Assessing the changes in the brain representations of individual STEM concepts in the course of learning

发现STEM概念是如何在大脑中呈现的，将使我们能够评估学生的科学学习，并更有效地教授STEM概念。该项目利用了研究人员之前的工作，这些工作展示了利用fMRI脑成像来确定单个概念的神经关联(大脑特征)的非凡新能力。通过了解重力和速度等物理概念的大脑特征，可以观察到大脑表征是如何在学习者的大脑中发展的，它们是如何组织的，以及它们如何依赖于那个人的学习背景和教学方法。如果我们知道大脑组织STEM概念知识的方式，我们就可以设计课程，向该组织系统传授知识，并在大脑水平上衡量学生的学习。这种方法不会取代传统的测试，但它将为这些测试提供一种新的基础，使它们能够评估替代的教学方法。研究人员此前已经证明，神经特征可以分解为有意义的潜在维度，这些维度在人与人之间非常相似，从而有可能将学生学习者的神经表征与教师或其他成功学习者的表征进行精确比较。以前从未尝试过的，也是这个项目的主要目标，是将概念学习的神经签名与各种学习结果联系起来。行为测试会评估学生吗？概念的获得和功能磁共振成像扫描将评估伴随着单个概念的大脑表征的获得。学生的神经表示将被分析其内在的完整性，衡量的标准是机器学习分类器从概念的fMRI签名中识别概念的准确性。这些将被与那些被证明掌握了概念的人(如高级学生和班主任)的神经表征进行比较。此外，该项目将评估与概念学习同时发生的脑组织(灰质和白质)的变化，以及参与概念表征的脑区之间同步(功能连接)的变化。这个项目的一个主要贡献将是基于大脑的理解，了解个人科学概念是如何学习的，以及这种学习如何与行为测量和个人差异有关。长期目标是为神经科学的发现奠定基础，为教学技术和评估提供信息，并作为其他战略的灵感，以促进普通学生群体和有失败风险的学生的成功学习。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。

Discovering how STEM concepts are represented in the brain will allow us to both assess student learning of science and to teach STEM concepts more effectively. This project makes use of previous work by the investigators that demonstrated the remarkable new ability to determine the neural correlates (brain signature) of an individual concept, using fMRI brain imaging. Knowing the brain signature of physics concepts like gravity and velocity makes it possible to observe how the brain representations develop in a learner's brain, how they are organized, and how they depend on that person's learning background and on the teaching method. If we know the brain's way of organizing STEM concept knowledge, we can design curricula that teach to that organizational system and measure student learning at the brain level. This approach will not replace conventional tests, but it will provide a new type of basis for those tests such that they can assess alternative instructional methods. The investigators had previously shown that neural signatures can be decomposed into meaningful underlying dimensions that are remarkably similar across people, making it possible to precisely compare the neural representations of student learners to the representations of instructors or of other successful learners. What has not been attempted before, and is the major goal of this project, is relating the neural signatures of concept learning to various learning outcomes. Behavioral tests will assess the students? acquisition of the concepts and fMRI scans will assess the acquisition of the concomitant brain representations of the individual concepts. The students' neural representations will be analyzed for their intrinsic integrity, measured by a machine learning classifier's accuracy in identifying a concept from its fMRI signature. These will be compared to the neural representations of people with demonstrated mastery of the concepts (such as advanced students and the class instructors). Additionally, the project will assess changes in brain tissues (gray and white matter) that co-occur with concept learning, as well as changes in synchronization (functional connectivity) between brain regions involved in the concept representations. A central contribution of this project will be a brain-based understanding of how individual scientific concepts are learned and how this learning can be related to behavioral measures and individual differences. The long-term goal is to build the foundation for neuroscience findings to inform teaching techniques and assessments, and as inspiration for additional strategies to promote successful learning in both the general student population and students at risk for failure.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.