Collaborative Research: Research in Improving Computational Thinking in the Formation of Engineers, a Multi-Institutional Initiative.

Abstract

The need for undergraduate engineering students to learn computing has dramatically increased as computing has become more important in engineering practice. Many engineering colleges have responded to this change by requiring their engineering students to take computing classes. Some of these classes are now central to the first year of college engineering education. Computing classes are considered to be extremely difficult by many students, especially those who have not been exposed to computing in high school. Inequities in the K-12 education system mean that some students often have less opportunity to be exposed to computing before college than others. As a result, integrating computing into engineering education may exacerbate existing inequities in engineering education and reduce diversity and inclusion in engineering. This research examines the integration of computing in engineering at three institutions that incorporate computing into engineering education in different ways. A computational thinking diagnostic, which measures the degree to which students are learning critical computing concepts in engineering classes, will be used to determine how much computing the engineering students are learning. A survey will examine how students with different backgrounds are responding to the challenges of doing computing in their engineering education program. Students will also be surveyed as the term progresses to identify students who are feeling increasing, steady or decreasing stress as the complexity of the material increases. Students will be interviewed about how computing is affecting their desire to become an engineer and their confidence in their ability to excel in engineering. Taken together this information will provide new knowledge of how the integration of computing in beginning engineering classes is changing engineering education and impacting who becomes an engineer. Previous research has demonstrated that while engineering and computational skills have substantial overlap, many engineering students have little or no prior experience with computational thinking. The goal of this project is to improve the way that computational thinking is taught in colleges of engineering by understanding multiple factors that affect computational thinking development. A mixed-methods research design involving a computational thinking diagnostic paired with qualitative analysis of interviews will explore answers to three research questions: (1) How does the integration of computing into the foundational engineering courses affect the formation of engineers? (2) In what ways do social identities (e.g. gender, ethnicity, first-generation college attending), choices (e.g. major, transfer status), and other factors impact the engineering student experience with computational thinking? (3) In what ways do computational thinking skills develop over time in engineering students? The PI team has direct access to the target population at three institutions (a large, public, land grant institution (Texas A&M), a medium sized, public, state flagship institution (University of Oklahoma), and a small, private, undergraduate university focused on engineering degrees (Milwaukee School of Engineering). Each institution has unique ways of integrating computational thinking into engineering programs. Having these three institutions collaborate provides varied curricular models for integrating computation into engineering, making comparative analysis powerful. The novelty and creativity of this project lies in the capacity of the research team to answer critical questions about why students succeed or fail to become engineers based on unique computational thinking opportunities that three diverse institutions and environments provide. This award reflects NSF’s statutory mission and has been deemed worthy of support through evaluation using the Foundation’s intellectual merit and broader impacts review criteria.

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