/employment-outlook-for-engineering- occupations-to-2024.htm. [Accessed January 13, 2019].[3] CareerOneStop, United States Department of Labor, “Careers with Most Openings,” [Online]. Available https://www.careeronestop.org/Toolkit/Careers/careers-most- openings.aspx?persist=true&location=US. [Accessed January 13, 2019].[4] National Academy of Engineering, “Changing the Conversation,” 2008.[5] M. W. Ohland, S. D. Sheppard, G. Lichtenstein, O. Eris, D. Chachra, and R. A. Layton, “Persistence, Engagement, and Migration in Engineering Programs,” Journal of Engineering Education, pp. 259- 278, Revised December 2008. [Online]. Available https://onlinelibrary.wiley.com/doi/10.1002/j.2168-9830.2008.tb00978.x. [Accessed January 13, 2019].[6
therefore can make a differencethrough my work.”AcknowledgmentsThis work is supported by the National Science Foundation under Grant No. EEC-1540301. Anyopinions, findings, and conclusions or recommendations expressed in this material are those ofthe authors and do not necessarily reflect the views of the National Science Foundation.References [1] J. R. Herkert, “Continuing and emerging issues in engineering ethics education,” The Bridge, vol. 32, no. 3, pp. 8–13, 2002. [2] K. Riley, M. Davis, A. C. Jackson, and J. Maciukenas, “‘Ethics in the Details’: Communicating Engineering Ethics via Micro-Insertion,” IEEE Transactions on Professional Communication, vol. 52, no. 1, pp. 95–108, Mar. 2009. [3] S. M. J. Howland, G. M. Warnick, C. B
related field or discipline, and their experiences or examples had to be related tothe item’s intent. Finally, for coherent response choice, students’ option made on the Likert scalehad to be coherent with their elaboration. We used Muis et al.’s [12] definitions and range ofacceptable beliefs (See Table 1) to guide our data analysis. We rated the cognitive validity scorefor the three sections first and then summed the scores to obtain a global validity score for eachitem. Based on the coding principles and criteria, two trained raters independently rated eachstudent’s responses of the items in terms of all three aspects of cognitive validity. We alsoallowed additional codes to emerge and group them into new emergent themes during analyses[19
-generation college students. While students who responded their parent/guardianlevel of education was “bachelor’s degree” or “master’s degree or higher,” were coded as 0 =continuing-generation college students. This dataset includes 804 (22%) students who identifiedas first-generation college students, 2,057 (55%) who identified as having one or more parent(s)with a bachelor’s degree or higher, and 850 (23%) who did not indicate parental level of education.It is difficult to determine why students do not report their parents’ level of education, somepossible reasons may include survey fatigue, inadequate time allocated to administering the surveyin class, or the student did not know parents’ level of education. The breakdown of first
theinstructor(s), which may include: Power Supply for a Fuel Cell System; Power ConditioningUnits for PV Water Pumping; PV Maximum-Power-Point-Tracking Controller; Design a Soft-Starter for a WT Induction Generator; and Control and Power Electronics of a Small WindPower for Battery Charging, etc. In our view, power electronics and renewable energy are twoimportant topics for today power and energy engineering students. In many cases, the two topicsare inextricably intertwined [31-36]. As the renewable energy sector grows, the needs forengineers qualified to design such systems grows as well. In order to train such engineers, thecourses are needed to highlight the unique engineering challenges presented by renewable energysystems. A key element of our
; expand thecontent for more advanced research; and transfer the content into additional platforms anddistribution channels outside of the current NYU Classes.[1] L. Holman, "A comparison of computer-assisted instruction and classroom bibliographicinstruction," Reference & User Services Quarterly, v ol. 40, (1), p p. 53-60, 2000.[2] C. A. Germain, T. E. Jacobson and S. A. Kaczor, "A comparison of the effectiveness ofpresentation formats for instruction: teaching first-year students," College and ResearchLibraries, v ol. 61, (1), pp. 65-72, 2000.[3] Q. Zhang, M. Goodman and S. Xie, "Integrating Library Instruction into the CourseManagement System for a First-Year Engineering Class: An Evidence-Based Study Measuringthe Effectiveness of
. Define scope 3. Map process 4. Verify map 5. ID opportunities for improvement 6. Choose opportunities for examination 7. Form a team(s) to examine individual opportunity(s) and propose new methods or improvements 8. Team tests methods and develops recommendations 9. Team presents recommendations to department and facilitates discussion 10. Implement consensus recommendation 11. Standardize method 12. Document/Map methodThe same group of faculty tackled the second most popular choice of projects from the originalsurvey. This project was selected to improve the student progression processes performed by thefaculty and staff in the COM department. This project would address another problem that wasfrequently
. While not a large problem in the past, students switching project teams after 1 or 2semesters caused disruption and shifted student workloads. The student preference form used isincluded in the Appendix A. Student teams were assigned, following preferences as much aspossible, during session 4. Table 5 – Engineering Projects 1 course content for Fall 2015 Session Topic Instructor(s) 1 Introduction, Safety and Security F/Y 2 Skills Inventory, Mission/Vision F/M 3 Team Organization M 4 Creative Problem Solving G 5 Design Specifications
. A key outcome of this research is a Framework of Professional Responsibilities toconsider how future research can examine student cognitions, behaviors, and dispositionsabout professional and ethical responsibilities. Components of the proposed framework havebeen previously described in the engineering education literature. For example, Gilbuena etal. (2015) described project management and timeline development as developed within acapstone project. However, the students’ discussion of professional and ethicalresponsibilities aligned most closely with Besterfield-Sacre et al.’s list of professional traits.Specifically, we identified self-management, task management, and team management as thekey components of students’ experience of
new course in manufacturing systems, served as a source foran undergraduate research projects, and has led to the establishment of an interdisciplinaryfaculty research collaboration. It is expected to yield additional benefits such as the developmentof interdisciplinary courses, additional interdisciplinary research projects, and industrialcollaborations in the areas of manufacturing systems, automations, and controls.References [1] Waldorf, D., Alptekin, S. E., & Bjurman, R. (2006). Plotting a bright future for manufacturing education:results of a brainstorming session. Industrial and Manufacturing Engineering, 4. [2] Dessouky, M. M., Verma, S., Bailey, D. E., & Rickel, J. (2001). A methodology for developing a web
practices of constructing an engineering identity in a problem-based learning environment. Eur J Eng Educ. 2006;31(1):35-42. doi:10.1080/03043790500430185.7. Meyers KL, Ohland MW, Pawley AL, Silliman SE, Smith KA. Factors relating to engineering identity. Glob J Eng Educ. 2012;14(1):119-131.8. Chachra D, Kilgore D, Loshbaugh H, McCain J, Chen H. Being and becoming: gender and identity formation of engineering students. In: American Society for Engineering Education Annual Conference & Exposition; 2008.9. Johnston S, Lee A, McGregor H. Engineering as captive discourse. Techné Res Philos Technol. 1996;1(3/4):128-136.10. McNair LD, Paretti MC, Kakar A. Case study of prior knowledge: Expectations and identity
Performance with Workshop Groups," Journal of Science Education and Technology, vol. 11, no. 4, pp. 347-365, 2002.4 S. C. Hockings, K. J. DeAngelis and R. F. Frey, "Peer-Led Team Learning in General Chemistry: Implementation and Evaluation," Journal of Chemical Education, vol. 85, no. 7, pp. 990-996, 2008.5 S. Brown and C. Poor, "In-Class Peer Tutoring: A Model for Engineering Instruction," International Journal of Engineering Education, vol. 26, no. 5, pp. 1111-1119, 2010.6 T. J. Webster and K. C. Dee, "Supplemental Instruction Integrated Into an Introductory Engineering Course," Journal of Engineering Education, vol. 87, no. 4, pp. 377-383, 1998.7 R. Jacquez, V. G. Gude, A. Hanson, M. Auzenne and S. Williamson
potential areas of improvement.The remainder of this paper will summarize the physical models that were developed and utilizedin Spring 2015 to clarify challenging concepts in the introductory reinforced concrete coursetaught at the University of Illinois. The description for each physical model includes: targetconcept(s), suggested instructional activities, construction materials, as well as photographs. Thepaper will conclude with student feedback on the effectiveness of the models based on mid- andend-term course surveys. The overarching objective of this work is to provide other civilengineering educators with sample teaching tools to enhance students’ understanding ofreinforced concrete analysis/design theory and ability to visualize
affective outcomes wereinvestigated with the goal of predicting and improving engagement and connection tocommunity across a diverse range of institutions, students, teaching styles, and faculty. In theportion of the study discussed here, qualitative analysis of focus group data was used to identifydifferences in student perceptions of formal (in class) and informal (out of class) faculty supportby class size and institution type at five different institutions in engineering and computerscience majors.Research SettingThe five participating institutions in this study, described according to their Carnegieclassifications34, and their key characteristics as drawn from institutional data and missionstatements are as follows: HBCU (Masters S): A
keeping pace and routines, such as arriving on time. Finally, our study echoesprevious research in engineering education in that self-efficacy can be altered (negativelyand positively) in relatively short periods of time, which has an important effect onacademic achievement. References1. Meyer, M., & Marx, S. (2014). Engineering dropouts: A qualitative examination of why undergraduates leave engineering. Journal of Engineering Education, 103(4), 525– 548.2. Pascarella, E. T. & Terenzini, P. T. (2005). How college affects students, volume 2. San Francisco, CA: Jossey-Bass.3. DesJardins, S. L., Ahlburg, D. A., & McCall, B. P. (1999). An event history model of student departure
Testing of Hypothesis step.References1. Carper, K. L. (Ed.). (2000). Forensic engineering. CRC Press.2. Delatte, N. J., & Rens, K. L. (2002). Forensics and case studies in civil engineering education: State of the art. Journal of Performance of Constructed Facilities, 16(3), 98-109.3. Schweitzer, N. J., & Saks, M. J. (2007). The CSI effect: Popular fiction about forensic science affects the public's expectations about real forensic science.Jurimetrics, 357-364.4. Chen, S. E., & Janardhanam, R. (2013). Forensic engineering education reform. Proceedings of the ICE- Forensic Engineering, 166(1), 9-16.5. The American Heritage® Dictionary of the English Language, Fourth Edition Copyright © 2004, 2000 by Houghton Mifflin
. Cynthia C. Fry, Baylor University Cynthia C. Fry is a Senior Lecturer of Computer Science and the Director of the Computer Science Fel- lows program at Baylor University. She teaches a wide variety of engineering and computer science courses, deploys a series of faculty development seminars focused on Curiosity, Connections, and Cre- ating Value, and works collaboratively and remotely with a series of colleagues on the development of EML-based courses. She is a KEEN Fellow.Dr. Kenneth W. Van Treuren, Baylor University Ken Van Treuren is an Associate Professor in the Department of Engineering at Baylor University. He received his B. S. in Aeronautical Engineering from the USAF Academy in Colorado Springs, Colorado
should befocused on the specific subjects instead of providing too much computational support. Thus,further research is necessary to identify what are the differences between different type ofchallenges and the level of scaffolding in student understanding and student performance intransfer tasks.AcknowledgementsThis research was supported in part by the U.S. National Science Foundation under the awards#EEC1329262 and #EEC1449238. Page 26.744.10References1 Turner, P., Petzold, L., Shiflet, A., Vakalis, I., Jordan, K., & St. John, S. Undergraduate computational science and engineering education. Society for Industrial and Applied
-stateproblem (Fig. 1) was adopted from an exercise at the end of Chapter 4 (“Two-Dimensional,Steady-State Conduction”) of Incropera et al.’s textbook25, while the transient, semi-infinitemedium problem (Fig. 2) was adopted from an exercise at the end of Chapter 4 (“Transient HeatConduction”) of Çengel and Ghajar’s textbook13.After the introduction of the problem statement and summaries of the educational objectives andrelevant FE and course theory, each ALM includes the following solutions steps (these steps areapplicable to thermal ALM’s using SolidWorks and SolidWorks Simulation, but similar steps arefollowed for ALM’s that use other software packages): 1. Using SolidWorks to create a 3-D model. The steps required to draw the model in
%), African American (3.8%), Hispanic/Latino American (9.2%). Twenty-six percent ofthe sample identified as international students, and a similar percentage (24.2%) identifiedEnglish as their second language.Protocol To evaluate the effectiveness of the new interpersonal communication focused content, arandomized controlled trial was conducted, as it provides the strongest evidence for evaluatingthe effectiveness of an intervention49 An essential component of randomized controlled trials isthat participants are randomly split between treatment and control groups. Control group(s) arenot exposed to the intervention, while treatment group(s) are. Following treatment groupexposure, differentiations between the treatment and control groups are
examination data.References[1] Garrison, D., & Vaughan, N. (2008). Blended Learning in Higher Education: Framework, Principles, and Guidelines. San Francisco, CA: John Wiley & Sons, Inc., 4-8.[2] Bourne, J., Harris, D., & Mayadas, F. (2005). Online Engineering Education: Learning Anywhere, Anytime. Journal of Engineering Education, 94(1), 131-146.[3] Dziuban, C., Hartman, J., Juge, F., Moskal, P., & Sorg, S. (2006). Blended Learning Enters the Mainstream, In C. Bonk, & C. Graham (Eds.), The Handbook of Blended Learning: Global Perspectives, Local Designs (195-206), San Francisco, CA: John Wiley & Sons, Inc.[4] Twigg, C. (2003). Improving Learning and Reducing Costs: New Models for Online Learning. Educause
a) The weight of the new chassis is still heavier than the original fuel cell car, which reduces run time. b) The fuel cell car`s maneuverability is limited by the size of the chassis and the type and number of sensors. c) Running time is still short (2 minute approximately) so it would be beneficial to increase this. d) New fuel cell car requires twice as much fuel in order to maintain original run times.The case activities, course concepts and report due dates were planned for five stages,summarized in Table 2. Ultimately, the students recommended design improvements for the nextversion of the chassis based on the case activity results. Students worked in teams of five andcompleted
social development into engineering studies8 or using PBL inleadership development9.On the other hand, general frameworks have been used for the universities to improve theirprograms and operations. The main assumption is that the same framework used by an industryis adjustable for all kind of organization, including higher education institutions. An example isthe Baldrige Education Criteria for Performance Excellence explored and adapted for some USuniversities in the 90’s. The Criteria provides codified values and concepts of performanceexcellence from industry to education. Even though models developed outside education Page 26.86.3environments
- Page 26.108.2income students, and/or students who start college significantly later than 18 years of age are atbest underrepresented, and at worst socially marginalized in many engineering classrooms.Furthermore, McIntosh explains that the myth of monoculture assumes that there is a single“normal” experience8. Recognizing and acknowledging that a “monoculture” is embeddeddeeply in the engineering education system may not be easy for those of us who are engineeringeducators and researchers. McIntosh points out that such a monoculture mirrors that of the USsocial system, not merely by what she calls “active forms” of interlocking oppressions, but moredeeply—in embedded forms—forms which “member[s] of the dominant group are taught not tosee”9
launchesstudents into a successful future by promoting academic engagement, encouraging success, andimproving the overall student learning satisfaction.References1. Advisory Committee to the National Science Foundation, Directorate for Education and Human Resources, “Shaping the Future: New Expectations for Undergraduate Education in Science, Mathematics, Engineering, and Technology (SME&T)”, NSF 96-139. Page 26.120.132. Cudney, E., Corns, S., Grasman, S., Gent, S., and Farris, J., “Enhancing Undergraduate Engineering Education of Lean Methods using Simulation Learning Modules within a Virtual Environment”, ASEE Annual Conference &
success. 4. Flipped classroom strategies that involve providing instructor feedback to students on an individualized basis require significant resources. Scheduling and proper classroom setup can pose additional challenges. Institutions must adapt to accommodate the changing educational needs.References 1. Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 201319030. 2. Prince, M. (2004). Does active learning work? A review of the research. Journal of engineering education, 93(3), 223-231. 3. Tucker, B
. 107th ASEE Annual Conference & Exposition, St. Louis, Missouri.14. System Dynamics Society (2015) www.systemdynamics.org15. Forrester, J.W. (1961) Industrial Dynamics. Cambridge, MA: The MIT Press. Reprinted by Pegasus Communications, Waltham, MA.16. Forrester, J.W. (1969) Urban Dynamics. Cambridge, MA: The MIT Press. Reprinted by Pegasus Communications, Waltham, MA.17. Aström, K.J., and Murray, R.M. (2008) Feedback Systems: An Introduction for Scientists and Engineers. Princeton University Press.18. Palm, W. J. (2014) System dynamics. New York, NY, McGraw-Hill Science.19. Zelinka, I., Vaclav, S. and Ajith, A. (2013) Handbook of Optimization: From Classical to Modern Approach. Berlin: Springer
images, it also tells you these theories behind” (Student CE_Se_03). “We use a lot of quantum in doing…like bonding… how the orbital form into bonds… the models of those help me … in pulling out … this is how a s orbital looks like, this is how a s orbital looks like…” (Student CE_Se_01).Integrated with interactive capabilities, students could manipulate and explore a givenphenomenon and understand the abstract concept, for example, one student said, “you could drag electrons like different levels and achieve like different colors and say wow that’s cool why did that happen. And you kind of, work through that in your head” (Student P_Ju_01). To off-load complicated mathematical calculations. Quantum mechanics
author(s) and do not necessarily reflect the views of the NationalScience Foundation.Bibliography1. Leaning, J. & Guha-Sapir, D. Natural Disasters, Armed Conflict, and Public Health. N. Engl. J. Med. 369, 1836–1842 (2013).2. Garriga, E. & Melé, D. Corporate social responsibility theories: mapping the territory. J. Bus. Ethics 53, 51–71 (2004).3. National Society of Professional Engineers. NSPE Code of Ethics for Engineers. (2007).4. Herkert, J. R. in Social, ethical, and policy implications of engineering: selected readings 45–73 (IEEE Press, 2000).5. Hess, J. L. et al. Empathy and caring as conceptualized inside and outside of engineering: Extensive literature review and faculty focus group analyses. in
. 20, no. 3, pp. 305-312, 2004.[8] C. Dym, A. Agogino and O. Eris, "Engineering design thinking, teaching, and learning," Journal of Page 26.1100.15 Engineering Education, no. January, 2005.[9] N. Hotaling, B. B. Fasse, L. F. Bost, C. D. Hermann and C. R. Forest, "A Quantitative Analysis of the Effects of a Multidisciplinary Engineering Capstone Design Course," Journal of Engineering Education, vol. 101, no. 4, pp. 630-656, 2012.[10] J. L. Zayas, J. S. Lamancusa, A. L. Soyster, L. Morell and J. Jorgensen, "The Learning Factory: Industry- Partnered Active Learning," Journal of Engineering Education, no. January 2008, pp