intelligence (AI) into higher education has acceleratedsignificantly over the past decade, with AI increasingly being leveraged to personalizelearning experiences, streamline administrative processes, and enhance data-drivendecision-making. Despite this rapid expansion, there remain considerable challenges andgaps in knowledge regarding the effective and ethical implementation of AI technologiesin educational settings. Many institutions continue to grapple with issues related to dataprivacy, algorithmic bias, and the broader implications of AI on both teaching andadministrative practices. This work in progress seeks to explore the perspectives andexperiences of key stakeholders, specifically faculty and academic management staff,concerning the
addresses all seven ABET learning outcomes through lectures, workshops, team work, and individual assignments and culminates in a group-based final presentation and written paper. In addition to the project experiences, students complete several professional development activities intended to increase their understanding of various topics integral to the engineering profession, including economics, ethics, safety, social context, and technical communication. s part of their professional development, students were asked to develop their own performanceAassessments. At the beginning of the course, students were asked to design a series of activities they could complete in one month’s time in the categories of
tools in thesenior capstone design project considering those hypotheses. The survey, located in Appendix A,asks the students to describe how their team collaborated during the previous week, rate theircontentment with their work role on a scale of 0-10, and rate their team member’s level ofengagement and work ethic in the previous week on a scale of 0-10. H-1 will be evaluated usingthe results of this survey. H-2 and H-3 will be evaluated using a combination of the surveyresults and final prototype testing and presentation results.4. Case Study – Design of Aeronautical Fixture for Undergraduate Education LaboratoryThe Senior Capstone Design course is traditionally a semester-long, sponsored design project forsenior mechanical engineering
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
and Scientists, the Gordon Maskew Fair Distinguished Engineering Educator Medal from the Water Environment Federation, the Engineering Education Excellence Award from the National Society of Professional Engineers, and the Robert G. Quinn Award from the American Society for Engineering Education. ©American Society for Engineering Education, 2025 Essentials of the Nurse+Engineer: Considering Nurses’ Awareness Raising of DEI Policy When Teaching Design in Engineering Education Daniel B. Oerther Missouri University of Science and Technology, 1401 North Pine Street, Rolla, MO 65409AbstractThe first tenant in the code of ethics of the Professional Engineer (PE
. Sociotechnical thinking, defined as engaging “the interplay betweenrelevant social and technical factors in the problem to be solved,” encourages students toapproach engineering challenges holistically, integrating technical analysis with societal,cultural, and ethical considerations [17]. This perspective seeks a more inclusive and sociallyresponsible approach to engineering, challenging traditional paradigms and expanding students’critical thinking. By engaging students with sociotechnical thinking by way of the ambiguities inherent ingeophysical methods in such cases and then collecting their responses, this study explores howengineering students perceive and respond to the integration of diverse ways of knowing andcultural knowledge systems
Paper ID #45692Foundational Methods for Inclusive Engineering Research: Reflexive DesignChoices to Foster Participation and Broaden ImpactDr. Elizabeth Volpe PhD, EIT, LEED-GA, University of Florida Elizabeth is a Civil Engineering postdoc at the University of Florida. Her research interests involve responsible and ethical AI in civil engineering, responsible engineering design, leadership, the experiences of early career engineers, social sustainability, and workforce sustainability. She is also interested in student and faculty development. Elizabeth received a B.S. from Clemson University and her and M.S. and Ph.D
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
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
, 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
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
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
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
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
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
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
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
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
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
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
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
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
Colorado Boulder in the Department of Civil, Environmental, and Architectural Engineering (CEAE) and Director of the Engineering Education Program. She has been active in the American Society of Civil Engineers (ASCE), including service on the Body of Knowledge 3 Task Committee and the most recent Civil Engineering Program Criteria Task Committee. Bielefeldt’s engineering education research interests include ethics, community engagement, and sustainability. She is a Fellow of the American Society for Engineering Education (ASEE) and a licensed Professional Engineer in Colorado.Dr. Rhonda K Young P.E., Gonzaga University Rhonda Young is an associate professor in the Department of Civil Engineering at Gonzaga University
by AI has made AI literacy a crucial competency forindividual development, turning its cultivation into a “human issue [3].” This need isparticularly urgent for higher education students [4], as industries worldwide require top talentswith AI literacy to drive the intelligent transformation of business processes and products,while making trustworthy and ethical decisions [5]. In response, students are calling for AIliteracy to be integrated into their higher education curricula to better prepare for the challengesof the intelligent era and future careers. For instance, a survey on the use of generative AIamong undergraduates [6], found that students most commonly recommended offering relevantcourses and lectures, with a particular focus on
and equity causes” [6, p.708]. As such, Black facultymentors see current and prospective student mentees as an extension of themselves [6]. In response,Black faculty mentors apply social empathic and equity ethic practices in their mentoringapproaches, which builds trust and rapport with students [6]. As a result, Black faculty mentors areflooded with a disproportionate number of requests from students as well as institutions toparticipate in formal and informal diversity-related service as compared with their Whitecounterparts [6]. However, there is still an overall lack of knowledge of the types of asset-basedstrategies used by Black faculty mentors [8]-[10] in lieu of their cultural taxation [6] and howprofessional development can be used
). Addressing these challenges requiresstrategic planning, leadership, ongoing training, ethical decision making, and a genuine effort tocreate an inclusive culture. The purpose of this paper is to highlight some of the strategies usedin building Wake Forest Engineering and what has now become one of the most diverseacademic units on the Wake Forest University (WFU) campus and the highest ranked (US NewsReport 2023) academic unit on campus. Despite WFU being a predominantly white institution,Wake Forest Engineering as one of the newest academic units on campus adopted hiringpractices that enabled the hiring of a very diverse engineering faculty team – over 50% femalefaculty, 25% racial and ethnic diversity, engineering disciplinary diversity, etc