Learning Internal Visualization Skills for Complex Engineering Concepts in Active Learning Classes

在NSF改善本科STEM教育计划：教育和人力资源（IUSE：EHR）的支持下，该项目旨在通过提高工程专业学生理解图形和其他视觉表示的能力来服务于国家利益。工程教师经常使用视觉表示，如笛卡尔和极坐标图，以帮助学生学习。然而，这些可视化可能会让学生感到困惑，除非他们知道可视化如何显示信息。这个项目将使用智能辅导系统来帮助学生学习特定的视觉特征如何显示特定的基础工程概念。 它还将针对学生在理解视觉表示方面的流畅性，类似于语言的流畅性。智能教程系统还将训练学生在他们不再在场时想象视觉效果。预计这些“内部”可视化技能将帮助学生更容易地从文本和方程中学习。实验将调查哪些支持导致学生的内部可视化技能和内容学习的最大改善。实验将在学生单独学习和合作学习的情况下进行，使项目团队能够确定视觉表征的哪些方面最好单独学习，哪些方面最好在团队中学习。这种理解对于理解主动学习课程的局限性和最大限度地提高效率非常重要。当视觉表示随后被抽象方程取代时，内部可视化技能可以增强学习。该项目将解决两个关键的知识差距：i）如何以提高内部可视化技能的方式最好地支持代表能力; ii）如何有效地支持个人和协作活动的代表能力，后者在主动学习中越来越重要。该项目将为教学如何帮助学生从视觉表现中受益提供新的见解。虽然该项目侧重于基础工程概念的学习，但它可能会产生为其他学科的教育技术资源开发提供信息的结果。该项目将产生一种创新的教育技术资源，为个人和协作学习提供视觉支持，这可能会提高学生在STEM方面的成功。NSF IUSE：EHR计划支持研究和开发项目，以提高所有学生STEM教育的有效性。IUSE计划通过“学生学习”（Student Learning）项目，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进行评估，被认为值得支持。

With support from the NSF Improving Undergraduate STEM Education Program: Education and Human Resources (IUSE:EHR), this project aims to serve the national interest by improving engineering students' ability to understand graphs and other visual representations. Engineering instructors often use visual representations, such as Cartesian and polar coordinate graphs, to help students learn. However, these visualizations can be confusing to students unless they know how the visualizations show information. This project will use an intelligent tutoring system to help students learn how particular visual features show specific foundational engineering concepts. It will also target student fluency in understanding visual representations, akin to fluency in a language. The intelligent tutorial system will also train students to imagine the visuals when they are no longer present. It is expected that these "internal" visualization skills will help students learn more easily from text and equations. Experiments will investigate which supports lead to most improvement in students' internal visualization skills and content learning. The experiments will be carried out in situations in which students learn individually and collaboratively, allowing the project team to establish which aspects of visual representations are best learned alone and which are best learned in a team. Such understanding is important for understanding the limits and maximizing the effectiveness of active learning classes.Internal visualization skills enhance learning when the visual representations are subsequently replaced by abstract equations. Two critical knowledge gaps will be addressed in the project: i) how best to support representational competencies in a way that enhances internal visualization skills; ii) how to effectively support representational competencies for both individual and collaborative activities, the latter being increasingly important in active learning. The project will provide new insights into how instruction can help students benefit from visual representation. Although the project focuses on the learning of foundational engineering concepts, it may yield results that inform the development of educational technology resources for other disciplines. The project will lead to an innovative educational technology resource that provides support for individual and collaborative learning with visuals, which may enhance students' success in STEM. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the IUSE 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.