The neurobiological mechanisms underlying gesture’s role in mathematical learning

所有的发言者在讲话时都会打手势。手势是一种动作--在空中进行的不直接影响物体的动作。手势和对物体的动作都可以促进学习，但将手势作为数学课的一部分，比将动作作为课程的一部分更容易记住和延伸这一课。这个研究项目使用神经数据来找出原因。有两个假设可能是正确的：(1)手势通过帮助儿童抽象出教学中使用的特定范例来促进学习。(2)行动将儿童与教学中使用的范例的细节捆绑在一起，从而阻碍了学习。很难在行为层面上将这两种机制分开，因为这两种假设都会导致相同的结果--通过手势学习比按照动作学习更好。这项研究使用神经成像来测量数学课上的活动，并确定在基于手势和基于动作的教学过程中，大脑的不同区域是否被激活。了解通过手势和动作进行学习的神经过程有助于区分这两个假设，并为教师在课堂上使用这些工具提供更好的建议。这项研究计划旨在区分数学课上两种情况下的两种假设：当儿童观察教师做出手势或动作时(研究1)；当儿童自己产生手势或动作时(研究2)。研究1使用功能磁共振成像(FMRI)，研究2使用功能近红外光谱(FNIRS)测量神经活动，而8至10岁的3年级和4年级儿童接受基于手势或动作的数学等价前代数概念(方程式两边必须相等的概念)的指导。抽象区域的神经活动预计发生在手势指导期间；目标区域的神经活动预计发生在动作指导期间)。教学过程中神经过程的差异将被用来预测儿童在教学后的学习结果。FNIRS是一项在教育神经科学中未得到充分利用的新技术，但有可能在课堂上用于同时测量多名学生学习期间的神经活动。这项工作是测试这种可能性的早期步骤。该项目由EHR核心研究(ECR)计划资助，该计划支持推进STEM学习和学习环境的基础研究、扩大对STEM的参与以及STEM劳动力发展的工作。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

All speakers gesture when they talk. Gestures are a type of action––an action done in the air that does not directly affect objects. Both gestures and actions-on-objects can promote learning, but having gesture as part of a math lesson makes it easier to remember and extend that lesson than having action as part of the lesson. This program of research uses neural data to figure out why. Two hypotheses, both of which might be correct, are possible: (1) Gesture promotes learning by helping children abstract beyond particular exemplars used in instruction. (2) Action impedes learning by tying children to the particulars of the exemplars used in instruction. It is difficult to disentangle these two mechanisms at the behavioral level because both hypotheses lead to the same outcome––better learning following gesture than action. The research uses neuroimaging to measure activity during a math lesson and determine whether different areas of the brain are activated during gesture- vs. action-based instruction. Understanding the neural processes that underlie learning through gesture vs. action can help distinguish between these two hypotheses, and lead to more finely tuned recommendations to teachers for using these tools in the classroom. The research program aims to distinguish between the two hypotheses in a math lesson under two conditions: when children observe an instructor produce gestures or actions (Study 1); when children themselves produce gestures or actions (Study 2). Study 1 uses fMRI (functional magnetic resonance imaging) and Study 2 uses fNIRS (functional near infrared spectroscopy) to measure neural activity while 8- to 10-year-old children in 3rd and 4th grade receive gesture- or action-based instruction in the pre-algebra concept of math equivalence (the notion that two sides of an equation must be equal). Neural activity in abstraction areas is expected to occur during gesture instruction; neural activity in object areas is expected to occur during action instruction). Differences in neural processes during instruction will be used to predict children’s learning outcomes after instruction. fNIRS is a new technology that has been underused in educational neuroscience, but has the potential to be used in the classroom to measure neural activity during learning from multiple students simultaneously. This work is an early step in testing that possibility.This project is funded by the EHR Core Research (ECR) program, which supports work that advances fundamental research on STEM learning and learning environments, broadening participation in STEM, and STEM workforce development.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.