Modeling the Conceptual Dynamics of College Students' Reasoning about Natural Selection

大学生自然选择推理的概念动态建模

• 批准号: 2300437
• 负责人: Julia Gouvea
• 金额: $ 48.78万
• 依托单位: Tufts University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2300437&HistoricalAwards=false
• 关键词: Modeling; Conceptual; Dynamics; College; Students

This project aims to serve the national interest by better understanding how students think about the foundational biological concept of natural selection in undergraduate biology education. Prior work has established that student thinking about natural selection can vary greatly depending on the specific features of questions students are asked, such the type of organism or the trait that is under selection. Understanding when and why this variation in student thinking arises is important for biology educators and curriculum designers. Using interviews and analyses of students’ written explanations, the project team will identify which knowledge elements students use in response to different problem contexts and prompts. This work will identify the knowledge elements students use when thinking about natural selection, characterize the relationships between different knowledge elements and aspects of context, and explore the commonalities of those patterns. The results will help educators identify various facets of student thinking and design curricula that can help students activate and integrate their thinking, and thus improve their understanding of natural selection.This project will study the influence of context on undergraduate biology students’ reasoning about natural selection by building resource-based models of cognition. The specific objectives are to identify and characterize the conceptual resources students use in reasoning about natural selection, to build models that can explain why different resources are activated in different contexts, and to test whether the aspects of context we identify can be used to predict common patterns of reasoning. First, to identify sets of resources and patterns of activation in students’ reasoning about natural selection, the project team will conduct clinical interviews with introductory-level biology students from Tufts University and Bunker Hill Community College. The interview prompts will be designed to explore dynamics and context-sensitivities in students’ thinking by intentionally varying and perturbing the problem contexts to examine the dynamics of students’ moment-to-moment thinking. Case-study analyses of interviews will be used to present novel mechanisms of resource use and cross-case analyses of interviews will identify common patterns in students’ reasoning. Next, the project team will test the predictions of the models developed by presenting writing prompts to a larger number of students at both institutions and collecting written explanations. The project team will manipulate context and information provided in prompts to examine whether different prompts systematically elicit different patterns of reasoning. This approach will allow the project team to test the predictive strength of the associations they find in cross-case analyses to identify common dynamics and stabilities. The success of the project will be evaluated by a team of researchers who are experts in resource-based modeling and students’ reasoning about natural selection. Project findings will be disseminated to learning scientists as well as to educators who teach evolution at the university level. This project has the potential to contribute to theoretical knowledge about cognitive dynamics and the role of context in shaping cognition. It also has the potential to change the nature of biology instruction by helping instructors anticipate and notice the knowledge that students are likely to activate when thinking about natural selection and through the design of curricula that intentionally draw out and build in opportunities to integrate different facets of students’ thinking.This project is supported by NSF's EDU Core Research (ECR) program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM 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.

该项目旨在通过更好地了解学生如何思考本科生物学教育中自然选择的基本生物学概念来服务于国家利益。先前的工作已经确定，学生对自然选择的思考可以根据学生被问到的问题的具体特征而有很大的不同，例如生物体的类型或正在选择的特征。了解学生思维的这种变化何时以及为什么会出现，对生物教育工作者和课程设计者来说非常重要。通过访谈和对学生书面解释的分析，项目团队将确定学生在应对不同的问题背景和提示时使用了哪些知识要素。这项工作将确定学生在思考自然选择时使用的知识元素，描述不同知识元素和背景方面之间的关系，并探索这些模式的共性。研究结果将有助于教育工作者识别学生思维的各个方面，并设计课程，帮助学生激活和整合他们的思维，从而提高他们对自然选择的理解。本项目将通过建立基于资源的认知模型，研究环境对生物本科生自然选择推理的影响。具体的目标是识别和表征的概念资源的学生使用的推理自然选择，建立模型，可以解释为什么不同的资源被激活在不同的情况下，并测试我们确定的方面是否可以用来预测常见的推理模式。首先，为了确定学生对自然选择的推理中的资源和激活模式，项目小组将对塔夫茨大学和掩体希尔社区学院的入门级生物学学生进行临床访谈。面试提示将被设计为通过故意改变和干扰问题的背景来研究学生的即时思维动态，以探索学生思维中的动态和背景敏感性。访谈的案例研究分析将用于呈现资源使用的新机制，访谈的跨案例分析将确定学生推理的常见模式。接下来，项目团队将通过向这两个机构的大量学生提供写作提示并收集书面解释来测试模型的预测。项目小组将操纵提示中提供的上下文和信息，以检查不同的提示是否系统地引出不同的推理模式。这种方法将允许项目团队测试他们在跨案例分析中发现的关联的预测强度，以确定共同的动态和稳定性。该项目的成功将由一组研究人员进行评估，他们是基于资源的建模和学生对自然选择推理的专家。项目的研究结果将分发给学习科学的科学家以及在大学一级教授进化论的教育工作者。这个项目有可能有助于认知动力学的理论知识和环境在塑造认知中的作用。它也有可能改变生物学教学的性质，通过帮助教师预测和注意到学生在思考自然选择时可能激活的知识，并通过设计课程，故意引出和建立机会，整合学生思维的不同方面。ECR计划强调基础STEM教育研究，产生该领域的基础知识。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响力审查标准进行评估，被认为值得支持。