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1. Developing an Introductory Computer Science Course for Pre-service Teachers

   Adler, Rachel F ; Beck, Kristan ( January 2020 , Journal of technology and teacher education)

   Computational thinking (CT) involves breaking a problem into smaller components and solving it using algorithmic thinking and abstraction. CT is no longer exclusively for computer scientists but for everyone. While CT does not necessarily require programming, learning programming to enhance CT skills at a young age can help shape the next generation of children with knowledge that can help them succeed in our technological world. In order to produce teachers who are able to incorporate programming and CT into their future classrooms, we created an introductory Computer Science course (CS0) targeting future K-8 STEM teachers yet open to any student to enroll and learn computer science. We used a mixed-methods approach, examining both quantitative and qualitative data based on self-reported surveys, classroom artifacts, and focus groups from four semesters of data. We found that after taking the course, students’ self-efficacy in CT increased and while education students initially had lower confidence in their computing abilities than computer science students in the course, by the end of the semester there were no differences in their perceived and actual coding abilities when compared with computer science students. Furthermore, education students had many ideas on how to incorporate similar projects into their own future classrooms. 

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2. An Introductory Aeronautics Course for Pre-Engineering Students to Understand How Drones (Flying Robots) Work

   He, S. ( June 2023 , The 130th ASEE Annual Conference and Exposition, June 25-28, 2023, Baltimore, MD)

   Robotics has emerged as one of the most popular subjects in STEM (Science, Technology, Engineering, and Mathematics) education for students in elementary, middle, and high schools, providing them with an opportunity to gain knowledge of engineering and technology. In recent years, flying robots (or drones) have also gained popularity as teaching tool to impart the fundamentals of computer programming to high school students. However, despite completing the programming course, students may still lack an understanding of the working principle of drones. This paper proposes an approach to teach students the basic principles of drone aeronautics through laboratory programming. This course was designed by professors from Vaughn College of Aeronautics and Technology for high school students who work on after-school and weekend programs during the school year or summer. In early 2021, the college applied for and was approved to offer a certificate program in UAS (Unmanned Aerial Systems) Designs, Applications, and Operations to college students by the Education Department of New York State. Later that year, the college also received a grant from the Federal Aviation Administration (FAA) to provide tuition-free early higher education for high school students, allowing them to complete the majority of the credits in the UAS certificate program while still enrolled in high school. The program aims to equip students with the hands-on skills necessary for successful careers as versatile engineers and technicians. Most of the courses in the certificate program are introductory or application-oriented, such as Introduction to Drones, Drone Law, Part 107 License, or Fundamentals of Land Surveying and Photogrammetry. However, one of the courses, Introduction to Drone Aeronautics, is more focused on the theory of drone flight and control. Organizing the lectures and laboratory of the course for high school students who are interested in pursuing the certificate can be a challenge. To create the Introduction to Drone Aeronautics course, a variety of school courses and online resources were examined. After careful consideration, the Robolink Co-drone [1] was chosen as the experimental platform for students to study drone flight, and control and stabilize a drone. However, developing a set of comprehensible lectures proved to be a difficult task. Based on the requirements of the certificate program, the lectures were designed to cover the following topics: (a) an overview of fundamentals of drone flight principles, including the forces acting on a drone such as lift, weight, drag, and thrust, as well as the selection of on-board components and trade-offs for proper payload and force balance; (b) an introduction to the proportional-integral-directive (PID) controller and its role in stabilizing a drone and reducing steady-state errors; (c) an explanation of the forces acting on a drone in different coordinates, along with coordinate transformations; and (d) an opportunity for students to examine the dynamic model of a 3D quadcopter with control parameters, but do not require them to derive the 3D drone dynamic equations. In the future, the course can be improved to cater to the diverse learning needs of the students. More interactive and accessible tools can be developed to help different types of students understand drone aeronautics. For instance, some students may prefer to apply mathematical skills to derive results, while others may find it easier to comprehend the stable flight of a drone by visualizing the continuous changes in forces and balances resulting from the control of DC motor speeds. Despite the differences in students’ mathematical abilities, the course has helped high school students appreciate that mathematics is a powerful tool for solving complex problems in the real world, rather than just a subject of abstract numbers. 

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3. Undergraduate Summer Research in High-performance Computing with Engineering Applications: An Experience Report

   Hou D., Liu Y. ( June 2020 , 2020 American Society for Engineering Education (ASEE) Virtual Annual Conference)

   null (Ed.)

   High Performance Computing (HPC) stands at the forefront of engineering innovation. With affordable and advanced HPC resources more readily accessible than ever before, computational simulation of complex physical phenomena becomes an increasingly attractive strategy to predict the physical behavior of diverse engineered systems. Furthermore, novel applications of HPC in engineering are highly interdisciplinary, requiring advanced skills in mathematical modeling, algorithm development as well as programming skills for parallel, distributed and concurrent architectures and environments. This and other possible reasons have created a shortage of qualified workforce to conduct the much-needed research and development in these areas. This paper describes our experience with mentoring a cohort of ten high achieving undergraduate students in Summer 2019 to conduct engineering HPC research for ten weeks in X University. Our mentoring activity was informed and motivated by an initial informal study with the goal to learn the roles and status of HPC in engineering research and what can be improved to make more effective use of it. Through a combination of email surveys, in-person interviews, and a manual analysis of faculty research profiles in X University, we learn several lessons. First, a large proportion of the engineering faculty conducts research that is highly mathematical and computational and driven by disciplinary sciences, where simulation and HPC are widely needed as solutions. Second, due to the lack of resources to provide the necessary training in software development to their students, the interviewed engineering groups are limited in their ability to fully leveraging HPC capability in their research. Therefore, novel pathways for training and educating engineering researchers in HPC software development must be explored in order to further advance the engineering research capability in HPC. With a multi-year support from NSF, our summer research mentoring activities were able to accommodate ten high-achieving undergraduate students recruited from across the USA and their faculty mentors on the theme of HPC applications in engineering research. We describe the processes of students recruitment and selection, training and engagement, research mentoring, and professional development for the students. Best practices and lessons learned are identified and summarized based on our own observations and the evaluation conducted by an independent evaluator. In particular, improvements are being planned so as to deliver a more wholistic and rigorous research experience for future cohorts. 

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4. Lived Experiences of African American Engineering Students at a PWI Through the Lens of Navigational Capital

   Damas, S. ; Benson, L. ( February 2022 , 2022 CoNECD (Collaborative Network for Engineering & Computing Diversity))

   There are significant disparities between the conferring of science, technology, engineering, and mathematics (STEM) bachelor’s degrees to minoritized groups and the number of STEM faculty that represent minoritized groups at four-year predominantly White institutions (PWIs). Studies show that as of 2019, African American faculty at PWIs have increased by only 2.3% in the last 20 years. This study explores the ways in which this imbalance affects minoritized students in engineering majors. Our research objective is to describe the ways in which African American students navigate their way to success in an engineering program at a PWI where the minoritized faculty representation is less than 10%. In this study, we define success as completion of an undergraduate degree and matriculation into a Ph.D. program. Research shows that African American students struggle with feeling like the “outsider within” in graduate programs and that the engineering culture can permeate from undergraduate to graduate programs. We address our research objective by conducting interviews using navigational capital as our theoretical framework, which can be defined as resilience, academic invulnerability, and skills. These three concepts come together to denote the journey of an individual as they achieve success in an environment not created with them in mind. Navigational capital has been applied in education contexts to study minoritized groups, and specifically in engineering education to study the persistence of students of color. Research on navigational capital often focuses on how participants acquire resources from others. There is a limited focus on the experience of the student as the individual agent exercising their own navigational capital. Drawing from and adapting the framework of navigational capital, this study provides rich descriptions of the lived experiences of African American students in an engineering program at a PWI as they navigated their way to academic success in a system that was not designed with them in mind. This pilot study took place at a research-intensive, land grant PWI in the southeastern United States. We recruited two students who identify as African American and are in the first year of their Ph.D. program in an engineering major. Our interview protocol was adapted from a related study about student motivation, identity, and sense of belonging in engineering. After transcribing interviews with these participants, we began our qualitative analysis with a priori coding, drawing from the framework of navigational capital, to identify the experiences, connections, involvement, and resources the participants tapped into as they maneuvered their way to success in an undergraduate engineering program at a PWI. To identify other aspects of the participants’ experiences that were not reflected in that framework, we also used open coding. The results showed that the participants tapped into their navigational capital when they used experiences, connections, involvement, and resources to be resilient, academically invulnerable, and skillful. They learned from experiences (theirs or others’), capitalized on their connections, positioned themselves through involvement, and used their resources to achieve success in their engineering program. The participants identified their experiences, connections, and involvement. For example, one participant who came from a blended family (African American and White) drew from the experiences she had with her blended family. Her experiences helped her to understand the cultures of Black and White people. She was able to turn that into a skill to connect with others at her PWI. The point at which she took her familial experiences to use as a skill to maneuver her way to success at a PWI was an example of her navigational capital. Another participant capitalized on his connections to develop academic invulnerability. He was able to build his connections by making meaningful relationships with his classmates. He knew the importance of having reliable people to be there for him when he encountered a topic he did not understand. He cultivated an environment through relationships with classmates that set him up to achieve academic invulnerability in his classes. The participants spoke least about how they used their resources. The few mentions of resources were not distinct enough to make any substantial connection to the factors that denote navigational capital. The participants spoke explicitly about the PWI culture in their engineering department. From open coding, we identified the theme that participants did not expect to have role models in their major that looked like them and went into their undergraduate experience with the understanding that they will be the distinct minority in their classes. They did not make notable mention of how a lack of minority faculty affected their success. Upon acceptance, they took on the challenge of being a racial minority in exchange for a well-recognized degree they felt would have more value compared to engineering programs at other universities. They identified ways they maneuvered around their expectation that they would not have representative role models through their use of navigational capital. Integrating knowledge from the framework of navigational capital and its existing applications in engineering and education allows us the opportunity to learn from African American students that have succeeded in engineering programs with low minority faculty representation. The future directions of this work are to outline strategies that could enhance the path of minoritized engineering students towards success and to lay a foundation for understanding the use of navigational capital by minoritized students in engineering at PWIs. Students at PWIs can benefit from understanding their own navigational capital to help them identify ways to successfully navigate educational institutions. Students’ awareness of their capacity to maintain high levels of achievement, their connections to networks that facilitate navigation, and their ability to draw from experiences to enhance resilience provide them with the agency to unleash the invisible factors of their potential to be innovators in their collegiate and work environments. 

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5. Impact of a Modeling Intervention in an Introductory Programming Course

   Rodgers, Kelsey J. ; McNeil, Jaqi C. ; Verleger, Matthew A. ; Marbouti, Farshid ( June 2019 , American Society for Engineering Education (ASEE) 126th Annual Conference and Exposition)

   This complete research paper describes the impact of a modeling intervention on first-year engineering students’ modeling skills in an introductory computer programming course. Five sections of the first-year engineering introductory programming course at a private, STEM+Business institution were revised to center around modeling concepts. These five sections made up the experimental group for this study. The comparison group consisted of four sections of the course that were not revised. Students in all these sections were given two different versions of a modeling problem two times in the semester to test their progress in gaining modeling skills. Each version required two submissions – a written solution and a coded solution. The assessment of these four submissions based on the three established dimensions of modeling were quantitatively analyzed in this study. The three dimensions within mathematical modeling that were the focus of this study were mathematical model complexity, modifiability, and reusability. Mathematical model complexity is being able to address the complexity of the problem. Modifiability addresses the generalizability of the model solution. Reusability is showing an understanding of the problem and the user. Statistical analysis showed that students in the experimental group had more gains in their demonstrated modeling abilities across all three dimensions than the students in the comparison group. This study demonstrated that intentional and explicit instructional strategies targeting model development resulted in greater gains in students’ demonstrated modeling skills and both their written and coded solutions to a complex modeling problem. 

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