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This research category paper examines the impact of computational thinking within first-year engineering courses on student pathways into engineering. Computational thinking and programming appear in many introductory engineering courses. Prior work found that early computational thinking development is critical to the formation of engineers. This qualitative research paper extends the research by documenting how pre-university privileges impact first-year student trajectories into engineering through a qualitative examination of student interviews from three institutions with different processes for matriculation into engineering majors. We identify the underlying assumptions of meritocracy that are concealing the role of educational privilege in selecting which engineering students will be allowed to join the field. We provide a suggestion for how institutions can include computational thinking in introductory engineering courses with less risk of furthering the marginalization of students with few academic privileges. 

This research category paper examines the impact of computational thinking within first-year engineering courses on student pathways into engineering. Computational thinking and programming appear in many introductory engineering courses. Prior work found that early computational thinking development is critical to the formation of engineers. This qualitative research paper extends the research by documenting how pre-university privileges impact first-year student trajectories into engineering through a qualitative examination of student interviews from three institutions with different processes for matriculation into engineering majors. We identify the underlying assumptions of meritocracy that are concealing the role of educational privilege in selecting which engineering students will be allowed to join the field. We provide a suggestion for how institutions can include computational thinking in introductory engineering courses with less risk of furthering the marginalization of students with few academic privileges. 

This research category paper examines the impact of computational thinking within first-year engineering courses on student pathways into engineering. Computational thinking and programming appear in many introductory engineering courses. Prior work found that early computational thinking development is critical to the formation of engineers. This qualitative research paper extends the research by documenting how pre-university privileges impact first-year student trajectories into engineering through a qualitative examination of student interviews from three institutions with different processes for matriculation into engineering majors. We identify the underlying assumptions of meritocracy that are concealing the role of educational privilege in selecting which engineering students will be allowed to join the field. We provide a suggestion for how institutions can include computational thinking in introductory engineering courses with less risk of furthering the marginalization of students with few academic privileges. 

This research-track work-in-progress paper contributes to engineering education by documenting progress in developing a new standard Engineering Computational Thinking Diagnostic to measure engineering student success in five factors of computational thinking. Over the past year, results from an initial validation attempt were used to refine diagnostic questions. A second statistical validation attempt was then completed in Spring 2021 with 191 student participants at three universities. Statistics show that all diagnostic questions had statistically significant factor loadings onto one general computational thinking factor that incorporates the five original factors of (a) Abstraction, (b) Algorithmic Thinking, (c) Decomposition, (d) Data Representation and Organization, and (e) Impact of Computing. This result was unexpected as our goal was a diagnostic that could discriminate among the five factors. A small population size caused by the virtual delivery of courses during the COVID-19 pandemic may be the explanation and a third round of validation in Fall 2021 is expected to result in a larger population given the return to face-to-face instruction. When statistical validation is completed, the diagnostic will help institutions identify students with strong entry level skills in computational thinking as well as students that require academic support. The diagnostic will inform curriculum design by demonstrating which factors are more accessible to engineering students and which factors need more time and focus in the classroom. The long-term impact of a successfully validated computational thinking diagnostic will be introductory engineering courses that better serve engineering students coming from many backgrounds. This can increase student self- efficacy, improve student retention, and improve student enculturation into the engineering profession. Currently, the diagnostic identifies general computational thinking skill 

Computational thinking is understood as the development of skills and knowledge in how to apply computers and technology to systematically solve problems. Computational thinking has been acknowledged as one key aspect in the taxonomy of engineering education and implied in multiple ABET student outcomes. Moreover, many introductory engineering courses worldwide have a component of programming or computational thinking. A preliminary study of enculturation to the engineering profession found that computational thinking was deemed a critical area of development at the early stages of instruction (Mendoza Diaz et al., 2018, 2019; Richard et al., 2016; Wickliff et al., 2018). No existing computational thinking framework was found to fully meet the needs of engineers, based on the expertise of researchers at three different institutions and the aid of a comprehensive literature review. As a result, a revised version of a computational thinking diagnostic was developed and renamed the engineering computational thinking diagnostic (ECTD). The five computational thinking factors of the ECTD are (1) Abstraction, (2) Algorithmic Thinking and Programming, (3) Data Representation, Organization, and Analysis, (4) Decomposition, and (5) Impact of Computing. This paper describes the development and revisions made to the ECTD using data collected from first-year engineering students at a Southwestern public university. The goal of the development of the ECTD is to capture the entry and exit skill levels of engineering students in an engineering program.