Paper ID #45818Coming to America and Helping Communities: Stories from Women in AcademiaDr. Angela R Bielefeldt, University of Colorado Boulder Angela Bielefeldt is a professor at the University of Colorado Boulder in the Department of Civil, Environmental, and Architectural Engineering (CEAE) and Director for the Engineering Education Program. She conducts research related to engineering ethics, sustainability, social responsibility, and community engagement. Bielefeldt is a Fellow of the American Society for Engineering Education and a licensed P.E. in Colorado. ©American Society for Engineering
ethical andprofessional responsibilities inengineering situations and makeinformed judgments, which mustconsider the impact of engineeringsolutions in global, economic,environmental, and societal contexts.5. an ability to function effectively on x x x xa team whose members togetherprovide leadership, create acollaborative environment, establishgoals, plan tasks, and meetobjectives.6. an ability to develop and conduct xappropriate experimentation, analyzeand interpret data, and useengineering judgment to drawconclusions.7. an ability to acquire and apply new xknowledge as needed, usingappropriate learning strategies.ABET-ETAC Student Outcomes1. an ability to apply knowledge, x xtechniques, skills
. Participating inwhole-class conversations during engineering design experiences can also help students expandtheir engineering thinking to include perspectives of care (McGowan & Bell, 2020) and socio-ethical deliberations.In a multi-year collaboration of university researchers and classroom teachers in first- throughsixth-grade classrooms, we have been enacting and studying five different types of whole-classengineering design conversations, which we refer to as Design Talks. Examples, including videoclips and transcripts, can be found on the project website at www.engineeringdesigntalks.org andin prior publications (Wendell et al., 2024; Wendell, Watkins, Andrews, & Malinowski, 2023;Wendell et al., 2022).As a teacher-researcher community of
encounter. All procedures and interactions were carried out with the approval of the Institutional Review Board (IRB) to ensure ethical considerations. D. Observations The post-assessment survey collected basic participant information, including name and grade level, along with four
13 14 15 . LLMs have been demonstrated toeffectively provide iterative and guided learning experiences 16 17 18 and instant feedback tostudents 19 17 10 20 . There are specific use cases that have shown that LLMs can be used to improveproblem solving and critical thinking 20 17 21 18 . Furthermore, many papers state that LLMs areuseful in supporting educators in the administrative overload 22 23 24 12 .Conversely, there are many papers that identify weaknesses that LLMs have in engineeringeducation. There are numerous studies that point out the widely recognized persistent issue ofinaccuracy of LLMs 25 26 27 15 . LLMs facilitate plagiarism 20 28 29 17 and present many ethical andresponsibility concerns 10 16 20 17 . LLMs also can have
health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors. 2. An ability to communicate effectively with a range of audiences. 3. An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts. 4. An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives.GradingGrading Scale A 94-100% B- 80-82.9 D+ 67-69.9 A- 90
computations. Achieving a balance between computational efficiency and highdetection accuracy is critical for real-time performance in dynamic driving environments.Additionally, AV deployment raises regulatory and ethical issues. In critical scenarios, AVsystems may need to make moral decisions, such as choosing between two harmful outcomes,which introduces complex ethical dilemmas [25]. Furthermore, the lack of standardizedregulations governing AV deployment across regions creates additional barriers to large-scaleadoption. Mask R-CNN Mask R-CNN is a groundbreaking model in deep learning, designed to perform instance segmentation by identifying and segmenting individual objects at the pixel level. Introduced by He et al. (2017
must not only possess technical expertise but also the ability to connectethical theories with engineering practices. An ethics-of-care approach, for instance, can enhancestudent understanding of sustainability by encouraging them to consider the broader social andenvironmental implications of their work [19]. By embedding these competencies into curricula,higher education institutions can ensure that their graduates are well-equipped to drive sustainabledevelopment in their respective fields.2.2 Sustainability in Curricula in Civil Engineering and Related DisciplinesCivil engineering, as a discipline, is uniquely positioned to contribute to global sustainabilityefforts due to its direct impact on infrastructure development and resource
, and Songdo. Highlight practical implementations of energy-efficient practices and discuss the challenges encountered. Encourage critical thinking through comparative studies of various Smart City models worldwide. B-2 Interdisciplinary Collaboration Capstone Project: Facilitate joint projects involving CM, CE, and Architecture students to solve Smart City design challenges collaboratively. Promote knowledge-sharing and integrated thinking across disciplines. Organize student participation in real-world projects or competitions to develop energy-efficient smart city prototypes. B-3 Policy and Ethical Considerations
] Attribute CEPs have the characteristic WP1 and some or all of WP2 to WP7: Depth of knowledge required WP1: Cannot be resolved without in-depth engineering knowledge at the level of one or more of WK3, WK4, WK5, WK6 or WK8 which allows a fundamentals-based, first principles analytical approach. Range of conflicting requirements WP2: Involve wide-ranging and/or conflicting technical, non-technical issues (such as ethical, sustainability, legal, political, economic, societal) and consideration of future requirements. Depth of analysis required
as they work on programmingtasks. Students with extended error resolution times are perceived to display strugglingbehaviors. By tracking the duration and frequency of error corrections, instructors can gaininsight into students’ debugging strategies.Furthermore, by integrating unit tests with the keystroke analysis, the tool enables theinstructors to dynamically assess code correctness. The pass/fail rates of the unit tests areclear measures of students’ progress.5 Ethical ConsiderationsGiven the focus of this research on student data collection and analysis, the study adheres toestablished ethical guidelines in order to protect the students’ privacy and maintain datasecurity. This research has been approved by our University’s
Ethics Pedagogy Can Accommodate Neurodivergent Students and Expose Ableist Assumptions," Building Inclusive Ethical Cultures in STEM, vol. 42, pp. 289-311, 2024.[36] M. Pilotte and D. Bairaktarova, "Autism spectrum disorder and engineering education - needs and considerations," in IEEE Frontiers in Education Conference, Erie, 2016.[37] J. L. Kouo, A. E. Hogan, S. Morton and J. Gregorio, "Supporting Students with an Autism Spectrum Disorder in Engineering: K-12 and Beyond," Jounral of Science Education for Students with Disabilities, vol. 24, no. 1, pp. 1-21, 2021.[38] D. R. Delp, ""Where Resources End and Teaching Begins: Experience with Students with Autism Spectrum Disorders in the Freshman Engineering Curriculum," in ASEE
traditional boundaries, integrate diverse perspectives, and work towardscreating innovative solutions that address the pressing needs of society [16]. The complexproblems also highlight the importance of integrating societal issues into engineeringeducation and practice, emphasizing the social responsibilities and ethical considerations thatengineers must uphold [18], [19]. Therefore, transdisciplinary approaches present a feasibleand effective way to address complex problems in engineering disciplines and beyond.Historical Context of TransdisciplinarityThe concept of transdisciplinarity was first introduced in 1970 at a conference discussinginterdisciplinarity and its applications in Europe [20]. Jantsch and Piaget argue thatmultidisciplinary
methods of engineering; introduce skills which are basic to engineering; and acquaintstudents with the interaction of skills, techniques, logic, ethical responsibility[2], and creativity inengineering problem formulation and solving. Although the curriculum is common, the actualschedule for each student is based on their incoming background and their anticipated major. Thescience and general education requirements are the same regardless of whether they enter the FirstYear Engineering Program or as a first-year student or as a transfer student. Upon the successfulcompletion of the first-year curriculum, students choose their major from any of the tendepartments or programs.First year students (and transfer students) also participate in an
course schedule (Table 3.1) includes preparation for professional andethical conduct in a clinical setting, opportunities for sharing and dissemination of experiences,training in engineering design cycle, prototyping, and module development for future work.Table 3.1: Weekly schedule for SIDE course. Course plan includes preparatory training forprofessionalism and professional conduct in a clinical setting, as well as reporting from clinicalexperiences, and integration of clinical experiences into the product development lifecycle. Week Content Reporting/Submissions 1 Introduction, Responsible Conduct in Research, Ethics CITI Certification
Paper ID #47581Contextualizing Engineering Education by incorporating Indigenous KnowledgeSystems (IKS) in the Curriculum DesignDr. Brainerd Prince, Plaksha University Brainerd Prince is the Associate Professor of Practice and the Director of the Center for Thinking, Language and Communication at Plaksha University. He teaches courses such as Reimagining Technology and Society, Ethics of Technological Innovation, and Art of Thinking for undergraduate engineering students and Research Design for PhD scholars. He completed his PhD on Sri Aurobindo’s Integral Philosophy from OCMS, Oxford – Middlesex University, London. He
funding fromother crucial educational priorities, forcing institutions to make difficult trade-offs.Significant disparities exist in AI implementation across institutional contexts, with resourcelimitations and technical infrastructure constraints creating educational equity concerns, asdocumented by Yigitcanlar et al. [7] and Sleem and Elhenawy [13]. This threatens to create a two-tiered system where only students at well-resourced institutions benefit from cutting-edgeapproaches. Additionally, ethical considerations surrounding algorithmic bias and transparency ineducational AI tools require attention, as students may internalize flawed patterns embedded inthese systems.The successful integration of AI in sustainable construction education
[11]. Therefore, combining technicalskills with interpersonal abilities is necessary to meet modern professional demands.Engineers lead multidisciplinary teams, manage complex projects, and adapt to globalchallenges [1], [2]. Beyond project management, leadership in engineering demandsstrategic foresight, ethical decision-making, and the ability to integrate technical and socialdimensions in complex systems [12]. This underscores the need for leadership training inengineering education to equip graduates with both technical and managerial skills.Leadership is a skill that involves communication, teamwork, and problem-solving, whichdrive innovation and help achieve goals. Many institutions adopt transformationalleadership models, which have
method continues to be used, and thispersistence is in part because the results can be analyzed at different levels, as will be explained inmore detail later.The paper is structured into three basic sections. The experimental conditions are explained inSection 1. The surveyed results are then presented in Section 2 and analyzed in Section 3. Basedon this data analysis, conclusions are drawn, and possible future work is discussed.Ethics approval for this research project was duly obtained from the University of OttawaResearch Ethics Board (REB), under file number H-02-24-10020.Description of Experimental MethodDuring this study, in the GNG1103 - ”Introduction to Engineering Design” course at theUniversity of Ottawa, students were taught
[1] listed in italics: • Keep careful, complete and systematic records of laboratory work (experiment) • Understand the importance of, and appropriate methods for, the calculation of errors and uncertainties. (experiment, data analysis) • Carry out experiments, using key equipment to make appropriate calculations and solve realistic, open engineering problems. (experiment) • Analyse data collected, apply theory to one’s own experimental measurements, evaluate results and draw conclusions. (data analysis) • Write technical reports to justify experimental study, record procedures in the laboratory, communicate results and make concise robust conclusions. (communication,ethics)The activity
byintelligent prompting and integrations like Wolfram Alpha [5]. Undergraduate perspectives onLLM-based tools were explored, revealing diverse perceptions regarding their benefits andchallenges. These findings contribute to discussions on balancing AI assistance with ethicalconsiderations and human engagement [6]. Additional insights into the evolving role of generative AI tools, such as ChatGPT, ineducation, draw parallels between the adoption of generative AI and historical technologicaldisruptions, emphasizing the need for responsible integration to address ethical and pedagogicalchallenges [7]. Complementing this discussion, another study outlined trends in engineeringeducation research, providing context for the integration of digital
, and from psychology. The overarching goal of the course was to develop aninterdisciplinary understanding of the necessary balance between the needs of society andengineering design. It explicitly addresses four societal impact outcomes in ABET Criterion 3:public health and safety impacts of design, ethical decision-making, collaborative productivity,and effective communication with diverse audiences [1]. This course is supportive of theEngineering One Planet (EOP) program of the American Society for Engineering Education(ASEE) [2]. In addition, the importance of making design decisions in economic, environmental,and societal contexts is emphasized from the perspectives of engineering and physical andmental health.IntroductionA new technical
ethical implications and societal impacts ensures they areprepared to develop responsible and sustainable solutions. With the increasing reliance ontechnology and the internet, protecting sensitive information from cyber threats has become a toppriority for individuals, businesses, and governments alike, and incorporating AI/ML into theprogram empowers students to become future leaders who drive progress in an increasingly digitalworld, with a strong emphasis on the critical field of cybersecurity. Approaching this need to fuseAI/ML in our cybersecurity curriculum starts by identifying the key applications of AI/ML incybersecurity. Once these are identified, we can determine the freshman, sophomore, and juniorcourses that can prepare the students
. deliverable based on human inputs. Engage in metacognitive reflection; Identify pros and cons of various holistically appraise ethical courses of action; develop and check consequences of other courses of against evaluation rubrics. Evaluate action; identify significance or situate within a full historical disciplinary context. Critically think and reason within the Compare and contrast data, infer cognitive and affective domains; trends and themes in a narrowly Analyze justify analysis in depth and with defined context; compute; predict; clarity
DEIBinitiatives is influenced by individual factors, such as racial and ethnic identity, as well asinstitutional culture and available resources. To be ready for change, faculty must see that changeis necessary, that the needed change will occur, and that there will be positive outcomes from thechange [7], [30]. Faculty of Color often bear the additional burden of advocating for DEIBchange while simultaneously navigating the challenges of systemic racism and discrimination[9]. For instance, even though Black faculty had higher service loads than their peers, they tookon additional voluntary diversity service, like mentoring Black students and anti-deficit teachingstrategies [31]. McGee describes this mindset as an equity ethic. An equity ethic requires
Engineering graduates will: • Have established successful careers in robotics, automation, or related fields, demonstrating their ability to apply principles of robotics engineering to responsibly solve complex problems. • Engage in continuous learning and professional development to stay abreast of advancements in robotics and emerging technologies. • Demonstrate leadership, ethical conduct, and effective communication in multidisciplinary teams, contributing to the progress of the robotics profession and society. • Contribute to the advancement of robotics and automation through innovation, research, or entrepreneurial endeavors, showcasing the ability to push the boundaries of knowledge and technology in
StrategiesSeveral commonly used grouping strategies emerged from the analysis of methods used bystudents to group the topics from the course into categories. Figure 3 summarizes these commonstrategies and reports the proportion of students who utilized each. Figure 3: Proportion of students who utilized each commonly used grouping strategy.Students who used Strategy 1 divided the course topics into three major categories: academic,personal, and well-being. The academic category included skills that might lead to betterperformance in their college coursework. The personal category included skills that could helpthem improve certain aspects of their personal lives, such as their work ethic or socialrelationships. The well-being category included skills
collection. ○ Verified Saws: 56 The system would require greater flexibility for the ○ Expected Saws (Bio Dept. Annotations): 77 unpredictability of wild leopards, which could possibly be ● Performance Test #24 (After Optimization, Using mitigated by additional tools. The implementation in the wild Original Audio File): could also face logistical and ethical hurdles. Deploying technology in remote areas may raise concerns about human ○ Detected Noises: 11 impact on
extreme environments, to name a few. This paper is a collaboration between a mathematics professor and a mechanical engineering professor, combin-ing expertise in applied mathematics and mechanical engineering applications to create an innovative pedagogicalapproach that bridges the gap between mathematical theory and materials engineering practice.2.2 Connection to ASEE Themes and the USAFA Leader of Character FrameworkThis work contributes to the ASEE theme of Inclusive Teaching Pedagogy through: • Course Design: Integrating Laplace transforms as a fundamental tool for modeling non-steady-state diffusion in engineering materials. • Engineering Ethics and Professional Practice: Encouraging critical thinking beyond formula
adapted to other programs looking to boost student connectionand comfort on campus.References[1] A. D. Ronan, "A scavenger hunt activity to welcome first-year students to the civilengineering department," in Proc. 2019 ASEE Annu. Conf. Expo., 2019.[2] S. Gray, E. Lindsay, and J. Walraven, "Orienthunt: The development of a scavenger hunt tomeet the needs of a first year engineering orientation," in Australasian Association forEngineering Education Conference 2011: Developing Engineers for Social Justice: CommunityInvolvement, Ethics & Sustainability, Fremantle, Western Australia, Dec. 5–7, 2011[3] K. Morgan et al., "Work-in-progress: Reflection & projection: An exploration of a scavengerhunt assignment in an introduction to aerospace