扩展执行认知,人工智能时代的学习成果

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Alexander M. Sidorkin
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引用次数: 0

摘要

人工智能从根本上改变了跨学科的专业知识,在高等教育课程和新兴工作场所实践之间造成了越来越大的差距。本文介绍了“扩展执行认知”作为人工智能时代的关键学习成果,战略分配认知努力,协调人工智能辅助任务和管理混合智能解决问题的能力。根据课程理论、执行功能心理学和分布式认知研究,我们认为,教育后的成功越来越依赖于人类与人工智能合作的元认知技能,而不是传统的学术能力。扩展执行认知需要开发准确的人工智能能力和局限性的心智模型,以实现有效的任务授权。所提出的框架提供了跨通识教育和学科特定背景的具体课程整合策略,包括捕捉元认知发展而不仅仅是产品评估的评估方法。通过围绕认知编排而不是内容生产重新定义学习成果,大学可以让毕业生为持续的技术进化做好准备,同时保留明显的人类能力作为教育的核心价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extended executive cognition, a learning outcome for the AI age
Artificial intelligence fundamentally transforms professional expertise across disciplines, creating an expanding gap between higher education curricula and emerging workplace practices. This paper introduces "Extended Executive Cognition" as a critical learning outcome for the AI age, the ability to strategically allocate cognitive effort, coordinate AI-assisted tasks, and manage hybrid intelligence problem-solving. Drawing on curriculum theory, executive function psychology, and distributed cognition research, we argue that post-educational success increasingly depends on metacognitive skills for human-AI collaboration rather than traditional academic competencies. Extended Executive Cognition requires developing accurate mental models of AI capabilities and limitations to enable effective task delegation. The framework presented offers concrete curriculum integration strategies across general education and discipline-specific contexts, including assessment approaches that capture metacognitive development rather than mere product evaluation. By reconceptualizing learning outcomes around cognitive orchestration rather than content production, universities can prepare graduates for continuous technological evolution while preserving distinctly human capacity as education's central value.
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