DEVELOPMENT OF AN INFORMATION AND EDUCATIONAL PORTAL OF DISTANCE LEARNING BASED ON EDUCATIONAL DATA MINING
DOI:
https://doi.org/10.37943/AITU.2022.48.68.003Keywords:
information and educational portal, data mining, Educational Data Mining, e-learning, learning analyticsAbstract
Currently, there is an increase in demand for distance education programs, which actualizes the problems of organizing the educational process at universities using these technologies. The article highlights and describes the characteristic features and
prospects of using the analysis of educational data in the information and educational portal of distance learning, in order to implement adaptive learning and learning in accordance with dynamically formed individual trajectories. The task is to create a fundamentally new information system of the university using the results of the analysis of educational data. One of the functions of such a system is to extract knowledge from the data accumulated during operation. Creating own system of this type is an iterative and time-consuming process that requires preliminary research and step-by-step prototyping of modules. The novelty lies in the fact that there is currently no methodology for developing such systems in Kazakhstan, so a number of experiments were conducted in order to collect data, select suitable methods for studying the collected data, and then interpret them. As a result of the experiment, the authors identified the sources of educational data available for analysis in the information environment of the university. The data of semester academic performance obtained from the Toraighyrov University information system, data obtained as a result of independent work of students and data obtained using specially developed Google-forms were taken as a basis. An
information and educational portal was created for the automated collection, processing and analysis of educational data. Based on the study of students’ behavior, it becomes possible to form recommendations for teachers to improve the content and structure, as well as recommendations for the training of students. The data contained in the activity logs are examined to obtain information, search for dependencies by filtering relevant logs, structuring information from them and providing data in a form convenient for analysis and drawing conclusions. The data of the main types of events generated as a result of recording user actions in the learning management system and scenarios for using the results of the analysis of these data are considered. The elements of the software implementation of this system are described in detail, conclusions are made about the availability of the data sources used, and conclusions are drawn about the prospects for further development.
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