concepts, andengineering tools like Excel and GIS in a project-based learning format. EENV 202, SustainableWaste Management, combines systems thinking concepts, an introduction to ethics and socialjustice topics, and technical content related to solid and hazardous waste management with a life-cycle assessment project on laboratory waste streams. The initial offering of these courses tookplace in the 2023-2024 academic year. This paper reviews the design and implementation ofthese two new project-based courses and shares lessons learned. The findings can guide otherprograms in collaboratively designing integrated project-based engineering courses (IPBC) forfirst- and second-year students.1.0 IntroductionEnvironmental Engineering (EENV) faculty at
values among engineering talents. Engineering education in China hastraditionally focused more on the imparting of professional knowledge and skills, buthas not placed sufficient emphasis on the content related to engineering philosophy andculture. Particularly, in the "Washington Accord" which outlines the qualityrequirements for engineering graduates, aspects such as "Engineers and Society,""Professional Ethics," and "Environment and Sustainability" are relatively lacking.There is an almost complete absence of dedicated courses on these topics at theundergraduate level.Purpose: Consequently, Zhejiang University has introduced the "EngineeringPhilosophy and Culture" course for all first-year engineering students, making it the"first lesson" for
expectations, supporting faculty intheir development, communicating effectively, behaving ethically, and managing the departmentin an organized and fair manner are valued for leading, developing, and supporting faculty.IntroductionEffective department head or chair leadership is an important part of both faculty and studentsuccess. The civil engineering community has invested significant effort into developingoutstanding faculty over the last 25 years through the American Society of Civil Engineers(ASCE) Excellence in Civil Engineering Education (ExCEEd) Teaching Workshop [1, 2]. Whilethere is evidence that the ExCEEd Teaching Workshop also develops great leaders [3] andfosters an inclusive environment [4], there has not been much effort applied to
, such as writing, coding, orsolving problems. Thus, education must evolve to teach students how to use this tool effectivelyand evaluate the quality of its work. Educators should aim to incorporate AI into their classroomsin ways that help students develop these skills so that students will be better prepared tocontribute to society in the future 3 .However, there are concerns about ethical implications relating to the grey areas of AI, such asprivacy, bias, and accountability 4 . Applied specifically to education, AI’s integration riskscreating an over-reliance on external tools, potentially hindering students’ ability to recall andapply knowledge independently. Educators have also raised concerns about the potential for“academically dishonest
0.60 0.58 -0.02 5 7 2 Week 11 - Professional Ethics 0.58 0.59 0.01 6 5 -1 Week 3 - Lifelong Learning and Professional Organizations 0.55 0.53 -0.02 7 10 3 Week 1.5 - Engr. Techniques for Success (Night event) 0.54 0.55 0.01 8 9 1 Week 12 - Personal and Professional Values in Engineering 0.53 0.59 0.06 9 6 -3 Week 4 - Academic Ethics 0.53 0.57 0.04 10 8 -2 Week 5 - Effective Teams & Valuing Diversity 0.46 0.44 -0.02 11 14 3 Week 0 - Tartan Engineer (Orientation) 0.44 0.46 0.02 12 12
, students areencouraged to engage in critical inquiry: questioning existing systems, reflecting on their ownassumptions, and connecting academic concepts to complex social issues. This ultimatelyprepares them to become thoughtful citizens equipped to address community challenges with bothintellectual rigor and empathetic understanding. Research has consistently shown that servicelearning leads to measurable improvements in student learning outcomes, including higherretention rates, improved problem-solving capabilities, and stronger ethical reasoning skills [2], [3].How does this help engineering students?Engineers, in particular, stand to gain tremendous value from service-learning experiences thatbridge technical expertise with community needs
sustainability, human-centricity, and resilience of industrial systems [2], [3], whereengineers are key players [4]. These societal and technological shifts demand not only technicalproficiency but also a blend of adaptive, interdisciplinary, and ethical capabilities [5], [6].However, existing engineering competency models lack empirical grounding in this new contextand do not sufficiently reflect the holistic skillsets now required [6]. This study addresses thatgap by empirically validating a future-oriented competency framework aligned with the evolvingdemands of Industry 5.0.2 Literature ReviewThe industrial landscape has undergone significant transformations from Industry 1.0 to Industry4.0, and with the steep trajectory, we can reach Industry 5.0
path to follow are some of life’s biggest.Further, decisions about where and who to work for are value-laden. Especially for soon-to-beengineering graduates, job choices can have distinct social and ethical pressures from oneself,friends, family, and society given that engineering work can conflict with societal beliefs aboutwhat is “good” (i.e., manufacturing weapons for the military, mining for precious metals, drillingfor oil, etc.). Although what is “good” may differ from person to person, the engineeringprofession has a duty to society often referred to as social responsibility. Social responsibility ishighlighted by professional societies and academic bodies as a key engineering principle [1], [2][3], and several Bodies of Knowledge (BOK
principles for equity-centered engineering education are therefore instructional infocus and address the development of equitable classroom environments, including equitableassessment strategies, and the need for assessment of equity content. To date, most publications on equity-centered engineering course implementationsdescribe efforts in engineering design or ethics courses and modules. This may suggest that anequity lens is only or most relevant in those courses; however, if the goal is to promote students’capacity for equity-minded engineering practice, educators must center equity in a variety ofimpactful courses across students’ academic paths [17]. Indeed, Leydens and Lucena [18] arguethat engineering science courses are perhaps the
students to thinkcritically about ethical considerations in engineering and empowers them to propose approachesthat promote inclusivity in design while thinking about how to mitigate and/or prevent bias.These objectives align with the course's broader goal of developing sociotechnical mindsets thatbridge the gap between technical expertise and social responsibility. The activity specificallyaddresses one of the course's guiding questions: "In what ways do cultural, personal, and societalfactors influence engineering decisions, processes, and outcomes, and how can we activelymitigate biases in these areas?" By engaging with this question through concrete examples,students begin to understand their responsibility as future engineers to create
Paper ID #49512Discussion Lead Paper for TELPhE Session on AIDr. Jerry W. Gravander, Clarkson University JERRY W. GRAVANDER is past chair of Clarkson’s University’s Department of Humanities and Social Sciences and currently is the co-chair of Clarkson University’s Department of Arts, Culture and Technology. He has written and presented widely on liberal education for engineering students, as well as engineering ethics and the philosophy of engineering. He was the 1996 recipient of the Sterling Olmstead Award of ASEE’s Liberal Education Division. ©American Society for Engineering Education, 2025
Paper ID #47445WIP: Self-tracking Time-On-Task to promote self-organization skills in anUndergraduate Engineering Design CourseDr. Constanza Miranda, The Johns Hopkins University, Laurel Constanza is a multidisciplinary academic interested in the intersection between the creativity of design, the ethics of cultural anthropology, and the tech aspects of engineering. She is the Assistant Dean for undergraduate mentoring at the Whiting School of Engineering in Baltimore and an associate teaching professor in BME. She holds a Ph.D. in Design with a focus in anthropology from NC State University and was a Fulbright grantee. As
content (e.g. economics, ethics) and skills (e.g. writing, oral presentations) that are usefuland necessary for both personal and professional development. However, students can often seethese courses as not useful or unrelated to their future careers. In this study, a first semestercourse in Civil Engineering was designed and delivered to make deliberate and clear theconnections between the general education portion of the curriculum and students’ future careersas civil engineers. An existing instrument was adapted to measure student aptitudes towardsdifferent skills and knowledge typically presented in general education courses and given to thestudent pre and post instruction, revealing statistically meaningful increases in the
project is approved by the Cal Poly IRB (2024-120-CP) and does not require anonymization of the department or institution. We intentionallysituate this project in the specific context of this work.This paper examines seven different syllabi in two junior-level courses and highlightssimilarities and differences in policies, teamwork dynamics, and emphases on ethics anddiversity in different sections of these courses via thematic analysis. ● “Computer Architecture” is the second course that students are introduced to in the realm of Computer Architecture and Organization, following one of two introductory Computer Organization courses. The course includes quizzes, labs, and exams focused on a particular ISA (Instruction Set
elements effectively and creating content tailored to both students andinstructors.IntroductionThe majority of engineering undergraduate programs lack sufficient guidance on social andethical responsibility in the field of engineering. Both the U.S. National Academy of Engineeringand ABET accreditation emphasize the necessity to embed ethics and social responsibility toaddress ethical, global, cultural, social, environmental, and economic impacts [1]-[3] Researchhas consistently demonstrated the value of sociotechnical awareness in engineers. For instance,engineers must prioritize public well-being and ethical responsibilities in their work [4]-[8],understand the societal impacts of engineering solutions [9]-[12], and challenge cultural normsthat
education culture and institutional change, focusing on marginalized students and educators. An AI enthusiast, Kellam explores the ethical and equity implications of generative AI in engineering education, leveraging AI to foster human connection, challenge inequities, and prepare students for an AI-driven future. ©American Society for Engineering Education, 2025 Critical Consciousness, Equity, and Speculative Futures: Reframing AI as a Catalyst for Human Connection and Systemic Change in Engineering EducationThis practice paper explores the intersection of power, equity, and artificial intelligence (AI).Through a theoretical argument and three narratives about my
between the groups and anotable preference for a more structured and practical educational approach, especially amongstudents with a more robust foundational knowledge. This highlights the relevance of personalizedand applied teaching methods in real-world contexts.This approach examines how AI tools can be effectively integrated into an educationalenvironment, preparing students to face future technological challenges with an innovativeperspective on information systems management.Keywords: Artificial Intelligence (AI), Information Systems (IS), Alternative Evaluation,Automatic Code Generation, Operational Efficiency, Decision Making, Automation, AI Ethics,Information Management, AI Tools.IntroductionIn the digital era, Artificial Intelligence
1Engineering Just Futures: Preparing Engineers to Integrate Technical, Sociocultural, and Environmental Perspectives [Work in Progress]Engineers of the future need to not only be technically skilled but also able to address complexproblems that include social, cultural, ethical, and environmental dimensions. Undergraduateengineering education therefore needs to prioritize the diverse skills needed for complex problem-solving practice [1]-[3]. Traditionally, undergraduate engineering education programs havefocused on technical training in the engineering sciences, to the exclusion of broader concerns [4]-[6]. There are, however, a growing number of programs that aim to expand engagement withsocial, cultural, and environmental
opportunities for students to apply technical learning in a real world context in additionto building professional teamwork and communication skills. However, students often focusmore on the technical solutions and deprioritize the contextual and human factors in design. Thishas been described as an instrumentalist orientation, which focuses on engineering education as anarrow means to solve technological problems and provide job training [3], [4]. Scholars have called for integrating STS theory into engineering education to expandstudents’ understanding of engineering practice [5], [6]. While ethics education is required forABET accreditation, many engineering ethics units are reductive, based on Western/GlobalNorth perspectives, and focused
addresses the integration of artificial intelligence (AI) topics intointroductory engineering courses. With the proliferation of AI in everyday life, it is important tointroduce the topic early in the engineering curriculum. This paper focuses on generative AI andmachine learning topics using two different educational strategies. The objective of this researchwas to explore students’ comprehension of AI and their motivation to engage in AI learning afterbeing introduced to AI tools.In a first-semester project engineering course, generative AI was introduced as a tool. Studentswere guided on the ethical and effective use of generative AI and were encouraged to discuss itslimitations. Students had the option to use generative AI for their writing
types of outlines. During an in-class ethics discussion, students were introduced to an ethics case study, then tasked with writing an outline for writing details about the case study.Results and DiscussionResults from the inclusion of these writing assignments is nascent but optimistic. During the Fall2023 semester writing assignment, the average student score on the rubric component of theassignment specified for writing, grammar and professionalism was 84.7%. In the Fall 2024semester writing assignment, after the presented technical writing assignments had beenintroduced, the average student score on the rubric component of the assignment specified forwriting, grammar and professionalism was 88%. Anecdotally, student writing was
Paper ID #47821Exploring the Intersection between Lifelong Learning and Workforce Developmentin EngineeringMr. Arsalan Ashraf, Virginia Polytechnic Institute and State University Arsalan Ashraf is a Ph.D. student in the Department of Engineering Education at Virginia Tech. His research interests include AI ethics, ethics and social responsibility, and lifelong learning. He has broad experience in academia and industry, which motivates him to do research on these vibrant areas. He is a first-generation student from a small village in Punjab, Pakistan. He completed his B.S. in Aviation Management from Lahore in 2017, and
demand for professionals equippedwith unique skill sets that complement AI systems is surging [1], [2]. To maintain a competitiveedge in this evolving environment, educational institutions must prepare students not only withtechnical knowledge but also with professional skills such as critical thinking, adaptability,creativity, collaboration, and ethical decision-making [3], [4]. These competencies are essentialfor thriving in AI-enhanced workplaces, where traditional roles are being redefined, andinterdisciplinary approaches are becoming the norm. In light of these challenges, the role ofeducators is pivotal in reshaping curricula and teaching strategies to address the gaps betweentraditional education and the demands of AI-driven industries [5
Technology Program. Thecurriculum revision focused on two key topics from the EOP framework: EnvironmentalLiteracy and Responsible Business and Economy. Through this integration, students wereintroduced to sustainability principles such as whole life cycle thinking, closed-loop systems, andinclusive business models that prioritize product durability, ethical practices, and responsivenessto evolving social, economic, and environmental demands. Retrospective pre- and post-courseevaluations revealed significant improvements in students' understanding of sustainabilityconcepts. These improvements were demonstrated by their ability to recognize opportunities foraddressing environmental challenges and assess risks and trade-offs in sustainable
area for engineering educators. Lee et al. [12] Uhlig et al. [19] emphasized the importance of teaching students how to use GenAI ethically and mentioned that ethics concerns are present with every new technology. Hooper et al. [20] examined AI and Ethics concepts and developed pre and post-learning is pretty straightforward, the processes to accomplishit, namely self-directed learning, have been defined differentlyethics. Responsible and ethical use of any support
, with their confidence rising from 3.13 to 4.13 .Additionally, confidence in citing authorship increased from 3.75 to 4.25, indicating progress inunderstanding proper citation practices.Research Enjoyment and Challenges. While students maintained a consistent level of confidencein their enjoyment of research and the excitement of the process, with both responses remaining at4. 50 on both surveys, there was a slight increase in their reported frustration during research.Confidence in handling frustration during research rose from 2.00 in the pre-survey to 2.50 in thepost-survey, suggesting that while research might have become more challenging, students gainedmore resilience in the process.Technical and Scientific Tools, Ethics, and Graduate
contribute to the successful completion of the project? Behaviors to consider: understands common vocabulary, completes background readings or research, knows how to use necessary equipment or technology, has ability to fill multiple roles within the group, etc. • Work Ethic: Was the team member dedicated to completing the amount of work necessary to achieve the goals of the group? • Overall Contribution: How much did each team member contribute to the overall successful completion of the project? • Feedback: Comments and justifications for scores provided in the other categories. This had no numerical value but provided insight into the students’ thought processes.Additionally, the instructor and each
are fourkey areas which will be most impacted: TK, TPK, TCK and TPACK as a whole. TechnologicalPedagogical Knowledge (TPK) focuses on how AI can enhance instructional methods, such asusing AI-driven analytics to track student progress or implementing chatbots for personalizedtutoring. Technological Content Knowledge (TCK) addresses how AI can facilitatesubject-specific instruction, such as using AI-driven simulations in engineering or automatedtranslation tools in language learning. Recent studies emphasize the importance of facultydevelopment in AI literacy, particularly in establishing clear institutional guidelines on ethical AIuse and assessment (Gambhir et al., 2024).While TPACK provides a structured approach to technology integration
academiccommunity. There is ongoing debate about whether faculty should teach students how to use GAItools, restrict their usage to maintain academic integrity, or establish regulatory guidelines forsustained integration into higher education. Unfortunately, limited research exists beyondsurface-level policies and educator opinions regarding GAI, and its full impact on studentlearning remains largely unknown. Therefore, understanding students' perceptions and how theyuse GAI is crucial to ensuring its effective and ethical integration into higher education. As GAIcontinues to disrupt traditional educational paradigms, this study seeks to explore how studentsperceive its influence on their learning and problem-solving.As part of a larger mixed-methods study
suggests that while GenAI tools can improve problem-solving and technical efficiency, engineering education must also address ethical, human-centered, and societal impacts. The dVC framework pro- vides a structured lens for assessing how GenAI tools are integrated into curricula and research, encouraging a more holistic, reflective approach. Ultimately, this paper aims to provoke dialogue on the future of engineering education and to challenge the prevail- ing assumption that technical skill development alone is sufficient in an AI-mediated world.1 IntroductionWe take as our starting premise that engineers have a responsibility to society, and conse-quently, that engineering educators have a responsibility to convey