2019 ASEE Annual Conference & Exposition

Advances in science and technology are shaping every aspect of our lives including education, work, healthcare, transportation, commerce, and entertainment. This societal transformation has created an increasing demand for a workforce well-trained in science, technology, engineering and mathematics (STEM) fields and representative of societal diversity. To meet this demand, the K-12 educational environment is witnessing a growing focus on engaging and exposing all students to advance technologies. However, creating technologically rich educational environments requires preparing teachers to become comfortable with integrating new technologies in classrooms. As one contribution to this growing need, we developed a robotics education workshop for teachers and students to collaboratively learn and practice fundamental engineering and robotics concepts during summer and then utilize this knowledge in classroom during the academic year.

A fundamental step in the engineering design process is to perform various analyses to study the efficacy of a proposed design before building it. This includes analyzing every feature of the designed product, considering ways in which it could fail, and refining it, before transforming the design into a physical artifact. An important part of such evaluation includes being mindful of the current economic conditions to ensure that the new products appeal to consumers, who expect unique and exciting products. Thus educational preparation of the STEM workforce must go beyond technical content and ought to inculcate students’ entrepreneurial knowledge, skills, and attitude so that they understand target markets and make valuable contributions.

Canvas tools are increasing being used by educators to encourage an improve product development. The Design Canvas of Kline et al. uses a model-based methodology to facilitate the acquisition and analysis of data in an engineering design project while keeping the business context in mind. This paper describes how the design canvas of Kline et al. was adopted and implemented in our workshop and investigates its benefits.

The robotics education workshop was held over four-weeks in summer and consisted of a two-week guided training and a two-week collaborative robotic project. Participants included 16 teachers and 36 students from 12 inner-city high schools. They were divided into nine teams. During the collaborative robotic project, four teams of seven teachers and 16 students were randomly chosen as the treatment group. These teams in treatment group were taught the design canvas model and prompted to utilize it for robotic product development. The remaining five teams of nine teachers and 20 students constituted the control group. The treatment and control groups worked in separate rooms and were instructed not to interact with one-another during the experiment. The performance of teams in the treatment and control groups was evaluated 16 times over the two-week duration by a team of engineering students who did not know whether a team belonged to the treatment or control group. The evaluators studied five factors, namely, understanding of problem statement, information and knowledge gathering, idea generation, design tradeoff, and idea and design iterations. Out of 16 evaluations, considering average performance, the treatment group teams out-performed the control group teams 15 times.