Search

In this paper we present the results of an interdisciplinary research based on the application of big data, date science, artificial intelligence and machine learning methods in educational analytics. Artificial intelligence techniques applied for the analysis of depersonalized data stored in the information and analytical system "E-education in the Republic of Tatarstan" from 2015 to 2020. BigData technologies were used in this work to perform high-performance computing related to initial preprocessing of raw data in computation cluster. By using the methods of artificial intelligence, we modelled one of the most important stages in the formation of the educational trajectories of schoolchildren, associated with the fact that after the 9th grade, schoolchildren either continue their studies in high school (grades 10-11), or move to the professional educational organizations. As the input data for neural network training, we used a vector containing the average marks for all quarters of pupils, obtained by using high-performance Dask-based cluster data processing system from initial raw data. We concluded that multi-layer neural network with two hidden layers was able to predict the pupil’s pass to 10th grade, and achieved the best performance with classification accuracy exceeding 70%. Also, the performance of trained neural network had been analyzed by visualization of Receiver Operator Characteristic (ROC)-curve and by calculation of recall, precision, specificity and area covered by the ROC-curve (AUX) parameters.

Based on the studies of the daily work of teachers in educational institutions, it was noticed that the teacher in the learning process makes decisions on average every minute. The primary school teacher interacts even more actively with their students. Although most of such interactions are not planned. The teacher is constantly looking for new ideas, they improvise, use innovations. And they always reflect on what they are doing. Many solutions are the product of teachers' personal pedagogical experience and their intuition. These solutions are often not included in the research results. The purpose of the study is to identify the main patterns of influence of the educational environment components on the effectiveness of teachers' professional activities. The problem of teachers’ professional development is gaining significance in scientific research. However, the educational environment itself contains a number of factors that contribute to the professional success of a teacher. Factors can help, stimulate the teacher to the most effective and efficient forms of work with students, or they can create obstacles, difficulties that lead to the teacher's failure to succeed. The empirical study revealed a number of features of the educational environment that impact the success of the teacher's professional activity based on the analysis of big data accumulated in the system “Electronic Education in the Republic of Tatarstan” and statistical reports. Further, it is planned to use the identified features in the management (possibly modification) of the professional development trajectory of the teacher.