engineering: A recent review of the educationliterature on mathematical practices in engineering found that only 2 out of 5,466 even discuss"uncertainty" or "error" [1]. A scoping review of textbooks actively used to teach engineeringcourses found that only 11% of textbooks mentioned "variability" [2]. Despite this neglect,variability remains important to engineering practice; for example, female automobilepassengers in the U.S. experience 47% higher odds of injury than males [3], a disparity that theGovernment Accountability Office attributes to poor statistical modeling practices in crashtesting [4].This project is a mixed-methods study of statistical thinking, informed by engineering practice.The early (qualitative) phases of this project
accreditation requirements for major engineering designexperience. The paper will also share data from the surveys of students and faculty mentors fromboth countries and recommendations for such collaboration in the future.IntroductionIn recent years, international collaborations in engineering education have become increasinglycommon, as they offer opportunities for cross-cultural exchange and global problem-solving.Several studies have emphasized the significance of such collaborations, highlighting the benefitsof diverse perspectives in tackling complex engineering challenges [1]. These partnerships oftenpromote cultural competency, teamwork across borders, and a broader understanding of globalengineering practices [1]. However, they are also
hours. Thus, instructors are able to utilize their time and effort to update lecture content,develop novel assessments, and devise active learning strategies to make the classroom moreengaging.Literature ReviewThe idea of automatic grading itself is not new. Publications from the 1960s discuss the use ofautomatic grading for programming assignments to manage growing class sizes [1-2]. Sincethen, many automatic grading tools have been introduced for various purposes including, but notlimited to, programming assignments [3-7]. Autograders have the potential to increase studentmotivation [8-9], enhance teaching and tutoring sessions [9-10], and improve student perceptionof the course [9]. However, developing autograders can be challenging since
to turn down orders due to a lack of available skilled workers atall levels (according to Verein Deutscher Ingenieure [1]).Unfortunately, these analyses have almost forgotten about the sociological conditions as decisionfactors for students, as Pfennig [2] states. Fislake [3] and Heine [4] add that these developmentsare merely a result of the cumulative effect of individual decisions. As a result, despite interest,talent, and a positive self-image of expected technical skills, there is a lack of enthusiasm for STEMcareers and studies.To address the problem, policymakers, business, academia and civil society are attempting toaddress the STEM skills gap through a variety of activities to promote sustained interest intechnical careers and to
critical exercises where students compare different platforms to determine suitabilityfor specific tasks, promoting a discussion on data ethics, privacy, and academic honesty. Topromote further implications for practice, the study showcases opportunities for reflection, bothas individual users and in groups through using Socratic Dialogue, as faculty and students testthe limitations of different platforms and address the ethics of using GenAI in a world thatincreasingly blurs the lines pertaining to Cyberethics.Keywords: Generative AI, Pedagogical Innovation, AI Usability Spectrum, Bloom’s RevisedTaxonomy, CyberethicsBackgroundWhen ChatGPT was released on November 30, 2022, it amassed a historic one million users inits first five days [1], with
Wear Balancing and Approximation for Efficient Non-Volatile Main Memory Management Rowena Quinn1 , Sherrene Bogle1 , and Marjan Asadinia2 1 Department of Computer Science, California State Polytechnic University, Humboldt, USA, Rowena.Quinn@humboldt.edu, Sherrene.Bogle@humboldt.edu 2 Department of Computer Science, California State University, Northridge, USA, marjan.asadinia@csun.edu Abstract Phase Change Memory (PCM) is an emerging non-volatile memory technology that lever- ages the thermal properties of chalcogenide glass to transition between amorphous and crys
by ASEE in 2024 suggests that the way collegiate engineeringeducation programs currently employ mathematics coursework is inherently problematic andrecommends that educators no longer allow the sequential calculus courses required by mostengineering programs to serve as a weed-out series for students interested in engineering [1].Instead, it recommends that “every motivated student [should] have a path to success, increasingthe number and diversity of students earning engineering degrees by removing math as anartificial barrier to the engineering career [1].” This ideology is supported by its notion that muchof the content of upper-level math courses required for an engineering degree is not needed bypeople who practice engineering after
; threshold concepts; undergraduate education; cognitiveapprenticeship model; STEM computational toolsIntroductionHow students learn and how to facilitate this process are long-standing questions in education ingeneral. Efforts to develop formal pedagogical frameworks to identify specific roadblocks andaddress them are prevalent in engineering education research. Some strategies that have shownincreased performance in engineering students include cooperative learning, active learningclassrooms, flipped-courses, and interactive assignments [1]. Some of these strategies are easier toimplement in the context of engineering courses, while others require more intentional design toaccomplish the desired learning outcomes of a given course.Chemical
students at academic institutions. Space is required formentorship that supports students emotionally. Findings and implications are discussed further.IntroductionMentorship has long been considered one of the cornerstones of personal and professionaldevelopment, from the arts to the sciences [1]. Within higher education, mentorship can be bothformal and informal in nature, encompassing everything from faculty-student relationships andworkplace mentoring programs to familial or peer connections. These relationships provideemotional support, practical guidance, and role modeling that influence growth and success [2].By addressing the diverse needs of mentees, mentorship serves as a critical tool to navigatechallenges, cultivate resilience, and
and career choicesamong students.Introduction Globally, there is a trend of students preferring computer-related majors within theSTEM fields, with enrollment rates surpassing those seen during the dot-com bubble of the late1990s [1, 2]. Furthermore, in East Asia, particularly in South Korea, the intense focus oneducation has led to an increasing number of students opting to study abroad due todissatisfaction with the domestic educational environment [3]. Alongside this trend, weconducted research to understand the background of Korean students’ decisions to studycomputer-related fields in the U.S. as well as their academic experiences after making thosechoices [4]. This qualitative case study explored how various factors, including
uprooted to a totally new place. Majority of the engineering students taketheir discipline specific courses starting from sophomore year and experience heightenedchallenges because of the transition from foundational courses to more rigorous, disciplinespecific courses [1]. This is considered as the time when they often reevaluate their majorsbecause of the academic stress among other reasons [2]. Literature shows that student retention and success remain critical challenges in highereducation, particularly among underrepresented and first-generation college students [3]. Severalstudies have highlighted the importance of class groups or support groups in the academicperformance of students. [4] reported that collaborative learning in small
paper, we analyzeinterviews with instructors and student partners (SPAs) to explore the effects of thesepartnerships in STEM classes at a large research-focused public institution. The study aims toanswer the following research questions: (1) How do STEM instructor teaching practices changerelated to working with a student partner? (2) What effects does serving as a student partnerhave on students in a large research-focused STEM institution?Literature ReviewReviewing the existing literature to understand the significance of student-faculty partnerships inenhancing teaching and learning is essential, as it provides a foundation for developinginnovative approaches that can improve educational outcomes. This review aligns with thepaper’s
, we share the design aims and lessons learned from delivering the workshop tofurther the discussions on generative AI among faculty through an interdisciplinary, collaborativelens – in doing so, we identify two primary themes among our participants' perspectives ongenerative AI that are relevant to our future work: 1) a need for generative AI curriculumintegration and skill development and 2) a need for more exploration of its ethical and socialimplications.Structure of the WorkshopOur workshop explored four interconnected themes, thoughtfully chosen to promote a holisticand interdisciplinary understanding of generative AI and its societal impact. Drawing from ourexpertise in communication, philosophy, computer science, and engineering
, CriticalThinking, and Problem-Solving. This course is offered every semester in large blended face-to-face/online sections to an annual total of 1060 students. After teaching the course for 11 semesters, weidentified several challenges with the data literacy assignments: 1. The assignments did not have students create data visualizations, an important element of communicating about data. 2. The assignments had too many elements, resulting in students focusing on formulaic assignment elements while avoiding doing the critical thinking to make arguments with data. 3. Assignments developed to address the diversity of student backgrounds and experiences were not engaging to students and often required them to research and
influenced their design processes and outcomes. The findingsinform how the SET can support engineering instructors in incorporating socially engaged designprinciples along with traditional engineering content in their courses.Study DesignParticipants and ContextFour SET modules were implemented in a two-semester capstone mechanical engineeringcapstone design course at a large Western university designated as a minority-serving institution.Students were divided into 7 teams to work on engineering projects (3 industry-sponsored, 3community-sponsored, and 1 student-led) and each team was composed of 4-5 students. Allstudents were required to complete the SET modules and reflection prompts. Of the 32 studentsenrolled in the course, 27 students consented
engineering education [1] and tofoster increased motivation during problem-solving tasks [2]. Understanding the nature of the problem is a critical first step in the process, providing the foundation for all subsequent efforts. Without a solid understanding of the problem, students cannot develop effective strategies to address it [3]. Students are encouraged to focus on relevant tasks and create significant connections between newly acquired information and their prior understanding of the task [4]. The accuracy of the solution in engineering problem-solving heavily depends on students’ capability to actively monitor and assess their involvement in the problem. The process of monitoring and evaluation constitutes a crucial aspect of self-regulation
. Traditional educationoveremphasizes theory while neglecting interdisciplinary connections, limiting students’ability to solve complex multi-physical field problems. Students often find courseworkdisengaging and disconnected from practice, affecting their interest and career outlook. Game-based learning (GBL) is gaining attention as an innovative approach ingeotechnical education [1]. This approach transforms complex engineering concepts intointuitive, interactive, and fun learning processes through task-driven gamified experiences.Our educational platform, MERGE, provides a virtual environment for geothermal pile 1design, covering site investigation, lab testing, numerical simulation, and structural
for skilled professionals in computing and emerging technology (EmTech) isincreasing at an accelerated rate. Between 2019 and 2029, computer and information technologyoccupations are projected to grow by 11%, surpassing other fields [1]. In Miami-Dade County,EmTech job opportunities are anticipated to grow by 7.3% over the next decade, exceeding thenational average [2]. However, a gap in skilled professionals remains, as county data indicatesthat 50% of EmTech roles require a bachelor's degree and 12% require a master's degree [3].Along these trends, the COVID-19 pandemic has increased economic disparities, with manyAmericans facing job insecurity or permanent layoffs, disproportionately affectingunderrepresented communities. [4]. With
metacognitive in their work refinements. This studycontributes to the growing body of literature on Generative AI in education, particularly inproviding scalable, timely, and relevant formative feedback on technical writing assessments.I. IntroductionIn problem/project-based instructional models, students are often required to demonstratetheir knowledge and skills through written reports and essays. These assignments are crucialfor developing students’ ability to convincingly communicate the evidence to support theirclaims. Dannels et al. [1] emphasize that students proficient in technical writing are betterprepared for the engineering profession’s demands. However, students tend to prioritizetechnical aspects of projects over writing quality, often
methodologies, weexplore how these practices equip faculty and institutional leaders to critique existing inequities,imagine transformative futures, and sustain long-term commitment to DEIJ work even amidincreasing resistance.FrameworkWe leverage research that shows that communities of transformation (CoT) are an importantlever for equipping faculty to make substantial changes to their beliefs and practices [1], [2].CoTs drive systematic change using collective learning and a shared vision. CoTs aredistinguished from other communities in that they are guided by a philosophy that typicallychallenges commonplace norms; they engage members in new practices through modeling; andthey provide relational support for members, often across institutions [1
University of Texas at Austin. ©American Society for Engineering Education, 2025IUSE: Research on Generative Design Thinking: Design Cognition, Tools, and EducationIntroduction and MotivationA paradigm shift has occurred in engineering design which drastically changes the role of thehuman designer by adding generative artificial intelligence (AI) algorithms (e.g., geneticalgorithms, variational autoencoders, generative adversarial networks, large language models) tothe Traditional Design (TD) process [1] – [3]. A key feature of design problems is that thevariables and constraints of the design space are initially unknown to the designer, i.e., theseproblems are “ill-defined” [4]. Thus, one
activities, andwas encouraged under the program to provide mutual support and assistance to each other. In thispaper, we set forth the goals for the cohort activities, discuss the success of the year one cohortactivities, and indicate what additional benefits the cohort provided that were not planned in thegrant proposal. Recommendations are provided for other institutions that may want to formsimilar cohorts, under this program or others.IntroductionThe concept of a “cohort” is well-established, with mention of cohorts of various types appearingin literature for quite some time. One such mention by Rosow, as far back as 1978 [1], discussedthe nature and purpose of cohorts in a broad sense. Cohorts can emerge naturally, as noted in [2],or they may
.-granting institution in California and twoCalifornia Community Colleges designed to support low-income, academically talentedengineering and computer science students.In ENGAGE, we utilize a Strengths-Based Approach (SBA) to support student success in bothtraining and professional development, and in program design and implementation. SBA utilizesGallup’s CliftonStrengths assessment to identify the strengths that students bring to theireducational journeys. Research by Gallup shows that the integration of CliftonStrengths has ademonstrated correlation with student retention and well-being [1]. Rooted in positivepsychology [2, 3] CliftonStrengths is an online assessment that identifies individuals’ top five“Themes of Talent,” organized in four
developed as part of the work supportedby this grant.IntroductionStudent experience related to working with and designing Internet of Things (IoT) as well as AIcapable products and applications continues to be relevant to those studying and graduating inengineering related fields. Many commercial systems have added IoT and/or AI functionality inthe last few years as the cost of processors, sensors, memory and cloud-based analytics and storageservices continue to be relatively affordable. In this project, lab exercise materials were developedat two HSIs, Texas A&M University-Kingsville and Texas A&M University-Corpus Christi, tointroduce students to IoT concepts utilizing a Raspberry Pi [1]. with sensors and a motor as wellas exercises using
teachers (PETs) followed a structured process to model four phenomena: 1. Observations and Hypothesis: PETs observed a phenomenon, created drawings of their observations and initial hypotheses, reflected on questions, and developed a driving question for the unit. 2. Collaborative Sensemaking: In groups, PETs used whiteboards to represent their understanding, refine their ideas, and discuss scientific concepts
colleagues, and used affective computing and biometrics to better understand how software developers do their work.Paige Rodeghero, Clemson University ©American Society for Engineering Education, 2025 Collaboration Station: Opening up Single-User Software Projects — I-Test & CSforAllAbstractThe need for collaborative software is more significant than ever in our modern world. Especiallyin large software companies, it becomes imperative to work efficiently with co-workers tocomplete large projects. Consider that nearly seven percent of Americans between ages six andeleven have been diagnosed with neurodivergency [1]. Some of these individuals will end upbecoming
need for biomedicalengineers is expected to increase substantially from the current 19,700 biomedical engineersreported to be employed in the United States as of 2023 [1]. The growth of this field warrants theattention of not only industry employers, but institutional BME departments at the undergraduatelevel to equip students with the specific skills and tools needed to be successful in professionalpractice. Inspired by this ongoing issue to prepare the future generation of BME students, and theexploration of the many factors that contribute to the development of a successful engineer, thisWIP focuses on the significance of metacognitive skills in preparing students. This exploratoryqualitative WIP seeks to explore how students currently make
[1]. Sustainable energy sources have steadily increased in usage, butdevelopment and adoption of sustainable technologies is still far behind necessary levels to meetemission reduction goals by 2050 [2],[3]. In addition to developing and using sustainabletechnologies, reducing energy consumption has been discussed as an opportunity to decreasereliance on non-renewable sources and emissions. Engineers are typically at the forefront of thesetechnological developments, indicating that the next generation of sustainable energy technologywill need sustainability and energy literate engineers. While sustainability literacy has expandedwithin engineering domains [4]-[7], energy literacy is understudied in engineering. However, fortechnological
numbers of studentswith anxiety, depression, and other limitations to mental health and wellness (MHW) [1], [2].Despite the growing frequency and awareness of MHW issues for students, few instructors aretrained to address these problems in the classroom [3], [4], [5]. Resources from universitycounseling centers [6] typically focus on acute crisis management and do not address morechronic issues. For example, requesting “wellness checks” from first responders (frequently lawenforcement officers) may not be appropriate for a disengaged student who fails to attend classor submit assignments. Such students are still clearly struggling with personal problems. Facultycannot and should not take on additional roles as counselors or therapists. However
practices and support efforts to create more inclusive and equitable environments forfinancially disadvantaged students. The findings will guide future research and initiatives aimedat reducing institutional barriers and fostering the success and retention of low-SES students inengineering.IntroductionEngineering is often hailed as a pathway to innovation and social mobility, yet its accessibilityremains unevenly distributed, shaped by enduring systemic inequities. Wide-scale barriers rootedin social, cultural, and economic disparities have long shaped the field, disproportionatelymarginalizing women, racial and ethnic minorities, and many other underrepresented groups. [1].Despite efforts to diversify the engineering workforce, these populations