into public, business, and academic makerspaces. Public makerspaces, such as those foundin libraries and universities, focus on promoting the making culture among general users by providing basictools, essential services, and knowledge exchange events, such as seminars and tech talks [1]. Businessmakerspaces emphasize entrepreneurship (e.g., UnternehmerTUM) and support start-ups and small businesses.Higher education makerspaces, on the other hand, carry the mission of revolutionizing the means of teachingand learning, moving from a teacher-driven mode to a learner-driven paradigm, fostering learning throughhands-on experiences, encouraging peer collaboration, and facilitating experiential learning to address real-world challenges. This unique
navigation’ in the space where engineering intersects broadersocietal needs. Key aspects include developing student agency, scaffolding design-relevantskills, and emphasizing problem scoping.IntroductionIn this paper navigational analogies are used to understand learning in design courses. Unlikecourses that are designed to teach engineering content and topics, design courses have severalkey differences [1]. Topical courses tend to emphasize disciplinary knowledge and assessstudent learning through exams and problem sets; methods that rely on having a "right" answer.This emphasis on acquisition of fixed knowledge can lead to topical courses being viewed as"gatekeepers" by faculty. It can be difficult to incorporate material outside of
recommendations to support inclusive, community-based future efforts to co-designengineering education tools. Additionally, we present supplementary resources to supportorganizing and implementing these recommendations, and we discuss aligning the goals of co-design with liberatory design efforts.1. IntroductionIt has been 50 years since the Individuals with Disabilities Education Act (IDEA) was passedand amended in the United States [1], [2]. This law and its amendments ensured that studentswith disabilities would receive a free and public education in the least restrictive environment,and that all educational opportunities, activities, and facilities would be accessible to them aswell. Since then, numerous educational entities and organizations have
supplements our existing training with twonew deliverables focused on safety. The first is a checklist that is introduced early in thecapstone course to make students aware of potential hazards and what types of work areprohibited without prior instructor approval. Later, after teams have finalized their designs onpaper, they are required to complete a written Project Hazard Assessment (PHA). We explainhow these processes are implemented and share lessons learned from their use in recent years.This process has helped to identify many safety hazards and we have been able to ensure thatteams have plans in place to manage these hazards. Since implementation, we have notexperienced a safety-related incident.1. IntroductionAt our university (University of
. He has conducted applied research in collaboration with industry and government partners for over 25 years. He has taught a wide array of classes in economics and data science, including three years teaching and mentoring multidisciplinary teams in Capstone 1 and 2.Dr. Karim Elish, Florida Polytechnic University Dr. Karim Elish is an Associate Professor of Computer Science at Florida Polytechnic University. He obtained his PhD and MS in Computer Science from Virginia Tech. Dr. Elish received the Florida Poly ABLAZE Award for Excellence in Teaching in 2017-2018 for his excellence in teaching practices reflecting the highest standards in pedagogy; a record of outstanding teaching effectiveness inside and outside the
complex, multisystem world they inherit (see Standard7 of the CDIO Standards 3.0, in [1]).This paper explores how faculty might teach students how to embody complexity leadershipwithin a capstone course that includes systems thinking as a learning outcome for students. Manycapstone courses, design courses, and similar existing engineering courses address systemswithout explicitly teaching systems thinking skills and habits. An engineering capstone designexperience provides an opportunity for students to apply knowledge and skills from their majorto complex engineering problems and engineering design. During this process, students considertrade-offs and multiple parts or perspectives. Many of the designs tackled in these courses are atthe system
AI technology. Findings supportcoursework related to engineering ethics and societal impacts, engineering policycommunication, and design projects focused on GenAI. Documents are presentedchronologically and interwoven with government initiatives to demonstrate the impact ofExecutive Orders on shaping AIs’ outcomes. Findings will enhance future engineers’ expertise inthe realities, challenges, and impacts of developing and responsibly governing AIs.IntroductionThe National Academies of Science and Engineering pointed out “Computing research has anobligation to support human flourishing, thriving societies, and a healthy planet [1]”. Thisobligation is a matter of taking responsibility and embedding responsible practices and policiesin AI
in the student survey varied between 18% and 26% of the total class size,making only certain statistical analysis methods and types of inferences appropriate.Keywords“Motivation”, “Learning Strategies”, “synchronous online”, “remote learning”, “HyFlex”,“in-person”, “MSLQ”AcknowledgementThis project was made possible in part through the support of the National CybersecurityConsortium and the Government of Canada (CSIN).IntroductionIntrinsic motivation can be viewed as the set of internal forces that drive people to behave indifferent ways and is the result of both the personality and the abilities of the individual,combined with their previous experiences [1]. These intrinsic motivation factors co-exist withother (extrinsic) motivating
Northwestern University, a MS in Human Factors Engineering from Tufts University, and a Doctorate in Ergonomics from Harvard University.Arpita Bhattacharya, University of Washington ©American Society for Engineering Education, 2025 Integrating Theory and Practice into a Design Foundations Course Sourojit Ghosh, Arpita Bhattacharya, Sarah Coppola, University of Washington, SeattleIntroduction Engineering education scholars have emphasized the need for holistic, integratedengineering education that prepares future engineers for the complex sociotechnical systems(STS) in which they will work [1], [2]. Design courses such as Cornerstone or Capstone coursesprovide
students’ development of sociotechnical ways of thinking, knowing,and doing in engineering [1-2]. However, scholars have critiqued common approaches tocommunity-based engineering design projects. First, while community-based engineeringdesign projects often attempt to employ participatory design strategies designed to fosterequitable participation for those historically excluded from engineering design processes [3],research on community-based engineering design project-based learning suggests theseprojects tend to be exploitative and extractive, often leaving community partner organizationsand community members without the benefits of the projects [3-7]. Thus, there is a need forengineering design educators to rethink common approaches to
faculty did not care enough about their well-being and thatfaculty were fostering studio environments in which students could not get enough sleep andcould not afford project materials. This pilot study points to a need for further research intofaculty-student relationships and interactions and faculty pedagogical choices in designeducation.Keywords: design education; diversity; equity; inclusion; race; gender1. IntroductionEven though designers create the products and spaces that people of all backgrounds use everyday, most design fields are not diverse. White men are overrepresented in architecture, designengineering, and industrial design, and white women are overrepresented in interior design in theUnited States [1], [2], [3], [4]. Of course
regarding over-reliance on AI. Thefindings will provide insights into how AI can be used effectively in engineeringeducation to develop critical thinking skills and offer practical recommendations forincorporating AI into engineering design curricula.1. IntroductionArtificial intelligence (AI) is transforming engineering practice by enabling rapid designoptimization and data-driven decision-making. In engineering education, AI tools offeropportunities to enhance critical thinking—a vital skill for navigating complex designchallenges. For this study, key terms are defined as follows: ● Engineering Education: The pedagogical framework for training students in engineering disciplines, emphasizing technical knowledge and cognitive skills like
coordinates the mechanical engineering senior capstone design projects and teaches senior design lectures and studios. Her research interests include engineering education and engineering design methodology. ©American Society for Engineering Education, 2025 1 Writing Assessment Training for Capstone Design InstructorsIntroduction Technical writing is vital for professional engineers, but engineering students oftenstruggle to master written communication [1]. To help students develop the necessary writingskills for their careers, many engineering programs implement writing intensive courses
learning objectives in human-centered design (HCD) across project-based courses withina Mechanical Engineering program. Engineering design education plays a vital role in preparingstudents for the increasingly complex, interdisciplinary, and user-centered challenges of modernengineering practice [1]. To address these evolving demands, this initiative focuses on unitingfaculty around shared pedagogical goals and enhancing the student learning experience through acohesive “design spine” [2,3]. At the heart of this effort is the recognition that engineeringproblems rarely have singular solutions, requiring a balance between technical rigor and human-centered approaches. This paper details the development and implementation of shared
a diversity of consulting,academic, and industrial sources. The factors that drive the adoption, use, and ongoing success ofthese tools are not well understood and are likely driven by a complex interaction of human,organizational, and economic factors. This paper investigates innovation method and tooladoption in industry through semi-structured interviews with individuals from a Fortune 500company. This work explores three resulting themes 1) individual incentives and motivation foradoption, (2) the appropriateness of tool selection for the organizational product domain andcompatibility with existing processes, and (3) executive and management support for adoption.The implications for engineering education are also discussed.Keywords
post-course surveys, guided reflection, and analysis of student-created artifacts to capture shifts in identity, creativity, and anticipatory competence. Thesestrategies collectively aim to promote a forward-looking culture within engineering education.By advancing discussion on pedagogical methods, institutional conditions, and evaluationframeworks, this paper contributes to an emerging discourse on the role of futures literacy inpreparing engineers to shape more inclusive, just, and resilient futures.IntroductionSince early descriptive accounts of how expert designers navigate uncertainty and addresscomplex, ill-defined problems [1, 2, 3, 4], design thinking has emerged as a valuable problem-solving paradigm with growing relevance to
incorporated into that design process. DM such as Journey Mapping,Functional Decomposition, Mind Mapping, CAD and Design Change Data Management, amongothers, are addressed. The effectiveness of different AI-based tools on the DM is reported.Some AI-based tools have little, or possibly even negative, impact when applied to certain DMwhile others can significantly enhance the effectiveness of the design process method.1. IntroductionThis paper reports on efforts to use AI-based tools (AI-T) to enhance various design methods(DM) used as part of a specific design process. The AI-T investigated include Chat-GPTCopilot, Miro Assist, Perplexity, CADscribe, Stable Diffusion, Viscom and JAVA as it is used tocreate a Multiagent System. The design process used
than technicalproblem-solving targeting efficiency or other technical metrics. The discipline seeks tounderstand stakeholders as complete beings with socio-emotional needs, rather than as purelyrational actors, abstract problem-solvers, or technical components. Scholars such as Boyemphasize that HCE is rooted in principles of Human-Centered Design but applied withinspecific engineering contexts [1].Although closely related, HCE and Human-Centered Design (HCD) differ in scope andapplication. HCD is both a discipline and a methodology focused on research, problem-solving,and experimentation, while HCE embeds human-centered principles throughout engineeringpractice and may leverage HCD to do so. While HCD informs HCE, the demands of
, Dr. Povinelli has worked with leading aerospace companies, as well as collaborating with universities and government research labs. He brings over thirty years of experience in both technical and educational fields, blending scientific rigor with humanistic insight to promote holistic, transdisciplinary pedagogies. ©American Society for Engineering Education, 2025 Integrating Visual Thinking into Design EducationMark J. Povinelli, College of Arts and Sciences, Syracuse UniversityIntroductionVision is one of the first senses to develop in infancy, starting with facial recognition and objecttracking [1], [2]. As the visual system matures, it supports memory, cognition, and