Model Eliciting Activities

An example of a MEA is calculating the nano roughness of a surface to evaluate the smoothness of artificial joints. From any standpoint, such an exercise would be an exciting undertaking for a freshman. The problem is realistic, can benefit society, and is set in the extremely interesting field of nanotechnology. This is one way MEAs excel over other problems: the depth and scope of the problems are appealing to more students.

To solve the MEA, students go through a development phase, similar to software engineering, that includes 1) understanding the problem, 2) express / test / revise different models for a solution 3) evaluate the working model 4) document the working model. MEAs focus on developing models conveniently alongside our book that emphasizes algorithmic models. Additionally, students must work in teams to collaborate, think, and make decisions. Therefore, MEAs offer a taste of how real world problem-solving is done in addition to offering a setting to cultivate interpersonal skills required in any project.

Initially the IPRO team compiled a list of 100 possible MEA concepts. After defining what a good MEA would be the team cut the list down to six concepts. From these six we chose two of the concepts to develope thoroughly: Detecting Riverbeds on Mars and Fighting Forest Fires. Within the development we have provided pre-lab worksheets, background information and skeleton code for the students to modify.

Detecting Riverbeds on Mars MEA

Fighting Forest Fires MEA