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Related Experiment Video

Updated: Sep 26, 2025

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Research on College English Classroom Teaching Model Based on Adaptive Genetic Algorithm.

Zhiling Yang1,2

  • 1School of Foreign Studies, Wenzhou University, Wenzhou, Zhejiang 325035, China.

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Summary

This study applies genetic algorithms to optimize college English course scheduling, addressing increased workloads and resource demands. The research also explores a genetic algorithm-based platform for dynamic English teaching models and activities.

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Area of Science:

  • Education Technology
  • Computer Science Applications
  • Computational Linguistics

Background:

  • College English teaching is shifting towards dynamic language ability development.
  • University education expansion has led to increased complexity in course scheduling and teacher workload.
  • Effective language application activities are crucial for cultivating students' abilities.

Purpose of the Study:

  • To optimize college English course scheduling using genetic algorithms.
  • To address hardware and software constraints in academic scheduling.
  • To design a genetic algorithm-based platform for dynamic English teaching models and classroom activities.

Main Methods:

  • Application of genetic algorithms for course scheduling optimization.
  • Parallel search for optimal scheduling solutions.
  • Design and implementation of genetic operators.
  • Development of a genetic algorithm-based English social platform.

Main Results:

  • A clear and concise solution for the English course scheduling problem.
  • Efficient parallel search for optimal scheduling.
  • A framework for dynamic teaching models and classroom activities.

Conclusions:

  • Genetic algorithms offer an effective approach to optimizing college English course scheduling.
  • The developed platform supports dynamic teaching models and enhances language application activities.
  • This research contributes to improving the efficiency of college English education.