currently being developed to enhanceundergraduate curricula to meet the industrial needs for engineers with education in lean. Thepurpose of the research is to address these expectations by developing learning modules thatincorporate lean simulation models into various Engineering Management, IndustrialEngineering, and Mechanical Engineering courses at Missouri S&T, Texas Tech, and SouthDakota State, respectively. In recent years, increasing global competition, rapidly changingtechnology, and a deficit of U.S. engineering graduates have intensified the need to producegraduating engineers who are effective problem solvers and analytical thinkers, yet who can alsocollaborate on interdisciplinary teams to address complex, real-world systems. A key
through the use of LEGO-based engineering robotics. The motivation forthis study was derived from Schunn‟s work but is different in that the measurement ofproportional reasoning was purposefully planned and included a sample size of thirty students,including a control group.Norton (2006) used a LEGO-robotics context to investigate the mathematics learning of 46seventh grade students. He found that (a) the LEGO-robotics activities afforded learningopportunities that also reinforced social relationships, (b) explicit scaffolding was needed bysome students to achieve the mathematics learning, and (c) many students were able todemonstrate greater than expected mathematics and science learning. The assessmentinstruments used by Norton included a
Engineering Management (MEM) degree. This degree was popularamong students of Civil and Environmental Engineering. Alumni with this degree have reportedsatisfaction with the content of their education and enjoy successful careers. However since fewof the other college of engineering programs embraced the degree, the degree was terminated inthe late 1990’s. At this point, the department created an Engineering Management Option withinour program by securing an agreement with the College of Business to provide two MBAcourses that could be taken by our students. These two courses provided finance andmanagement instruction to engineering students but did not require prerequisites normal to otherMBA curricula. Ensuing retirements and budgetary issues
encourage students to investigate dynamic principles that atextbook or formal lectures cannot address and are generally organized into three sections: 1) An introduction - which includes (nominally three) interactive examples of applications, introductory text, graphics, animated simulations, etc., and background tutorial materials that provide a sense of real life configurations available; 2) A design, experimentation and analysis “playspace” - which allows the user to design and test circuits in a series of highly interactive models via an analytical engine that can process chosen input(s) and generate output (in the form of graphic plots, audible signals, etc.); 3) Problem sessions and games - consisting of specifically tailored
that include thefollowing systems: Navy UHF Fleet Communications Satellite (FLTSAT) down link GOES UHF down link FM radio dipole antenna C band Television-Receive Only (TVRO) link S band direct line of sight television link L band Global Positioning System (GPS)The exercise for the UHF systems is to pick one of the satellites in view, point the helix antennaat that satellite, peak the signal and find the 3db beam width by moving the antenna off centeruntil the appropriate signal drop is observed. In addition, when the peak signal is found, theazimuth, elevation and signal to noise ratio (SNR) are recorded. Students are introduced tocomponent gains and cable losses at this point, but actual values are provided in class. A
.BackgroundBloom's Taxonomy of Educational ObjectivesIn the early 1950's Benjamin Bloom[ 7 ], in conjunction with other educators, developed ataxonomy of educational objectives ranging from simple memorization to complex evaluation, asoutlined in Figure 1. Traditional teaching and testing methods tend to stress primarily the threelowest levels of Bloom's taxonomy -- knowledge, comprehension, and application. These levelsare easy to teach, comprehend, and evaluate, because problems based upon these levels tend tohave a specific concrete answer that is either right or wrong. The problem with the lower levelsof Bloom's taxonomy is that although they are useful for teaching students how to solve classictraditional problems, our students still have difficulties
Connecticut Box U-222 Storrs, CT 06269-3222 Tel: (860)486-0321 Fax: (860)486-2959 E-mail: mcutlip@uconnvm.uconn.eduINTRODUCTION Until the early 1980’s, computer use in Chemical Engineering Educationinvolved mainly FORTRAN and less frequently CSMP programming. A typical com-puter assignment in that era would require the student to carry out the followingtasks: 1.) Derive the model equations for the problem at hand, 2.) Find an appropri-ate numerical method to solve the model (mostly NLE’s or ODE’s), 3.) Write anddebug a FORTRAN program to solve the problem using the selected numerical algo-rithm, and 4.) Analyze the results for validity and
= 50 rad/s, or f3dB = 7.96 Hz. Since it is unlikely thatmeaningful temperature variations will fluctuate more rapidly than 7.96 Hz, the low-pass filterprovides a convenient means of filtering out high-frequency noise. Closing the G-pad provides a reference from ground to the filtered low signal via a 100KΩresistor. The 100KΩ resistor ensures that only enough current passes to provide a reference toground so that the filtered high and low signals can still float within the common mode range.With this arrangement, the differential input will reject up to 10 Volts of EMI energy on thesignal wires8. Page 3.153.7 An especially important
parameters of the model and ∈i is a measurement error in yi. It isassumed that ∈i is independently and identically (i.i.d.) distributed. The vector of estimatedparameters βˆ T = (βˆ 0 , βˆ 1 Κ βˆ n ) is usually calculated using the least squares error approach, by Page 3.157.2minimizing the following function: N S 2 = ∑ [yi − (β 0 + β1 x1i + β 2 x 2i Λ + β n x ni )] 2 (2
from the National Science Foundation under theCCLI program through the grant number DUE#0837747REFERENCES[1] Bonwell, C.C. and Eison, J.A., Active Learning: CErating Excitement in the Classromm” ASHE-ERIC Higher Education Report Number 1, The George Washington University, School of Education and Human Development, Washington, DC. 1999[2] Davis, C. and Wilcock E. Teaching Materials using Case Studies, UK center for Materials Education, University of Liverpool, Liverpool L69 3GH[3] White, H.B., To Improve the Academy, Richlin, L. (Ed), Vol. 15, pp. 75-91, Stillwater, OK: New Forums Press and the Professional and organizational Network in Higher Education.[4] Chubin, D. E., May, G. S., and Babco, E
. Thesetags are: - bold font, - italic font, - subscript, - superscript, - paragraphbreak, and - symbol font. Up to two random variables named var1 and var2 may beinserted anywhere in the question statement. The random variable minimum value, maximumvalue, and step size dictate the range and division of the random variables and are entered in theappropriate fields of Figure 4. The axis system (2- or 3-dimensional) is determined by entering 2or 3, respectively, in the Axis field. The minimum number of the various graphical objects isthen entered into appropriate fields. Acceptable units, separated by #’s, are entered in the Unitsfield. Point deductions for major and minor errors are entered into their respective fields. Thetitle for the graphic
). Rising Above the Gathering Storm: Energizing and employing America for a brighter economic future. Washington, D.C.: National Academies Press. Available online at: http://www.nap.edu/catalog/11463.html.6. Graham, R., Crawley, E., & Mendelson, B. R. (2009). Engineering leadership education: A snapshot review of international good practice. Bernard M. Gordon MIT Engineering Leadership Program.7. Farr, J. V., Walesh, S. G. & Forsythe, G. B. (1997). Leadership development for engineering managers. Journal of Management in Engineering, 13(4), 38-41.8. Torr, S. R., & Ofori, G. (2008). Leadership versus management: How they are different and why. Leadership and Management in Engineering, 8(2), 61-71.9. Bowman
, J. S., & Newman, S.E. (1989). Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics. In L. B. Resnick (Ed.), Knowing, Learning and Instruction: Essays in Honor of Robert Glaser (453 - 494). Hillsdale, NJ: Lawrence Erlbaum Associates.7. Lave, J. (1991). Situating Learning in Communities of Practice. In L. B. Resnick, J. M. Levine, and S. D. Teasley (Eds.), Perspectives on Socially Shared Cognition (63 - 84), Washington, D.C.: American Psychological Association.8. Vygotsky, L. S. (1978). Mind in Society: The Development of Higher Psychological Processes, Cambridge, MA: Harvard University Press.9. Brown, J. S., Collins, A., & Duguid, P. (1989). Situate Cognition and the
. Benson, T., 1997, Interactive Educational Tool for Classical Airfoil Theory. AIAA-1997-849.6. Hepperle, M., 2008, JavaFoil, http://www.mh-aerotools.de/airfoils/javafoil.htm7. Allison, J., Bidaiah, S., Colwell, D., DeFranco, R., Findley, M., Hall, E., Miller, B., and Kemper, B., Universityof Colorado Design/Build/Fly 2008 - 2009: A Guide to Designing a Stable Flying Wing Aircraft. AIAA.8. Boyer, L., and Peck, C. AC 2009-1346: AIAA Design, Build, Fly Project Highlights. ASEE 2009.9. Arena, A., Experience with the Student Design/Build/Fly Contest at Oklahoma State University. 6th AIAAAviation Technology, Integration and Operations Conference. AIAA 2006-783310. Broughton, A. An Approach to Integration of Academic Studies with Practical Applications
principle of operation of fuel cells and designprinciples of hybrid power systems. The topics covered include the need and benefits of AEDG,modeling of wind and PV power generation, energy storage devices, power electronicinterfacing, and principle of operation of fuel cells as well as hydrogen production7-18. The Page 15.414.4benefit of such broad coverage is to give the students a broad view of the various components ofAEDG. Each student picks one area to explore further by studying and presenting one or tworesearch paper(s) to the class as well as doing an end-of-term project developing a written reportand presenting the results of their work to
consent form at the beginning ofthe semester indicating that their answers could be used in this project.The introductory microprocessor course used in this project contains 11 laboratory exercises.Online quizzes were given after exercises 3-7 to collect information on the student understandingof the learning objectives. The following table gives the topic and order of the 11 laboratoryexercises conducted in our microprocessor course. The table shows, for each lab session, theassessment tool used and the targeted objective(s) measured. Table 1. List of laboratory experiments, targeted objectives, and assessment tools used. Laboratory Experiment Objective(s) Assessment Tool(s) 1 Introduction to
. Distributed systems: concepts and design. Addison-Wesley,second edition, 1994.[7] J. Farley. Java: distributed computing. O’Reilly and Associates, 1998.[8] S. P. Amarasinghe. Multicores from the compiler's perspective: a blessing or a curse? Keynote Speech,International Symposium on Code Generation and Optimization (CGO), San Jose, CA, March 2005.[9] S. Carr, J. Mayo and C-K Shene. ThreadMentor: a pedagogical tool for multithreaded programming. InACM Journal on Educational Resourses in Computing, Vol. 3, Issue 1, March 2003.[10] C. Shene and S. Carr. The Design of a multithreaded programming course and its accompanyingsoftware tools. The Journal of Computing in Small Colleges, Vol. 14 (1998), No. 1 (November), pp. 12 - 24.[11] Homepage of MIT 6.189
15.690.9Students expressed that they would have really liked to be able to use the calculator that isdesigned in the final class project earlier in the quarter to learn about unsigned and signednumbers and 2’s complement arithmetic. While we have previously included a first experiencewith the FPGA board, based on student recommendations we are replacing the ping-pong gamewith the binary calculator. The ping-pong game and other designs will be available for studentsto download and experiment with outside of class.As we have continually evolved the experiments some quarters we included a project related toDeMorgan’s theorem and in other quarters we did not. In the quarters it was included studentsdemonstrated a much better understanding of DeMorgan’s
observation by the remote users. Page 22.26.83. Assessment Tool DevelopmentThe assessment data was collected using the quiz feature within the Desire2Learn coursemanagement system, which allowed auto grading of the survey and multiple choice questions.Online quizzes were given after exercises 3-9 to collect information on the student understandingof the learning outcomes. The following table gives the topic and order of the 11 laboratoryexercises conducted. The table shows, for each lab session, the assessment tool used and thetargeted outcome(s) measured [7]. Table 1. List of laboratory experiments, targeted outcomes, and assessment tools used
Page 15.1020.121. A Companion to Science and Engineering Indicators 2004, National Science Foundation Report. http://www.nsf.gov/statistics/seind04/c0/c0s1.htm#c0s1l4, Retrieved on March 2005.2. National Science Foundation Statistics on Women, Minorities and Persons with Disabilities in Science & Engineering, http://www.nsf.gov/statstics/wmpd/sex.htm, accessed on Jan 2010.3. Freeman, C. E., Trends in Educational Equity of Girl s and Women: 2004. Retrieved from http://nces.ed.gov/pubs2005/equity/Section9.asp.4. Bentz, N. E., & Hackett, G. (1986). Applications of Self-Efficacy Theory to Understanding Career Choice Behavior. Journal of Social and Clinical Psychology, 4, 279-289, 1986.5. Beyer, S., Rynes, K., Perrault, J., Hay, K
, extracurricularactivities, and recommendations by school officials.”In the mid 1990’s the Ujima Program was impacted by the University’s emphasis on “smallerand better” campus recruitment and the overall size of the student body. As a result, the criteriafor admissions was modified for the Ujima Scholars Program by the Admissions Office in 2000in direct response to the University’s call for Colleges to raise the SAT threshold. The minimumSAT was increased from 750-800. Students with SATs between 750 and 800 with a strong highschool GPA were considered. Also students with a GPA below 2.0 and a SAT score of 950 orhigher would receive consideration if extenuating circumstances could be substantiated. TheUjima Scholars enrollment pattern remained steady until 1996
+ I2 = 2.74 mA 12V R2 R3 V3 V1 = 4.59 V — Find: R1, R2, and R3 Is Figure 7: Series-Parallel Circuit The design proceeds as follows: V1 4.59 V Ohm's Law (R1): R1 = = = 389 I s 11.8 mA Kirchhoff's Voltage Law (Outer Loop): V3 = 12 V − V1 = 12 V − 4.59 V = 7.41 V V3 7.41 V Ohm's Law (R2): R2 = = = 2.70 k
-DSPTonalityDue to the presence of a large amount of noise in the signal, the original tone of the signal mightget masked. Tonality is a measure of the signal‟s tone-like or noise-like characteristic. TheSpectral Flatness Measure (SFM), defined as the ratio of the geometric mean to the arithmeticmean of the power spectrum, is used to compute the tonality for each frame 4. P(k ) Re2[ X (k )] Im2[ X (k )] (2) GM {P(k)} (3) SFM (dB) 10 log10 AM {P(k)} SFMdB
. These can provide ideas of best practices that can belearned from these different institutions in different cultural contexts for other engineeringeducators across the world.AcknowledgementsS. M. Lord would like to thank all those at USD and SEU who made her sabbatical time at SEUin Spring 2012 possible. Page 17.9.11References[1] Unique features of USD’s Engineering Programs available at http://www.sandiego.edu/engineering/ Last Accessed 14 May 2012.[2] McKenzie, L. J., M. S. Trevisan, D. C. Davis, and S. W. Beyerlein, “Capstone Design Courses and Assessment: A National Study,” Proceedings of the 2004 ASEE Annual Conference, Salt Lake
. Page 17.30.1 c American Society for Engineering Education, 2012 INTERNATIONAL COLLABORATION IN CURRICULUM AND LABORATORY DEVELOPMENT Dr. K. P. Isaac Member Secretary, All India Council for Technical Education, India kpisaac@yahoo.comAbstract The aim of any country‟s higher education system is sustainable developmentand achieving higher growth rates. India aims to increase the higher educationenrolment rate from about 12 percent at present to 30 percent over a decade. Technicaleducation at all levels in India is witnessing a consistent growth by establishing newinstitutions, addition of courses and increase in seats
a very special, active and dynamic partnership between industry, accreditationauthorities and educations. This paper discusses these partnerships, advantages andchallenges for the future in Australia and how the partnership flows into a global market.IntroductionIn the early part of this decade, engineering accreditation bodies worldwide reviewed theirnational guidelines for engineering education to consider restructuring them such that theycould determine whether universities were actually delivering graduates ready foremployment and, more importantly, able to cope with the future requirements of theprofession. These reviews resulted in a refocusing of the engineering curriculum to outcomesrather than process. The UK‟s Royal Academy of
Page 21.55.2partnerships and collaborations”. The strategic plan went on to say that, “As science and1engineering (S&E) expertise and infrastructure advance across the globe, it is expected that theUnited States will increasingly benefit from international collaborations and a globally engagedworkforce leading to transformational S&E breakthroughs.”6 The 2010 Globalization of Scienceand Engineering Research report further highlights how the data show a global recognition ofthe need to move towards knowledge intensive economies and the important role that scienceand technology plays in “generating new jobs, economic prosperity, responses to national issuesand/or global challenges, and global competitiveness”7The importance of placing
School DLocation Lexington, KY Columbus, GA San Antonio, TX Newtown, CTTotal Enrollment 656 1,065 2,500 1,715Minority Enrollment 32% 27% 45% 5%Grade(s) 8 9 and 10 11 and 12 11 and 12Students Surveyed 50 32 35 13Teacher’s Discipline Technology Science Physics TechnologyTable 3. Characteristics of surveyed schools
-2002Accreditation Cycle.” 2. Alford, E. M., N. S. Thompson, J. Brader, B. Davidson, S. Hargrove-Leak, and E. Vilar. “IntroducingEngineering Graduate Students to Learning Theory and Inquiry-Based Learning: A Collaborative, InterdisciplinaryApproach.” Proceedings of the 2003 American Society for Engineering Education Conference.3. Barnett, V. Sample Survey principles and methods, London: Edward Arnold, 1991.4. Bransford, J. D., Brown, A., & Cocking, R. (Eds.). How People Learn: Brain, Mind, Experience, and School,Washington, DC: National Academy Press, 2000, 12-13.5. Donath, L. and R. Spray. “Linguistic Evidence of Cognitive Distribution: Quantifying Learning AmongUndergraduate Researchers in Engineering.” Proceedings of the 2004 American Society for
make its first appearance? It has probably been around since the first softwareengineer wrote a program using buffers.The first noted problems with buffer overflow occurred around 1973 [5], but only withinsoftware engineering circles. A famous article appeared in IEEE regarding the Therac-25incidents mentioned above, but when the events occurred in the late 1980’s not much attentionwas focused on buffer overflow. The buffer overflow problem became known world-wide in1988 with the Morris Internet Worm. It has continued to be a problem since, as evident by theCERT Coordination Center’s November 11, 2003 buffer overflow advisory regarding Window’sWorkstation Service. Below are some infamous buffer overflow problems in the history ofsoftware