team has developed exercises for theintroductory Statics course that serves as most students’ first introduction to engineeringproblem solving.Currently, the U.S. engineering workforce remains 90% white and male; engineering, inparticular, has not attracted women and URMs. Baccalaureate degrees received by bothURMs and women in engineering peaked in 1999-2000 and have trended downwardsince then[1] A study conducted by Engineers Dedicated to a Better Tomorrow used theNSF WebCASPAR database to document that although about one half of earnedbaccalaureate degrees in S&E as a whole go to women, in physics, engineering,engineering technology, and computer science, these rates dropped to one in five[2].While in 2008 women earned 18.5% of
statistical concepts which are frequentlymisunderstood by students at this level16.It should certainly be pointed out to students that this approach provides a very conservativenumber because it assumes worst case addition of inaccuracies and that more sophisticatedtechniques will be introduced later. If students are familiar with basic statistical techniques wecan differentiate between random and systematic errors and show that random errors can bereduced by averaging the results of repeated measurement. In this case, for random errors, therange can be replaced with 2s / n , where s is the experimental standard deviation and n is thenumber of samples averaged. This gives a 95% coverage interval for normally distributed dataand, by Chebyshev’s
to the current phase “Expansion Development” (NSF DUE-1022750).References1. Acharya R, Wasserman R, Stevens J, and Hinojosa C: Biomedical imaging modalities: a tutorial. Computerized Medical Imaging and Graphics 19:3-25, 1995.2. Allan GL, and Zylinski J: The teaching of computer programming and digital image processing in radiography. Intl. Journal of Medical Informatics 1998; 50:139-143.3. Alon P: Bringing the Internet and multimedia revolution to the classroom. Campus-Wide Information System 17:16-22, 2000.4. Athanasiou S, Kouvaras I, Poulakis I, Kokorogiannis A, Tsanakas P, and Koziris N: TALOS: An interactive
weeks in introductory soils courses. The high-techflavor of x-ray CT can be attractive to these students. Anecdotal comments from students usingthis approach have been positive and encouraging; however, the newness of this approachprecludes the presentation of statistical assessments in this paper. A more quantitativeassessment of student learning will be assembled in future semesters based on additional studentfeedback.AcknowledgementsExperimental x-ray CT analyses conducted by former students Brent Nielsen, Josh Nichols, andBryant Robbins were useful in developing the simplified approach described in this paper. Theirvaluable contributions are acknowledged and greatly appreciated by the authors.References Cited1. Alshibli, K. A., Batiste, S
retail price of this new OMAP- Page 22.1118.2based system is $149 (USD),2 while the suggested retail price for the still-available C6713 DSK is$395 (USD). When compared to the TMS320C6713 DSK, this new experimenter kit has several Figure 1: The new LogicPD Zoom OMAP-L138 eXperimenter Kit.changes, and depending upon the intended application these changes may or may not be consid-ered improvements. The OMAP-L138 SoC includes a multi-core processor that contains both aC6748 VLIW digital signal processor and an ARM926EJ-S RISC general purpose processor, bothrunning at 300 MHz. In the experimenter kit configuration, the processor has 64
and frequently with little interaction. This paperdiscusses the potential of BIM for improving collaborative AEC education, and proposes a wayforward for Universities, based on the outcomes of a series of surveys and interviews with arange of industry and academic stakeholders in the AEC professions, examining current andfuture practice in this important area.The need for collaboration in the AEC professionsIn the U.S., approximately eight per cent of the total workforce in 2007 was employed inconstruction and the industry contributed $611 billion, or 4.4 per cent of the gross domesticproduct (GDP) in that year1. Similarly, the construction industry represents approximately six percent of both Australia‟s and the UK‟s GDP2, 3. But despite the
history of engineering distance learningat the University of Florida, and a one year snapshot of enrollments and students. The core ofthe work goes through UF EDGE basic model used to optimize resources and time including: thecombined distance and campus classroom structure, infrastructure for online delivery, coursemanagement system and online optimization tools, curriculum for online delivery, and thedistance exam proctoring process.1. Introduction: UF EDGE History, Departments, and Students.The University of Florida began offering on-site distance learning instruction at select Floridacompanies in the 1950’s. In 1964, the UF College of Engineering launched the first livegraduate engineering courses broadcast from UF with real time two-way
course time restrictions and itwas based on puzzle questions that may not accurately identify critical thought.DiscussionThis paper focuses on the beginning portion of the study involving three cohorts and their fouracademic years at the University of Louisville. The freshman data on the CA (critical thinkingassignment) and the IFR (independent faculty rating) of the CA is being used to create thebaseline for comparison as each of thecohorts’ progress through their academic careers at J.B.Speed School of Engineering. The second year data have been collected for two cohorts, butcohort 2 has not been analyzed yet. The IFR for cohort 2’s second year will be completed in2011.Table 4 shows the freshman data for each cohort. Since the pre/post CTA was
. Dodds, A. Howard, S. Tejada, and J. Weinberg, pp. 35-41. Technical Report SS-04-01. Menlo Park, CA: AAAI Press, (2004). 2. S. Coradeschi and J. Malec “How to make a challenging AI course enjoyable using the RoboCup soccer simulation system, in RoboCup-98: Robot soccer world cup II: Lecture notes in artificial intelligence, vol. 1604, pp.120-124, ed. M. Asada and H. Kitano. Berlin: Springer, (1999). 3. M. Goldweber, et al. “The use of robots in the undergraduate curriculum: Experience reports,” Panel at 32nd SIGCSE Technical Symposium on Computer Science Education, Charlotte, North Carolina.. 4. F. Klassner, “Robotics as a Unifying Theme for Computing Curriculum 2001”, National Science Foundation
education and occupational codes.2. BackgroundIn this paper, definitions for STEM fall into one of two domains: education or occupation. Thespecific discipline categories used in the education domain are derived from the National Centerfor Education Statistics Classification of Instructional Programs 20008 and the Classification ofInstructional Programs 19909. The standard Occupational Classification (SOC) system is used inthe occupational domain.CIP and CIP CodesThe National Center for Education Statistics (NCES), of the U. S. Department of Education,developed the Classification of Instructional Programs (CIP). CIP includes all the disciplinesoffered in academic institutions and universities in the United States. For each discipline, there isa
.pdf [Accessed Dec 08, 2010]3. Chakraborty, S., Sharma, S. and Ray, S. (2007), Samsung Electronics (A&B): In India, , Page 22.1226.7 HBR Case Study, 906M34-PDF-ENG and 906M35-PDF-ENG4. Huang, M., Riggs, B.K., Lynn, B.C., Dongsheng, W. and Gaffney, P. (2006), Eliminate the Middleman? , HBR Case Study R0603X-PDF-ENG5. Kane-Sellers, L., Koerber-Walker, J. and Zoghi, B. (2004), Connecting Resources: A Primer for Electronics Distribution, Thomson Custom Publishing.6. Kaufman, S.P. (2007) Arrow Electronics-The Apollo Acquistion, HBR Case Study 607007- PDF-ENG7. Miller, M., Moran, A., Richardson, B., Waguespack, T., Carter, R. and
challenging factors they experiencedduring their studies at US universities. There were five different options to be selected from 1. Admission 2. Getting VISA 3. In school 4. I did not have difficult phase 5. Other (Please specify) Figure 2, shows the respondent‟s ratings of difficult phases during graduate studies. Themost difficult phase for both current students and alumni was „in school (coursework, funding,adjusting with culture, etc)‟. Alumni ranked securing job after graduation as equally difficult tothis. As shown in graph, „obtaining a job after graduation‟ was one of the most difficult phaseschosen by alumni, as this option was not provided to current students
, Refrigeration, Compressors, and Heating Systems, by Westphalen D. and Koszalinski S., Office of Building Equipment, DOE, Arthur D. Little Reference No. 36922-00, 2001.4. U.S. Household Electricity Report, Energy Information Administration, http://www.eia.doe.gov/emeu/reps/enduse/er01_us.html, 2005.5. U.S. Department of Energy Solar Decathlone Homepage, http://www.solardecathlon.gov/, 2011.6. The Future of HVAC, Part 1: A Revolution in HVAC Design, by D. Wulfinghoff, 2007.7. U.S. Green Building Council LEED Information, http://www.usgbc.org/DisplayPage.aspx?CategoryID=19, 2011.8. NCEES PE Exam Specifications, http://www.ncees.org/Exams/PE_exam.php, 2011.9. LEED Green Associate Candidate Handbook, Green Building Certification Institute, 2010.10
-15]. The Engineering Clinicalso has been shown to provide students with the opportunity to strengthen their core “a-k”ABET competencies. In addition, the Engineering Clinic provides ample opportunities to dealwith many of the “other” areas that a program needs to address such as ethics, economicconsiderations, and societal impacts. Bibliography[1] J. L. Schmalzel, A. J. Marchese, J. Mariappan and S. A. Mandayam, "The Engineering Clinic: Afour-year design sequence," presented at the 2nd An. Conf. of Nat. Collegiate Inventors and InnovatorsAlliance, Washington, D.C., 1998.[2] J. L Schmalzel, A. J. Marchese and R. P. Hesketh, "What's brewing in the Clinic?," HP EngineeringEducator,2:1, Winter 1998, pp. 6-7.[3] "Civil & Environmental
insight into this innovative learning experience.IntroductionAlthough remote laboratory experiments have been studied for educational applications since theearly 1990’s, they are still in their infancy, and are only recently becoming a reality. 1 Moore’sLaw proposes that computer technology development doubles every year, and completeddevelopmental stage can then be utilized the next year to continue these advancements. 2 Takinginto account this exponential growth in computer technology, remote laboratories are now at adevelopmental stage where their potential to become an essential tool for science education ispromising.It is not uncommon to see simulations of experiments used as supplementary educational tools.These virtual laboratories exist
present future plans.† This material is based upon work supported by the National Science Foundation underInnovations in Engineering Education, Curriculum, and Infrastructure (IEECI) Grant No.093510. Any opinions, findings and conclusions or recommendations expressed in this material Page 22.573.2are those of the author(s) and do not necessarily reflect the views of the National ScienceFoundation (NSF).VESLL: Virtual Engineering ExperienceVESLL is establishing an online interactive learning environment designed to introduce studentsto engineering concepts through visualization and collaborative problem solving. Our long-termvision is to create a
campus. Co-PI Anthony Dotson leads the VRC team. As a retiredU. S. Army Lieutenant Colonel, Mr. Dotson is in a position to provide important informationabout, and access to, military/veteran students. BCTC is in the process of developing a similarresource center for their campus efforts. Mr. Alexander DeSha, a National Guard veteran of theIraq war, was hired in November 2010 as the Military and Veterans Student ServicesCoordinator to lead the development for BCTC. Mr. DeSha is lending his experience to theircenter development efforts.The VRC focuses on four main areas of support to veterans; recruiting, transition, retention, andtransition again. While many institutions are leaning heavily on the first two, UK feels that toprovide the best
of the module are depicted in Figure 3 and 4. Figure 3. Different views of the scenarios Figure 4. Virtual lecture, parameter adjustment, and interactionScenario 2: A human cannonball is launched with an initial velocity v m/s at an angle θ, find thedistance and height the cannonball can travel. Mathematically, we can solve the problem byfinding the cannonball’s vertical and horizontal initial speeds and calculating the distances basedon two different equations (depicted in Figure 5). vy v θ vx v x = v ⋅ cos θ and v y = v ⋅ sin θ
inventories. Journal of Engineering Education, 2007. 96: p. 205-212. 4. McGee, M.G., Human spatial abilities: Psychometric studies and environmental, genetic, hormonal, and neurological influences. Psychological Bulletin, 1979. 86(5): p. 889-918. 5. Boersma, N., A. Hamiln, and S. Sorby. Work in progress-impact of a remedial 3-D visualization course on student performance and retention. in 34th Annual ASEE/IEEE Frontiers in Education Conference. 2004. Houghton, MI. 6. Hsi, S., M.C. Linn, and J.E. Bell, The rol of spatial reasoning in engineering and design of spatial instruction. Journal of Engineering Education, 1997. 86(2): p. 151-158. 7. Miller, C.L. and G.R. Bertoline, Spatial visualization
teams varies asthe CDE is dependent on faculty, postdoctoral researchers, graduate students, and their labspace. Over the past two years, research teams have worked in the engineering disciplines ofbiomedical engineering, chemical engineering, civil and environmental engineering,mechanical engineering, and electrical and computer engineering. Research teams are assignedafter participants have been provided with an overview of each field of engineering either byfaculty members or graduate and undergraduate students. Based on their desired interests,SEI participants select and rank the top two/three areas of engineering where they would liketo conduct research. Using these selections, the executive program director and leadcounselor(s) assign
. Mustar, P.,‖ Technology Management Education: Innovation and Entrepreneurship at MINES ParisTech, Page 22.633.6 a Leading French Engineering School‖, The Academy of Management Learning and Education (AMLE), 8:3, 2009, pp418—4255. Luryi, S. and Tang, W. and Lifshitz, N. and Wolf, G. and Doboli, S. and Betz, J.A. and Maritato, P. and Shamash, Y.,‖ Entrepreneurship in engineering education‖, Frontiers In Education Conference-Global Engineering: Knowledge Without Borders, Opportunities Without Passports, 2007. FIE'07. 37th Annual‖ IEEE, 2008.6. Chang, J.C. and Sung, H.Y.,‖Planning and implementation
version of this concept inventoryexam. Be aware that this is a work in progress. Please send inquiries to the David Lanning(lannind@erau.edu) or Wahyu Lestari (lestariw@erau.edu).Acknowledgements This material is based upon work supported by the National Science Foundation under Grant No. 0837009. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Page 22.645.9The authors also wish to thank student assistants Matt Bender and Brad Pols for their
m is embracedd by engineerringmanagerss as a part off their organnizations logiistics and project managgement proceess. An effecctivepractice of o quality/prrocess managgement imprroves the efffectiveness of o a system asa a whole byyaddressinng the overalll process, raather than thhe ‘silo’ (i.e.,, the lack of collaboratioon andstandardiization betw ween businesss units) apprroach. Qualitty/process management m can controlvariationn within the system s in ordder to produuce more connsistent qualiity, in the prrocess improovingthe comppetitive edgee of an organnization
Perspectives on Engaging Future Engineers, Journal of Engineering Education, Special Centennial Issue. Vol. 100, No. 1, pp. 48–88. 2. Brophy, S., S. Klein, M. Portsmore, and C. Rogers. 2008. Advancing engineering education in the P-12 classrooms. Journal of Engineering Education 97 (3): 369–87. 3. Katehi,L. Pearson, G., Feder, M. (2009) The Status and Nature of K-12 Engineering Education in the United States. The Bridge, 3(3). Retrieved January 5, 2011, from http://www.nae.edu/Publications/TheBridge/Archives/16145/16161.aspx 4. D. Evangelou, J. Dobbs-Oates, A. Bagiati, S. Liang, & J. Young Choi (2010). "Talking About Artifacts: Preschool Children's Explorations with Sketches, Stories and Tangible Objects
variousanalog/mixed-signal VLSI circuits such as current sources and sinks, amplifiers, S/Hcircuits, switching-capacitance circuits, analog-to-digital and digital-to-analogconverters, etc. They are expected to be able to design analog VLSI layouts, decidetransistor sizing, and simulate the designed VLSI circuits.2.4. EE 549 - VLSI TestingAs VLSI continues to grow in its complexity, VLSI testing and design-for-testabilityare becoming more and more important issues. This course covers VLSI testingtechniques such as such as VLSI fault modeling (stuck-at-fault), automatic testgeneration, memory testing, design for testability (DFT), etc. VLSI scan testing andbuilt-in self-test (BIST) are also covered. Students learn various VLSI testingstrategies and how
Multi-level Multi-dimensional Perspective with Mental ModelsAbstractEntrepreneurship education programs typically include a large range of student outcomesincluding knowledge, skills, and attitudes as well as outcomes that go beyond the classroom.Because of the extent of inclusions and the broad range of effects, assessing the effectiveness ofentrepreneurship education programs is frequently challenged. Based upon Block and Stumpf[1]’s idea of “hierarchy of criteria” for evaluation, the main purpose of this research is to providea multi-level multi-dimensional perspective that systematically investigates factors related to thesuccess of entrepreneurship education programs. Such programs, in turn, can stimulate and bringsuccess to new
category where our categorization largely follows the original paper4 although we haveupdated the categories to reflect the questions given on the newest version 5.0 of the DT-SSCItest. Category # Questions Mathematical Background (B) 5 Linearity and Time Invariance (LTI) 4 Convolution (C) 3 Transform Representations (T) 5 Filtering (F) 2 Sampling (S) 2 Pole Zero Plots
Examination 5 2 Draw Select Conclusions W.S.U. Rubric 4 Analyze Data 3 Collected Page 22.250.7APPENDIX B: Rubrics courtesy of W S U, Pullman, WA. Rubrics based on Likert Scale5 Has demonstrated excellence
the natural frequency of the system, and the output voltage was measuredacross the capacitor. The circuit resulted in a transfer function as shown in Equation (2). 1 T ( s) = R 1 (2) 2 s + s+ L LC The transfer function was used to create Bode plots of gain and phase angle for thedifferent values of inductance. The plots were then used to predict the
Development and Usage Representation is provided below; more detail is available inSeniow et al.’s work.12Model Development and Usage RepresentationStudent journals and memorandum reports are the primary source of information as they containall notes, references, results and calculations relevant to the project and its development overtime. Model components are identified in student journals and verified in other sources (reports,run data, oral presentations). A student researcher assembles this information and constructs thepreliminary Model Representation. A faculty member, a domain expert, then reviews andevaluates this information for accuracy and correctness. The separation of the studentresearcher’s production of the preliminary Model