认知负载对对听觉和语言刺激大脑反应的编码模型的影响和预测在教育多媒体中的教育多媒体
Amir Hosein Asaadi1,2, S Hamid Amiri1, Alireza Bosaghzadeh1
1Department of Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Islamic Republic of Iran.
Scientific reports
|April 21, 2024
概括
设计不佳的教育多媒体增加了认知负载,损害了注意力和语义处理. 来自脑电图 (EEG) 的时间反应函数 (TRF) 可以检测这些效应,有助于设计更好的学习工具.
科学领域:
- 认知科学 认知科学
- 神经科学是一个神经科学.
- 教育技术的教育技术
背景情况:
- 教育型多媒体广泛使用,但由于设计不佳,可能会造成认知负载.
- 了解和预测认知负载对于优化学习体验至关重要.
- 脑电图 (EEG) 提供了一种测量与认知负载相关的大脑活动的方法.
研究的目的:
- 用EEG调查多媒体设计对认知负载的影响.
- 探索行为测量,认知负载和神经反应之间的关系.
- 评估时间响应函数 (TRF) 在检测认知负载效应方面的实用性.
主要方法:
- 参与者接触了两种版本的教育多媒体 (Mayer的原则应用与不应用).
- 记录了EEG数据,以及后测试和自我报告的认知负载问卷.
- 使用音频封面,单词频率和线性编码模型来导出TRF.
主要成果:
- 在两个多媒体版本之间,行为数据和TRF显著不同.
- 与行为数据相关的TRF组件的幅度和延迟的变化.
- 较高的认知负载与注意力下降和延迟,语义处理减少有关.
结论:
- 在多媒体学习过程中,认知负载会对注意力和语义处理产生负面影响.
- 来自EEG的TRF提供了对认知负载的神经相关的见解.
- 编码模型可以帮助检测和潜在地减轻教育环境中的认知负载.
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