This work-in-progress innovative practice paper describes an active learning in-class activity to be used in introductory programming courses. In the software development industry, critical thinking, problem-solving, code review, and debugging are vital skill sets software engineers require to build software that meets requirements. Commercial software companies often have extensive code review processes to make sure that developed code is of high quality. Many new developers work in quality assurance and maintenance of software products. For these jobs, learning to understand code written by peers is an essential skill. Code review skills are rarely explicitly taught in required programming classes in CS, especially at the entry-level. In beginning programming classes, students are usually thrilled if they can find one way to make a program work. They rarely see, let alone generate, multiple approaches to solving a single problem. In this research, we propose an active learning approach that provides students with experience reviewing and analyzing existing code. In our activities, students practice code review skills by exploring multiple approaches to solve a single problem. We have developed an in-class active learning approach, called Code Insight, for entry-level programming courses. Code Insight activities are designed based on student-created answers to previous homework and midterm problems. Students are given the code to upload into their development environment, so they have the tools available that a typical software developer would have. Students use a classroom response system to report the correctness of these solutions by responding to multiple-choice questions. Preliminary results show that students prefer doing this activity to listening to lectures. In addition, students report that they learn more programming from this structure of the exercise. The degree to which Code Insight can improve student learning in beginning programming will be assessed using performance on other learning assignments, particularly those on programming questions in the midterm and final examinations.

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

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.

Margolis and Fisher's book, Unlocking the Clubhouse (UTC), has long been regarded as seminal to the understanding of the lack of gender diversity in computing. This book found that boys and girls had different experiences with computers in the home and school environment, and that these different experiences had a direct impact on the desire of students to study computing. We wanted to know if the explanations Margolis and Fisher found were applicable for students in a more typical CS program in 2017, so we conducted a study to investigate the home and pre-college experiences of students who are currently majoring in CS or Computer Engineering (CE), and these students' pathway into computing majors. We recruited 11 participants from a large public institution in the Midwest U.S., and conducted interviews of these students using a protocol adapted from UTC. We performed a qualitative iterative and inductive analysis of these interviews and found that while technology access had greatly improved, views and attitudes were much slower to change. We discovered that fathers preferentially teaching sons about computing, while less prevalent than it was in UTC, still occurs. We also found that the participants, including the women, had more diverse pathways into computing than what Margolis and Fisher found. This suggests that UTC needs to be fully replicated at broad range of institutions to get a more complete picture of the multitude of pathways women use to enter into computing careers.

The Research Institute for STEM Education (RISE) brings together a multi-disciplinary research team whose mission is to study the complex array of factors contributing to diverse students' successful academic experiences in science, technology, engineering, and mathematics majors (STEM) in the United States (U.S.). Utilizing a combination of narrative and artifact analysis, RISE develops recommendations to educators and academic policy makers based on those factors. RISE also strives to promote a more equitable and diverse cultural climate within engineering education. This paper will review the recommendations made during fifteen years of research on equity in U.S. engineering education for consideration by engineering educators working in other cultural contexts. The recommendations can be loosely categorized into seven domains: communication, college culture, department culture, classroom culture, faculty-student interactions, student-peer interactions, and academic pathway.

We describe the construction and assessment of a plan to foster student success in Computer Science (CS) in response to continued enrollment growth. We examined cross correlations of grades from student transcripts from the past four years to determine what patterns of grades in early classes were indicative of future success. The resulting statistics and visualizations showed that students generally did better in the first class than subsequent classes, suggesting that C grades in the first class might indicate difficulty. We also examined students enrolled in the pre-capstone software engineering course. The analysis showed that no graduating CS major had received a C in both first two programming courses. We examined the data to be sure that the proposal would not diminish the participation of members of underrepresented groups disproportionately. As a result, the CS faculty approved a change in prerequisite for the third course to require that student receive an A or a B in at least one of the first two courses. GPA data was also analyzed and found to be a poor predictor of success in computer science, demonstrating that our previous approach to limiting enrollment was inferior. This new approach has advantages over the previous GPA-based plan, but enrollment management plans risk making college harder for at risk students to succeed in CS. The biggest limitation of this plan is that it is expected to make only a small change in CS enrollment.

Roughly one in eleven engineering faculty members in the United States are full-time and are not in tenure-track positions. It has been established that non-tenure track faculty members can enrich an engineering program by bringing industry skills and practical career experience into the classroom. These full-time non-tenure track faculty members have varied experience and they have varied career goals. Some of them may desire tenure-track positions while others may not. In many engineering programs, there is no clear path for a full-time non-tenure-track faculty member to attain tenure. This study consists of interviews with ten full-time non-tenure-track electrical engineering faculty members who teach in eight large, public, research universities. The survey will explore the career goals of those faculty members including the desire for an electrical engineering tenure-track position as well as which aspects of a tenure-track position would be desirable, such as career stability, participation in departmental governance, and a greater voice in program decisions. We will also explore aspects of seeking a tenure-track position that may not be desirable, such as the increased workload involved in research and publishing, or a perceived necessity to teach fewer courses as more effort and time is given to research. This study consists of interviews with ten full-time non-tenure-track electrical engineering faculty members who teach in eight large, public, research universities. The survey will explore the career goals of those faculty members including the desire for an electrical engineering tenure-track position as well as which aspects of a tenure-track position would be desirable, such as career stability, participation in departmental governance, and a greater voice in program decisions. We will also explore aspects of seeking a tenure-track position that may not be desirable, such as the increased workload involved in research and publishing, or a perceived necessity to teach fewer courses as more effort and time is given to research.

Engineering Competition Teams (ECT) recruit and integrate new members every year. We interviewed groups of students at two national and international competitions about the methods they use to recruit and retain students, in an effort to understand why ECT have low participation of students from underrepresented groups. None of the teams that were interviewed were especially diverse, in spite of our efforts to interview diverse students. We categorized their recruitment activities into strategies that require direct person interaction with a degree of personal invitation (active) and those that do not (passive) using a theoretical framework provided by Cegler [1]. Not all passive recruiting is done in ways that completely avoid personal interaction. Thus, for ECT, Cegler's passive category was separated into two categories: direct and indirect recruiting. Teams generally had more numerous recruiting strategies than integration strategies. We analyzed integration strategies using the theoretical framework of legitimate peripheral participation [2]. We found that while a handful of teams were using strategies that could fit into this theoretical framework, most were making critical mistakes including trying to integrate too many students and failing to allow new recruits to work at meaningful projects. The paper concludes with recommendations for recruiting and integration practices that may improve team diversity.

The ACM/IEEE CS2013 Curriculum provides a somewhat rigid identification of topics to be covered by a model computer science curriculum. It was developed with significant input from industry, educators and other stakeholders and represents best practices in terms of Computer Science education. ABET is the accreditation body accrediting computer science programs in the US, and it also accredits a number of international programs. ABET's goal is to allow programs to identify their own outcomes and measure their success in delivering programs that achieve this, while also ensuring that all students receive a solid core education including key areas of the discipline without being excessively prescriptive. Both documents address excellence in computer science education. Changes to the Computer Science program criteria are being recommended which will more closely align the two documents in terms of identifying key areas to be covered by programs. This session provides participants with the opportunity to hear about the proposed changes and the rationale behind them and to offer feedback and input into the process.

Student, experiential-learning, engineering, competition teams (SELECT) provide an opportunity for engineering students to practice engineering technical and professional skills. The low representation of women in SELECT is often rationalized as a lack of interest by individual women rather than systemic processes that discourage or exclude women. We employ a qualitative-interpretive design and a cultural constructionist lens to bring into focus the interplay of individual interests, understandings of appropriate gender roles, and structural elements that contribute to a culture of inclusion or exclusion. Primary data consist of 90-minute semi-structured interviews of eight team members and one non-member. By interpreting the narrative portraits of two female students, we show the construction of a team culture where in general women are discouraged from participation based on stereotyped gender roles, by night campus attitudes, and by peers who challenge or ignore their skills, contributions, and interests. One woman persevered through the male-dominated culture because she received the encouragement and support of male peers who engaged as comrades and champions. This paper offers recommendations for institutions to demonstrate commitment to equitable access to experiential learning and to nurture student peer cultures that challenge historic gendered ideologies and rhetoric.

Inspired by research that indicates that direct competition is not always comfortable for female students, we redesigned an existing class competition to permit students to choose whether they wished to participate in either direct or indirect competition. We pilot tested it in the Spring of 2013 in a undergraduate/graduate class on introductory artificial intelligence at the University of Oklahoma. Although the results for female students are inconclusive due to their small number, we observed that international students embraced the indirect competitions. This suggests that allowing the option of indirect competition may also appeal other groups of students who can be marginalized in engineering. Our results indicate the international students prefer the less risky option of indirect competition.

The software industry needs our graduates to have significant and meaningful experiences with teamwork. A new design has been developed for a teamwork exercise based on peer code review. This design uses the three Ss of building assignments for cooperative learning: Same problem, Specific choices, and Simultaneous report. Students perform peer code review individually, and within and between stable small groups. The code can be sanitized student work or may be altered by the instructor to meet specific course learning objectives. The review is done in three phases. First, individuals answer yes or no to questions that evaluate the quality of the design and code. Then each group answers the same set of questions. When the groups have completed their evaluation, the class joins together to reveal and discuss the answers. This design was successfully implemented during the 2003-2004 academic year in an introductory programming class. This design is applicable to more advanced classes with significant programming assignments. Future work includes extending this structure to give students experience with other software engineering artifacts early in their academic careers.

An algorithm is described which performs curvilinear grouping of image edge elements for detecting object boundaries. The method works by generating hypotheses and selecting the best one. A neighborhood definition based on Delaunay graph is used to keep the number of generated hypotheses small. An energy minimizing curve is fit to the generated hypotheses to evaluate the grouping and locate discontinuities.>