Mission for a Holistic Education: Pilot ImplementationAbstractThe evolution of engineering education over the past few decades reflects the growingcomplexity of the challenges engineers encounter in today’s world. Where once technicalproficiency was the primary emphasis of engineering education, there is now a growingrecognition of the distinct but complementary role that professional formation plays in shapingwell-rounded engineers [1] [2] [3]. A holistic approach to engineering education will help usshape future engineers who possess the foundational knowledge and applied skills in theirdiscipline, as well as across disciplinary boundaries, along with global and cultural awareness,social responsibility, ethical leadership, and sustainability
Measurement Laboratory MIME 209 [3] Mathematical Applications Group D. 9-12 credits from: COMP 445 [3] Computational Linguistics COMP 550 [3] Natural Language Processing COMP 579 [4] Reinforcement Learning ECSE 415 [3] Introduction to Computer Vision ECSE 446 [3] Realistic Image Synthesis ECSE 507 [3] Optimization and Optimal Control ECSE 526 [3] Artificial Intelligence ECSE 544 [4] Computational Photography ECSE 552 [4] Deep Learning ECSE 557 [3] Introduction to Ethics of Intelligent Systems MECH 559 [3] Engineering Systems Optimization Or any 400 or 500 level special topics courses in the area of artificial intelligence with the
Capstone CourseKeywords: Capstone Projects, Electrical Engineering Education, Generative AI in Education,ChatGPT, Entrepreneurship in Engineering, Marketing and Design Requirements, ABET.1. IntroductionIn recent years, many engineering programs have integrated entrepreneurship education into thecapstone experience, blending technical engineering skills with entrepreneurial processes,namely ideation, customer discovery, client validation, and commercial viability [3] Theseprocesses enable students to translate their technical knowledge into economically relevantengineering practice. The objective is to produce graduates who are not only technicallyproficient but also capable of navigating the business landscape, ethically aware, and responsiveto
practice during the lecture time as well. After this set oflectures, students can complete Task 6 (Section 2.1.6).The last big topic is 3D design. In these lectures, students learn how to design custom parts in acomputer-aided design (CAD) suite. As with web design, the goal is not to make the studentsexperts in CAD, but rather to give them the skills to create functional prototypes for novelsituations. After these lectures, students can tackle Task 7 (Section 2.1.7).For the rest of the lectures, there are various topics. One lecture is used to demonstrate how toefficiently debug embedded systems with surface mount components. Another lecture is used todiscuss ethics in embedded systems [14, 15, 16, 17]. Finally, the last lecture brings an
of 25 second-year engineering students were selected using stratified random sampling toensure demographic and academic diversity.4.1.3 Data Analysis:Surveys were administered online and in-person.Statistical Techniques: • Descriptive statistics (mean, standard deviation) to summarize survey responses. • Correlation analysis to assess relationships between hands-on preparation and academic outcomes. • Regression analysis to identify predictors of success in engineering coursework.4.2 Qualitative Methods4.2.1 Interviews and Focus Groups: Semi-structured interviews were conducted with 25 students, lasting 30–45 minutes each.4.3 Ethical ConsiderationsThis study adhered to ethical research
challenges,particularly in terms of academic integrity and the ethical implications of AI-generated content.The potential for misuse, such as plagiarism or over-reliance on AI-generated solutions, is agrowing concern. This has led institutions to rethink traditional assessments and establishguidelines for ethical AI use. As AI continues to evolve, higher education must balance thepotential of these technologies with the need to maintain critical thinking, creativity, andintellectual integrity.In previous research, numerous studies have explored the impacts of ChatGPT on variouseducational domains, including computer science, engineering, mathematical modeling, andconstruction management. For instance, a study [1] examines how ChatGPT can enhance
Paper ID #46868Exploring Minority Undergraduate Students’ Hands-on and Research Experiencesin a Summer QISE Laboratory CourseYiXiang Shawn Sun, Virginia Polytechnic Institute and State University Shawn Sun is an Engineering Education PhD student at Virginia Tech. He is co-advised by Dr. Qin Zhu and Dr. Jenni Case. He is also the Assistant policy analyst fellow at Research Institute for Democracy, Society, and Emerging Technology (DSET, Taiwan). His research interests include Emerging technologies-informed engineering education; Engineering ethics; Engineering culture; Global engineering education; STEM policy analysis
engineering design to produce solutions that meetspecified needs with consideration of public health, safety, and welfare, as well as global, cultural, social,environmental, and economic factors”, criterion (3) “an ability to communicate effectively with a range ofaudiences”, and criterion (4) “an ability to recognize ethical and professional responsibilities inengineering situations and make informed judgements, which must consider the impact of engineeringsolutions in global, economic, environmental, and social contexts”.ConclusionsElectrical and computer engineering students are often not engaged in humanitarian engineeringprojects because many of these projects are focused on provisioning clean water or building structuresto communities. Yet, as we
difference.Measuring the EffectivenessAnonymous surveys were administered to assess students' perceptions of the integratedapproach, its impact on their learning, and overall satisfaction. Ethical approval for this studywas obtained from the University of Toronto under protocol number RIS Protocol Number46956. A mixed-methods research design was employed, combining quantitative survey datawith qualitative feedback from open-ended questions.The goal of the survey was to ask the students on their experience to answer our researchquestions. For our first research question, “Does incorporating cross-disciplinary content inprogramming labs improve students’ perceptions of real-world applications of programming?”,we asked students to what extent related-to-other
areessential.References1. Multisim. http://ni.com2. SPICE: http://ni.com3. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. https://arxiv.org/abs/1810.04805. 2019.4. Rishi Bommasani, et al. On the Opportunities and Risks of Foundation Models. https://arxiv.org/abs/2108.07258. 2021.5. Wayne Xin Zhao, et al. A Survey of Large Language Models. https://arxiv.org/abs/2303.18223. 20236. https://chatgpt.com7. Alvarez, J.M., Colmenarejo, A.B., Elobaid, A. et al. Policy advice and best practices on bias and fairness in AI. Ethics Inf Technol 26, 31 (2024). https://doi.org/10.1007/s10676-024- 09746-w8. Valerio Capraro, et. al., The impact of generative
, data-processing paths, control logic and stored- program machines.To limit the scope of this study, only the analog section of the course will be considered,primarily due to the effort required in categorizing and reassessing all student exam papers. Also,the course sits between tightly scaffolded prerequisite and subsequent analog electronics courses,so the analysis could provide insight into the students’ success in the future based on these examresults. This research was approved under Human Ethics Protocol 29248.MethodologyThe analog section of the exam comprised of five questions, totaling 86 marks. Some questionswere also split into smaller sub-questions related to the overall theme/topic of the question. Eachquestion was assessed
: Diversity Trends at Programs [18]The College actively partners with regional high schools and community colleges to expandawareness of engineering careers. Outreach activities, including hands-on demonstrations andmentoring, have proven effective in encouraging broader participation in STEM [18]–[21].Additionally, the curriculum design draws on prior experience with vertically integrated coursesequences, which reinforce skill development from foundational to advanced levels [22].Courses that address global and ethical engineering dimensions help students understand theirwork's societal impacts and the diverse communities they may serve [10]. Beyond the classroom,student-led organizations enrich the academic experience by offering peer mentoring
with the implications of chatgpt for researchers, clinicians, and educators,” Issues in mental health nursing, vol. 44, no. 3, pp. 141–142, 2023.[20] Talia Waltzer and Audun Dahl, “Why do students cheat? perceptions, evaluations, and motivations,” Ethics & Behavior, vol. 33, no. 2, pp. 130–150, 2023.
cryptography. d) To create a multidisciplinary approach that combines quantum computing, cryptography,and cybersecurity to provide a holistic understanding of the challenges and opportunities in securecomputing. e) To equip students with the skills to analyze vulnerabilities in classical hardware and quantumsystems, and design robust solutions for secure communication and computation. f) To foster interdisciplinary collaboration by combining principles from electrical engineering,computer science, and quantum physics in the curriculum. g) To prepare students for cutting-edge research or industry roles by building expertise in securesystem design, hardware security techniques, and quantum cybersecurity protocols. h) To address ethical
. Work on a team 7. Recognize basic ethical issuesMany topics in the class are introduced lightly with the understanding that they will be exploredmore in-depth in the years to follow. The learning outcomes are accomplished through a series ofin-class activities, formal laboratory sessions, and out-of-class projects. The lab sessions focusmore on the education surrounding common lab equipment and instrumentation. Projects areteam-based, with a prompt that allows choice for creativity and uniqueness while providingconstraints. In-class activities are aimed at providing students with a starting point to labs andprojects. The in-class activities and lab prep are where Tinkercad was mainly utilized in thecourse to help aid in their learning, as
,relevance, and satisfaction, as defined by Keller [25]. A pre-post, quasi-experimental design wasused in this study, with one group of students receiving PBLA-based instruction (experimentalgroup) and another group receiving traditional lecture-based instruction (control group). Since theexperimental group participated in the practice-based learning activities, while the control groupreceived traditional instruction, an ethical dilemma could exist here because the control group couldhave been treated unfairly, or held at a disadvantage, by not receiving the PBLA instruction.However, the control group continued to receive a standard instructional approach that aligns withestablished educational best practices for introductory circuits courses. The
. Paul, Minnesota. He completed his B.S. and M.S. in electrical and computer engineering at Iowa State University, with a focus on Computing and Networking Systems in his graduate program.Dr. Nicholas D. Fila, Iowa State University of Science and Technology Nicholas D. Fila is an assistant teaching professor in the Department of Electrical and Computer Engineering at Iowa State University. He earned a B.S. in Electrical Engineering and a M.S. in Electrical and Computer Engineering from the University of Illinois-Urbana-Champaign and a Ph.D. in Engineering Education from Purdue University. His research interests include empathy, ethics, design thinking, and course design.Dr. Henry Duwe, Iowa State University of Science and