技术增强的语言学习中的工作记忆:从互动到人工智能介导的情境的系统审查
1Department of Public Foreign Language Teaching and Research, Jilin University of Finance and Economics, Changchun, China.
Frontiers in psychology
|March 6, 2026
概括
语言学习中的人工智能改变了工作记忆 (WM) 的需求,有可能改善学习. 然而,人工智能研究缺乏直接的WM评估,需要对人工智能的进一步研究.
科学领域:
- 认知科学 认知科学
- 教育技术的教育技术
- 获得第二语言的学习.
背景情况:
- 工作记忆 (WM) 对于第二语言学习至关重要,尤其是在技术方面.
- 之前的研究重点是AI前的计算机辅助语言学习 (CALL) 和WM交互.
- 人工智能在语言学习中的兴起需要了解它对WM需求的影响.
研究的目的:
- 审查和比较工作记忆 (WM) 在语言学习技术的两个时代被概念化和研究的方式:交互式和人工智能介导.
- 分析两个时代的教学设计,WM结果,认知负载和测量.
- 确定研究缺口,并提出人工智能介导的语言学习和WM的未来方向.
主要方法:
- 使用PRISMA 2020指南进行系统审查.
- 历史比较设计综合了31个经验研究 (27个交互时代,4个人工智能介导时代).
- 基于教学特征,WM结果,认知负载和测量,与跨时代比较的研究分析.
主要成果:
- 交互式CALL经常诱导认知过载,并突出了个体的WM差异.
- 人工智能介导的工具显示了转变:人工智能写作增加了执行需求,自适应阅读调节了认知负载,VR/AR指令有局限性.
- 人工智能驱动的学习减轻了任务,重新分配了WM资源以实现内部化.
结论:
- 人工智能介导的语言学习工具质量地改变了WM的需求,潜在地优化了认知负载.
- 在人工智能介导的研究中,在直接的WM评估中存在一个显著的差距,阻碍了因果推理.
- 未来的研究应该整合经过验证的WM措施和能力治疗交互设计,以建立基于证据的AI适应性.
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