Open AccessVector interpretation of students’ residual knowledge assessment
Author(s) -
Sergey Ivanovich Makarov,
Svetlana Aleksandrovna Sevastyanova
Publication year - 2018
Publication title -
samarskij naučnyj vestnik
Language(s) - English
Resource type - Journals
eISSN - 2782-3016
pISSN - 2309-4370
DOI - 10.17816/snv201874309
Subject(s) - comparability , residual , computer science , interpretation (philosophy) , presentation (obstetrics) , field (mathematics) , process (computing) , test (biology) , visualization , artificial intelligence , relation (database) , data mining , machine learning , data science , mathematics , algorithm , medicine , paleontology , combinatorics , biology , pure mathematics , radiology , programming language , operating system
Residual knowledge assessment is one of the procedures used in the Russian education system to monitor the quality of education at various levels. Typically, this procedure is considered to be a computer testing of the previously learned disciplines. The analysis of test results gives grounds for making necessary decisions. This determines the importance of reliable, accessible and informative presentation of monitoring results. The paper contains a method of visualization and interpretation of residual knowledge assessment results. The authors think that it is possible to use this method for analyzing the problems of training at the individual and group levels. For statistical information processing it is offered to use a vector form of data presentation. The paper contains examples of using a vector model for estimating the level of residual knowledge in three or more disciplines. The authors propose an approach that solves the problem of test results comparability carried out in various estimation systems. The main conclusions and results can be used directly in the educational process, in the field of education management, in psychological and pedagogical work.