CPACE - An NSF CPATH Project

CPACE: A Collaborative Process to Align Computing Education with Engineering Workforce Needs

The CPACE Initiative: Overview CPACE I & CPACE II

    In the global economy of the 21st century, the preparation of a competitive U.S. workforce with knowledge and understanding of critical computing concepts, methodologies, and techniques is essential. The Collaborative Process to Align Computing Education with Engineering Workforce Needs (CPACE) project brings together Michigan State University (MSU), Lansing Community College (LCC) and the Corporation for Skilled Workforce (CSW) to design and implement a process to transform undergraduate computing education within the engineering and technology fields. The CPACE team developed a partnership among various stakeholders –university, community college and business and industry leaders – to identify the computational skills that are essential for a globally competitive engineering workforce. Our goal is to redesign the role of computing within the engineering programs at MSU and LCC to develop computational competencies – informed by industry needs – by infusing computational learning opportunities into the undergraduate engineering curriculum.

    During the first phase of the project (CPACE I), we interviewed and surveyed engineering stakeholders to understand engineering workplace needs for computational competence both at the practical-tool level and at the computational problem solving level. Central themes emerged that are consistent with other research on engineering education (National Academy Press, 2005; The Carnegie Foundation for the Advancement of Teaching, 2008); employers place high value on: (a) interpersonal skills such as communication, ability to organize and present data, and the ability to function in a team; (b) critical and innovative thinking and problem solving; and (c) employers see trends towards computational globalization which translates to the need for engineers to understand business practices and the importance of integrating engineering data across larger systems. The ability of engineers to understand computational principles in the context of the engineering practice allows them to select and use computation to solve engineering problems. With regard to specific software, Excel, design and modeling software, and data and project management software were identified as very important to the engineering practice (Vergara et al., 2009a; 2009b).

    After identifying workforce needs for computational competence and skills, we translated our findings into Computer Science (CS) concepts and used those as the foundation for integrating computation in the engineering curricula (Vergara et al., 2011). The chart in Figure 1 shows the distribution of the computational competencies required in the engineering workplace mapped to CS concepts that can be used to implement curricular changes. Our goal is to better align our engineering graduates capabilities to solve disciplinary problems utilizing computational skills with the needs of industrial stakeholders represented in this distribution.

    

Figure 1. Distribution of engineering workplace computational competencies aligned to CS concepts (Vergara et al., 2011). 

 
    In CPACE II our goal is to infuse computational problem-solving competencies throughout the curricula. To achieve an integrated computing experience, our strategy entails using problems derived from contemporary industrial engineering practice. The problems are developed in consultation with stakeholders from industry, and faculty from engineering and computer science (CS) to ensure that they exemplify relevant industrial scenarios within the discipline. These problems provide a context where students are required to apply various computational concepts for their solution. Initial implementation includes Chemical (CHE) and Civil (CE) Engineering at MSU and pre-engineering courses at LCC. Key courses are addressed across all four years of the engineering curricula. Following a mixed methods approach, quantitative and qualitative data are collected. We collect student surveys at the beginning and end of target courses. The goals of the student surveys are: (a) to measure general attitudes towards engineering; (b) to measure attitudes towards computational problem solving; (c) to determine the use and application of computational tools. In addition, we conduct focus groups and faculty and student interviews. Standard class data on learning outcomes and sample course work e.g. final report on the assigned problem and relevant homework assignments from the target courses at LCC and MSU are collected and assessed.  We are currently in the process of analyzing the data for preliminary reports on student outcomes refer to Vergara et. al., (2012).

Publications and ResourcesPlease follow the link to find relevant CPACE publications.

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Contact us at: cpace@msu.edu

This material is based upon work supported by the National Science Foundation under awards 0722221 and 0939065. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).

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