Collaborative Research: 3D Virtual-Rock Models for Testing Category Learning Theory to Improve Student Learning in Physical Geology

协作研究：用于测试类别学习理论的 3D 虚拟岩石模型，以提高学生在自然地质学方面的学习

• 批准号: 1937389
• 负责人: Scott Brande
• 金额: $ 21.47万
• 依托单位: University of Alabama at Birmingham
• 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: 2020-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1937389&HistoricalAwards=false
• 关键词: Collaborative; Research; 3D; Virtual; Rock

This project aims to serve the national need for highly effective undergraduate STEM education. Specifically, the project aims to enhance the teaching of rock identification and categorization in introductory undergraduate geoscience classes. Helping students learn about categorization, such as rock types in geology, is important in science curricula because categories are the building blocks of basic thought processes in humans. Categories provide an efficient means for humans to reason and draw inferences about the nature of the world. The project hypothesizes that students will learn how to categorize rocks better if they can study both physical rock samples and three-dimensional computer models of rocks. Consequently, the project will develop interactive three-dimensional computer models of rocks to supplement students’ interaction with physical rocks. The project will conduct research on the effect that using the computer models has on student learning. In addition, the project will develop teaching resources to supplement the computer models. These resources and the three-dimensional computer models themselves will be made widely available to geoscience educators throughout the nation. The aims of the project are to: 1) develop 3-D computer models of at least four different examples of ten different types of rocks; 2) conduct research on how students develop classification schemes for rocks with consideration of the impact on learning resulting from the order in which the rocks are viewed; and 3) provide the new computer models of rocks to the geoscience community of learners. The domain of rock classification appears to be both a challenging and highly representative example of natural-science category learning. Therefore, the experimental results obtained in this project should provide training guidance across the broad expanse of STEM disciplines in which students are tasked with learning and inducing categories from the study of individual objects. The results of the project have the potential to inform and improve standard practice in teaching science categories, and by so doing assist societal efforts to promote STEM education. Finally, the technology that will be used in the project will provide the geoscience-education community with a channel for instruction of students who are currently underserved because they have limited access to physical laboratory facilities. This project is supported by the NSF Improving Undergraduate STEM Education Program: Education and Human Resources. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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.

本项目旨在满足国家对高效本科STEM教育的需求。具体而言，该项目旨在加强本科地球科学入门课程中岩石识别和分类的教学。帮助学生学习分类，比如地质学中的岩石类型，在科学课程中很重要，因为分类是人类基本思维过程的基石。范畴为人类对世界的本质进行推理和推断提供了一种有效的手段。该项目假设，如果学生能够同时学习岩石实物样本和岩石的三维计算机模型，他们将学会如何更好地对岩石进行分类。因此，该项目将开发岩石的交互式三维计算机模型，以补充学生与物理岩石的互动。该项目将研究使用计算机模型对学生学习的影响。此外，该项目将开发教学资源，以补充计算机模型。这些资源和三维计算机模型本身将广泛提供给全国的地球科学教育者。该项目的目标是：1)开发至少四种不同岩石类型的三维计算机模型；2)研究学生如何制定岩石的分类方案，并考虑到观察岩石的顺序对学习的影响；3)为地学学习者提供新的岩石计算机模型。岩石分类领域似乎是自然科学分类学习的一个具有挑战性和高度代表性的例子。因此，本项目获得的实验结果应该为广泛的STEM学科提供培训指导，在这些学科中，学生的任务是从单个对象的研究中学习和归纳类别。该项目的结果有可能为科学类别的教学提供信息和改进标准实践，并通过这样做帮助社会努力促进STEM教育。最后，该项目将使用的技术将为地球科学教育界提供一个指导学生的渠道，这些学生目前由于无法获得物理实验室设施而得不到充分的服务。本项目由美国国家科学基金改进本科STEM教育计划：教育与人力资源资助。通过其参与学生学习轨道，该计划支持有前途的实践和工具的创建，探索和实施。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。