Interdisciplinary Training in Neuroscience for Faculty and Undergraduates from 2- and 4-year Institutions

密苏里大学哥伦比亚分校的这个改进本科STEM教育（IUSE）项目解决了计算神经科学领域生物科学教师专业发展的需求。计算神经科学是一个新兴领域，它根据构成神经系统的结构的信息处理特性来研究大脑功能。它是一门跨学科的科学，将神经科学、认知科学和心理学的不同领域与电子工程、计算机科学、数学和物理学联系起来。虽然领先的生物学教育家呼吁建立强有力的跨学科课程，包括物理科学、信息技术和数学，但许多生物学和行为科学家缺乏定量科学方面的足够培训，限制了他们对这一领域工具的理解和使用。同样，工程师和定量科学家缺乏必要的生物科学和神经科学方面的培训，无法理解生物学中不同系统的细节，也无法促进与生物学家的互动，以开发相关的先进计算工具。PI团队正在利用他们之前在美国国家科学基金会资助的计算神经科学课程开发工作中获得的知识，以及他们提供名为“教授本科生神经科学的硬件和软件实验”的专业开发研讨会的七年经验。通过该项目提供的讲习班提高了2年制和4年制院校的神经科学教师的教学专业知识。师生团队参加为期一周的研讨会，其中包括通过自由软件实验强调计算的教学方法。将这些专业知识带回他们的家乡机构，研讨会参与者正在增加学习计算神经科学的本科生的数量和多样性。此外，将为四个师生团队提供为期两周的强化课程开发课程。这些严谨的研讨会提供数学、软件、教学和计算神经科学课程模块开发方面的培训，并为教师和学生团队开发和实施软件模块到他们的课程提供为期一年的支持计划。在项目的过程中，PI团队还通过开展研究来确定学生学习和教师专业发展以及实施有效教学实践的障碍，从而增加了我们对实施有效教学实践障碍的认识。了解这些障碍将有助于制定克服这些障碍的策略，从而使有效的教学实践能够在国家高等教育机构中得到更广泛的采用。

This Improving Undergraduate STEM Education (IUSE) project from the University of Missouri - Columbia addresses the need for professional development for biological sciences faculty in the area of computational neuroscience. Computational neuroscience is an emerging area that studies brain function in terms of the information processing properties of the structures that make up the nervous system. It is an interdisciplinary science that links the diverse fields of neuroscience, cognitive science, and psychology with electrical engineering, computer science, mathematics, and physics. While leading biology educators call for strong interdisciplinary curricula that include physical science, information technology, and mathematics, many biological and behavioral scientists lack adequate training in the quantitative sciences, limiting their understanding and use of tools from this area. Similarly, engineers and quantitative scientists lack the training in biological sciences and neuroscience necessary to understand the details of the diverse systems in biology, and facilitate improved interactions with biologists to develop relevant and advanced computational tools.The PI team is building on the knowledge they have gained through their prior NSF-funded work in the development of a computational neuroscience course, as well as on their seven years of experience providing a professional development workshop entitled "Hardware and Software Experiments to Teach Undergraduate Neuroscience." The workshops offered through this project are enhancing the teaching expertise of faculty in neuroscience at both 2- and 4-year institutions. Faculty-student teams participate in one-week workshops that include instructional methodologies emphasizing computation via free software experiments. Bringing this expertise back to their home institutions, workshop participants are increasing the number and diversity of undergraduates studying computational neuroscience. In addition, an intensive two-week curriculum development course will be offered to four faculty-student teams. These rigorous workshops provide training in mathematics, software, teaching, and development of curricular modules in computational neuroscience and include a one-year long support program for faculty-student teams as they develop and implement software modules into their curriculum. In the course of the project, the PI team is also augmenting our knowledge of obstacles to the implementation of effective instructional practices by carrying out studies to identify barriers to student learning and to faculty professional development and implementation of effective teaching practices. Understanding these impediments will facilitate development of strategies to overcome them so that effective instructional practices can be more widely adopted in the nation's institution of higher education.