Mechanix: A natural sketch interface tool for teaching truss analysis and free-body diagrams
Mechanix: A natural sketch interface tool for teaching truss analysis and free-body diagrams
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Mechanix：用于教授桁架分析和自由体图的自然草图界面工具
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
J. Linsey
中科院分区：
文献类型：
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作者：
O. Atilola;Stephanie Valentine;Hong;D. Turner;Erin M. McTigue;T. Hammond;J. Linsey
大规模开放在线课程、在线辅导系统和其他计算机作业系统通过提供更多的学生反馈和利用在线系统的可扩展性，正在迅速改变工程教育。虽然在线作业系统提供了巨大的好处，但工程教育工作者越来越担心的是，学生们正在失去绘制草图的关键艺术，以及将真实系统简化为准确但简化的自由体图(FBD)的能力。例如，一些在线系统允许将力拖放到FBD上，但不允许用户绘制FBD的草图，这是学习过程的关键部分。在本文中，我们讨论了一个草图识别工具MECHANIX，它为工科学生学习如何绘制桁架FBD和解决桁架问题提供了一个有效的手段。该系统允许学生将FBD草图绘制到平板电脑上，或者使用鼠标和标准计算机显示器。使用人工智能，机械不仅可以确定图表的组件形状和特征，还可以确定这些形状和特征之间的关系。由于MECHANIX是特定于领域的，因此它不仅可以使用这些关系来确定学生的作业是否正确，还可以确定为什么它不正确。然后，MECHNIX能够向学生提供即时、建设性的反馈，而无需提供最终答案。在这份手稿中，我们记录了Machix的内部工作原理，包括幕后的人工智能，并展示了对学生学习影响的研究。评估表明，对于节点桁架分析的教学方法，MECHNIX与纸笔作业一样有效；使用该程序的学生的焦点小组显示，他们认为MECHNIX提高了他们的学习效果，并且他们在使用时高度投入。
Abstract Massive open online courses, online tutoring systems, and other computer homework systems are rapidly changing engineering education by providing increased student feedback and capitalizing upon online systems' scalability. While online homework systems provide great benefits, a growing concern among engineering educators is that students are losing both the critical art of sketching and the ability to take a real system and reduce it to an accurate but simplified free-body diagram (FBD). For example, some online systems allow the drag and drop of forces onto FBDs, but they do not allow the user to sketch the FBDs, which is a vital part of the learning process. In this paper, we discuss Mechanix, a sketch recognition tool that provides an efficient means for engineering students to learn how to draw truss FBDs and solve truss problems. The system allows students to sketch FBDs into a tablet computer or by using a mouse and a standard computer monitor. Using artificial intelligence, Mechanix can determine not only the component shapes and features of the diagram but also the relationships between those shapes and features. Because Mechanix is domain specific, it can use those relationships to determine not only whether a student's work is correct but also why it is incorrect. Mechanix is then able to provide immediate, constructive feedback to students without providing final answers. Within this manuscript, we document the inner workings of Mechanix, including the artificial intelligence behind the scenes, and present studies of the effects on student learning. The evaluations have shown that Mechanix is as effective as paper-and-pencil-based homework for teaching method of joints truss analysis; focus groups with students who used the program have revealed that they believe Mechanix enhances their learning and that they are highly engaged while using it.