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This full research-track paper demonstrates growth in computational thinking in a cohort of engineering students completing their first course in engineering at a large Southwestern university in the United States. Computational thinking has been acknowledged as a key aspect of engineering education and an intrinsic part of multiple ABET outcomes. However, computing is an area where some students have more privileges (e.g. access and exposure to meaningful use of computers) than others. Integrating computing into engineering, especially early in the curriculum, may exacerbate existing experiential disadvantages students from excluded social identities experience. Most introductory engineering programs have a component of programming and/or computational thinking. A comprehensive literature review showed that no existing computational thinking framework fully met the needs of students and professors in engineering and computer science. As a result, this team created the Engineering Computational Thinking Diagnostic (ECTD). This diagnostic was assessed and improved during the 2019-2020 academic year. Data was collected from a cohort in a first-year engineering course that included topics in mathematics, engineering problem solving, and computation. Pre- and post-test data analysis with 62 participants documents statistically significant student growth in computational thinking in this course. Significant differences were not found by gender or a limited racially-based analysis. This diagnostic is of interest and relevance to all institutions providing engineering and computing programs. The short-term impact of this research includes an innovative approach to gauge student abilities in computational thinking early in a course in order to add appropriate intervention activities into lesson plans. The long-term impact is the creation of a measurement of student learning of computational thinking in engineering for courses and programs that wish to develop this important skill in their students.
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