Collaborative Research: Cognitive and Neural Indicators of School-based Improvements in Spatial Problem Solving

这项由詹姆斯·麦迪逊大学、乔治城大学和西北大学联合开展的项目，将考察高中生(学习地球科学的学生)学习空间思维技能，观察教育结果以及行为和神经学指标。已经有相当多的证据将空间能力与未来的STEM(科学、技术、工程和数学)成就联系起来。该项目将重点放在一门高中课程--地理空间学期--上，该课程旨在改善空间思维。该项目将寻找作为课程结果的大脑活动模式的变化，以及教育、行为和神经测量之间的关系。先前的研究表明，实验室中的空间训练可能会减少表现上的性别差异；该项目将寻求在现实世界的高中空间学习中衡量这种影响，并确定有助于解释性别差距如何和为什么缩小的神经机制。该项目将推动EHR(教育与人力资源)委员会在研究STEM学习的认知和神经基础方面的工作。该项目的总体目标是在行为和神经层面为空间STEM教育发展一种机械式的变革理论。为了实现这一目标，该项目将综合衡量成果：教育(例如，课程)、行为(例如，心理旋转和嵌入式图形识别标准测试中的核心空间能力、空间语言的使用)和神经(例如，支持空间思维能力的大脑区域的神经效率和灰质体积，以及大脑区域之间的互连网络)。空间地理空间学期的学生将与在其他高级科学课程中接受标准(非空间)STEM教育的同龄人进行比较。神经测量将通过在测试前和测试后的时间点进行的功能和结构磁共振成像来获得。总的来说，该项目将解决高中STEM教育背景下的大脑可塑性问题。该项目将使用机器学习技术，以假说驱动和数据驱动的方式辨别空间学习的神经学影响，并检查空间STEM学习对认知和大脑影响的性别差异。分析将侧重于将神经、行为和教育层面的变化联系起来，以期对使空间STEM学习有效的机制有一个完整的理解。

This project, to be conducted by James Madison University, Georgetown University, and Northwestern University, will examine learning spatial thinking skills by high school students (who are studying geoscience), looking at educational outcomes as well as behavioral and neurological measures. There is already considerable evidence linking spatial ability and future STEM (science, technology, engineering, and mathematics) attainment. The project will focus on a high school course, the Geospatial Semester, that is designed to improve spatial thinking. The project will look for changes in patterns of brain activity as a result of the course, as well as relations among the educational, behavioral, and neurological measures. Prior research indicates that spatial training in the laboratory may reduce gender differences in performance; this project will seek to measure this effect in real world high school spatial learning, and to identify neural mechanisms that help explain how and why the gender gap closes. This project will advance the work of the EHR (Education & Human Resources) Directorate in studying the cognitive and neural basis of STEM learning.The overall goal of the project is to develop a mechanistic theory of change for spatial STEM education at the behavioral and neural levels. To achieve this goal, the project will measure a combination of outcomes: educational (e.g., coursework), behavioral (e.g., core spatial ability on standard tests of mental rotation and embedded figure identification, use of spatial language), and neurological (e.g., neural efficiency and grey matter volume in brain regions that support spatial thinking ability, interconnectivity networks across brain regions). Students in the spatially-based Geospatial Semester will be compared to peers receiving standard (non-spatially-based) STEM education in other advanced science courses. Neurological measures will be obtained by functional and structural magnetic resonance imaging performed at pre- and post-test time points. In general, the project will address the issue of brain plasticity in a high school STEM education context. The project will use machine learning techniques to discern neurological effects of spatial learning in both hypothesis-driven and data-driven ways, and examine gender differences in the effect of spatial STEM learning on cognition and the brain. Analyses will focus on relating changes across neural, behavioral, and educational levels toward an integrated understanding of the mechanisms that make spatial STEM learning effective.