member of a knowledge in broader public, policy, professional and communication of a and historical, Competencies principles and then science principles and then apply that the experiment for practice, user needs, multidisciplinary team mechanics. social impact, or ethical conduct project to technical
transformation and artificial intelligence 3. Enhancing Undergraduate Education and 5. Enabling regional initiatives in entrepreneurship Curriculum Improvement and innovation 4. Ethics and Society in Engineering Education 6. Entrepreneurship and innovation to overcome the 5. Government, Industry, and University economic and financial crisis 6. Management of Engineering Education 7. Equal rights, opportunities and spaces for women in 7. Online and Remote Laboratories Latin America and the Caribbean in the 8. Recruitment and Retention in Engineering professional field 9. Technology for
Paper ID #47277Harnessing the Power of GenAI: A New Era for Data Science Education forCivil and Environmental EngineeringMatthew Yukio Takara, Carnegie Mellon University Matthew Yukio Takara is a Ph.D. student in the civil and environmental engineering department at Carnegie Mellon University. He holds a B.S. in civil engineering with a minor in data science from the University of California, Berkeley and a M.S. in civil engineering from Carnegie Mellon University. In addition to his interest in engineering education research, his thesis research focuses on the sustainable and ethical use of AI and sensing technologies in
University, Syracuse, NY. Registered Professional Engineer (Ohio). Robinson’s teaching approach comes from an amalgam of academic, industrial (Bell Labs), governmental (VA) and clinical experiences, plus an interest in science and ethics from his undergraduate days.Ms. Loretta Driskel, Clarkson University Since the late 1990’s my passion has been to create engaging, diverse teaching and learning experiences for students and faculty. As the senior instructional designer at Clarkson University, I have presented at conferences such as the Online Learning Consortium and I have presented at a wide variety of other venues including ADEIL; Sloan-C International Online Learning; Sloan-C Blending Learning; eLearning Consortium of
about and practice sustainability. Bielefeldt is also a licensed P.E. Professor Bielefeldt’s research interests in en- gineering education include service-learning, sustainable engineering, social responsibility, ethics, and diversity.Ms. Leslie Nolen, American Society of Civil Engineers Leslie Nolen, CAE, serves as director, educational activities for the American Society of Civil Engineers. She brings over 20 years of association management experience to her work with ASCE’s Committee on Education on issues of importance to the undergraduate and graduate level education of civil engineers. American c Society for Engineering Education, 2021 Civil
experience, perceived reliability of AI-generated content, and the extentto which AI aligns with their learning goals [9-12]. Moreover, concerns about the accuracy of AIoutputs and ethical considerations, such as potential biases in AI algorithms, have been raised byboth students and educators [13-16].Studies involving generative AI tools in STEM education suggest a mixed response: studentsappreciate the efficiency and accessibility of AI tools but remain cautious about over-reliance andthe lack of critical evaluation skills when using AI-generated solutions. This highlights the needfor educational interventions that not only incorporate AI tools but also teach students how tocritically evaluate and effectively integrate these technologies into
contradictions that arise in students’education surrounding ethics, including how engineering instructors often allude to theimportance of ethics in engineering practice but then avoid explicit discussion of ethical mattersthat arise in the context of students’ coursework. This type of contradiction served as a catalystfor our thinking about some of the other ways in which engineering students receive and copewith conflicting messaging across their educational experience, especially where implicitpractices regularly contravene explicit messages. As with the hidden curriculum scholarship inengineering education generally, we are interested in how implicit messaging undermines effortsto create more inclusive, more authentic educational experiences
, 5 ethics, etc.). The other activities in that third instance were modeled on a class that had been well-received by students but had not been optimized to support doctoral students. ● Wave 2-Pivot. The fourth instance marked a new direction; a direction in which the student selected readings played a role in 100% of the learning experience. Responding to comments that the engagement with the student-selected readings in instance 3 had promise but was too fast; in instance 4, engagements with the student-selected readings were distributed over the entire 10-week term. In addition, instance 4 featured 12 analysis questions (each coupled with conceptual readings) that were applied to the student-selected
Paper ID #37226Engineering or Physical Sciences: How to Choose? An Exploration of HowFirst-Year University Students Choose between Studying the PhysicalSciences and EngineeringDr. Janna Rosales, Memorial University of Newfoundland, Canada Janna Rosales works at the crossroads of the sciences and humanities, where she explores the intent, values, and needs that go into the decisions we make about technology. She teaches ethics and profes- sionalism in the Faculty of Engineering and Applied Science at Memorial University of Newfoundland. She collaborates with the Memorial University-based MetaKettle Project, which studies the
) papersincluded the term “social justice,” compared to 49 in 2015 [8]. Although mentioned, socialjustice was not the primary focus of the majority of these articles. Bielefeldt interviewed 1,268faculty who embed ethics and societal impact issues in their classes and found that 27% of thesurveyed faculty integrate social justice/poverty topics into their teaching [8]. The facultyinterviewed believed that teaching social justice topics was insufficient in their programs,although no broad consensus exists on what level would be sufficient.In general, the literature demonstrate that two primary approaches have been used to integratesocial justice into the engineering curricula: one approach dedicates a single course that focuseson teaching engineering ethics
et al. [20], the recent non-traditional approaches of gamification [21], behavioralaspects [22], multidisciplinary techniques [23], and ethical aspects [24].AI Education. AI is a challenging topic for beginners to learn due to complex fundamentaltheories (e.g., machine learning, game theory) [25]. In order to motivate learners and help themlearn, researchers proposed several methods to teach AI to students including the cumulative wayto teach AI components [26], the use of games [25, 27–29], emotional intelligence [30], andconsideration of ethical aspects [31, 32]Cybersecurity and AI Education. In terms of the studies that consider both cybersecurity andAI education, there exists only one study in the literature. Farahmand [33] shared the
solidunderstanding of professional and ethical responsibilities.Civil Engineering Program Learning OutcomesThe program learning outcomes set to help graduates of the civil engineering program to gaincompetence, and to apply the knowledge of mathematics, science, and engineering. The plan wasdesigned to enable students to gain the skills to design and conduct experimental testing,simulate, analyze, and interpret data and can design a system to meet the set needs withinrealistic boundaries such as environmental, social, economic, political, ethical, health and safety,and sustainability. Students are expected to have the capacity to work effectively onmultidisciplinary teams, to develop the skills to classify, articulate, and solve engineeringdiscrete problems
and/or improving things [6]-[7]. In particular, wedraw upon Lucas and Hanson’s [7] habits of mind framework that identifies and describes sixengineering habits of mind and seven learning habits of mind for their potential to informinstructional practices and learning cultures across pre-kindergarten to post-secondary contexts.We used both habits of mind – engineering and learning – for what they both afforded. Forexample, learning habits of mind include Ethical Consideration, the concern for the impact ofengineering on people and the environment, which is not captured by engineering habits of mindbut remains a value important to the field of engineering [8-9].ASEE [10] has described HoM as one component that leads to the development of
-wide learning outcome called information fluency, where students willdemonstrate an ability to “define a specific need for information; then locate, evaluate, and applythe needed information efficiently and ethically.” This institution-wide outcome would be usedas an indicator of performance in ABET EAC Student Outcome 7.In the 2016-17 academic year, an institution-wide assessment found the assessment scored forstudents in the Mechanical Engineering program were below the benchmark for informationfluency. In response, the Mechanical Engineering faculty collaborated with the campusengineering librarian to develop instruction in information literacy in the appropriate courseswithin the curriculum. Information literacy modules were developed and
sustainability. Bielefeldt is also a licensed P.E. Professor Bielefeldt’s research interests in en- gineering education include service-learning, sustainable engineering, social responsibility, ethics, and diversity. American c Society for Engineering Education, 2021 Kindness in Engineering EducationAbstractIn light of the disruptions in higher education brought about by COVID responses, faculty wereencouraged to be more accommodating of student issues. These edicts largely could be construedas showing kindness. But why should faculty kindness toward students only be manifested in theface of a global pandemic? Even before the pandemic there was a growing
are four main attributeswithin this dimension: 1) The epistemological openness attribute captures the inclination of anengineer to “recognize and value the subjective experiences and perspectives of others as validand important source of knowledge” [1, p. 135]. Epistemological openness allows a researcher tocapture the thought process behind the various actions of an engineer. 2) The second attribute isthe micro to macro focus which informs the need for an engineer to consider the systems-levelimplications of their action along with the individual level implications. 3) The reflective valueawareness attribute covers the need for ethical and professional impact of an engineer’s action.The ability to reflect on their own values and improve
ethics. Her book Extracting Accountability: Engineers and Corporate Social Responsibility will be published by The MIT Press in 2021. She is also the co-editor of Energy and Ethics? (Wiley-Blackwell, 2019) and the author of Mining Coal and Undermining Gender: Rhythms of Work and Family in the American West (Rutgers University Press, 2014). She regularly pub- lishes in peer-reviewed journals in anthropology, science and technology studies, engineering studies, and engineering education. Her research has been funded by the National Science Foundation, the National Endowment for the Humanities, and the British Academy. American c Society for Engineering
University of New York (CUNY). She currently teaches relational and non-relational database theory and practice and Data Science courses to undergraduates in the Computer Systems Major. Her research focuses on three key computer areas: Web: research on the mechanisms used to organize big data in search result pages of major search engines, Ethics: techniques for incorporating ethics in computer curriculum specifically in data science curriculum and programs/curricula: evaluating Data Science programs in the US and China.Dr. Qiping Zhang, Long Island University Dr. Qiping Zhang is an Associate Professor in the Palmer School of Library and Information Science at the C.W. Post Campus of Long Island University, where she also
department is always looking to improve how material relevant to major explorationis incorporated into its introductory course as it can have a significant impact on individualstudents as well as the retention and persistence statistics in the engineering majors.Over the years, the General Engineering department has implemented a variety of methods toencourage and/or require students to learn about the different engineering majors offered atClemson. For several years, students were required to complete a series of assignments as part ofan “Individual Reflection Portfolio.” These assignments required students to researchinformation about the different engineering disciplines then write reflections related toengineering ethics and future engineering
resource factors [3]. The medical information community believes it is ethically responsibleto share clinical trial data [4]. A survey of patients participating in a clinical trial revealed 85 %of the majority perceived the benefits of sharing de-identified data outweigh any negatives [5].There remains an ongoing debate regarding best practices, merits, challenges and approaches onseeking consent to data sharing [6] – [9].Despite research indicating benefits of sharing data, some researchers are unwilling to reportscientific findings. An investigation of 1329 researchers’ data practices indicates scientists do notmake their research data electronically available to other researchers [10]. An analysis of 160reviewed articles published in the
]. Along a similar line, a potentialarea of future research will be to draw upon the tools and techniques from cognitive psychologyfor learning analytics. For example, a neuroscience research tool called portableelectroencephalogram, or EEG, has been used in cognition-based education research, forexample, on the relationship between brain-to-brain synchrony and learning outcomes [56]. Thistool could be used in engineering education research to capture brain activities; the obtained newdata source could then be integrated with other student data to predict learning outcomes amongengineering students. Another area of challenge that needs to be addressed is creating ethical policies for usingdata analytics methods in research. The limited
2018-19 accreditation cycles minor changes (underlined). Applicable beginning in the 2019-20 accreditation cycleImbedded in Criteria 3 and 5: Engineering design is the process of devising a system,Criterion 3. … within realistic component, or process to meet desired needs andconstraints such as economic, specifications within constraints. It is an iterative, creative,environmental, social, political, decision-making process in which the basic sciences,ethical, health and safety, mathematics, and engineering sciences are applied tomanufacturability, and convert resources into solutions. The process Engineeringsustainability
retention rates have beenlinked to one’s disposition towards a method of learning [8, 9]. In other words, if astudent is more inclined to learn using a particular method, then they are more likely tobenefit from using that method. This was studied using the survey by querying studentsabout a hypothetical assignment from MATE 232 (Materials, Ethics, and Society). Thenthey were asked questions about which assignment submission method they were moreinclined to choose and which assignment submission method they thought would resultin greater retention of information. An example of the hypothetical assignment is shownin Appendix B.ResultsEnvironmental ImpactAssignment components that were identified by at least 70% of survey respondents’answers were
Organizational Leadership and Supervision, students will be able to: *Problem Solver - (thinks critically, collaborates, analyzes, synthesizes Implement strategies for personal, professional, and and evaluates, and perseveres).1. organizational success. (OLS 10000 and OLS 48700) *Community Contributor – (builds community, respectfully engages own Illustrate ways human behaviors influence organizational culture and and other cultures, behaves ethically, anticipates consequences).2. success. (OLS 25200 and OLS 32700
MET210Wcont.DocumentationWhich one of the following passages uses the appropriate documentation method?Method 1The eleven outcomes (Criterion 3) which apply to all engineering programs are asfollows:(a) an ability to apply knowledge of mathematics, science, and engineering;(b) an ability to design and conduct experiments, as well as to analyze and interpret data;(c) an ability to design a system, component, or process to meet desired needs withinrealistic constraints such as economic, environmental, social, political, ethical, health andsafety, manufacturability, and sustainability,(d) an ability to function on multi-disciplinary teams;(e) an ability to identify, formulate, and solve engineering problems;(f) an understanding of professional and ethical responsibility
(N=10)participating in an NSF-funded Research Experiences for Undergraduates (REU) program at alarge research university. Positive learning outcomes gains pertained to communication skills,validation of career path, experimentation skills, valuing cross-disciplinary expertise and lifelonglearning, and gaining confidence in working independently. Low ranked learning outcomespertained to (a) leadership skills, (b) project management skills, (c) understanding ethical issues,and (d) identifying problems. Further, qualitative data analysis revealed that undergraduateresearchers faced a number of challenges and frustrations pertinent to (a) scheduling, (b) timemanagement, (c) running experiments with limited familiarity to instruments and
preparation seminar and in the majordesign experience courses. Additional assessments are done with the Fundamentals ofEngineering exam, an oral examination conducted by the members of the Industrial AdvisoryCouncil, and an extensive written and oral exit survey.Although their learning outcomes vary, all of the engineering programs at the university assessstudents for ABET criteria 3 a to k. However, there is no uniform time during students’ study forassessing students for the professional outcomes (MDE outcomes 4, 6 to 10 and 12). Forexample, some programs assess students for ethics in regular courses throughout the curriculum,some use sophomore professional seminars, others do this assessment with juniors inprofessional seminars, some programs wait
administered at thebeginning of the course to compile baseline information on students. The second survey wasadministered at the end of the course as a point of comparison. This survey included elaborateinformation such as the reason the student choose this program, academic background, workexperience, hobbies, short term and long term goals, expectations from the lab, area in which thestudent hopes to improve and the student’s perception of an ideal mentor. The students were alsoasked to rate themselves in various skills such as research skills, writing, presentation, softwareknowledge, hardware knowledge, website creation, leadership, professional ethics, mentoringskills, etc. To get a fair idea of the schedule of the student, the survey included
professional ethics. Since 1975, Dr. Pappas has consulted on a wide variety of topics including management skills, technical and scientific writing, public speaking, interpersonal communications, sexual harassment prevention, employee relations, creative thinking, diversity, and conflict negotiation. Page 14.331.1© American Society for Engineering Education, 2009 Cognitive Processes Instruction in an Undergraduate Engineering Design Course SequenceI. Introduction Critical to effective and innovative design are the intentional thinking practices that gointo the analysis