Abstract
While college English teaching is steadily changing from static knowledge transfer to dynamic language ability development, classroom activities centered on language application are becoming more and more important in cultivating students' language application ability. In recent years, education has been paid more and more attention, the scale of university education has gradually expanded, the professional categories have become more and more complete, the curriculum has become larger and larger, and the number of students has grown by leaps and bounds. The teaching resources (teachers, classrooms, teaching equipment, etc.) and the workload of English teachers are increasing. In order to effectively improve the efficiency of college English teaching, the paper proposes to apply genetic algorithms to the actual English course scheduling problem in colleges, taking into account all the various hardware and software constraints and the expected course scheduling goals, so as to provide a clear and concise solution to the course scheduling problem plan (parallel search for optimal scheduling) and the design and coding structure of each genetic operator. Furthermore, this study creates a genetic algorithm-based English social platform and examines the design aspects of dynamic teaching models and classroom activities of college English students in the context of this paper.
Highlights
A major source of worry for university English instructors, as well as many language scholars and students, has been how to enhance the quality of teaching and learning of English at university and how to increase the efficacy of language learning
As language education has progressed over the years, it has moved away from the conventional static paradigm toward a dynamic one, and the teaching process is no longer limited to the typical “teacher talks at the podium while pupils sit in the classroom and listen.”
Aside from that, this study investigates the teaching methodology used in a college English classroom and develops a social platform for learning English that is powered by a genetic algorithm [17]
Summary
A major source of worry for university English instructors, as well as many language scholars and students, has been how to enhance the quality of teaching and learning of English at university and how to increase the efficacy of language learning. Like KDDI’s intelligent scheduling system, are lacking in effective solutions for the complicated and specific demands of some schools, such as long and short courses, tutor classes, and school-based course scheduling, among other things [14, 15] Using these issues as a starting point, we develop a solution to the English scheduling problem, including a method to automatically divide the teaching classes without taking into account conflicts in the class schedule when generating the initial population, thereby removing the requirement that individuals in the initial population must be feasible solutions; in addition, we introduce the concept of gene editing into the variation operator, which allows us to automatically locate and eliminate on-target candidates [16]. (4) Some classes are not scheduled immediately after others, and so on
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