Modeling the Dynamics of Teaching Russian as a Foreign Language Using the Lotka — Volterra Model

Abstract

Background. In the context of globalization, the demand for teaching Russian as a foreign language (RFL) is growing. This is driven by increased interest in Russian culture and literature, as well as by the expansion of Russia’s economic and cultural ties with other countries. However, traditional methods of assessing progress (tests and exams) fail to account for the nonlinear nature of language acquisition, reducing the effectiveness of RFL curricula.

Objective. The aim of this study is to apply the Lotka — Volterra mathematical model, traditionally used in ecology to describe species interactions, to the process of learning Russian as a foreign language. The paper proposes an adaptation of the model, where the “prey” is the knowledge of the target language (Russian), and the “predator” is the process of forgetting and interference.

Methods. The methodology includes calibration of the parameters of the mathematical model based on data from 30 foreign students and computer modeling of the dynamics of language interaction over 12 months.

Results. The results demonstrate nonlinear oscillatory dynamics. The model allowed us to determine the system’s stable equilibrium point and key learning performance metrics, such as the cycle period (15.8 weeks) and knowledge balance (68.3%).

Conclusions. The study resulted in the development of a software package and an algorithm for generating pedagogical recommendations for predicting the effectiveness of educational programmes. This approach is based on the application of bioecological principles to language teaching. The practical value of this work is confirmed by the ability to predict “forgetting crisis” points 2–3 weeks in advance and optimize teaching loads based on an analysis of system dynamics.