Researchers’ Capacity to Identify and Address the Ethical Dimensionsof Their WorkIntroductionThis paper sketches the motivations for and nature of a workshop on research integrity/ethics thathas been designed for and will be delivered to practicing researchers. This workshop is part ofthe IREI (Innovative Research and Ethical Impact) project at [blinded for review], funded byNSF (National Science Foundation) Institutional Transformation grant #[blinded for review]through its ER2 (Ethical and Responsible Research) program. The motivations for this workshopinclude that while research institutions are required to provide research integrity training toresearchers supported by funding from the NSF, NIH, and other agencies, there is little evidencethat the
students to see ethical considerations as part of their future work [21]. In manyrespects, they offer a powerful instructional tool: students become familiar with importanthistorical examples of malpractice as well as more mundane examples of breaches inprofessional behaviour [22] [23]. Case studies also encourage students to develop theircritical thinking and practice judgment calls related to conflicting values and stakeholderinterests that are inevitable in real engineering projects [24], [25].While case studies are an important entry for getting familiar with ethics concepts and moralreasoning, they may offer an overly simplified portrayal of the types of epistemic ambiguity,distribution of risks, value sensitive design and power differentials
Overview The course invited students to explore the usage of Generative Artificial Intelligence (GAI) tools and LargeLanguage Models (LLMs) in the User-Centered Design (UCD) process, as they considered the various advantagesand limitations they bring. It was established that interested students would need to have completed the departmentalIntroduction to UCD course (or equivalent) as a prerequisite for enrolling in this class. The course was set up as a mixture between a seminar-style and project-based structure, with daily readingsbeing due before the start of the class followed by in-class discussions and a short section of class periods beingdedicated to group work. The learning goals for the course were as follows: 1
instruction-based methods such as ethical casesstudies, quizzes and discussions [8] [9]. Other studies examined practical approaches such asinteractive development environments, where students are nudged with automated betterarchitecture choices while working on software development [10]. Finally, the psychologicalelement of empathy as a design factor in senior capstone design projects has been evaluatedthrough engaging students in the design of products for handicapped users [11].Our variation of this integrated disciplinary approach combines ethical considerations withbehavioral and motivational ones. Thus, we advocate for a collaborative research initiativebetween applied engineering and psychology. Our overarching objective is to respond to
- ware engineering, data analysis, machine learn- ing, project management, customer service Position Level Job position level Mid, Entry, Senior Certifications Professional certifications Google Analytics Cer- tified, Certified Scrum Master, AWS Certified
examinerelationships between DIT2 scores and selected variables.Future work on this project will include a repetition of the DIT2 survey for the same respondentsat the end of their second year in college, coupled with qualitative surveys and institutional datain a mixed-methods approach to facilitate identifying components of a liberal arts education thatinfluence changes in the ethical reasoning scores over the course of their college experience.IntroductionStudent development of moral/ethical reasoning is now an established part of the undergraduateengineering curriculum due to the publishing of ethics codes by professional engineeringorganizations, ABET’s Student Outcome 4, required for accreditation, and the complex waysengineering solutions interface
the following research question: What arethe similarities and differences in ethical concerns and mitigation strategies discussed in the policydocuments across these five countries?The justification for choosing the five countries is as follows: 1) These five countries/regions (namely:USA, UK, China, EU and India) provide a large portion of the world’s AI research, investment, and marketinfluence. For example, the US, UK, EU, and China combined contributed 101 notable Machine Learning(ML) algorithms, whereas India was the second largest contributor to Github’s AI project [19]. 2) The U.S.and China are leading in the development and application of commercial AI, and control the biggest AIdriven economies [20]. 3) The EU and UK are at the
component of technical competence rather than an ancillary concern. To illustrate these points, it is important to understand the difference between compli-ance and ethics, which are two essential but distinct concepts, especially in contexts likeengineering or other professional fields. Compliance is part of ethics, but ethics is broaderthan mere compliance. Compliance refers to adhering to rules, laws, standards, or proceduresestablished by an external authority. It is often a minimal requirement to avoid sanctions orlegal consequences. For example, an engineering project must comply with safety standardsestablished by regulators to be approved. In contrast, ethics concerns the moral principlesand values that guide a person’s or organization’s
learning environments. More information can be found at http://whoisxilin.weebly.com/Dr. Xi Wang, Drexel University Dr. Xi Wang is an Assistant Teaching Professor at Drexel University. She received her Ph.D. and M.Eng both in Civil Engineering, from the University of Kentucky and Auburn University. She is licensed as a Professional Engineer and LEED Green Associate. She is teaching a range of courses in construction management and will be assisting capstone design projects that directly serve regional construction firms. Her research interests include technology adoption in workforce development in the construction industry, sustainable developments in construction education, and learning motivation for student
. Stories have long been used in K-12 and college education. In particular,stories have been used in college education for students to learn about pioneers in STEM 18 ,practice decision-making 19 , etc. Furthermore, stories from traditional culture contain culturalcontexts that are often missing in case studies used for engineering ethics currently.2 DESIGN OF TEACHING MODULESFor this project, we used stories as a vehicle to help students connect virtues to engineering ethics.The main teaching modules we developed are Virtue-of-the-Week modules. To give studentsmore practice on connecting virtues to engineering ethics, we also developed an in-class activityand a student writing assignment.2.1 Selecting StoriesWe started by selecting stories
upcomingcurriculum adjustments.6. Conclusion and RecommendationsBecause the FE data consistently shows a below-average performance on ethics questions, VMIcan consider alternative means to improve students' professional engineering ethical formationand, in turn, FE exam performance. First, VMI can consider tracking how students apply ethicalframeworks in capstone projects or internships to observe and evaluate the integration of ethicsinto engineering practice. Surveys or interviews with alumni can also offer valuable insights intothe long-term impact of ethics education on professional practice. Alternative approaches in theclassroom may include more case study analysis using codes of ethics, structured reflectiveessays to focus on professional issues
basic discipline-specificconcepts, along with assignments that raise student awareness of other key skills important forABET course requirements including design, ethics, computer simulations, and life-longlearning. Each department has developed its own version of this course, numbered 121, toexpose students to their major discipline earlier in their program of study. The 121-courseoffered by the Department of Electrical and Computer Engineering (ECE 121) was selected forredesign, instead of developing a new course, because the course was already part of thedepartment core-curriculum (preventing administrative barriers necessary for introducing a newcourse from impacting the project). The limitations of this decision are that the course time
. This experience suggests that one potential role for GenAI ineducation is to address gaps or deficiencies in existing course materials. In an engineering ethicscourse, the use of GenAI can provide additional information on the environmental and societalimpacts of engineering projects. GenAI could also be used to locate information about the policyimplications of historic events and long-term impacts of engineering failures. The case studiesfeatured here had far-reaching, multi-faceted effects on the communities impacted. While thetechnical and decision-making processes featured in the textbook are important, GenAI can beuseful for developing a more holistic view of engineering case studies.Our study demonstrated that the best results from
Engineering (NAE), Infusing Ethics into the Development of Engineers, Washington, DC: National Academies Press, 2016.[11] GoodCorporation, “Ethics in the engineering profession: A GoodCorporation report for the Royal Academy of Engineering,” London, UK: GoodCorporation Ltd. Available: https://raeng.org.uk/media/x0lbgvco/ethics-in-the-engineering-profession.pdfAppendix A: HEEE Agenda and Schedule Time (EDT) Description 9:00-9:30 AM Informal gathering and networking 9:30-10:00 AM Opening: Welcome, about NIEE, project background/objectives 10:00-10:15 AM Summary of pre-event survey results 10:15-10:45 AM Breakout session #1 (exploratory) 10:45-11:00 AM Breakout reports, identifying
things to involveuniversities in innovation processes. In the summer of 2024, there was a call with several sub-projects entitled “Ethical Innovation in Health Care Technology”. One of these sub-projectswas related to the development of a PPP. Based on extensive data analysis, the PPP helps toidentify patients' presumed treatment preferences when they are no longer able to make deci-sions themselves. The PPP acts as a neutral and emotionally uninvolved support system. Thiscan be particularly helpful in cases where relatives are unable to cope or existing living willscannot be clearly applied to the current situation. Such technological support not only relievesthe burden on relatives, but also strengthens the confidence that the medical care