main temporal phases of activation of engagement: preparatory, active, evaluation and correction. The long-term and short-term options for using the engagement model with their methods of implementation, expected results and realization mechanisms are proposed. The implementation of the short-term version of the engagement model is carried out through a system of digital monitoring of emotional and cognitive reactions of a person in a digital environment. The possibility of managing and self-managing students' engagement in educational activities in a digital environment is shown
On the formation of the ability to perceive the depth, volume and spatial perspective of flat images as a basic component of the technology for the human creative potential development
This article identifies new opportunities for initiating human creativity through activation of visual perception. It considers the possibility of increasing the level of creativity through the indirect formation of visual constructs when referring to the associative thinking of students. It shows that the potential development of creativity is due to the level of the subject development and the ability to perceive any flat images with the effects of depth, volume, and spatial perspective (hereinafter referred to as the 3D phenomenon). The results of student learning and testing students in grades 7-11 of one of the schools (Gymnasium) in Kazan are presented. Technology patents were obtained on training and surveys
A Complex Neural Network Model for Predicting a Personal Success based on their Activity in Social Networks
The development and improvement of effective tools for predicting human behavior in real life through the features of its virtual activity opens up broad prospects for psychological support of the individual. The presence of such tools can be used by psychologists in educational, professional and other areas in the formation of trajectories of harmonious person's development. Currently, active research is underway to determine psychological characteristics based on publicly available data. Such studies develop the direction of “Psychology of social networks”. As markers for determining the psychological characteristics of people, various parameters obtained from their personal pages in social networks are used (texts of posts and reposts, the number of different elements on the page, statistical information about audio and video recordings, information about groups, and others). There is a difficulty in obtaining and analyzing a data set this big, as there are non-linear and hidden relationships between individual data elements. As a result, the classic methods of information processing become inefficient. Therefore, in our work to develop a comprehensive model of success based on the analysis of qualitative and quantitative data, we use an approach based on artificial neural networks. The labels of the input records are used to divide the subjects of the study into five clusters using clustering methods (k-means). In the course of our work, we gradually expand the set of input parameters to include metrics of users' personal pages, and compare the results to determine the impact of qualitative parameters on the accuracy of the artificial neural network. The results reflect the solution of one of the tasks of the research carried out within the framework of the project of the Russian Science Foundation and serve as material for an information and analytical system for automatic forecasting of human life activity based on the metrics of his personal profile in the social network VKontakte