【作 者】：
王国华， 聂胜欣， 薛瑞鑫
【关 键 词 】：
多媒体学习； 在线学习； 认知负荷； 测量方法； 测量技术
【栏 目】：
理论探讨
【中文摘要】：
认知负荷是在线学习及多媒体学习领域研究的焦点问题，如何科学、有效地测量学习者的认知负荷是相关研究开展的基础，更是减少学习者认知资源消耗、提升学习成效的关键。文章以国内外近20年来的301篇实证研究论文为基础，使用客观—因果二维四象限分类法对不同类型的认知负荷测量方法与技术进行分类，并对相关测量方法与技术的理论假设、优点及不足进行分类评述，并得出些许启示。通过分析发现，不同测量方法各有优劣并具有互补性，基于认知科学和信息科学的测量方法值得重点关注，深度学习技术会成为未来认知负荷测量的关键技术。
【英文摘要】：
Cognitive load is the focus of research in the field of online and multimedia learning. How to measure learners' cognitive load scientifically and effectively is the basis for relevant research, and is also the key to reducing the consumption of learners' cognitive resource and improving learning effectiveness. Based on 301 empirical research papers in the past two decades at home and abroad, this paper uses the objective-causal two-dimensional four-quadrant classification method to classify different types of cognitive load measurement methods and techniques, and reviews the theoretical hypotheses, advantages and disadvantages of related measurement methods and technologies, and draws some insights. Through analysis, it is found that different measurement methods have their own advantages and disadvantages and are complementary to each other. Measurement methods based on cognitive science and information science are worthy of focus. Deep learning technology will become the key technology of cognitive load measurement in the future.