I-Corps: Evaluating the Market Potential of the Mechanix Sketch Recognition Software

大型大学的入门工程课程每年的入学人数往往超过数百名学生，而MOOCS和在线课程的班级人数甚至更大。在班级规模和学生多样性如此巨大的教室中实现差异化教学是非常具有挑战性的。在这样的课堂上，教授们只能通过多项选择题来评估学生是否掌握了一个概念。然而，在多项选择的情况下，学生只需要确定答案，而不是创建答案，收到的反馈只是二元性质（正确或错误）。此外，工程教育工作者越来越担心的是，学生正在失去草图的关键技能和采取真实的系统，并将其简化为一个准确的，但简化的自由体图（FBD）的能力。所提出的软件程序，机械，提供了一个人工智能的，可扩展的在线教学平台，工程和物理instruction.Mechanix是一个基于草图的辅导系统，为工程专业的学生在静力学课程注册。机械不仅允许学生手绘平面桁架和自由体图的解决方案，就像他们会用铅笔和纸，但它也检查学生的工作。它使用草图识别来确定草图的组件形状和特征以及这些形状和特征之间的关系。然后，Mechonix使用这些关系来确定学生的作业是否正确以及为什么不正确，使Mechonix能够立即向学生返回个性化的反馈，否则在大班中是不可能的。迭代校正过程有助于学生学习。此外，Mechanix减轻了教师的资源密集型负担，甚至是非常复杂的手绘作品。这使教师能够探索创造性的解决问题的材料，否则可能过于资源密集的评估。Mechanix软件已成功部署在三所学校的课堂上，有300多名学生参与，显示出良好的学习和学生参与效果。在这个项目中，I-Corps团队试图确定在那些市场中的客户需求，在这些市场中，Mechonix可能以其目前的形式产生最大的影响：学习机构，教师，学生和教育内容提供商。该团队还试图确定Mechonix与这些需求和可能需要的变化的一致性;并确定是否存在可能应用该技术的其他市场。

Introductory engineering courses within large universities often have annual enrollments exceeding several hundreds of students, while MOOCS and online classes have even larger classes. It is very challenging to achieve differentiated instruction in classrooms with class sizes and student diversity of such great magnitude. In such classes, professors can only assess whether students have mastered a concept by using multiple-choice questions. However, in a multiple choice scenario, students only have to identify the answer rather than create the answer, and the feedback received is only of a binary nature (right or wrong). Additionally, a growing concern among engineering educators is that students are losing both the critical skill of sketched diagrams and the ability to take a real system and reduce it to an accurate but simplified free-body diagram (FBD). The proposed software program, Mechanix, provides an artificially intelligent, scalable online instructional platform for engineering and physics instruction.Mechanix is a sketch-based tutoring system for engineering students enrolled in statics courses. Mechanix not only allows students to hand-draw solutions with planar truss and free body diagrams, just as they would with pencil and paper, but it also checks the student's work. It uses sketch recognition to determine both the component shapes and features of the sketched diagram and the relationships between those shapes and features. Mechanix then uses those relationships to determine whether a student's work is correct and why it is incorrect, enabling Mechanix to return immediate personalized feedback to the student otherwise not possible in large classes. The iterative correction process facilitates student learning. Additionally Mechanix relieves the instructor of the resource intensive burden of grading even very complex, hand-sketched work. This enables the instructor to explore creative problem solving material that may be otherwise too resource intensive to evaluate. The Mechanix software has been successfully deployed in the classroom at three schools with over 300 participating students, showing promising learning and student engagement results. In this project the I-Corps team seeks to determine customer needs in those markets where Mechanix may have the greatest impact in its current form: learning institutions, instructors, students and providers of educational content. The team also seeks to determine the alignment of Mechanix with those needs and changes that may be required; and to determine whether there exist additional markets where this technology may be applied.