The digital twin virtual simulation platform has strong visualization and interactivity, which can transform abstract theoretical knowledge into vivid and imaginative virtual scenes, helping to improve students’ learning interest and enthusiasm. This paper introduces the digital twin education application framework, discusses the specific application methods of digital twin technology in Russian distance teaching, and constructs the corresponding Russian language teaching mode. For the examination management module, an improved genetic algorithm is used to realize the intelligent grouping of papers for remote Russian language teaching. The comparison results of the genetic algorithm before and after the improvement show that the fastest time of the genetic algorithm before the improvement is not less than 7500ms, and the difficulty of the generated test paper is not in the moderate [0.4~0.6) range. While the improved genetic algorithm is in the moderate range in terms of grouping difficulty, and the time can be reduced by at least 2 s. The article also proposes to introduce the improved fuzzy clustering algorithm incorporating AFSA into learning behavior analysis to portray learners. The final experiment confirms that the AFSA-FCM based model can accurately cluster learners, thus portraying learner profiles in a deeper and more comprehensive way. It helps teachers to carve out the characteristics of different learner groups and provides a key basis for decision-making in teaching and learning support services.
