Abstract

Aim and Objective. In the conditions of modern reality, the importance of solving environmental problems of a global and regional nature makes it relevant to search for ways to improve the process of mathematical training of future ecologists. One of such directions is the motivation to study mathematics and its applications. The purpose of the study is to identify and test the methodological conditions that ensure the strengthening of the mathematical motivation of students – future ecologists in the process of teaching mathematics at a university. Materials and methods. The Mathematics Motivation Questionnaire (MMQ) was chosen as the main diagnostic tool, and the author's questionnaire compiled on the basis of this questionnaire, taking into account the specifics of teaching mathematics to future ecologists, was chosen as an additional diagnostic tool. 205 students of environmental training directions of Vyatka State University took part in the implemented survey. Statistical analysis of the obtained results was performed using the Mann-Whitney U test. Results. For the first time, a technology for diagnosing the mathematical motivation of students – future ecologists based on modern research is presented. A number of methodological conditions have been formulated that ensure the strengthening of the motivation under study, which clarifies and expands the ideas about the system of mathematical training of future ecologists. The analysis of motivation for admission to the university revealed a number of problems, which the intervention was aimed at overcoming. Its effectiveness was confirmed by significant differences in the MMQ questionnaire (Uemp = 100 < Ucr = 113; p < 0,05) and according to the author's questionnaire (Uemp = 72 < Ucr = 88; p < 0,01). Based on the re-evaluation, the transformation of the motivational attitudes of students - future ecologists from static beliefs about the nature of mathematics to dynamic ideas was revealed. Conclusion. The practical significance of the study is determined by the possibilities of using its results to improve the mathematical training of future ecologists, as well as by optimizing the process of teaching mathematics to maintain productive motivation.

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