在个性化认知训练中探索人工智能的潜力:系统性审查
Maxime Adolphe1,2,3, Marion Pech1, Masataka Sawayama4
1Flowers, Inria, Bordeaux-Sud-Ouest, France.
PloS one
|June 17, 2025
概括
人工智能 (AI) 技术个性化认知训练 (CT) 课程,以解决个人差异. 虽然承诺参与和有效性,但需要更多的研究来验证这些适应性AI方法在CT.
科学领域:
- 神经科学是一个神经科学.
- 计算机科学 计算机科学
- 心理学 心理学 心理学
背景情况:
- 认知培训 (CT) 研究面临的挑战是响应者的异质性.
- 使用人工智能技术的个性化课程正在成为一种替代一种适合所有人的方法.
研究的目的:
- 系统地审查利用人工智能技术的计算机CT中的自适应方法.
- 分析人工智能驱动的个性化CT对学习机制和有效性的结果.
主要方法:
- 一个系统的文献搜索到2023年6月,确定了19个计算机化CT研究,使用AI进行个性化.
- 分析重点是基于人工智能的个性化方法,CT设置,目标人群,绩效跟踪和转移效应.
主要成果:
- 一半的研究使用了宏观适应方法 (通常用于多个认知领域),而另一半使用了微适应方法 (通常用于单个认知领域).
- 两项研究报告了对CT有效性的有利影响;五项研究强调了增强的训练经验 (动机,参与,多样化的途径).
- 在所有研究中都发现了方法上的缺陷,包括缺乏对照组和小样本.
结论:
- 人工智能驱动的个性化CT显示出增强参与度和潜在有效性的承诺.
- 需要使用强大的方法进行进一步的研究,以经验上支持并充分理解这些自适应CT技术.
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