Evolutionary paths of college students’ English learning strategies in the AI era
AI时代下大学生英语学习策略演化路径研究

摘要

为研究人工智能的发展对大学生学习英语的观念及策略的影响模式，本研究基于演化博弈理论的框架，构建了包含教育政策、技术治理与社会规训的演化博弈模型，系统揭示了AI时代下大学生英语学习策略的演化路径及其稳定机制。通过分析积极学习、中性学习与消极学习三类策略的互动关系，结合AI教学认可权重、AI监管机制与企业AI协作认可度的协同作用，探讨AI时代下大学生英语学习策略演化路径。研究表明：（1）在强监管框架下，政策激励与能力溢价的协同效应可推动积极学习策略占据主导地位。（2）弱监管环境中，技术替代效率的持续提升易诱发消极学习策略的泛化，形成“AI依赖陷阱”。（3）中性学习策略的稳定性则依赖于人机协同效应与社会信号衰减的动态平衡，其演化呈现阶段性波动特征。基于此，本研究提出分层治理框架以实现AI技术赋能与英语自主学习的协同发展。

Abstract

The rapid development of artificial intelligence (AI) is reshaping college students’ ideas and strategies for English learning. Based on the framework of evolutionary game theory, this study constructs an evolutionary game model including educational policies, technological management, and social discipline to systematically reveal the evolutionary paths and stabilization mechanisms of college students’ English learning strategies in the AI era. By analyzing the interactions among three strategies—proactive learning, neutral learning, and passive learning—and considering the synergistic effects of AI teaching accreditation weights, AI monitoring mechanisms, and recognition of AI collaboration by enterprises, this study explores the evolutionary trajectories of these strategies. The findings show that (1) under a strong regulatory framework, the synergy between policy incentives and competency premiums can drive active learning strategies to dominate. (2) In contrast, weak regulatory environments may lead to the proliferation of passive learning strategies due to continuous improvements in AI substitution efficiency, forming an “AI dependency trap”. (3) The stability of neutral learning strategies relies on the dynamic balance between human-AI collaboration and the attenuation of social signals, exhibiting phased fluctuations in their evolutionary paths. Based on these insights, the study proposes a hierarchical governance framework to achieve coordinated development between AI-enabled empowerment and autonomous English learning.