Liu Xiaobo, Zhang Yu
Institute of Education, Tsinghua University, Beijing, China.
Br J Educ Psychol. 2025 Jun;95(2):446-463. doi: 10.1111/bjep.12729. Epub 2024 Dec 18.
Cognitive load theory is widely used in educational research and instructional design, which relies heavily on conceptual constructs and measurement instruments of cognitive load. Due to its implicit nature, cognitive load is usually measured by other related instruments, such as commonly-used self-report scales of mental effort or task difficulty. However, these concepts are different in nature, as they emphasize distinct perspectives on cognitive processing. In addition, real-world learning is more complex than simplified experimental conditions. Simply assuming that these variables will change in a monotonic way with workload may be misleading.
This study aims to examine whether these measures are consistent with each other, and to discover the neurophysiological basis underlying the potential discrepancy.
The study collected data in both a real-world (Study 1, 22 high school students in 13 math classes) and a laboratory setting (Study 2, 30 students in 6 lab-based math tasks).
In addition to self-report measures, the study also collected multimodal neurophysiological data, such as electroencephalography (EEG), electrodermal activity (EDA), and photoplethysmography (PPG).
The results show that although the difficulty level can be perceived with difficulty ratings, it does not lead to the corresponding level of mental effort. Only within an appropriate level of load, can we observe a positive correlation between self-report difficulty and mental effort. Neurophysiological evidence also supports the conceptual discrepancies and group differences, indicating distinct neurophysiological mechanisms underlying these 'similar' constructs.
These findings also emphasize the need for combining these concepts to better evaluate students' cognitive load.
认知负荷理论在教育研究和教学设计中被广泛应用，这在很大程度上依赖于认知负荷的概念结构和测量工具。由于其内在性质，认知负荷通常通过其他相关工具来测量，例如常用的心理努力或任务难度的自我报告量表。然而，这些概念在本质上是不同的，因为它们强调了对认知加工的不同观点。此外，现实世界中的学习比简化的实验条件更为复杂。简单地假设这些变量会随着工作量以单调的方式变化可能会产生误导。
本研究旨在检验这些测量方法是否相互一致，并发现潜在差异背后的神经生理基础。
该研究在现实世界（研究1，13个数学班级中的22名高中生）和实验室环境（研究2，6个基于实验室的数学任务中的30名学生）中收集了数据。
除了自我报告测量外，该研究还收集了多模态神经生理数据，如脑电图（EEG）、皮肤电活动（EDA）和光电容积脉搏波描记法（PPG）。
结果表明，尽管可以通过难度评级感知难度水平，但它不会导致相应水平的心理努力。只有在适当的负荷水平内，我们才能观察到自我报告的难度与心理努力之间存在正相关。神经生理学证据也支持了概念差异和组间差异，表明这些“相似”结构背后存在不同的神经生理机制。
这些发现还强调了结合这些概念以更好地评估学生认知负荷的必要性。
