个性化人工智能工具用于第二语言说话:性别和自闭症特征的作用
Yiran Du1, Chenghao Wang2, Bin Zou2
1Institute of Cognitive Neuroscience, University College London, London, United Kingdom.
Frontiers in psychiatry
|February 11, 2025
概括
自闭症特征的个体报告AI语言工具的感知较低,性别调节了一些影响. 这凸显了教育技术中包容性AI设计的需要.
科学领域:
- 教育技术的教育技术
- 人工智能的人工智能
- 神经多样性是一种神经多样性.
背景情况:
- 在教育技术研究中,个体差异至关重要.
- 了解自闭症特征和性别如何影响人工智能工具的感知对于包容性L2学习至关重要.
研究的目的:
- 调查自闭症特征,性别和对第二语言 (L2) 说话实践人工智能工具的看法之间的关系.
- 确定性别是否调节了自闭症特征和人工智能工具感知之间的关联.
主要方法:
- 111名大学生完成了广泛的自闭症表型问卷 (BAPQ) 并评估了五个维度 (PU,PEOU,AT,BI,UB) 的AI工具.
- 使用了相关性和回归分析,并探索了性别特定的适度.
主要成果:
- 在自闭症特征或整体AI感知方面没有发现显著的性别差异.
- 自闭症特征与人工智能工具的感知有负相关性.
- 性别调节了一些关系;男性显示自闭症特征和感知易用性 (PEOU) 和使用行为 (UB) 之间的联系更强烈.
结论:
- 当前的人工智能设计可能无法完全支持具有明显自闭症特征的个体.
- 个性化和适应性的教育工具对于L2实践中的包容性和有效性至关重要.
- 这项研究将神经多样性和性别与基于人工智能的语言学习中的技术接受联系起来.
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