Abstract:The relevance of environmental and economic activity requires professional training of specialists and, accordingly, new organizational and pedagogical conditions for effective education. It is also necessary to develop control and measuring materials that would have all the qualities (validity, reliability, consistency, significance and objectivity) to obtain the most reliable results in justifying the need and sufficiency of the identified conditions. The intensification of information processes in vocationa… Show more
“…Related scholars pointed out that educational machine learning is a new research field formed by the combination of machine learning and learning science (Salamatov et al, 2021). Educational machine learning aims to create conditions for students' learning through observation and understanding of the process of learning.…”
The work used the current mature computer technology, machine learning technology, and other high-tech to explore the comprehensive application of educational information management under the Internet to provide educational scientific researchers with a retrieval platform for educational statistical information. Deep learning was used to extract useful network features more effectively and make the machine learning model fully consider the constraints of satisfying the constraints and optimization objectives in the problem. Based on the classification of the restricted Boltzmann machine, the Gauss-binary conditional classification of the restricted Boltzmann machine model was proposed as the routing decision unit, with the given specific training algorithm of the model.
“…Related scholars pointed out that educational machine learning is a new research field formed by the combination of machine learning and learning science (Salamatov et al, 2021). Educational machine learning aims to create conditions for students' learning through observation and understanding of the process of learning.…”
The work used the current mature computer technology, machine learning technology, and other high-tech to explore the comprehensive application of educational information management under the Internet to provide educational scientific researchers with a retrieval platform for educational statistical information. Deep learning was used to extract useful network features more effectively and make the machine learning model fully consider the constraints of satisfying the constraints and optimization objectives in the problem. Based on the classification of the restricted Boltzmann machine, the Gauss-binary conditional classification of the restricted Boltzmann machine model was proposed as the routing decision unit, with the given specific training algorithm of the model.
“…The modern situation of green economy digitalization actualizes the problem of developing innovative principles of professional training of specialists in higher education institutions. Methodologically competent assessment of the level of PEEC of university graduates as a component of their human capital [7][8][9] is the key to an effective response to the needs of society, employers and students themselves, who need to know the criteria to assess their readiness for the profession in general, qualitative effective performance of their work in a particular workplace, ability to respond quickly to changes in different spheres of social life. The adequate approach to such an effective response is largely due to the objective need to develop innovative pedagogical tools as a set of interrelated tools (methods, techniques, methods, means) of pedagogical interaction between the subjects and objects of the educational process.…”
The current situation of green economy digitalization actualizes the problem of developing innovative principles of professional training in universities. The key conditions for the training of highly qualified personnel in accordance with the needs of society and employers as participants of educational relations are of particular importance due to the qualimetric assessment of educational achievements of students (QAA), which has been actualized since 2000 by conceptual research within the framework of the Programme for International Student Assessment (PISA). The material for the study was modern approaches, algorithms and models of QAA in higher education institutions. The main methods of research were theoretical analysis of published scientific literature on the problem of digital assessment of the level of professional competence of university graduates in the field of green economy-sustainable development, primarily, their professional environmental and economic competence (PEEC) based on a ranking analysis of expert information on the impact of different factors. At the same time, the problems which are the result of multifactor dependencies typical for pedagogy are put into the structured category and the apparatus of mathematical modelling and selection of optimal solutions is scientifically grounded to solve them. The most significant pedagogical factors were selected according to their influence on the level of PEEC formation as a result of using the method of expert group evaluation and ranking the selected opinions of experts, the consistency of which was previously revealed by calculating the Kendall's concordance coefficient. The principles of the systematic approach applied in the pedagogical research, using the conceptual provisions of quantitative measurements, numerical modelling and mathematical statistics based on factor planning allowed us to present the results of the experiment to identify the final dependence of the level of PEEC formation as a regression model as the initial step in the developed platform (underlying concept) of qualimetric assessment of the dominant factors of PEEC formation. The initial principles of such a concept are formulated, providing opportunities for studying and analyzing the influence of various pedagogical factors and organizational and pedagogical conditions, choosing the ways of generating educational trajectories.
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