decade. The production rate, stable at just under 2boats per year for the past 15 years, is projected to exceed 5 boats annually by 2030 due togeopolitical uncertainty. This growth will necessitate a substantial increase in the submarineindustrial base (SIB) workforce, with 15,000 annual new hires through 2032 [1]-[5]. Theseexpansion efforts have driven considerable investment in developing a STEM-literate navalworkforce pipeline in regions of high SIB density. This need is demonstrated in effortspioneered in southern New England, developing new pedagogies for K-12 outreach and teachersupport programs [6], [7].This transitory period “could lead to a period of heightened operational strain for the SSN force,and perhaps a period of weakened
, 2025 Incorporating the Envision Rating System as a Teaching Tool for Sustainability in Civil Engineering InfrastructureAbstractThe Institute for Sustainable Infrastructure’s Envision Rating System [1] is becoming a widelyused framework for guiding design work and assessing resiliency, social equity, andenvironmental justice of civil infrastructure projects. To prepare our students and equip themwith the knowledge base to proactively utilize this framework as a design tool, we haveincorporated the Envision Rating System as a teaching tool with several touchpoints in therequired civil engineering curriculum. Envision is introduced in a required sustainable civilengineering course, examined in an engineering mechanics
valuable experience and confidence that may positively influence theirfuture success as engineers.INTRODUCTIONThe scientific community has increasingly prioritized efforts to diversify Science, Technology,Engineering, and Mathematics (STEM) fields, driving investigations into strategies to promoteequity. Despite minor progress, studies have consistently reported a significantunderrepresentation of women, minorities, and persons with disabilities in engineering,particularly among individuals earning graduate degrees [1, 2]. This disparity has been attributedto a perceived lack of connection to the engineering community and limited access to researchopportunities, both of which contribute to feelings of isolation [3]. Students experiencing
. Contextualizedapproaches, including around sustainability, have potential to improve learning outcomes and to prepare graduates toaddress grand challenges. [1]Elkington’s Triple Bottom Line [4], [5]). Grasping these three dimensions and theirinterrelationships is a key outcome of the minor.However, beyond the three pillars, it is well accepted that a core element of sustainabilitythinking, mindset, or competency is systems thinking [6], [7], [8], [9]. Moreover, a basicunderstanding of sustainability must include a scientifically literate conceptualization of theunderlying earth systems and the corresponding natural biogeochemical cycles that govern theflow of energy and matter through these systems, as a baseline from which to understand thehuman impacts that
investigate two primary research questions: 1.What are mechanical engineering students’ perceptions on engineering and mechanicalengineering? and 2. How do these perceptions change after completing their first internship?We interviewed 12 mechanical engineering students who were completing their first engineeringinternship. These students varied in levels of program completion from students who completedtheir first semester of their second year of studies in Spring 2024 to students who had completedtheir second semester of their third year of studies in Spring 2024. These students wereinterviewed both at the beginning of their internship and upon completion of their internship. Weasked them to define engineer, engineering, mechanical engineer, and
Variation in Incentive Techniques Affect AttendanceAbstractLecture attendance in engineering classes is critical for improving grades, developing afundamental understanding of material, and bettering social bonds [1], [2]. Late-afternoon Fridaylectures often experience a decrease in attendance and this decrease can have negative effects onstudent success [3]. Therefore, the primary objective of this work was to increase Fridayattendance in a senior level, required Mechanical Engineering (ME) class. This was done byintroducing a Friday lecture schedule that had three rotating incentives on Fridays: in-personquizzes with a lecture, in-person group work/homework sessions and a lecture, and asynchronous, Zoom lecture (not in-person). Attendance data
personal abilities (Ownership), define cleargoals and actionable steps (Wisdom), habitually advance toward these goals while reflecting onprogress (Execution), and self-regulate while accessing supportive resources (Resilience) [19].Building on insights from the pilot program that the developers completed, the following are thekey features of the POWER platform: 1. Non-Directive Coaching: Facilitates self-discovery by asking questions rather than giving direct advice, encouraging students to take control of their learning and decisions. 2. Personalized Interactions: Customizes conversations per student, providing guidance that aligns with each individual's unique situation and goals. 3. Goal Setting and Tracking: Aids
operating systems courses in a meaningful way. Ourpedagogical approach and selected assignments are presented, demonstrating tools to scaffold CSstudents to develop hardware-based skills and create an experiential learning environment. Positivestudent learning outcomes were observed, and a retrospective survey quantifies knowledge gainedin full stack development. Recommendations are provided for future IoT courses, highlighting thevalue of experiential learning and interdisciplinary integration to develop well-rounded computerscience professionals.1 IntroductionInternet of Things (IoT) has continued to gain importance in many industries. IoT applicationsare present in many vital sectors such as government, healthcare, energy, transportation
participants collaborate with graduate studentmentors, engage in discussions with faculty members engaged in digital health research, explorereal datasets, and create grade-appropriate lesson plans. This paper focuses on the overallprogram design and the experiences of an elementary STEM teacher who participated in theprogram and implemented the lesson with her students. Literature ReviewArtificial Intelligence (AI) and Machine Learning (ML) in Elementary Curriculum The integration of AI and ML into elementary education is an emerging area of interestthat has the potential to equip young learners with foundational skills critical for the future [1].As technology continues to evolve, it is becoming
that address these purposes. We aredeveloping mixed reality circuits labs to augment laboratory and classroom instruction ofconcepts critical to understanding electrical circuit theory and circuit implementation withthe expectation of improving student outcomes in learning circuit theory and in buildingactual circuits. Four labs were developed to address deficiencies students deal with inlearning circuits: 1) Bread-Board Basics and Series Circuits, 2) Parallel Circuits, 3)Series/Parallel Circuits, and 4) Superposition and Thevenin and Norton’s Theorems. Priorto deployment, development of the MR lab software platform was necessary as was testingand troubleshooting. This article discusses the development process, critical paths andunanticipated
; it supports anengineering system that avoids questioning its privileged position in society. Epistemic injustice fromengineering pushes to create an epistemic hierarchy where the different ways of knowing are rankedaccording to their value (Kramer, 2022) (Figure 1). In other words, engineering, through the engineers,seeks to preserve its position in society, creating beliefs and practices that maintain other ways ofknowing outside its boundaries. In that sense, those ways of knowing that are not aligned withengineering’s priorities, beliefs, and values fall into the “others” category. They are also judged for theirvalue to society. This hierarchy is also evidenced in education and academia, where othering is embodiedin subjects, areas
enhance learning. Due to the variation in the participant experience,we created two video versions on the same topic. Version 1 relies on traditional PowerPoint-styleslides with text and audio for a more conventional learning experience. Version 2 embedsrecorded videos and relevant images to enhance visual comprehension. This study aims toevaluate these two video versions and identify which version serves the basic purposes of clarity,usefulness, and relevance for students. The following research question guides this study: Whichvideo version demonstrates greater clarity, usefulness, and relevance in explaining key energy-saving concepts? The data were collected from 7 participants using a post-survey after eachvideo. The survey consisted of
engagement after using sequentiallive coding. Also, the descriptive statistics indicate that students who participated had improvedengagement in all aspects except cognitive engagement. The study's results highlight thatstudents' engagement mostly declines in conceptually hard courses like programming. However,students who participated in sequential live coding had higher engagement with the course thanthose who didn't participate. The study's results warrant creating learning environments thatfoster engagement to improve student's learning outcomes.IntroductionUndergraduate students generally find computer programming concepts difficult to learn [1], [2]often due to a lack of an appropriate learning environment [4], few opportunities to
tosustainable development, inclusive of social, environmental, and economic aspects for currentand future generations [1]. Outside of engineering, the Education for Sustainability movementhas long emphasized the importance of both cognitive and affective outcomes, but its applicationin engineering has been limited. In a study grounded in the Diffusion of Innovation theory, teninnovators and early adopters of educating mechanical engineering students in the U.S. andCanada about sustainability were interviewed about their experiences and practices. Although theindividuals were not directly asked to discuss emotions, this emerged as an important theme inmany of the responses to the questions about lessons learned in education for sustainability
texts that discuss engineering ethics – [1], [2], [3] are someexamples. To set reasonable boundaries on this broad topic this paper adopts several constraints.First, we address one specific call in the request for proposals: “define or deliberate the meaningof ‘public welfare’ and ‘common good’ in engineering degree programs.” This framing firstlimits the scope to the education of engineering students within degree programs. Limiting thescope to education excludes impact outside degree programs. Engineering education is highlyintersectional with other aspects of human existence such as politics and governance, technologyimpacting on how people live their lives, and the economy and quality of life in the developedand developing world; a very
value creation, telling a personal story,and using strong communication tools such as voice projection, eye contact, and clear, concisestatements to emphasize their purpose as a student at Western New England University. Theinstructors focused on the importance of practicing and working towards speaking naturally andfluently about themselves in a professional manner.Students were given a 1-page pitch worksheet to outline their pitch (Appendix A) and timeoutside of class to draft their first pitch script. In the following class, they presented to anindividual classmate and received feedback on pitch story/theme, communication style andnoticeable things to improve the quality of the pitch. After receiving peer feedback, studentsmade a <3
students to comprehend complexconcepts, new resources were also made available. Previous studies have demonstrated theefficacy of virtual reality in providing opportunities for student participation [1]. California StatePolytechnic University Pomona has invested in state-of-the-art Virtual Reality (VR) laboratoryfor thermal fluids. This project explores the efficacy of an enhancement, the incorporation of anArtificial Intelligence (AI) assistant. The AI was created so it can assist students in bridging gapsbetween theoretical understandings and engineering practice, while also expanding access to awider range of students. In practice, we are evaluating for student performance, studentunderstanding, and student experience.Recent data from 2020-2023
study, but also discuss ABET,Engineers Australia, and other international frameworks. As required by all accreditationsystems, all surveyed engineering programs included sustainability education as part of the core,required curriculum. However, we find that departmental culture and discipline-specificperceptions may play a larger role than accreditation requirements in shaping and promotingsustainability education. As a result, curricula (and student experience) varies significantlybetween programs and between universities. We further discuss existing challenges faced bystudents and instructors in this context, and how these challenges relate to accreditation.1 IntroductionIt is difficult to overstate the effects of unsustainable human
activities.A key objective of this adaptation is to prepare students for a future where AI-generated solutionsmay surpass even the best human abilities. However, a skill that remains irreplaceable is theability to critically assess the correctness of solutions—whether human or AI-generated. Thispaper presents findings in the form of student reflections on this modern adaptation ofcomparative analysis.1 IntroductionAeroelasticity is a field in aerospace engineering combining aerodynamics and structuralmechanics to understand the interaction between aerodynamic forces and structural responses. Atthe University of Colorado Boulder, a sophomore-level Aerospace Sciences Lab introducesstudents to these concepts through an experiential learning framework
bottlenecks, andevaluate the impact of course dependencies and prerequisites on student progression and success.This tool also evaluates each course in the curriculum in terms of blocking factor (a measure towhich that course acts as a gateway to later coursework), delay factor (the length of the longestpathway involving a given course), centrality (a measure of how many prerequisites the courseinvolves as well as how many courses involve the target as a prerequisite), and structuralcomplexity (the impact of the course on student progression). The complexity metric is thenaggregated by term and across the program.The mapping of the revised curriculum is depicted in Figure 1. The numerical values for eachcourse are the complexity metric as calculated
engineering education research, which most recently has focused on incorporating authentic engineering educational experiences through engineering history education and open-ended modeling problems designed to initiate the productive beginnings of engineering judgement and engineering identity. ©American Society for Engineering Education, 2025 Perceptions of Undergraduate Mechanical Engineering Students Regarding the True Nature of Engineering PracticeIntroduction Historical data suggests that only about one in two students initially enrolled in anengineering program at an institution of higher learning will finish that degree program withinfour to six years [1]. For most engineering
and aware of the potentialchallenges when this tool is applied.While work introduced here shows promise in addressing the gap that engineering studentsmay experience between their academic preparation and upcoming workplace expectations, amore rigorous course design and thorough assessment are needed for future iterations. Thisarticle seeks to share the work-in-progress with conference audiences to gather constructivefeedback. Study Historical Cases, Learn Today’s Tools, and Prepare for the Future A. IntroductionSince the public release of ChatGPT in 2022, the AI space has been growing exponentially andreceived enormous attention from all sectors of society [1-3]. The rapid adoption [1, 2] of suchdisruptive tools [3] by the industry
, suggesting that shorter,focused content enhances memory retention and helps maintain attention on specific learningtasks [20]. A systematic review and meta-analysis [11] demonstrated that microlearningsignificantly improves academic performance in higher education compared to traditional macro-learning approaches [1]. The study attributes this improvement to reduced cognitive load,flexible learning environments, promotion of ‘self-directed learning, and timely feedback.The widespread popularity of platforms such as YouTube and TikTok underscores theeffectiveness of delivering bite-sized content, reflecting a growing preference for concise andaccessible information dissemination. TikTok, in particular, has been studied within theframework of
application of AI to education. ©American Society for Engineering Education, 2025 WIP: Efficacy of Connecting Engineering and Calculus through AI Problem Generation1. IntroductionCalculus courses have long served as gatekeepers to STEM fields, presenting significantchallenges to students and contributing to high rates of attrition in engineering programs [1], [2].Despite being foundational, these courses often fail to connect abstract mathematical concepts totheir practical applications in engineering, leaving students disengaged and unprepared for real-world problem-solving [3]. This disconnect has been identified as a barrier to retention, withmany students citing calculus as a primary reason for abandoning STEM
undergraduates approached contextual factors during problem-scoping, a critical partof the design process, was studied by Kilgore et al [1]. Other studies have characterizedengineering students’ design processes with regard to the breadth of problem-scoping andconsideration of the design context. Some research studies uncovered differences in the breadthof problem-scoping exhibited by “novice” student engineers and “expert” designers, who aretypically advanced professionals with significant work experience. Christiaans and Dorst [2]found that novices solicited less information and exhibited less extensive problem-scoping,compared with expert designers. Additional studies include analyzing undergraduate studentproblem-scoping activity across academic
Peirce Starling (Leyf Starling) is a founding faculty member and current Director of the First Year Engineering Center at the University of Virginia. She is currently developing curriculum and teaching the Foundations of Engineering 1 and 2 courses as well as advising 1st year engineering students. Starling earned a BS in Mechanical Engineering (UVA ’03); enhanced that with a MAT in Special Education-General Curriculum (University of North Carolina- Charlotte ’07); and she has taught math, science, engineering, and robotics for over 20 years in both public and private middle schools, high schools, and universities. Her goal and passion is to make engineering accessible at all levels and across disciplines. Starling
in a First- Year Engineering CourseIntroductionRetention of undergraduate engineering students has been of significant concern at manyuniversities as the percentage of students who begin in engineering programs and successfullycomplete their degree has remained stagnant at approximately 50% for the past several decades[1]. Retention of first- and second-year students is a particularly pressing issue; these studentstypically have the largest drop-out rates from STEM majors [2]. Several authors have attemptedto understand why students leave engineering and other STEM programs and have found that alack of belonging in engineering [3], academic reasons [3], and a lack of connection and qualityrelationships with peers and
, and ODEs.By leveraging modern computational tools such as Julia, Large Language Models(LLMs), and Wolfram Alpha Pro, the course shifts the focus from tedious handcalculations to conceptual mastery and real-world application. Three engineeringprojects reinforce this approach: (1) numerically integrating drone IMU accelerationdata to estimate velocity and position while correcting acceleration bias, (2)optimizing motion through gradient descent and equality constraints in applicationssuch as basketball trajectories and gymnast posture, and (3) modeling and designingcontrollers for a planar BallBot using state-variable models andLaplace-transform-based feedback control. Student evaluations indicate strong engagement: 85% of students reported
building; it is about understanding how pastinnovations, challenges, and failures have shaped the world we live in today. From theconstruction of ancient aqueducts to the development of cutting-edge technologies, engineeringhas always been deeply intertwined with human history, culture, and society. However, inengineering education, the rich history of mathematicians, scientists and engineers who madesignificant contributions which greatly improved human beings’ lives are often overlooked.Some researchers recognized these issues and worked on integrating historical content intoengineering education [1-7]. Godoy [4] presents the development and application of an on-linemodule to learn historical perspectives in relation to an engineering topic. The
training session are tailored according to the outcomes of acomprehensive questionnaire that explores knowledge of the basics of sustainable circularengineering design and the circular pedagogical methodology used. Of special significance is thestudents’ interest shown after this short training in learning the more advanced engineeringcourses that will equip them to apply their technical knowledge to technology developmentsdesigned towards a better world, not only for future generations but also for the present.IntroductionThe paradigms of sustainability and the circular economy (CE) are creating new constraints onthe design and development of products for everyday use [1],[2],[3]. The circular economypromotes a restorative and regenerative system