Paper ID #8600On Engineering Design Education: Exposing Students to Design KowledgeDr. Waddah Akili, Iowa State University Waddah Akili is an academician and a civil engineering consultant in Ames, Iowa. Has published in various fields including: geotechnical engineering, foundations, and pavement materials & design. He has been involved with contemporary engineering education issues, addressing a wide range of topics of interest and relevance to engineering institutions and practicing engineers, in the US and abroad
. determining the goal or the dependent variable. The four independent variables are as follows:Table 2: Additional References for the Variables of the a. Behavior divided into Smoking, Alcohol consumption andModel. Stress related to depression.Variables References b. Condition divided into Obesity, Blood pressure, CholesterolCholesterol level (Grundy et al., 1993) level, Diabetes, Genetics and Menopause in women.High Blood
] Page 24.789.14 Figure 1 The Four Pillars of FigureManufacturing 1 Graphic Representation Knowledge (SME 2011) of the Four Pillars of Manufacturing Knowledge [Used with permission from the Society of Manufacturing Engineers] A B C D E F G H IFigure 2 Aspects of the Four Pillars of Manufacturing Knowledge that are directly relatedto Materials Science. The letters refer to elaborations about materials/manufacturingrelationships in the subheadings within Section 5 of this paper. See also the overalldiscussion in Section 5 on the Materials section of the Four Pillars model
/externship(summer after 1st year, 2nd year, etc.). Other factors reviewed include: (a) overall goals for theinternship/externship; (b) type of internship/externship host institution (e.g., company,government lab, academic medical center); (c) source of housing and travel financial support forthe internship/externship; (d) policies for ownership of intellectual property generated during theinternship/externship; and (e) assessment methods used to evaluate the effectiveness of theinternship/externship.Introduction The investigators lead a biomedical engineering graduate training program in ImagingScience and Informatics, funded by a training grant (T32) from the National Institute ofBiomedical Imaging and Bioengineering (NIBIB). This
to remain in the engineering environment,and other performance measures that are measured on time scales in between the short and thelong haul. This paper reports on preliminary analyses of these measures between two verydifferent university environments. While all measures in this study assess the way a studentfeels about his or her engineering program, different measures look at distinctly different aspectsof the affective experience in how students perceive their (a) own ability (self-efficacy); (b)chosen field and program (task value); (c) allies in the program (peer support and facultysupport); and (d) institutional culture (university belonging
. Page 24.593.10References[1] Dagan, B. (2008). Master data management systems to be useful for ccs, other functions. Natural Gas, 24(10), 25-29. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=31872515&site =ehost-live [2] Dyché, J., & Levy, E. (2006). Serving many masters: a closer look at MDM; as important to business strategy as the EDW was, the processing of the item master was ultimately much more critical to business operations. swtuopproxy.museglobal.com. Advance online publication. Retrieved from swtuopproxy.museglobal.com/MuseSessionID=fd925b9615e67115f7e6173a6599 d7e2/MuseHost=proquest.umi.com/MusePath/pqdweb?index=0&did=145494226 1&
Paper ID #9569Social Responsibility Attitudes of First Year Engineering Students and theImpact of CoursesDr. Angela R Bielefeldt, University of Colorado, Boulder Angela Bielefeldt, Ph.D., P.E., is a Professor in the Department of Civil, Environmental, & Architec- tural Engineering at the University of Colorado Boulder. She has been on the faculty since 1996. She serves as the ABET Assessment Coordinator for the Department. Professor Bielefeldt teaches introduc- tory courses for first year engineering students, senior capstone design, and environmental engineering specialty courses. She conducts engineering education
were integrated intothe curriculum and introduced at three high school sites, i.e.; two in Arizona and one in Teaching Energy Concepts using Chain Reaction Machines (Work in Progress)Trinidad and Tobago. A total of 65 students ranging from age 13 to 18 participated in theexperience.This paper presents: a) detailed account of the design of the energy and anaerobicdigestion module and b) descriptions of the ways students applied this learned knowledgein the design and development of their chain reaction machines. The paper concludeswith a discussion of how this experience can be adapted for inclusion in formal, in-classscience courses at the middle and high-school level.Overall Structure of the STEAM Machines
to thepractices within the proposed design for a particular problem. dependency of the variables as well as how those are tweaked towards the achievement of the goal. III. DESIGN GUIDELINES B. FiguresDesign science and design activities play hand in hand. While The model was designed in order to accomplish the defineda research process as a whole, it is a problem solving process goal given certain independent variables which have eitheras well. In order to do that effectively, certain design positive or negative effect on the goal. The relationship ofthese elements would have a significant effect on the
to sharing our expertise withthem, we create a win-win situation for everyone.References1. Al-Khafaji, A.W. and Fuessle, R.W. (2014). Internationalization and Civil Engineering Program Innovation. Third Annual ASEE International Forum, Indianapolis, IN (in press). Page 20.20.9 8 2. Mintz K., Talesnick M., Amadei B., Tal T. (2014). Integrating sustainable development into a service-learning engineering course. Journal of Professional Issues in Engineering Education and Practice, 140 (1).3. Asolekar, S.R., Kalbar, P.P., Chaturvedi, K. M., Maillacheruvu K.Y., (2013). Rejuvenation of
] Gardiner, K. M., “Education for Future Manufacturing,” Proceedingsfashion by competing departments and colleges [22]. International Manufacturing Education Conference, CIMEC-2002, Univ. of Twente, Enschede, The Netherlands, April 3-5, 2002, ISBN 90-365- 17346, pp. 359-366.A key notion must be that every commercial, industrial or [8] Gardiner, K. M., and Korin, S. B., “Furthering the Integration ofmanufacturing system extends for many layers beyond actual
Structural Equations Modeling,” Manag. Inf. Syst. Q., vol. 22, no. 1, p. 14, Mar. 1998.[8] S. J. Finney and C. DiStefano, “Non-Normal and Categorical Data in Structural Equation Modeling,” in Structural Equation Modeling: A Second Course, United States of America: Information Age Publishing, Inc., 2006, pp. 269 – 314.[9] C. M. Cunningham and C. P. Lachapelle, “The impact of Engineering is Elementary (EiE) on students’ attitudes toward engineering and science,” in ASEE Annual Conference and Exposition, Louisville, KY, 2010.[10] IBM Corporation, IBM SPSS Statistics for Windows. Armonk, NY: IBM Corporation, 2012.[11] L. K. Muthén and B. O. Muthen, Mplus. Los Angeles, CA: Muthén & Muthén, 2012.[12] D. Hooper, J. Coughlan, and M. R
Carolina. He is a registered Professional Engineer,P.E., in the State of Commonwealth of Massachusetts. He is the ASEE’s campus representative at the James B. Francis College of Engineering. He was inducted in the ASEE’s Academy Fellows in 2012 based on his excellence on teaching research service to the ASEE. He is also thegraduate Semiconductor/VLSI certificate coordinator. He has been teaching and has an industrialexperience of 40+ years. He is the author of over 200 theses, dissertations and papers publishedand presented in journals/conferences of national and international repute. 7. AcknowledgementsThe author is highly grateful to the sponsors of the program from the Hi-Tech Industry
Page 24.469.7 blank, or numerical questions. The quizzes were worth 10% of the course grade and the students received their score as soon as they submitted their answers. We allowed the students to retake the quiz as many times as they wanted until they got the score they were satisfied with. Most students ended up cycling through the entire pool of questions each week. While this did not force the students to read the entire chapter, at least it helped them read the parts of the book that we thought were the most important by our choice of question. Typical questions are listed below:! 1) To improve the lifetime of a part that experiences fatigue you can: A. Paint the surface B. Lower the mean
deprived of the opportunity to take background courses such as 2D-signal processing,computer communications, radiography, and sensors and instrumentation. Compare to traditionalelectrical engineering students, the lack of hands-on lab experience becomes more apparentwhen students are working on capstone senior projects.One strategy we used to solve this issue was to include a mixed capstone project groupcomprising of computer, electronic, and biomedical engineering students. This strategy workedfor few groups but the success rate was less than thirty five percent due to the students’ lack ofpreparation and disadvantage of knowledge compared to traditional electrical engineeringstudents.To rectify this situation we proposed and developed this
Paper ID #8815Career Self-efficacy of the Black Engineer in the U.S. Government WorkplaceMr. Scott Hofacker PE, US Army Dr. Hofacker is a recent graduate of The George Washington University’s Graduate School of Education and Human Development. His research area is the career self-efficacy of racially underrepresented mi- norities in the engineering workplace. Dr. Hofacker is also the Concept Design and Assessment Focus Area Lead for the US Army’s Aviation and Missile Research, Development and Engineering Center at Redstone Arsenal, Alabama. He is responsible for the strategic planning of science and technology efforts
courses available from edX,Coursera, and Udacity and other courseware providers. Fig. 4 presents the virtual experiment Page 24.351.6associated with curriculum resources available at the web-based massive open online course(MOOC) platform edX, d a b e c Figure 4. Virtual experiment on X-ray powder diffraction integrated with the MIT course “Introduction to Solid State
. Our analysis of ratings for each of the 11 skills(not counting “sensitivity to time” and “taking questions”) shows, in general, that the reliabilityof the overall rubric is acceptable. However, there is some variation in the reliability of eachskill. In particular, for the overall results we see a. High reliability for 10 of the skills, b. Moderate reliability for an additional 1 skill.Specific results for each skill and in each setting are displayed below. Page 24.605.8Industrial Engineering Session inter-rater reliabilityAs shown in Table 2, in this session, for pairwise comparisons, every skill demonstrates
collaboration withcolleagues at our university and beyond.REFERENCES 1) Jesiek, Brent K., Yi Shen, and Yating Haller. (2012). "Cross-Cultural Competence: A Comparative Assessment of Engineering Students." International Journal of Engineering Education, 28(1): 144-155. 2) Harris, Philip R., and Robert T. Moran, “Managing cultural differences, global leadership strategies for the 21st century”, sixth edition, Amsterdam: Elsevier/Butterworth- Heinemann, 2004. 3) Downey, G.L., Lucena, J.C., Moskal, B., Bigley, T., Hays, C., Jesiek, B.K., Kelly, L., Lehr, J.L., Miller, J., Nichols-Belo, A., Ruff, S., and Parkhurst, R. (2006). “The Globally Competent Engineer: Working Effectively with People Who Define Problems
curveswith MATLAB allows students to visually solve for the (x,y) coordinates of their intersections,thus answering actual physics concepts of trajectories.For example, students typically know that a projectile thrown at a 45° angle will travel thefurthest distance. However, if there is a sloped hill, some students mistakenly believe that 45° isstill the angle that will lead to the furthest distance travelled. In the following lab example, thecurve is a polynomial of the second degree. Yet, the graphical approach applied here is identicalto the cable tension that finds the intersection of the curves and solves for physics property of thetrajectory as shown in Figures 5 and 6. (Refer to Appendix B for the complete example of Mini-Project #2
computational competencies throughout the engineeringcurricula by integrating problems of disciplinary engineering practice.CPACE Project Overview Page 24.1268.2 The CPACE project is divided in two phases, CPACE I and II. During CPACE I we: a)identified the computational competencies needed in the engineering workplace; b) developed a‘data-to-computer science (CS)-concept map’ to translate our research findings into fundamentalCS concepts that can be used in curricular implementation. Our results are consistent with otherresearch on engineering education13, 14 and details of the process and findings from CPACE I arepresented elsewhere15, 16.CPACE I
-med) and those that do not. Thisaddition, we were asked to change our first year curriculum to potentially allows for students to shift from one pathway tohave a “common first year” with the other departments within another within each grouping.the college, which included an Introduction to Engineeringcourse in the fall and a department-specific course in the B. Biologyspring. Finally, we were asked to reduce the number of Moving the biology course to the second year enablesrequired courses to allow more flexibility in schedules for the transfer students to get on track more easily, especially if theystudents. To this end we were asked to add two “free are moving from another engineering
. Shah, J.J., Kulkarni, S.V. and N. Vargas-Hernandez. 2000. Evaluation of idea generation methods for conceptual design: effectiveness metrics and design of experiments. Journal of Mechanical Design, 122: 377- 384.16. Shah, J. J., Smith, S. M., and N. Vargas-Hernandez. 2003. Metrics for measuring ideation effectiveness. Design Studies, 24(2): 111–134.17. Vargas-Hernandez, N., Shah, J. J., and S. M. Smith. 2010. Understanding design ideation mechanisms through multilevel aligned empirical studies. Design Studies, 31(4): 382–410.18. Nelson B. A., Wilson J. O., Rosen D., and Yen J. 2009. Refined metrics for measuring ideation effectiveness. Design Studies, 30(6): 737–743.19. Verhaegen P.-A., Vandevenne D., Peeters J., and Duflou J. R
Rao, University of Northern Iowa Dr. Nageswara Rao, P. (P. N. Rao) is a professor of Technology at University of Northern Iowa in Cedar Falls, Iowa. He taught at Indian Institute of Technology, New Delhi, before coming to USA. He received his B. E. degree in Mechanical Engineering from Sri Venkateswara University, Tirupati, M. E. degree from Birla Institute of Technology and Science, Pilani and Ph. D. from Indian Institute of Technology, New Delhi, India. His current teaching and research interests include Manufacturing Engineering, Metal Cutting, CNC, CAD/CAM, Product Design, Sustainability, Additive Manufacturing (RP), CIM, Tool De- sign, CAPP, MEMS and Nano Education, and Technology Education. He is the author
for secondary admission to the College of Engineering. These include theintroductory calculus, chemistry, physics, engineering, and computing courses. The tutoringcenter is co-located with the academic and co-curricular program facilities and operates Sundaythrough Thursday evenings. Tutors are upper-level students who have received a grade of A-/B+or better in each of the courses they support.Both resident and non-resident persisters viewed the tutoring program offered through the CoReExperience program favorably with over 90% of respondents indicating it as a positive or verypositive experience. However, we found that residents used tutoring more often than non-residents. Nearly 54% of residents indicated they attended tutoring at least
sustainability modules, to ensure intended learning outcomesare achieved. Bibliography1. Falk, J. H. (2003). Personal meaning mapping. In G.Caban, C.Scott, J.Falk, & L.Dierking (Eds.), Museums and creativity: A study into the role of museums in design education Sydney: Powerhouse Publishing.2. Sampson, V. (2006). Two-Tiered Assessment. Science Scope: Teacher’s Toolkit. 46-49.3. Bell, P., Lewenstein, B., Shouse, A.W., & Feder, M.A. (Eds.). (2009). Learning Science in Informal Environments: People, Places, and Pursuits. National Research Council of the National Academies. Washington: The National Academies Press.4. Falk, J. H. & Storksdieck, M. (2005). Using the Contextual Model of Learning
for this sample, so the question was reworded for more consistency within the questiongroup. In addition, two other questions were reworded for clarity. This resulted in the followingnew question items for Q3. Q3 My questions are answered (a) quickly / (b) clearly / (c) completely / (d) by the (a-d) instructor or TA. Similarly, validation and investigation of the results of Q4, the help-seeking construct, showedthat the questions about contacting an expert personally could be collapsed because we didn’tactually need to distinguish between the instructor and TA, or between email and telephone. Thequestions are now represented by one question, “By email (phone) to instructor or TA”. Inaddition, “searching online” was added
achievement and gender affect the earnings of STEM majors? Apropensity score matching approach. Research in Higher Education. doi 10.1007/s11162-013-9310-y.4 Thomas, S. L., & Zhang, L. (2005). Post-baccalaureate wage growth within 4 years of graduation: The effects ofcollege quality and college major. Research in Higher Education, 46(4), 437–459.5 Carnevale, A. P., Smith, N., & Melton, M. (2011). STEM: Science, technology, engineering, mathematics.Washington, DC: Georgetown University, Center on Education and the Workforce.6 Langdon, D., McKittrick, G., Beede, D., Khan, B., & Doms, M. (2011). STEM: Good jobs now and for the future(ESA Issue Brief No. 03-11). Washington, DC: U.S. Department of Commerce.7 Hoachlander, G., Sikora, A. C
Paper ID #10863The CARE (Center for Academic Resources in Engineering) Program at Illi-noisProf. William H. Mischo, University of Illinois at Urbana-Champaign William Mischo is Head, Grainger Engineering Library Information Center and Professor, University Library at the University of Illinois at Urbana Champaign (UIUC). He has been a Principal Investigator on a number of digital library grants from the National Science Foundation (NSF), including the National Ethics Portal grant, several National Science Digital Library (NSDL) grants, and the Digital Library Initiative I grant. He has also received an Institute of Museum
. Catropa, D. (2013) ‘Big (mooc) data,’ Inside Higher Ed., (http://www.insidehighered.com/blogs/stratedgy/big-mooc-data) 4. Allen, E. and Seaman, J. (2013) ‘Changing course: ten years of tracking online education in the United States,’ http://files.eric.ed.gov/fulltext/ED541571.pdf 5. Cecil, J. et al. (2013) ‘Virtual Learning Environments in Engineering and STEM Education,’ Proceedings of the 43rd Annual FIE Conference, Oct 23-26 Oklahoma, USA. 6. Maiti, A., & Tripathy, B. (2013). Remote Laboratories: Design of Experiments and Their Web Implementation. Educational Technology & Society, 16 (3), 220-233. 7. Sahoo, N.C. (2013) D.C. motor-based wind turbine emulator using LabVIEW for wind energy