【作 者】：
刘哲雨， 刘 畅， 许博宇
【关 键 词 】：
计划调节学习支架； 在线深度学习； 功能性近红外光谱技术； 设计规则
【栏 目】：
学习环境与资源
【中文摘要】：
在线学习支架可用于改善学习者的计划调节，规划学习任务，引导学习行为，促进在线深度学习。已有计划调节学习支架设计更多依赖经验，缺少基于脑加工机制的设计规则研究。文章采用功能性近红外光谱技术动态追踪深度学习过程的脑区激活情况，探究计划调节学习支架对在线深度学习过程的影响机制；采用测量问卷评估支架对深度学习结果的影响。研究结论指出：深度学习基础阶段、早期阶段与晚期阶段，两种类型的计划调节学习支架均有利于激活深度学习过程的脑区，自主性计划调节学习支架对深度学习结果的促进作用最显著，启示研究者优先采用自主性计划调节学习支架促进在线深度学习；深度学习三个阶段的脑区激活情况与深度学习结果均具有正相关关系，启示研究者可以根据脑区激活情况判断在线深度学习是否真实发生以及发生的程度。最后，基于实验结论提出计划调节学习支架的设计规则及应用建议。
【英文摘要】：
Online learning scaffolds can be used to improve learners' plan regulation, plan learning tasks, guide learning behaviors, and facilitate online deep learning. However, the existing design of plan-regulated learning scaffolds has relied more on experience and there is a lack of research on design rules based on brain processing mechanisms. This study uses functional near-infrared spectroscopy to dynamically track the activation of brain regions in deep learning to investigate the influence mechanism of plan-regulated learning scaffolds on online deep learning. A questionnaire is used to evaluate the differences in the effects of scaffolding on deep learning. This study concludes that both types of plan-regulated learning scaffolds facilitate the activation of brain regions in deep learning processes in the basic, early, and late stages of deep learning, and both autonomous plan-regulated learning scaffolds have the most significant effect on deep learning outcomes, suggesting that future researchers should preferentially use autonomous plan-regulated learning scaffolds for online deep learning. Additionally, the activation of brain regions in all three stages of deep learning has a positive correlation with deep learning outcomes, which reveals that future researchers could judge whether and to what extent online deep learning occurs based on the activation of brain regions. Finally, based on the study results, the design rules and application suggestions of the plan-regulated learning scaffolds are proposed.