通过人工智能集成增强文学评论:关于认知效率的案例研究
1Jerusalem College of Technology, Jerusalem, Israel.
Acta psychologica
|October 4, 2025
概括
这项研究将认知效率 (CE) 定义为记忆回忆和信息处理速度. 它还引入了一种新的人工智能辅助系统审查方法,平衡人工智能能力与人类专业知识,以便进行更严格的研究.
科学领域:
- 认知科学 认知科学
- 人工智能的人工智能
- 信息科学 信息科学 信息科学
背景情况:
- 认知效率 (CE) 缺乏统一的定义和跨学科的一致测量,阻碍了跨学科的合作.
- 在文献评论中应用人工智能 (AI) 工具的系统方法尚不发达.
- 现有的研究差距阻碍了CE的概念明确性和文献评论的高效执行.
研究的目的:
- 提出一种关于认知效率 (CE) 的综合定义.
- 开发和介绍一种使用人工智能进行系统文献审查的新,代的方法.
- 解决学术研究当前人工智能应用的局限性,并加强审查的严格性.
主要方法:
- 对96篇学术文章进行了人工智能辅助的系统审查,以定义CE.
- 开发了一种新的代方法,将人工智能工具与人类判断相结合,用于系统审查.
- 分析了AI在文章理解,主题识别和数据合成方面的能力和局限性.
主要成果:
- 提出了CE的统一定义:"衡量一个人的记忆回忆和在给定的反应时间内处理信息的能力".
- 在个人文章理解和主题识别方面展示了AI的优势.
- 在系统性审查中确定了复杂数据合成和论文间比较中的当前AI局限性.
结论:
- 拟议的定义为认知效率研究提供了清晰度和一致性.
- 这种新的方法提供了一个强大的框架,可以在系统的文献评论中利用AI.
- 将人工智能与人类专业知识相结合,提高了学术研究的效率和严谨性.
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