Enhancing Visualization Skills and Conceptual Understanding Using a Drawing-Recognition Tutoring System for Engineering Students

使用工程专业学生的绘图识别辅导系统增强可视化技能和概念理解

• 批准号: 1725423
• 负责人: Julie Linsey
• 金额: $ 42.91万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1725423&HistoricalAwards=false
• 关键词: Enhancing; Visualization; Skills; Conceptual; Understanding

Visual and spatial skills are important for scientific and engineering innovation. The ability to represent real systems through accurate yet simplified diagrams is a crucial skill for engineers. A growing concern among engineering educators is that students are losing both the skill of sketching and the ability to produce the free-body diagrams (FBDs) of real systems. These diagrams form the basis for various types of engineering analyses. To address this concern, investigators will redesign and test a cutting-edge educational technology for engineering concepts of statics and mechanics. The sketch-based technology developed at Texas A&M University, called Mechanix, enabled students to hand-draw FBDs, trusses, and other objects using digital ink and provided helpful feedback. The upgraded Mechanix software will include enhanced artificial intelligence (AI) to understand the sketches and provide immediate feedback to the student for individualized tutoring. Instructors will also receive real-time detailed information from the system so they can clarify misconceptions and guide students through problem solutions during classes. This free-hand sketch-based system will focus learning on the fundamental engineering concepts and not on how to use a software tool. These engineering concepts directly relate to a wide variety of designs including bridges, buildings, and trusses that are vital to the infrastructure of the nation's cities. The project will help prepare engineers with improved abilities to develop these designs that are essential in society.This project will aim to demonstrate the impact of the sketch-recognition based tutoring system on students' motivation and learning outcomes, both generally and among students of diverse backgrounds. The Mechanix system will be converted to an HTML5 format to work on all devices and expand its accessibility for institutions with various technological requirements. Additional AI algorithms will be developed to accommodate more types of statics problems, increased sketch-recognition accuracy and speed, and improved feedback mechanisms for instructors that merge performance information for the students in a class. The upgraded system will be studied in various engineering courses across five different universities, and introduced to over 2,500 students in engineering and related fields. The investigators will utilize controlled classroom experiments, digital data collection, pre/post concept testing, focus groups, and interviews to explore the external validity of Mechanix as a learning tool. Analysis of Covariance will be used to compare outcomes for students using Mechanix and students in control groups. Project outcomes and the Mechanix software will be shared through the project website, professional development workshops, and publications.

视觉和空间技能对于科学和工程创新很重要。通过准确但简化的图表代表实际系统的能力对于工程师来说是一项至关重要的技能。在工程教育工作者中，人们日益关注的是，学生既失去素描技巧，又失去了生产实际系统的自由图（FBD）的能力。这些图构成了各种类型的工程分析的基础。为了解决这一问题，调查人员将重新设计和测试一种统计和力学工程概念的尖端教育技术。基于素描的技术在德克萨斯A＆M大学开发，称为Mechanix，使学生能够使用数字墨水对FBD，桁架和其他对象进行绘制，并提供了有用的反馈。升级的Mechanix软件将包括增强的人工智能（AI），以了解草图并为学生提供个性化辅导的立即反馈。讲师还将从系统中获得实时详细信息，以便他们可以澄清误解并指导学生通过课堂上的问题解决方案。这个基于手法的自由草图系统将把学习集中在基本工程概念上，而不是如何使用软件工具上。这些工程概念直接与各种各样的设计有关，包括桥梁，建筑物和桁架，这些设计对国家城市的基础设施至关重要。该项目将有助于使工程师具有改进能力开发这些在社会中必不可少的设计的能力。该项目将旨在证明基于草图 - 识别的辅导系统对学生的动机和学习成果的影响，无论是多种背景的学生。 Mechanix系统将转换为HTML5格式，以在所有设备上使用，并扩大其对具有各种技术要求的机构的可访问性。将开发其他AI算法，以适应更多类型的静态问题，提高草图 - 识别准确性和速度，并改善向班级学生合并绩效信息的教师的反馈机制。升级的系统将在五个不同大学的各种工程课程中进行研究，并介绍了2500多名工程和相关领域的学生。调查人员将利用受控的课堂实验，数字数据收集，预/后概念测试，焦点小组和访谈来探索Mechanix作为学习工具的外部有效性。协方差分析将用于比较使用机械和对照组的学生的学生的结果。项目成果和Mechanix软件将通过项目网站，专业开发研讨会和出版物共享。

项目成果

Changing Homework Achievement with Mechanix Pedagogy: Increasing the Efficacy of a Measurement Tool for Construction Majors,” American Society for Engineering Education Annual Conference, Minneapolis, Minnesota.

《利用 Mechanix 教学法改变家庭作业成绩：提高建筑专业测量工具的效率》，美国工程教育学会年会，明尼苏达州明尼阿波利斯。

• 发表时间: 2022
• 期刊: American Society for Engineering Education Annual Conference
• 作者: Talley, K.

Changing Homework Achievement with Mechanix Pedagogy: A Recap

使用 Mechanix 教学法改变家庭作业成绩：回顾

• 发表时间: 2022
• 期刊: ASEE annual conference exposition proceedings
• 作者: Runyon, M.

Changing Homework Achievement with Mechanix Pedagogy

通过 Mechanix 教学法改变家庭作业成绩

• 发表时间: 2019
• 期刊: American Society for Engineering Education Annual Conference
• 作者: Bante, S.

An Intelligent Interface for Automatic Grading of Sketched Free Body Diagrams

草绘自由体图自动分级的智能界面

• DOI: 10.1145/3379336.3381471
• 发表时间: 2020
• 期刊: Proceedings of the 25th International Conference on Intelligent User Interfaces Companion
• 作者: Runyon, Matthew;Williford, Blake;Linsey, Julie;Hammond, Tracy
• 通讯作者: Hammond, Tracy

Predicting Success of Engineering Student Makers: Relationships between Makerspace Involvement, Academic Performance, and Engineering Design Self-Efficacy

预测工程专业学生创客的成功：创客空间参与、学业成绩和工程设计自我效能之间的关系

• 发表时间: 2022
• 期刊: International Journal of Engineering Education
• 影响因子: 1
• 作者: Weaver, M. B.;Hilton, E.;Alemán, M. W.;Nagel, R.;Linsey, J.
• 通讯作者: Linsey, J.