Data Mining methods are used to predict student learning charcteristics

The regular scientific seminar of department 10 of the ANAS Institute of Information Technology was held. The employee of the department, Gulara Mammadova, presented a presentation "Development of Data Mining Methods for Predicting Educational Features of University Students". She noted that the main goal of the higher education institution is to increase students' academic success.

She said university teachers should monitor students' learning, determine what areas they are making progress and whether they need additional education.  Universities should also use modern intellectual methods of data analysis to help students effectively solve all the problems they face while studying.

The speaker noted that it is possible to use the methods of intellectual education (EDM - Educational Data Mining) to analyze the large amounts of data generated in the learning process and to predict student performance. "Prediction helps keep track of student performance," Mammadova said, adding that teachers identify students with special needs and take appropriate measures to improve their learning activities.

She emphasized the availability of different methods of intellectual analysis to predict the data and noted the pros and cons of each. She provided practical examples of using these techniques for predicting training activities. She noted that the use of EDM technology in forecasting can improve the quality of the learning process, optimize students' performance, and increase their success.

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