EXP: Collaborative Research: PerSketchTivity- Empowering and Inspiring Creative, Competent, Communicative, and Effective Engineers through Perspective Sketching

网络学习和未来学习技术计划资助的努力将有助于设想下一代学习技术，并推进我们对人们如何在技术丰富的环境中学习的了解。Cyberlearning Exploration（EXP）项目通过构建示例和研究其促进学习的可能性以及使用它们的挑战来探索新型学习技术的可行性。这个项目探讨了技术是否可以支持学习徒手素描。草图已经被证明在许多领域中发挥着重要作用，包括工程，并且快速草图的能力已经被证明可以通过使工程师更容易地产生想法并传达它们来提高创造力。这个项目将修改支持识别草图的人工智能工具，以直接帮助教本科工程师如何画好草图。研究将检查该工具是否有助于学生学习素描技能，以及重要的是它如何影响他们的空间推理能力。因此，如果这项研究成功，不仅将创造工具，让人们更好地学习素描，但也将推进我们的理解空间推理和素描是如何联系在一起的，并最终可能导致更有效的工程教育。该项目提出了两个相互关联的工作链：开发软件工具，并在本科工程课程的背景下进行研究。该软件工具将使用一组异质的分类器，以帮助提供反馈给学习者，因为他们执行了一系列的素描练习平板电脑。设计过程将在工具上探索什么类型的反馈是最有帮助的，以及如何使用不同的分类器来检测不同水平的素描技能。研究计划将包括研究素描训练是否会导致空间推理技能的进步，它是否会影响设计自我效能感和对素描的态度，将空间技能转移到其他课程的设计活动中，以及素描技能如何与空间推理任务的成功相关。 此外，通过包括以用户为中心的设计过程的迭代开发，将导出基于草图的工具的设计原则。数据源将包括定性和定量数据，如测试前和测试后的空间推理任务，结构化访谈，调查和工件分析。此外，将在课堂上使用新工具的学生（N=约30-40）与使用传统工程课程（很少徒手草图和一些等距图）和没有AI工具的草图课程的约30名学生的对照组进行比较。

The Cyberlearning and Future Learning Technologies Program funds efforts that will help envision the next generation of learning technologies and advance what we know about how people learn in technology-rich environments. Cyberlearning Exploration (EXP) Projects explore the viability of new kinds of learning technologies by building examples and studying their possibilities for fostering learning as well as challenges to using them well. This project examines whether technology can support learning to freehand sketch. Sketching has been demonstrated to play an important role in a number of domains, including engineering, and the ability to quickly sketch has been shown to improve creativity by making it easier for engineers to generate ideas and communicate them. This project will modify artificial intelligence tools that support recognizing sketches to directly help teach undergraduate engineers how to sketch well. Research studies will examine whether the tool helps students learn sketching skills, and importantly how it influences their spatial reasoning ability. Thus, if successful this research will not only create tools to allow people to learn to sketch better, but also will advance our understanding of how spatial reasoning and sketching are linked, and could eventually lead to more effective engineering education.The project proposes two interconnected strands of work: developing the software tool and conducting research studies in the context of undergraduate engineering courses. The software tool will use a heterogenous set of classifiers to help provide feedback to learners as they perform a sequence of sketching exercises on tablets. The design process will iterate on the tool to explore what types of feedback are most helpful and how different classifiers can be used to detect different levels of sketching skill. The program of research will include studying whether sketching training leads to advances in spatial reasoning skills, whether it affects design self-efficacy and attitudes towards sketching, transfer of spatial skillsets to design activities in other courses, and how sketching skills correlate to success on spatial reasoning tasks. In addition, through iterative development including user-centered design processes, design principles for sketching based tools will be derived. Data sources will include both qualitative and quantitative data such as pre- and post-test spatial reasoning tasks, structured interviews, surveys, and artifact analysis. Additionally, students (N=approximately 30-40) using the new tool in class will be compared to control cohorts of approximately 30 students who either use traditional engineering curricula (little free-hand sketching and some isometric drawing) and a sketching curriculum without the AI tool.