Open AccessA problem of long distances in the educational environment
Author(s) -
I S Nikiforov,
P. I. Paderno
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1703/1/012050
Subject(s) - relevance (law) , computer science , task (project management) , process (computing) , set (abstract data type) , correctness , resource (disambiguation) , field (mathematics) , job analysis , position (finance) , knowledge management , management science , job satisfaction , engineering , psychology , computer network , social psychology , mathematics , systems engineering , finance , political science , economics , pure mathematics , law , programming language , operating system
A process of the specialist’s professional development involve two aspects of the decision-making support: choosing a field of study (by an applicant) and choosing an applicant for a job position and training (by a company). The correctness of solving this task depends greatly on developing methods allowing to identify potential of an applicant. The goal of this research is developing a formalized approach to create the metrics in the educational environment, which would allow comparing applicants to each other in terms of compliance with the requirements of a certain job. The methods: the research uses system analysis approaches; models of characteristics changing during the training; scaling of heterogeneous values; integrating particular estimations (getting integral estimation) based on expert opinions. The results: the analysis allowed identify a set of dependencies related both to a study subject and job requirements, distinctive features and resource characteristics of learning technologies. Several models and an approach to assessing a prospective applicant were suggested taking into account a multi-dimensional resource, which is required to train a certain applicant up to the required level. The practical relevance: the suggested approach allows to make formalized setting and further addressing a set of evaluation and optimization tasks related both to the best choice of future job (for an applicant), and a choice of most promising applicants and learning techniques (for a company).