Abstract
Currently, the most of the processes at the educational analytical centers entirely depend on the human factor. Automation of the real-time monitoring system for the educational processes can be possible through the development and improvement of the information technologies, algorithms and computational methods, such as machine learning methods, analysis and visualization of big data processes. This paper covers the issues of the development of automated system for monitoring of educational processes from the point of view of data collection, data management, and data modeling. It includes the stages of data collection with the description of data engineering methods, data management procedures, algorithms of data cleaning and filtering, data modeling and visualization processes as well as the description of intelligent algorithms for scoring analysis of results. The principal feature that characterizes the development of the mentioned automated system is the using of availability of user experience data from existing educational sites and other open data sources that allow us to create a complete vision of the educational processes’ state at various levels.
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Acknowledgement
This research was supported by grant of the program of Ministry of Education of the Republic of Kazakhstan BR05236699 Development of a digital adaptive educational environment using Big Data analytics. We thank our colleagues from Suleyman Demirel University (Kazakhstan) who provided insight and expertise that greatly assisted the research. We express our hopes that they will agree with the conclusions and findings of this paper.
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Atymtayeva, L., Kozhakhmet, K., Savchenko, A. (2020). Automated System for Monitoring of Educational Processes: Collection, Management, and Modeling of Data. In: Shishkov, B. (eds) Business Modeling and Software Design. BMSD 2020. Lecture Notes in Business Information Processing, vol 391. Springer, Cham. https://doi.org/10.1007/978-3-030-52306-0_24
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