Computer Simulation and Optimization of Second Language Writing Strategies from the Perspective of Dynamic Systems Theory

Abstract

In response to the growing demand for effective second language (L2) writing strategies, this study aims to explore and optimize L2 writing strategies from a dynamic systems perspective. Utilizing computer simulation, the research investigates the interaction and adaptation of writing strategies in L2 learners. The research method involves the development of a computational model that simulates the writing process of L2 learners. This model captures various writing strategies, such as planning, drafting, revising, and self-monitoring, and analyzes how these strategies evolve over time in response to different linguistic and cognitive challenges. Data from L2 learners’ writing samples and writing process logs are used to calibrate and validate the simulation model. The results of the computer simulation demonstrate that L2 writing strategies are not static but rather adapt dynamically to the writer’s proficiency level, task demands, and cognitive resources. The simulation reveals that certain strategies, such as frequent self-monitoring and adaptive planning, are more effective in improving writing quality and efficiency. Additionally, the study identifies individual differences in strategy use, with some learners benefiting more from specific strategies than others. The findings underscore the complexity of L2 writing and suggest that personalized feedback and strategy training based on the simulation outcomes can significantly enhance L2 writing performance. The findings reveal significant insights into the dynamic nature of writing strategies, highlighting the importance of individual differences and context. The study concludes that computer simulation offers a promising approach for understanding and enhancing L2 writing strategies, potentially leading to more personalized and efficient writing instruction.