Assessment of the relevance of the student survey results in the educational process

Abstract

Many educational institutions implement feedback mechanisms in their activities, this also occurs according to the requirements of educational standards, public accreditation organizations, international quality standards. But it is not always clear how to competently and effectively use the data obtained due to the unsuitability of such data in its original raw form. The study is aimed at developing a methodology for filtering student reviews about the studied disciplines from irrelevant ones in order to further use them in the management system of an educational institution and the educational process. The study used the methods of statistical data analysis and estimation of the parameters of a logistic regression model using STATISTICA 10.0 and Jamovi 1.8.1 programs. Spearman's and Kendall's correlation coefficients were used to assess the direction and strength of the link between quantitative indicators. Cramer's V test was used to assess the relationship between dichotomous indicators. For clustering observations, the K-means method was used with the setting of measuring the minimum distances. The results of the study showed statistically significant relationships (p < 0.05) between indicators of educational activity and student feedback, which made it possible to use these indicators to classify reviews. The study using the cluster analysis made it possible to obtain the optimal number of clusters for solving the task of classifying and confirming the adequacy of the developed methodology. Thus, the correlation analysis showed a direct moderate relationship between irrelevant reviews obtained by the methodology and three-cluster classification at r = 0.70, and Cramer's V test showed a strong association with the results of three-cluster classification (0.70). Using the classification results as a training sample, a logistic regression model was built with an adequacy of 94.97%. The results of the study lead to the conclusion that the obtained methodology and the logistic regression model can be used to clean the initial feedback data from irrelevant reviews based on the indicators of students' learning activities.