There is consensus among US Materials Science and Engineering departments (driven by discussions with government, academic, and national lab stakeholders) that undergraduates require a deeper understanding of computational tools. The 2011 White House Materials Genome Initiative to accelerate the development of new materials asserts that computer-aided materials design--and training of the next generation workforce in computer-aided design--is vital to national competitiveness and welfare. Skills in computational materials modeling and design are desirable to employers hiring our graduates into industrial R&D and product development positions (e.g., Ford Motor Company, Boeing, John Deere), national labs, and academic research positions. To address these growing needs, our faculty team has developed and deployed a series of computational modules throughout the introductory coursework for our Materials Science and Engineering curriculum.
These modules have been delivered through context-rich collaborative solving sessions in a number of courses. During these sessions students work in teams to complete a worksheet that contains a single, longer disciplinary problem that ties to that week's topic. These worksheets are pulled from real world examples to showcase more in-depth applications of the material and engage students in problem solving and teamwork. Students follow up team worksheets with a individual weekly report. These worksheets and reports require students to use computational tools to help them perceive the usefulness and relevance of these tools for the coursework. Additional office hours are offered with a computational teaching assistant (who is trained to work with a few different classes using the computational modules in class) to support students using these computational tools. Our current enrollment is 110-120 students per class, and we offer three recitation sections capped at 40 students each.
This work has been championed by faculty working within a Community of Practice, implementing curricular changes collaboratively to improve the sustainability of the effort. The implementation of these computational modules has expanded to increase the number of courses using modules and the number of faculty developing and delivering them. In this paper, we will share more details about the modules and present results on the effectiveness of the Community of Practice model for implementing curricular changes in a sustainable manner.
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