METHODS EDUCATIONAL DATA MINING IN E-LEARNING SYSTEMS
DOI:
https://doi.org/10.32689/maup.it.2024.2.5Keywords:
e-learning system, Educational Data Mining, learning analytics, information technologyAbstract
The possibilities of implementing data mining in educational analytics are investigated, the main directions of intellectual analysis of educational data in the framework of interaction of participants in the educational process are highlighted. The use of e-learning systems in the educational process leads to the accumulation of large volumes of educational data and digital footprints of students. The use of Educational Data Mining methods for analyzing this information, forecasting and visualizing it in the form of interactive reports allows to reveal hidden knowledge and patterns that significantly improve the training of future professionals. The purpose of the work is to investigate the development of intellectual analysis of educational data, the main tasks and methods of intellectual analysis to identify promising areas of its application in information systems and e-learning technologies of higher education institutions. Methodology. Based on the analysis of literature sources, the main tasks are reviewed and the stages of intellectual analysis of educational data are identified in order to improve the efficiency of the learning process in higher professional education. By means of system analysis, a scheme of the process of working with big data generated by e-learning systems is proposed. The relevance of using Data Mining methods in higher education is reviewed and substantiated. The scientific novelty of the study is to substantiate the scheme of information technology using data mining methods obtained from LMS to optimize educational processes and predict student trajectories. Conclusions. It is proved that the development of information technology based on the use of data mining methods in the implementation of e-learning systems contributes to solving problems related to understanding student behavior, improving the quality of e-courses, improving teaching methods, reducing the cost of organizing the learning process and determining further directions of educational analytics in accordance with global trends.
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