, analyze and interpret data, and use engineering judgment to drawconclusions. [8]” Comparison to objective b from the a-k criteria shows that a major componentwas added to this outcome – that students must demonstrate engineering judgement in drawingconclusions for experiments. This is significant due to the strong emphasis placed on engineeringjudgement by working engineers who cite such judgements as the ultimate guide to designdecisions [9]. The inclusion of engineering judgement in this student outcome, and nowhere elseexplicitly in the outcomes (except for possibly a reference to judgement in outcome 4 whichdeals with ethics) gives an indication of ABET’s views about the purpose of laboratories asgoing beyond practical necessities. It seems
enhance cognitive learning.Learning and Teaching ActivitiesTo enhance students' learning experience, infographics are significant learning tools of teachingthat are adaptable to any set of learning. [12]Learning ActivitiesSome of the benefits of learning using the infographic tool include: a) The improvable comprehension of concepts, ideas, and information [13] b) The enhancement in the ability of critical thinking and development in the organization of ideas [14] c) The improvement in the recall of information and retention [15]The content is typically presented in a concise manner using infographics. To improve the students'engagement with the material and increase the chance of interaction, the educators can also designvarious
otherwise abstract multiphase fluidprocesses occurring within hydrocarbon reservoirs. Figure 6 shows the top view of the printed3D models with drainage and imbibition processes. In addition, in the same project, students arerequired to estimate several petrophysical properties such as porosity, grain size distribution,fluid saturation, contact angle, and displacement efficiency using open-access image processingsoftware. (a) (b) (c)Fig. 6-3D printed macro-models showing (a) the model is fully saturated with water (blue), (b)the model after drainage with air to achieve the irreducible water saturation, and (c) the modelafter imbibition to achieve the residual gas saturation [8].Undergraduate
. Postsecondary engineering students are regulardigital technology users in various forms, from study and notetaking tools to entertainmentsystems, making them highly susceptible to the negative effects of technology overuse. The mainpurpose of this research is to support health and wellness in undergraduate engineering studentsby a) promoting effective technological literacy skills and b) improving self-efficacy inunderstanding technology-life balance. The resulting best practices from this work, which havebeen condensed into an easily accessible framework, are intended to support students inmaintaining digital wellbeing throughout their lifetime. The proposed framework will allowindividuals to access research-informed strategies to improve and maintain
Paper ID #44541Social Foundations of Education as a Model for Social Foundations of Engineering:Possibilities for Engaging the Philosophy of EngineeringDr. Kathryn A. Neeley, University of Virginia Kathryn Neeley is Associate Professor of Science, Technology, and Society in the Engineering & Society Department of the School of Engineering and Applied Science. She is a past chair of the Liberal Education/Engineering & Society Division of ASEE and isWilliam J Davis, University of Virginia William J Davis, Ph.D. is an Assistant Professor in Science, Technology, and Society in the Department of Engineering and Society
for Digital Transformation: Professional Education.”https://professional.mit.edu/course-catalog/applied-generative-ai-digital- transformation[13] UC Berkeley School of Information. “Data Science 290. Generative AI: Foundations, Techniques, Challenges, and Opportunities.” https://www.ischool.berkeley.edu/courses/datasci/290/genai[14] Brown, N., Xie, B., Sarder, E., Fiesler, C., & Wiese, E. S. (2024). Teaching Ethics in Computing: A Systematic Literature Review of ACM Computer Science Education Publications. ACM Transactions on Computing Education, 24(1), 1-36.[15] Goetze, T. S. (2023, March). Integrating ethics into computer science education: Multi-, inter-, and transdisciplinary approaches. In Proceedings of
.3. The 2011 ASEE annual conference featured two milestones in the emergence of theengineering education research community: a. The Main Plenary organized by Jack Lohmann and Karl Smith and facilitated by Karl Smith, featured the engineering education research and development work of Michael Prince, Khairiyah Mohd Yusof, Jacquelyn Sullivan, Arnold Pears, David Darmofal, and Anna Dollar. b. The Networking Session, titled A Celebration of the Engineering Education Research Community, included a brief report on the Rigorous Research in Engineering Education and the Collaboratory for Engineering Education Research (CLEERhub), and the National Research Council Discipline-Based Education Research
Learning, Dublin. Gill. See chapter5.11. Grimson, W (2014). Engineering and philosophy in Heywood, J and A. Cheville(eds). Philosophical Perspectives on Engineering and Technological Literacy. A Publicationof the TELPhE division of the American Society for Engineering Education. Washington DCp 3512. ibid.13. Philosophy and the Young child curriculum promoted at Montpelier College. Firstmajor publication on this topic seems to have been Matthews, G. B (1980). Philosophy andthe Young Child. Cambridge MA. Harvard University Press.14. Festinger, L (1959). A Theory of Cognitive Dissonance. Stanford. Stanford UniversityPress.15. Johnson Abercrombie, M. L (1960) “The Anatomy of Judgement”. “An Investigationinto the Processes of
Paper ID #41301Cultivating Tomorrow’s Innovators: Navigating the Landscape of High SchoolAI LiteracyMs. Erin Bosarge, University of South Alabama Erin Bosarge is a Ph.D. candidate in the Instructional Design and Development program at the University of South Alabama, focusing on integrating artificial intelligence literacy into high school curricula. As a research assistant, she has contributed to teacher training workshops and observed the implementation of AI lessons in classrooms, gaining practical insights. Her dissertation will examine student and teacher perceptions of AI and assess how the AI4K12 framework might
developing a more fundamental understanding of the early stages of the design process to improve design practice and pedagogy, and also improve the tools with which designers of complex sociotechnical systems work. She was previously a Stanton Nuclear Security Postdoctoral Fellow at the Harvard Kennedy School’s Belfer Center for Science and International Affairs. Prior to her appointment at the Belfer Center, Aditi worked at the OECD Nuclear Energy Agency, her work, endorsed and funded by policymakers from the NEA member countries, focused on bringing epistemologies from the humanities and social sciences to academic and practitioner nuclear engineering, thus broadening their epistemic core. At the NEA, Aditi also led the
Paper ID #42866Curriculum-embedded Epistemological Foundations in Nuclear EngineeringHaley Williams, University of California, Berkeley Haley Williams is a Ph.D. candidate at the University of California – Berkeley in the Department of Nuclear Engineering. Her research includes studies of speciation and structure in molten fluoride salts. Beyond nuclear, her research interests extend to critical materials recovery and synthesis via molten salts. She is also interested in the values that underlie engineering education, and as a recipient of the Ron Gester Fellowship, she studies how beliefs about the roles and
the subject and facilitates faculty learning communities and is the co-author of ”Studying Engineering – A Road Map to a Rewarding Career”. ©American Society for Engineering Education, 2024 Evaluation of the Utilization of Generative Artificial Intelligence Tools among First-Year Mechanical Engineering StudentsAbstractGenerative artificial intelligence tools, such as ChatGPT, are freely available to anyone,including college students. Some perceive these tools as a game changer for higher educationbecause they can enhance student learning experiences in various ways. The integration ofgenerative AI tools in higher education has the potential to revolutionize teaching and learning