Learning Style Identification System: Design and Data Analysis

- Glazunova, Olena (orcid.org/0000-0002--0136-4936), Morze, Nataliia (orcid.org/0000-0003-3477-9254), Golub, Bella (orcid.org/0000−0002−1256−6138), Burov, O. Yu. (orcid.org/[0000-0003-0733-1120]), Voloshyna, Tetyana (orcid.org/0000-0001-6020- 5233) and Parhomenko, Oleksandra (orcid.org/0000-0002--0136-4936) (2020) Learning Style Identification System: Design and Data Analysis In: 16th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer, c. Kharkiv, Ukraine.

[img] Text
20200793.pdf - Published Version

Download (1MB)

Abstract

The article analyzes different approaches to design adaptive educational systems on the basis of students' learning style identification. As a result of the investigation a system to identify the student's learning style with the data analyzing module has been designed and implemented. A data analyzing module is applied for the further adaptation of digital educational content and educational methods to students' learning style. The data background for the module to analyze learning style identification system is the universal e-learn environment users’ database, the results of learning style identification due to VARK (visual, audial, read-write, kinesthetic) model or any open external information like psychotype, type of intelligence, etc. Data storage uses the concept of data warehousing to predict special methods for data model design taking into account the integrity of datasets from different sources, object orientation, consistency, data consolidation or multidimensional data architecture to simplify analytical queries. The data analyzing technologies being applied within the system are based on the information retrieval approach using SQL language; OLAP and Data Mining technologies. The results of the system implementation gave an opportunity to fix the correlation of learning styles with other personal characteristics like psychotype, gender, secondary education level, academic achievements, etc. The represented data of data analysis concerning IT major students give reason for the conclusion about the necessity to adapt digital content to multimodal and kinesthetic learning style, to apply learning methods and technologies on the basis of project tasks, group communication and collaboration.

Item Type: Conference or Workshop Item (Paper)
Keywords: Learning Style, Design of the Learning Style Identification System, Technologies of Data Analysis
Subjects: Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 004 Computer science and technology. Computing. Data processing > 004.9 ІКТ ( Application-oriented computer-based techniques )
Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 1 Philosophy. Psychology
Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 3 Social Sciences > 37 Education > 378 Higher education. Universities. Academic study
Divisions: Information Technologies and Learning Tools > Department of Technologies of Open Learning Environment
Depositing User: с.д/п.н.с. Oleksandr Burov
Date Deposited: 04 Dec 2020 11:58
Last Modified: 04 Dec 2020 11:58
URI: http://lib.iitta.gov.ua/id/eprint/722572

Downloads

Downloads per month over past year

Actions (login required)

View Item View Item