approximates a lifestyle with an equal split of time invested at work, and time outside ofwork. Work-Life-Fit is focused on the individual and the company. Work-Life-Fit might be bestsummarized as 1) When People Work, 2) Where People Work, and 3) How Much People Work[1]. While there might be an assumption that Work-Life-Fit is only focused on reducing thehours an employee works, it is more focused on how to leverage the hours that an employeewants to work.Employees frequently receive emails outside of regular work hours [2]. Anecdotally, the authorssent an email mid-afternoon on a Saturday to four working individuals. All four had respondedwithin an hour. This is representative of the new normal. If so, and we are all working outsidethe traditional
unsuitable [1].The DBR approach attempts to interlink the development of innovative solutions for practicaleducational problems with the acquisition of scientific knowledge [2] and follows a cyclicaland iterative process in which design, testing, analysis and redesign continuously build oneach other. On the one hand, this increases the quality of innovations in teaching and learningresearch and, on the other hand, relevant findings are gained for the specific field of practice[3]. The core idea of DBR is that learning situations are not investigated in isolated laboratoryenvironments, but in real situations [4]. The objectives pursued are always twofold: on theone hand, relevant problems from educational practice are to be solved and, on the other
efforts focusing on possible future work.IntroductionUtilization of 3D scanning in engineering education is becoming common [1], [2] with thedigitalization of reverse engineering practices as a part of companies’ digital transformationefforts, and some applications like custom human product development areas such as orthoticsand prosthetics are already employing 3D scanning in full extent [3]. This paper focuses onteaching engineering students non-industrial uses of 3D scanning, especially preservation of artand historical artifacts.Recent decades witnessed development of 2D flat bed scanners allowing us to digitize historicaldocuments, books, and even paintings, making these works available to the masses. But as thesedevices became common in our
Learning Framework portion of the paperThe theoretical frameworks of Behaviorism [1] and Cognitivism [2] support that learning is bestachieved when supplemented with activity [3]. Behaviorism indicates that when studentsperform a behavior, they learn that topic on a deeper level. For example, consider a class incollege that you felt was the most useful. Most of the time, that class had a lot of examples andpractice in class in which you could apply the material. Cognitivism allows students to apply thetopics through open-ended assignments like case studies or group discussions to better learn thetopic [4]. By applying the concepts directly in activities in class, students
measurementinstruments and exploring the long-term effects of hybrid instructional models. Keywords: Engineering Education, LCDLMs (Low-Cost Desktop Learning Modules), Virtual Learning, Hands-On Learning, ICAP Framework (Interactive, Constructive, Active, Passive)INTRODUCTIONEngineering education has long emphasized the importance of interactive, hands-on learningactivities to foster deep understanding and practical skill acquisition [2,6,7, 18]. Traditionallecture formats, while still prevalent, often lack the level of engagement and experientialrelevance that can be achieved through well-designed, low-cost, and easily deployable teachingtools [1, 3, 5, 6,17, 21]. In particular, Low-Cost Desktop Learning Modules (LCDLMs) haveemerged as promising instructional
(SDGs) [1]. Yet traditional engineering education often prioritizestechnical rigor over creative problem-solving, leaving graduates underprepared for open-ended,real-world challenges [2,3]. Studies reveal a troubling trend: senior engineering students generatefewer innovative solutions than first-year peers, signaling a decline in creative capacity as educationprogresses [4,5]. Industry leaders increasingly stress that engineers must complement technicalskills with creative agility to address unstructured problems [6].Creativity is particularly pertinent to engineering design and problem-solving as it enablesengineers to rethink problems, question assumptions, and explore unconventional solutions. Inengineering, creative thinking goes beyond
progress made in implementing FYE2.0 to date and discusses plans for the future.1.0 BackgroundFirst-year engineering programs (FYE) are a common way for students to be introduced to theengineering profession. [1]. FYE programs typically include one or two introductory courses on avariety of topics. The content of FYE courses can include any combination of topics such as design,communication, professional skills (e.g., teamwork, leadership), and engineering specifictechnology/tools (e.g., MATLAB, CAD) [2]. Fostering interactions between first-year studentsand faculty/upper division engineering students have been shown to aid in the retention ofengineering students. The goals of FYE programs are typically: • Provide FYE students with
collaborative cloud storage(Microsoft OneDrive and Google Drive) have transformed how engineers model and share theirwork [1, 2]. Digital tools offer enhanced capabilities, including 3D modeling, simulation, andreal-time collaboration, which are now integrated into many professional workflows. Research highlights the value of digital notebooks in education, emphasizing their abilityto provide students with interactive, hands-on learning experiences that extend traditionaldocumentation methods [3]. These tools also foster critical thinking and iterative design byallowing students to incorporate advanced features such as real-time feedback and collaborativeediting [2].Benefits and Limitations of Digital and Physical Notebooks Both physical
the deviceaccess to a heat gun and standard shop-vac or any other vacuum cleaner is required. Manyschool theatre departments or woodshops, as well as janitorial staff, often already have access toshop-vacs. A common $20 heat gun will suffice. Finaly, the consumable material for this projectis recycled milk jug plastic, which comes at no cost to the school. Current research published atASEE conferences with vacuum forming has been mostly focused on using vacuum forming tocreate an experiment or experience but little on making the vacuum form itself [1-5].2. Vacuum Forming2.1 The Process of Vacuum FormingVacuum forming is a process in which a thin sheet of plastic is heated to a temperature just belowits melting point, in which it becomes
assisting doctors in delicate surgeries.Thus coining the new 4Ds (Dull, Dirty, Dangerous, and Dear) of Robotics [1]. Robotics presents a versatile educational launchpad for STEM education because of itsinterdisciplinary nature. Starting with the LEGO Mindstorms launched in 1993 [2] , Roboticswas quickly absorbed into STEM education and soon became a member of the classrooms andhomes by the early 2000s. Robotics competitions like FIRST and FLL and other informaleducation avenues also helped kick off engagements in robotics for the youth [3], [4].Interestingly, all these interventions focused on the educators’ intentions of using robotics as atool to teach and nurture students’ interest in STEM, however, the students remained silent
industry experience to her academic roles. She has a proven track record of addressing critical environmental challenges. In her recent endeavors, Dr. Worthy is actively collaborating with the Lemelson Foundation to institutionalize the Engineering for One Planet framework at Kennesaw State University. This initiative reflects her commitment to sustainability and innovative engineering practices. ©American Society for Engineering Education, 2025 Improving Major Selection and Academic Trajectories: The Impact of a Common First-Year Engineering Orientation CourseAbstractThis Complete Evidence-Based Practice paper studies the impact of Kennesaw StateUniversity’s new, 1 credit hour engineering
Capstone CourseKeywords: Capstone Projects, Electrical Engineering Education, Generative AI in Education,ChatGPT, Entrepreneurship in Engineering, Marketing and Design Requirements, ABET.1. IntroductionIn recent years, many engineering programs have integrated entrepreneurship education into thecapstone experience, blending technical engineering skills with entrepreneurial processes,namely ideation, customer discovery, client validation, and commercial viability [3] Theseprocesses enable students to translate their technical knowledge into economically relevantengineering practice. The objective is to produce graduates who are not only technicallyproficient but also capable of navigating the business landscape, ethically aware, and responsiveto
that there are significant impacts of the generation of problems on studentperformance compared with conventional textbook problems. The insights of this research offervaluable guidance for redefining traditional engineering problems.Keywords: Engineering Problem generation, Generative AI, Student Performance, EngineeringEducation 1. IntroductionEngineering problems are a fundamental element of formal education pedagogy. Traditionalengineering problems are formed by acquired knowledge and experience. The process ofproblem formation serves as an essential phase in problem-solving that could directly impact theoutcome [1], [2], [3]. A deficient problem-generation approach can lead to hindrances inapplying earned knowledge which causes unclear
-based capstone design project. This two-semester, four course, 11 credit hoursequence includes both engineering and technical communication courses and is co-taught byengineering and communications instructors. Each student invests nearly 500 hours in a team-based project. Each team of six to nine (or more) students completes the design, fabrication andflight testing of an unmanned aerial vehicle. Students document their work through four writtenreports and eight oral presentations (i.e., design reviews and test readiness reviews). While eachteam member has a distinct technical role, all work is completed collaboratively [1], [2].The intensity of the project and its collaborative nature present unique challenges for bothcapstone students and
tools likeChatGPT in academic and personal contexts. The post-survey evaluates changes in awareness,confidence, and interest after the lecture and assignment. Results provide insights into AI’simpact on academic performance and efficiency, guiding curriculum development. Additionally,the cohort will be surveyed again in three years to assess their long-term AI experiences andcareer readiness. 1. IntroductionArtificial Intelligence (AI) traces its origins to the mid-20th century when researchers beganexploring the possibility of creating machines capable of simulating human intelligence [1]. Earlyefforts focused on symbolic reasoning [2], problem-solving [3], and basic learning algorithms [4].As computing power increased, data became more
their confidence in leadership, creative thinking, and problem-solving.IntroductionAs part of a Kern Entrepreneurial Education Network (KEEN) Fellowship I received in AY2023,I incorporated a semester-long project to have recent alumni engage undergraduate engineeringstudents and lead classroom activities focused on the entrepreneurial mindset (EM) and the threeCs: curiosity, connections, and creating value.[1] “It spiked my interest in understanding howengineering students develop through their… professional experiences and how [those positionthem to incorporate] entrepreneurial mindset into their work. Especially the three Cs,” was astudent’s seminar survey response. The development of an EM is important for engineeringstudents as they prepare
participants exhibited varying degrees of engagement with goodpedagogy, each with corresponding implications for racial equity. Our two key arguments are (1)Good pedagogy can pave the way for equity, including racial equity, and (2) An improvement ingeneral pedagogy and efforts to improve racially-equitable pedagogy can happen concomitantly.While good pedagogy may not guarantee (racial) equity, bad pedagogy is more likely toperpetuate (racial) inequity. We saw that when faculty members actively engage in good pedagogy that encouragesstudent participation, e.g., even utilizing simple active learning techniques like "think-pair-share"(as seen with Faculty 1) and involving students in class activities (as demonstrated by Faculty 2),they are more
environments and how institutional agency influences student success. This research spans three different spheres of influence including 1) student experiences, 2) higher education institutions, and 3) societal contexts. Her most recent research considers the intersection of Latinx identity and STEM identity at Hispanic Serving Institutions that are also community colleges.Margarita Rodriguez, University of California, Santa Barbara ©American Society for Engineering Education, 2025 1 Bridging Pathways: Empowering Latinx STEM Students Through Belonging, Support, and
pedagogical approach can vary widely betweeninstitutions and individual instructors. However, the use of active-learning, sometimes inconjunction with a flipped classroom approach, has become a popular mode of course delivery[1], [2]. The data available comparing various methods sometimes finds that active-learning canhave positive impacts on learning [3] or student motivation [4] but there are also plenty ofexamples where the method of instruction and class format have limited impact on studentoutcomes [5], [6], [7], [8].This study investigates whether the use of a high-fidelity motion capture lab for anundergraduate dynamics class project leads to a better student experience. Marker-based motioncapture systems are commonly used in a variety of
topreserve critical thinking and foundational writing skills. Both groups called for clearerinstitutional policies and structured guidelines for the ethical use of AI tools in educationalcontexts.The findings underscore the need for a balanced and proactive framework to leveragegenerative AI’s benefits while safeguarding educational integrity. Key recommendationsinclude: (1) establishing clear institutional policies on permissible AI use; (2) developing AIliteracy modules to foster critical engagement; (3) implementing process-oriented assessmentmodels, such as version history reviews and reflective writing logs, to emphasize students'intellectual contributions; (4) promoting active faculty involvement in guiding ethical AI use;and (5) adopting
serving as the C0-Director of the InstituteGuillermo Aguilar, Texas A&M UniversityClaire Bowman-Callaway, Texas A&M University ©American Society for Engineering Education, 2025 Evaluating Teaching Culture Change within a Mechanical Engineering Department1. Introduction Engineering education is changing rapidly, particularly as contemporary engineeringproblems require increased curiosity, experimentation, and deeper understanding and as effortsto diversify the demographics of engineering students have intensified [1], [2]. Academicengineering departments must be prepared to adapt to these changing environments andanticipate the future needs of their diverse student
University ofCentral Arkansas. With 12 years of experience in education, he has taught various science courses at bothsecondary and post-secondary levels and has held multiple STEM-related positions within the ArkansasDepartment of Education. ©American Society for Engineering Education, 2025 Expanding a State-wide Data Science Educational Ecosystem to Meet Workforce Development NeedsAbstractThe University of Arkansas has been developing a State-wide Data Science (DS) EducationalEcosystem over the last five years. A new project, funded by a HIRED grant from the ArkansasDepartment of Higher Education, builds on this existing DS Ecosystem. The program componentsinclude: 1) DS Ecosystem Expansion
developed for the 2017/2018 school year by RSECS. At the time this series wascreated the school was also becoming a National Academy of Engineering Grand ChallengeScholars Program (NAE GCSP) school [1] as well. There are 14 NAE Grand Challenges, andthough this course is for non-majors, we decided to develop it around one of the NAE GrandChallenges, “Engineer the Tools of Scientific Discovery”. Simultaneously, RSECS also wasapplying to be part of the Kern Entrepreneurial Engineering Network (KEEN), and weincorporated many elements of KEEN into the sequence of courses which stress entrepreneurialminded learning (EML), and the three C’s, Curiosity, Connections, and Creating Vale (3C’s) [2].A committee convened in 2016/2017 to strategize what the new
standard of quality for which students, employers, andsociety can be confident that graduates of an ABET accredited program are prepared to enter thediscipline after graduation. ABET criteria are developed by professionals associated with the 34technical societies that comprise ABET [1]. Although originally focused on accreditingengineering and technology programs, today, ABET also accredits college and universityprograms in other areas such as the applied and natural sciences and computing. Programs can beaccredited at the associate’s, bachelor’s, and master’s degree levels. ABET General Criteria, andwhere applicable, Program Criteria, identify elements required in the program curriculum.ABET is a non-profit, non-governmental organization with
engineering, undergraduate engineering, industrypartnerships1 IntroductionRetention and graduation of students are key goals of undergraduate engineering education.Design education and hands-on experiences play a critical role in supporting engineeringretention because they encourage sense of community through team-based learning, exposestudents to real-world applications of engineering, and support creativity and sense of “fun” [1],[2]. More specifically, first-year engineering design courses can provide positive foundationsthat support building a student’s engineering identity and sense of belonging in STEM. Whenstudents are provided hands-on learning opportunities that support their development of technicalskills, their confidence builds [3
settings.1 IntroductionWith recent advancements in machine learning, increasingly sophisticated and innovativetechnologies have been developed to address problems across various domains. One notableoutcome of these advancements, which has gained significant popularity in recent years, isgenerative artificial intelligence (GenAI). GenAI encompasses techniques and tools, such asChatGPT and Gemini, which are capable of generating meaningful text, images, audio, video, andother outputs based on training data [1]. This broad range of potential applications has encouragedpeople to explore diverse ways of using GenAI to help address various challenges. Educationstands out as one of the most promising fields embracing AI’s capabilities [2], [3].One
self-directed learning opportunities. In this course, students learn how togather and analyze data as part of the engineering design process, apply systems thinking to anengineering or societal phenomenon, collaborate with peers to find solutions, and effectivelypresent solutions to an audience. Moreover, students are exposed to the introduction of theapplication of machine learning techniques to environmental datasets and Google Earth enginefor remote sensing datasets.This work will aim at reporting four main issues, namely (1) the unique components of thecurrent integrated data science course, (2) an account of selected environmental engineeringprojects using Python, (3) a survey result collecting data on students’ perception about the
Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology. His research interests are engineering faculty and students beliefs about knowledge and education with a special focus on how those beliefs interact with engineering education as a culture. ©American Society for Engineering Education, 2025 Developing an AI/ML activity for a BME physiology courseIntroductionThe current employment landscape is likely to undergo significant changes as the prevalence of data-drivenwork increases. The types of engineering jobs available and the skills required for these jobs will be affected[1]. Rather than the traditional computational skills (e.g. writing code, data
-sectioncourse, where each lecture section consists of approximately 200 students in various engineeringmajors, with 50-minute lectures on Mondays, Wednesdays, and Fridays. One section receivedtraditional instruction, while the other section spent a portion of class time (10-15 minutes) eachFriday discussing real-world applications of the course content. The sections were surveyed at thebeginning and end of the semester to assess their impressions of (1) their curiosity about thematerial, (2) the connections to real-world applications and (3) the value created by the coursecontent. These three themes were selected around the “3C’s” of the Kern EntrepreneurialEngineering Network (KEEN) entrepreneurial mindset (Curiosity, Connection, Creating Value).The
with agile and responsive supply chains [1–3]. While these technologies bringsignificant benefits, their growing adoption has also increased the complexity of manufacturingsystems, making them increasingly difficult to manage, secure, and optimize. Thesetransformative changes make it critical for the 4IR workforce to have a strong understanding oftopics in 4IR, requiring reskilling of the existing workforce in addition to training a newworkforce, a mammoth task on scale [4]. However, such engineering training programs facemultiple obstacles. For instance, although online training programs are cost-effective, easy toscale, and are preferred for reskilling/upskilling efforts [5], 4IR workforce training requiresaccess to specialized hardware