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Selection of criteria for a decision support system for an art university
- Source :
- Informatics and education. :56-62
- Publication Year :
- 2021
- Publisher :
- Publishing House Education and Informatics, 2021.
-
Abstract
- Automation of decision support is proposed by including special criteria with the overall configuration of an automated decision support system for creative universities. A prototype of an automated decision support system for creative universities has been developed, which will allow assessing the achievements particularly talented students and identifying the needs in the learning process in order to help organize the educational process in accordance with identified capabilities. Use of a decision support system based on the Bayesian classifier is suggested to assess and evaluate factors contributing to the progress in teaching students particular techniques, and in perspective to assess the possible resources that will be required to make changes to the learning plan. The existing approaches to the assessment of students academic performance are analyzed. The list of specific performance indicators, which are important to be taken into account when assessing the achievements of students of creative specialties, is given. The system should contribute to the formation of the learning plan, taking into account the capabilities of both a group art workshop as a whole, and special needs of an individual to develop, if necessary an individual approach.
- Subjects :
- Decision support system
Learning plan
Computer science
business.industry
Process (engineering)
05 social sciences
0211 other engineering and technologies
050301 education
021107 urban & regional planning
Special needs
02 engineering and technology
Automation
Naive Bayes classifier
Engineering management
Performance indicator
business
Specific performance
0503 education
Subjects
Details
- ISSN :
- 26587769 and 02340453
- Database :
- OpenAIRE
- Journal :
- Informatics and education
- Accession number :
- edsair.doi...........f0a042152fd39edb36cf7cb627df52bc
- Full Text :
- https://doi.org/10.32517/0234-0453-2021-36-3-56-62