School of Psychology and Cognitive Science, Shanghai Changning-ECNU Mental Health Center, East China Normal University, Shanghai, China; Neuropsychology and Functional Neuroimaging Research Unit (UR2NF), ULB Neuroscience Institute (UNI), Université Libre de Bruxelles, Bruxelles, Belgium; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Department of Psychology, New York University, New York, USA.
Neuroimage. 2020 May 1;211:116657. doi: 10.1016/j.neuroimage.2020.116657. Epub 2020 Feb 15.
The neural mechanisms that support naturalistic learning via effective pedagogical approaches remain elusive. Here we used functional near-infrared spectroscopy to measure brain activity from instructor-learner dyads simultaneously during dynamic conceptual learning. Results revealed that brain-to-brain coupling was correlated with learning outcomes, and, crucially, appeared to be driven by specific scaffolding behaviors on the part of the instructors (e.g., asking guiding questions or providing hints). Brain-to-brain coupling enhancement was absent when instructors used an explanation approach (e.g., providing definitions or clarifications). Finally, we found that machine-learning techniques were more successful when decoding instructional approaches (scaffolding vs. explanation) from brain-to-brain coupling data than when using a single-brain method. These findings suggest that brain-to-brain coupling as a pedagogically relevant measure tracks the naturalistic instructional process during instructor-learner interaction throughout constructive engagement, but not information clarification.
支持通过有效教学方法进行自然学习的神经机制仍然难以捉摸。在这里,我们使用功能近红外光谱技术在动态概念学习期间同时从教师-学习者对偶体测量大脑活动。结果表明,大脑间的耦合与学习成果相关,并且关键的是,它似乎是由教师的特定支架行为(例如,提出引导性问题或提供提示)驱动的。当教师使用解释方法(例如,提供定义或澄清)时,大脑间的耦合增强则不存在。最后,我们发现,当从大脑间耦合数据解码教学方法(支架与解释)时,机器学习技术比使用单脑方法更成功。这些发现表明,大脑间耦合作为一种与教学相关的测量方法,在整个建设性参与过程中,跟踪教师-学习者互动期间的自然教学过程,而不是信息澄清。