in the Department of Civil, Environmental, and Architectural Engineering (CEAE) and Director of the Integrated Design Engineering (IDE) program. The IDE program hosts a BS degree in IDE accredited by the ABET EAC under the general criteria and a new PhD degree in Engineering Education. Bielefeldt is a Fellow of the ASEE and a licensed P.E. in Colorado. ©American Society for Engineering Education, 2024 The Paint Bucket Model of Dis/ability in STEM Higher Education: Axioms 1-3AbstractDis/ability is a complex, evolving, and nuanced concept. Recognizing the absence of a cleardefinition of dis/ability, the first author proposed a “paint bucket dis/ability
Paper ID #42929Rosie’s Walk: A Culturally Responsive Computational Thinking PK-1 Challenge(Resource Exchange)Tiffany DavisNea SannDr. Mia Dubosarsky, Worcester Polytechnic Institute Dr. Mia Dubosarsky has been a science and STEM educator for more than 20 years. Her experience includes founding and managing a science enrichment enterprise, developing informal science curriculum for young children, supporting Native American teachers in the development of culturally responsive science and math lessons, developing and teaching graduate level courses on assessment in science education, and working with thousands of educators
,including gender, race/ethnicity, and sexual orientation [1], considered within the context ofengineering doctoral education. Drawing on organizational climate research and intersectionalitytheory, the project aims to use a student-centered approach to shed light on the specificorganizational climate present in doctoral engineering department by engaging with studentsfrom diverse groups. We aim to answer three research questions: 1. What focused climates arepresent in doctoral engineering departments? 2. How do climate perceptions differ byintersecting social categories? 3. How do climate perceptions relate to organizationalcommitment to degree completion? For this project, we intend to reintroduce organizational climate science into
Paper ID #42470Board 1: Empowering Underrepresented Minority Students in One AviationProgram: Integrating a National Airport Design Competition into the CurriculumDr. Yilin Feng, California State University, Los Angeles Yilin Feng is an assistant professor at California State University, Los Angeles. She received her Ph.D. degree from Purdue University. Her research interest is in airport simulation, operation, and management. ©American Society for Engineering Education, 2024 Empowering Underrepresented Minority Students in One Aviation Program
Paper ID #41098Race to R1: An Analysis of Historically Black Colleges or Universities (HBCUs)Potential to Reach Research 1 Carnegie Classification® (R1) StatusDr. Trina L. Fletcher, Florida International University Dr. Trina Fletcher is an Assistant Professor of Engineering and Computing Education at Florida International University and the founder of m3i Journey, a start-up focused on research-based, personalized, holistic, innovative, relevant, and engaging (PHIRE) financial literacy education. She serves as the Director of the READi Lab (readilab.com) where her research portfolio consists of equity, access, and inclusion
Paper ID #40700Using a Summer Bridge Program to Develop a Situational JudgmentInventory: From Year 1 to Year 2Ms. Malini Josiam, Virginia Tech Department of Engineering Education Malini Josiam is a Ph.D. candidate in Engineering Education and a M.S. student in Civil Engineering at Virginia Tech. She has a B.S. in Mechanical Engineering from UT Austin (2021). Her research interests include improving equity in engineering and sustainability.Dr. Walter C. Lee, Virginia Polytechnic Institute and State University Dr. Walter Lee is an associate professor in the Department of Engineering Education and the director for research at
, demographic surveys, and three tasks. Descriptive statistics and statistical tests provide insights.Performance discrepancies between IT and non-IT backgrounds are statistically significant. Feedback indicatespositive perceptions of low code. 1. Introduction In recent years, the intersection of technology and education has undergone a profound transformation, withemerging paradigms reshaping traditional approaches to teaching and learning. One such paradigm that hasgarnered increasing attention is low-code development—a revolutionary approach to software creation thatempowers individuals, regardless of their technical background, to design and deploy fully functional applicationswith minimal coding expertise. Low-code platforms provide
, have emerged as critical platforms for fostering creativity, problem-solving, andentrepreneurial skills among engineering students. These events not only provide participantswith opportunities to apply their technical knowledge and collaborative abilities but also exposethem to real-world challenges that mirror those faced by professionals [1]. A recent study alsofound that ICPs improved students self-awareness and open mindedness [2]. However, despitetheir potential benefits, ICPs are often accompanied by significant barriers that may hinder thebroad participation of all student groups, especially underrepresented students in STEM.Addressing these barriers is crucial for creating inclusive and effective learning environmentsthat address the
four-bar mechanism often involves multiple objectives and constraints, such asminimizing mechanical stress while maximizing motion efficiency or achieving a specificmotion trajectory. ML algorithms, particularly optimization techniques like Genetic Algorithms(GA), along with more advanced AI methods such as deep learning, can automate and improvethis process by efficiently searching through a large space of design possibilities. [1, 2, 3] GAsmimic natural selection processes, evolving better designs through iterations. In four-barmechanism synthesis, GAs can optimize the estimation of parameters related to link lengths andjoint positions to achieve desired motion profiles (e.g., coupler curve shape or motion path)without manually solving
learning, and data visualization [1]. Thisintegration is crucial for handling the increasing complexity and size of data sets in chemicalengineering research and practice [2]. Data science has particularly impacted molecular sciencein chemical engineering, with applications in molecular discovery and property optimization [3].The development of a cyberinfrastructure for data-driven design and exploration of chemicalspace further underscores the potential of data science in transforming chemical research [4].The alignment of data analytics and strategy is transforming the chemical industry, with dataplaying a crucial role in production, research, marketing, and customer service strategies [5]. Theuse of big data and analytics in chemical
thisstudy is crucial in understanding how these advanced techniques are applied to real-world data.The dataset employed in this study comprises a rich and diverse collection of student data from 30different universities. This data set includes several covariates or variables integral to understand-ing the educational landscape and student outcomes.3.1 Data DescriptionThe dataset features a range of variables designed to capture the multifaceted nature of studentexperiences and outcomes across various universities. These variables include: 1. Program Complexity: This is a discrete variable reflecting the complexity of each program that students attend at a given university. The complexity metric could encompass factors like the
students to learn about real-world problemsthat can be solved by engineering design [1] – [5]. These programs are variable depending on theresources of the University: some programs have developed summer internships to provide aclinical immersion experience, while others have sought to bring the immersion during a moreconventional classroom setting [6]. Literature has reported that these programs which provideeffective immersion experiences result in an increase in students’ self-reported knowledge andskills, in addition to general confidence. These experiences often extend beyond needsidentification, as students connect with potential users and witness the community impact. It alsocreates room for interdisciplinary involvement, such as the
individual, empowerment”(Ladson-Billings, 1995, p. 160). Critical consciousness is the third tenet of Ladson-Billings’s(1995) CRP extends “a student’s efficacy in identifying STEM norms and practices that formvisible and invisible exclusionary barriers in STEM programs and STEM fields” (Castaneda,2019, p. 1). Unlike Freire’s initial focus on developing the critical consciousness of men,Ladson-Billings (1995) focused on students, specifically their challenging the status quo. Theseworks have facilitated the development of more contemporary frameworks for measuring andengaging in critical consciousness, especially in K-12 student development and research.Three Elements of Critical Consciousness Other contemporary formulations of critical
students working onsoftware development projects?ParticipantsDuring Fall 2022, all participants went through a competitive application process to ensure themost productive learning environment. A total of 107 students applied to participate and 33students were interviewed. In the end, ten upper-level students majoring in computer sciencewere selected for the program (as shown in Table 1), and each student received a $2,500fellowship to lessen financial burdens. A technology company provided student fellowships.Students were required to participate during Spring 2023 (16 weeks) and commit approximately8-10 hours a week. Student teams were mentored by two faculty members to ensure that studentsreceived a quality learning experience.Table 1
typically include some level of personal finance rangingfrom loans and savings up to complexities of investing for retirement, insurance, social security,stocks and bonds, and annuities. Class testing has demonstrated that students have a keen interestin personal finance examples [1].In earlier work [2] and again here, we assert that with the opportunity to teach engineeringeconomy students about retirement planning comes with the responsibility to do so. Engineerswho fail to plan and invest for retirement will face additional challenges when it comes to theethical challenges of engineering practice.This paper is an introductory case study of how FICA taxes and social security benefits can bedetermined and linked together to calculate an internal
learning, team-projects and writing-based assignments, with special focus on learning through real-world applications ©American Society for Engineering Education, 2024 Creation of Open-Source Course Materials for Engineering Economics Course with Help from a Team of Students - Lessons Learned Tamara R. Etmannski Assistant Professor of Teaching, Department of Civil Engineering, The University of British Columbia, Vancouver, BC, Canada tamara.etmannski@ubc.ca1. IntroductionIn accordance with program accreditation prerequisites [1], engineering students across Canadaare mandated to undertake an Engineering
both the new and/orthe old curriculum were asked to rank their academic experience including factors such as coursecontent, workload, stress, engineering identity, graduate attributes, and more. This paper willoutline and discuss the process that was undertaken to evaluate, design, consult, implement, andnow re-evaluate multi-year curriculum changes, including a continual improvement process.MotivationAs software systems and related technologies have become increasingly complex, the demandsplaced on software engineering education have grown [1, 2]. Current priorities in softwareengineering pedagogy include experiential learning and alignment with modern, industry-relevant practices to solve problems [1, 2, 3]. Like many institutions, the
27.8% oftotal graduates, even though members of these groups account for almost 35% of all collegestudents [1], [2]. Although all these percentages are higher than they were in 2012, there is still along road to travel before full equity in these fields is reached.Inclusivity in InstructionInclusivity can be defined as “an intentional practice of recognizing and working to mitigatebiases that lead to marginalization or exclusion of some people” [3]. Students’ social identitiesdo have effects on how they learn and whether they stay the course in their major throughgraduation [4]. Unfortunately, many students from backgrounds underrepresented in STEM canfeel alone or unwelcomed and eventually change their major to one where they believe they
engineeringeducation by establishing innovation infrastructures [1]. These initiatives focus on enhancingstudents' innovation competencies, as summarized in the framework researched in [2], whichcomprises skills such as problem-solving, design thinking, creativity, project management,prototyping, teamwork, and leadership, etc. One effective pedagogical approach in this regard ischallenge-based learning (CBL) [3], which engages students in the identification, analysis, design,and implementation of solutions to open-ended sociotechnical problems [4]. CBL is inherentlymultidisciplinary, drawing on diverse perspectives and skills required in product development [5]and design thinking [6]. In complement to the traditionally theoretical richness of
broaden and strengthen the pipeline of graduates, thereby contributing positively tothe challenge of developing a diverse and robust industry workforce.Keywords: Aviation Education, Collegiate Aviation, Aviation Maintenance, Professional FlightTechnology, Aviation Management, MentorshipIntroduction The lack of all forms of diversity in the aviation and aerospace industry is a concern formany stakeholders. The marginal representation of women in various aviation and aerospacecareers has been addressed in previous studies [1], [2], [3]. Women are underrepresented acrossall levels of aviation careers starting from young female aviators in collegiate programs and atthe C-Suite level where women represent only 6% of airline chief executive
performancebased on the coefficient of determination R2 value (0.94) revealed that the model demonstratesgood performance in predicting the bulk modulus of the perovskite materials used during thepractical sections. The survey results after the teaching and practical sessions indicate that thelearning modules are an effective introduction for novice engineering students in this domainand raise awareness of the importance of this important sub-section of AI.Keywords: Engineering Education; Artificial Intelligence; Machine Learning; Perovskites;Materials Science 1. IntroductionMachine learning (ML) is a subfield of artificial intelligence (AI) that has been effectivelyapplied in various problem domains such as computer vision [1], speech recognition [2
instructors.We add the voices of these instructors to the literature on how science, engineering, andtechnology college instructors are selecting resources. We discuss what engineering and otherSTEM librarians can do to increase resources from diverse perspectives, OER, and other OAresources used in these courses, which may make the coursework more accessible to additionalstudents.IntroductionMany college courses require students to use a textbook [1] or other instructional materials (IM),and the selection of these is a key component for the design of college courses [2]. Some coursesmay rely on committees to select core IM, and some pre-professional curricula may be quiteprescribed, while other course instructors may have the discretion to select
. Theoretical FoundationInformed Career PlanningCareer decision making can be either informed or uninformed. Uninformed career planning isfairly passive and dictated by chance or circumstance, while informed decision making requiresindividuals to take an active role in the process of selecting a future occupation [1]. Withinformed career planning, individuals consciously explore their personal characteristics, therewards that they may accrue through their occupation, and the environmental variables that mayinfluence their experience in the workplace [1].Theory of Value-based Career Decision MakingThe Theory of Value-based Career Decision Making is an approach to informed career planning.This theory states that each person has a unique set of core
CompetencyAbstractComputing systems face diverse and substantial cybersecurity threats. To mitigate thesecybersecurity threats while developing software, engineers need to be competent in the skill ofthreat modeling. In industry and academia, there are many frameworks for teaching threatmodeling, but our analysis of these frameworks suggests that (1) these approaches tend to befocused on component-level analysis rather than educating students to reason holistically about asystem’s cybersecurity, and (2) there is no rubric for assessing a student’s threat modelingcompetency. To address these concerns, we propose using systems thinking in conjunction withpopular and industry-standard threat modeling frameworks like STRIDE for teaching andassessing threat modeling
underscores thesignificance of case-based learning in instilling ethical principles and critical thinking skills infuture engineers, ultimately contributing to the cultivation of responsible professionals in thefield.IntroductionIncorporating ethics into engineering education, particularly in senior design courses, has been atopic of interest and research, for example [1]-[6]. The Accreditation Board for Engineering andTechnology (ABET) requires that all accredited engineering programs must ensure theirgraduates possess the capacity to identify ethical and professional obligations in engineeringscenarios and make well-informed decisions. These decisions must consider the consequences ofengineering solutions in global, economic, environmental, and
SkillsetsIntroductionAcross the United States, biomedical engineering (BME) undergraduate programs havedeliberately designed curricula with a broad and diverse scope [1], [2]. This intentional approachaffords students the ability to pursue a wide array of career paths upon completing their education;however, programs have faced criticism for their efficacy in adequately preparing students forcareers in the field of biomedical engineering (BME) [3], [4]. Stakeholders (i.e., employers) in thebiomedical field have reported BME graduates’ expertise and technical skills to be limited,compared to other engineering majors. Importantly, recent efforts have been made to determinethe professional and technical skills that stakeholders in the biomedical field deem required
time the course is completed, therefore it is becoming imperative that we leverage the 0 This material is based upon work supported by the National Science Foundation under Grant No. 2022299latest advances in neuroscience that highlight the need to focus on building new neuron inter-connects via experiential learning design to form an Integral Engineer[7].The educational sector is currently facing several significant challenges. These include : 1)the implementation of remote labs [1], 2) the need for skills specific to the semiconductorworkforce [9], and 3) the development of soft skills that are crucial for succeeding in today’sjob market [14][27].This paper sets out with a clear and focused objective: to use 21st-century tools such
engage in these processes as part of mathematicalmodeling, and how this approach can be useful for providing future recommendations forcurricula and learning outcomes alignment in engineering education.IntroductionThe challenges of the 21st century require students to engage in activities that enable them to“learn the importance of such decisions as what to measure, what to keep constant, and how toselect or construct data collection instruments” [1, p. 58]. This activities are especially critical forengineering students because engineers are required to develop measurement processes duringthe mathematical modeling of designs [2]. Despite the significance of developing measurementprocesses in engineering education, ABET student learning outcomes
, which are all vital in their respective fields.IntroductionThe Professional Science Master's (PSM) degree arose in the late 1990s to fill a gap betweenoverqualified PhDs and underprepared undergraduates in science fields [1]. PSM programsprovide graduate-level science training plus professional skills valued by employers [2]. Theadvantages of PSM degrees include career preparation, practical experience, high employability,networking opportunities, specialized knowledge, and lower cost versus a PhD. The PSM alignswith best practices proposed for master's degrees by higher education organizations [3], [4], [5].MTSU's PSM program (MSPS degree) meets the requirements for formal PSM affiliation [6].The interdisciplinary MSPS integrates science and
discussed the changes that would make them feel more welcome and includedwithin academia and their department(s) (cultural and/or infrastructural changes). They alsoprovided advice and recommendations to future queer and trans graduate students. The panelreceived overwhelmingly positive feedback, and the audience expressed their willingness andenthusiasm to learn and support queer and trans graduate students. Overall, the lessons learnedfrom the Queer and Trans Graduate Students Panel are as follows: 1) Provided an opportunity to inform about the specific obstacles that many queer and trans students experience in graduate education. 2) Contributed to the knowledge of designing, facilitating, and conducting a student experiences