The brain organization of STEM concept knowledge: a neurally-based foundation for training, measuring, and assessing concept learning from basic knowledge to expertise

STEM概念知识的大脑组织：基于神经的基础，用于训练、测量和评估从基础知识到专业知识的概念学习

• 批准号: 2215741
• 负责人: Robert Mason
• 金额: $ 62.5万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2215741&HistoricalAwards=false
• 关键词: brain; organization; STEM; concept; knowledge

The premise of this project is that an understanding of how STEM concepts are organized in the brain would enable the enhancement of STEM concept learning and its assessment. Research has shown that although students vary in how accurately or completely they acquire knowledge related to a STEM concept, their neural filing systems are remarkably similar, in terms of which brain systems are the sites of particular aspects of concept knowledge. Understanding this neural organization common to everyone makes it possible to take that organization into account in the course of instruction. In effect, it makes it possible to “teach to the brain”. More specifically, it makes it possible to develop innovative cognitive training techniques based on modern machine-learning guided neuroscience to supplement traditional STEM learning. The goal is to formulate a detailed theory of how basic STEM concept knowledge in multiple STEM disciplines is neurally organized, how the underlying organization develops with learning, and how the organization is impacted by instructional and ability factors across STEM domains. Findings from this project would advance the understanding of the ontology of scientific concepts, theories of instructional design, and AI (machine-learning) guided instruction. Altogether these advances would facilitate more effective interventions towards expert-level knowledge. The design of this project will purposefully include both University and Community College students with a large range of STEM abilities in traditionally under-studied groups. This project will assess the brain representations of STEM concepts (using several fMRI measures) in 4 different domains (physics, biology, chemistry, and mathematics) in students at multiple levels of expertise and assess the changes in those representations using machine-learning analysis of fMRI data under different types of instruction (class instruction, in-lab concept instruction, and expertise-focused training). The goal of the instruction will be to generate neural representations in novice learners that are similar to those of instructors or domain experts. This project builds on the investigators’ prior NSF funded work which demonstrated that fMRI can identify the underlying neural dimensions of physics concepts, and can predict and assess learning of these concepts (more so than traditional behavioral measurements). This research continues investigation of how neural data can usefully guide instruction by extending the approach to additional STEM domains and by guiding cognitive instruction with the accompanying neural assessment.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.

该项目的前提是，了解 STEM 概念在大脑中的组织方式将有助于增强 STEM 概念的学习及其评估。 研究表明，尽管学生获取与 STEM 概念相关的知识的准确度或完整程度存在差异。 ，他们的神经归档系统非常相似，就大脑系统而言，理解每个人共有的神经组织可以在教学过程中考虑到该组织。它使得“教导大脑”成为可能。更具体地说，它使得开发基于现代机器学习引导的神经科学的创新认知训练技术来补充传统的 STEM 学习成为可能，其目标是制定关于多个 STEM 学科中的基本 STEM 概念知识如何进行神经组织、如何进行的详细理论。底层组织随着学习而发展，以及组织如何受到 STEM 领域的教学和能力因素的影响。该项目的研究结果将促进对科学概念本体论、教学设计理论和人工智能（机器学习）指导的理解。指导.总共这些进步将有助于对专家级知识进行更有效的干预，该项目将有目的地将具有广泛 STEM 能力的大学和社区学院学生纳入传统上研究不足的群体中。不同专业水平的学生在 4 个不同领域（物理、生物、化学和数学）中的概念（使用多种 fMRI 测量），并使用不同类型教学下的 fMRI 数据的机器学习分析来评估这些表示的变化（类指导，实验室概念教学的目标是在新手学习者中生成与教师或领域专家相似的神经表征。该项目建立在研究人员之前 NSF 资助的工作的基础上，该工作证明了功能磁共振成像可以做到这一点。该研究继续研究神经数据如何通过将方法扩展到其他 STEM 领域并通过指导来有效地指导教学。认知指导以及伴随的神经评估。这授予 NSF 的法定使命，并通过评估反映使用基金会的智力优点和更广泛的影响审查标准，被认为值得支持。