ECR DBER DCL: Describing the Neurobehavioral Effects of Modeling-Based Instruction in Undergraduate Life Sciences Education

ECR DBER DCL：描述本科生命科学教育中基于建模的教学的神经行为效应

• 批准号: 2000605
• 负责人: Tammy Long
• 金额: $ 18.74万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2000605&HistoricalAwards=false
• 关键词: ECR; DBER; DCL; Describing; Neurobehavioral

This project aims to serve the national interest by conducting basic research about the neurobiology of learning in undergraduate life sciences education. This Level 1 STEM learning and learning environments project aims to broaden understanding of who is affected by modeling-based instruction in undergraduate life sciences, and how they are affected. Modeling is vital to STEM professions and national standards call for modeling instruction at all levels of STEM education. Despite behavioral work indicating that modeling-based instruction enhances STEM learning, there is a critical gap in understanding what mechanisms make it effective and which students benefit most from this instructional approach. The proposed project draws on the body of knowledge about STEM expertise from cognitive science. Specifically, as disciplinary experts interact with or create models of biological systems, they continuously engage in error checking to evaluate a model’s credibility and simultaneously inhibit information that is irrelevant to the task. Specific regions of the experts' brains become activated as they evaluate models. These regions include the lateral prefrontal and anterior cingulate regions, which are linked to error detection and inhibition. These observations suggest that error checking and inhibition are integral brain functions for development of STEM expertise. However, it is not known whether undergraduate STEM students, who are not yet disciplinary experts, use similar processes and associated neural systems during modeling-based instruction. It is also not yet known whether error checking and inhibition influence students’ long-term retention of disciplinary and modeling knowledge. A deeper understanding about how modeling-based instruction benefits students and for whom it is most effective may be used to develop more effective STEM instruction to meet the needs of all students. The goals of this project are to (a) describe the nature and extent to which undergraduate life sciences students engage in error detection and inhibition during model evaluation, and (b) determine how these processes are associated with long-term knowledge retention. Interviews with students will enable characterization of the types and extent of error detection. Brain scans using fMRI will determine the functional neural responses. Comparative interviews and neurological scans after one year of instruction will determine how variation in ability to detect errors predicts long-term retention of conceptual and model-based knowledge. Results from this research will be disseminated at research conferences and through peer-reviewed literature. The research will inform development of a modeling-based instruction case study on learning for undergraduate life science students. The proposed project is a joint effort between the University of Nebraska-Lincoln and Michigan State University and is supported 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.

该项目旨在通过开展关于本科生命科学教育中学习的神经生物学的基础研究来服务于国家利益。这个1级STEM学习和学习环境项目旨在扩大对本科生命科学中基于建模的教学影响的人以及他们如何受到影响的理解。建模对STEM专业至关重要，国家标准要求在各级STEM教育中进行建模教学。尽管行为工作表明，基于建模的教学提高了STEM学习，但在理解什么机制使其有效以及哪些学生从这种教学方法中受益最大方面存在着重大差距。拟议的项目借鉴了认知科学中有关STEM专业知识的知识体系。具体来说，当学科专家与生物系统交互或创建生物系统模型时，他们不断地进行错误检查以评估模型的可信度，同时抑制与任务无关的信息。 当专家评估模型时，他们大脑的特定区域会被激活。 这些区域包括外侧前额叶和前扣带区，它们与错误检测和抑制有关。这些观察结果表明，错误检查和抑制是STEM专业知识发展不可或缺的大脑功能。 然而，目前尚不清楚尚未成为学科专家的本科STEM学生是否在基于建模的教学中使用类似的过程和相关的神经系统。错误检查和抑制是否会影响学生对学科知识和建模知识的长期保持，目前还不清楚。更深入地了解基于建模的教学如何使学生受益，以及对谁最有效，可以用来开发更有效的STEM教学，以满足所有学生的需求。本项目的目标是（a）描述本科生命科学专业学生在模型评估过程中进行错误检测和抑制的性质和程度，以及（B）确定这些过程如何与长期知识保留相关。与学生的访谈将使错误检测的类型和程度的特点。 使用功能磁共振成像的脑部扫描将确定功能性神经反应。一年教学后的比较访谈和神经系统扫描将确定检测错误能力的变化如何预测概念和基于模型的知识的长期保留。这项研究的结果将在研究会议上和通过同行评审的文献传播。这项研究将为生命科学本科生的学习提供一个基于建模的教学案例研究。拟议的项目是内布拉斯加大学林肯分校和密歇根州立大学的共同努力，并得到了EHR核心研究（ECR）计划的支持，该计划支持推进STEM学习和学习环境基础研究的工作，扩大参与STEM，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准。