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
promotion. The tenure andpromotion process in academia is complex and challenging, particularly for Black women, whoface unique structural and institutional barriers throughout the process related to race, gender,and intersectionality [1]-[3]. Throughout this journey, many Black women experiencemicroaggressions from faculty and students, invalidation of their research, and a devaluation oftheir service contributions. Thus, coaching has evolved into a proactive tool for career andleadership development and has gained momentum in both institutional settings, such asAAC&U’s Project Kaleidoscope’s STEM Leadership Institute and Office of UndergraduateSTEM Education’s Center for the Advancement of STEM Leaders. Coaching is designed toempower and
they would face in ensuring they have a computerable to run the software they may need to complete their research project within the program.Alongside technical skill-building, the participants are also supported to develop communicationskills such as presenting and science writing, and are provided with peer mentors who help shareimplicit hidden curriculum knowledge. A goal of the program is to also boost students'confidence and sense of belonging within engineering, as both are key factors in the persistencein students pursuing engineering studies [1]. A program capacity for two students annuallyensures robust funding and individualized support for the participants, including post-programcareer support by program staff. To date, all eight
., Virtual Community of Practice email listserv through the American Societyof Engineering Education). The research team found a large portion of participants wererecruited through snowball sampling, specifically snowball recruiting from local oSTEMorganizations at institutions across the U.S.The research team collected participant interest and demographic information through an interestsurvey that asked participants to self-identify their gender, race/ethnicity, geographic location,work setting, current employment and career stage. They specified their work setting as (1)academia or education, (2) nonprofit, (3) industry, (4) government or military, (5) none of theabove or (6) fill in the blank other. The team collected in-depth information on
graduate students to obtainadditional student perspectives on this approach and gauge its wider applicability. Thisinterdisciplinary Graduate Translational Engineering Research approach provides an example ofusing social science research methods in the early stages of graduate engineering research toenhance both graduate research and training in value creation through research.Keywords: Technology transition, translation engineering, value creation, adaptation of technology, lab tomarket transition, graduate engineering research, research proposal, user research, workshop1. IntroductionToday, embracing science, technology, engineering and innovation is considered an importantstrategy for socioeconomic growth and well-being around the world [1], [2
[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
trends of its integration into industrytools seeking to enhance productivity. In doing so, it also contributes meaningfully to theirprofessional development.Keywords: AI in Education, In-class Coding Assistance, Student Engagement, Real-timeFeedback, Enhanced Learning,IntroductionThe rapid advancement of technology has reshaped how education is delivered, with artificialintelligence playing an increasingly pivotal role. One such AI-driven innovation is ChatGPT 4.0,a sophisticated language model developed by OpenAI. Since its debut in November 2022 [1], thistool has been widely utilized in academic settings, significantly impacting various fields of study.Its evolution reflects a broader trend in AI, where intelligent systems are
defining individual students as “rural” based on geographical location is insufficient to account for variances in their interest in computer science careers and their own self-identity as someone who could be a computer scientist. We use this information to inform future research and propose new avenues for engaging “rural” students in computer science.1 IntroductionThe Computer Science For All Initiative [1] set a goal of “offering every student the hands-oncomputer science and math classes that make them job ready on day one” [2]. Previousresearch has shown that rural students have less access and less participation in computerscience education than their urban peers [3]. In fact, approximately one in five students inthe
been employed to screen resumes and identify the best candidates.While this may streamline recruitment, it has also led to instances of bias, where certaindemographic groups are unfairly excluded or prioritized. These biases often stem from historicaldata used to train the models, which may reflect existing inequalities in the workforce. Suchoutcomes not only raise ethical concerns but also risk violating anti-discrimination laws.Addressing these issues requires developing algorithms that account for fairness and biasmitigation, alongside rigorous testing and transparency in how decisions are made. Without suchmeasures, machine learning risks reinforcing systemic inequalities rather than promotinginclusivity and diversity in the workplace. 1
of complex fluids. Within engineering education, his research interests lie in mapping Industry 5.0 to Education 5.0, curriculum design, pedagogical strategies for innovation, enriching and empowering the student learning experience at Higher Education Institutes (HEIs). ©American Society for Engineering Education, 2025 Chemical Process Design to meet Industry 5.0 competencies. Daniela Galatro1 and Sourojeet Chakraborty2 1 Department of Chemical Engineering & Applied Chemistry, University of Toronto ON M5S 3E5 Canada 2 Department of Chemical & Biomolecular Engineering, Johns Hopkins University, Baltimore MD 21218 USA
considered under “Black, Latine, and Multi-racial”group. We assigned the non-Hispanic White and non-Hispanic Asian students to the “White andAsian” group. The non-first-generation students had at least one parent completing a collegeeducation, a bachelor’s degree, or any postgraduate degree (Master’s/Ph.D.). Out of the 20 participants, 6 students were sophomores, 13 students were juniors, and 1 was asenior student. In terms of demographic background, the distribution was as follows: 40% women(N=8), 60% men (N=12), 50% Black, Latine, and Multi-racial (N=10), 50% White and Asian(N=10), 15% first-generation (N=3), and 85% non-first-generation (N=17).Survey The undergraduate students enrolled in the Cell Biology for Engineers course were invited
incrementally and with support. In the context ofmodern education, the integration of technology into scaffolded learning presents bothopportunities and challenges. Kim and Hannafin emphasize the necessity of combiningscaffolded learning with technology-enhanced environments, highlighting various forms ofenhanced learning and identifying potential issues where scaffolding can be effectively applied[1], [9].This synergy between technology and scaffolding not only enriches the learning experience butalso addresses diverse learning needs, making education more accessible and engaging forstudents. Moreover, the importance of a student-centered approach in higher education cannot beoverstated. Hannafin and Land argue that such an approach accommodates the