have a clear understanding of whatthe word individual means. Instructional systems must be designed to meet the needs of theindividual, whenever possible. The author believes that there are five principles on whichinstructional systems are designed, created, formulated and implemented. The five principlesare: Define, Design, Develop, Deploy and Decide. Appendix B briefly outlines these five principles. Ernest Boyer’s research also motivated the author to experiment on new ideas in theclassroom. This is because, in the nineties, Ernest Boyer argued in “Scholarshipreconsidered: Priorities of the professoriate” that knowledge is acquired not only throughresearch, but also through synthesis, practice, and teaching (Boyer
. Page 15.859.1© American Society for Engineering Education, 2010 Measurement of Hands-On AbilityIntroduction“Practical ingenuity,” according the National Academy of Engineering, is a necessary attributefor the engineer of 20201. Hands-on ability is considered an important characteristic of practicalingenuity2. Two of the ABET criteria address hands-on skills: ability to design and conductexperiments and interpret data (criteria b); and ability to use the techniques, skills, and modernengineering tools necessary for engineering practice (criteria k)3. Employers value hands-onability and routinely ask recruits about hands-on experiences outside of classes4. A “tinkeringdeficit” has also been identified that puts females
). Creativity as an Exact Science. Luxembourg: Gordon and Breach.2. Anderson, J.R. (1983). The Architecture of Cognition. Cambridge, MA: Harvard University Press.3. Angelo, T., & Cross, P. (1993). Classroom Assessment Techniques: A Handbook for College Teachers. San Francisco, CA: Jossey-Bass.4. ASME Council on Education (2004). A Vision of the Future of Mechanical Engineering Education. ASME.5. Ball, L., Evans, J. B., Dennis, I., & Ormerod, T. (1997). Problem-solving strategies and expertise in engineering design. Thinking and Reasoning, 3, 247-270.6. Bilalić, M., McLeod, P., & Gobet, F. (2008). Inflexibility of experts – Reality or myth? Quantifying the Einstellung effect in chess masters. Cognitive
, Membrane ElectrodeAssemblies (MEAs) with similar catalyst loadings and variable nafion membrane thicknesses ofN117 (0.177 mm), N115 (0.127 mm) and N212 (0.076 mm) were purchased and utilized. A fuelcell with an active area of 50 cm2 was assembled and connected to an electronic loading deviceto record output current, voltage and power. A temperature controlled system was used to set thecell temperature in the range from 20 °C to 70 °C, in 10 °C increments. It was found that at atemperature of 50 °C, MEAs containing N212 and N115 experienced a significant powerincrease; higher temperatures did provide higher power but were not as significant as theincrease from 40 °C to 50 °C. It has also been observed that thinner membranes, at 50 °C andabove
curriculum, student performance during the summer2009 semester of Statics (115 students) was compared to performance in seven prior coursestaught by the author between 2005 and 2008. At the University of Louisville, student co-opexperiences are required and thus three full semesters are conducted each year. As such, whenstudents are in sequence, Statics is normally scheduled for the summer semester of theirsophomore year.Figure 4 displays a comparison of the grades for the previous courses and for the Summer 2009session. As shown in the figure, it appears that there was a significant shift of students to highergrades. Many of the “B-C” students appear to be in the “A-B” range. Unfortunately, the “F”students appear to have benefited little from the
power microwave source and passive component research and development, medical device development, and educational research. He has a B.S. degree in Mathematics, a B. A. degree in Spanish Language, and B.S., M.S., and Ph.D. degrees in Electrical Engineering.Lan Xiang, Montgomery College DR. LAN XIANG is an Associate Professor of Department of Physics, Engineering and Geosciences at Montgomery College. Lan earned BS and MS in Electrical Engineering from Xi'an Jiaotong University, China, and a Ph.D in Electrical Engineering from University of Pennsylvania. She currently teaches a variety of first two-year Electrical and Computer Engineering courses
Lemon Battery This interactive session will include am A1 Study of electrical circuits MON 125 Using a lemon as a battery source Sustainability – Alternative Power This interactive session will include 10:00 am to 11:30 B Study of solar power am Use of everyday materials to build a solar cooker Student Life 11:30 to 12:15 pm Lunch with a Buddy
AC 2010-2266: INTRODUCING HYBRID DESIGN APPROACH AT THEUNDERGRADUATE LEVELFiras Hassan, Ohio Northern University Dr. Firas Hassan is an assistant professor at Ohio Northern University. He finished his PhD studies at The University of Akron and worked for one year as a visiting professor. His area of research is hardware implementation of real-time embedded image processing algorithmsSrinivasa Vemuru, Ohio Northern University Srinivasa Vemuru obtained his bachelors and masters degrees in Electrical Engineering from Indian Institute of Technology, Madras in 1984 and 1986, respectively. He received his PhD from the University of Toledo in 1991. From 1991-2001 he served as faculty member in
moreindependent processors into a single package, which is capable of executing multiplethreads simultaneously. The L2 cache on a multicore processor can be either private orshared, as depicted in Figure 1 (a) and (b), respectively. Clearly, multicore processors cannaturally benefit multithreaded programs by running them on different cores concurrentlyto improve the throughput. However, unlike other advances of microprocessors aiming atthe transparent increase of single-threaded performance (e.g., frequency scaling, pipelines,caches, and superscalar architectures), multicore processors cannot automatically reducethe latency of single-threaded programs. In many cases, there is no way to effectivelyutilize the performance of additional processor cores or
. Projects under the New FormatEngineering Discipline ProjectsEnvironmental Sewer line to replace septic systems, Site remediation, Trouble- shooting operational issues at a wastewater treatment plantStructural Historical building load analysis, New structuresTransportation Interstate intersection, Road intersection, New gas pipeline Outcome Assignments Integrating the requirements of ABET assessment, the BOK, and the onsite internship experience was made fairly straightforward but the already in-place outcome assessment assignments. The assessment schedule is now on a three-year rotation and the outcomes assessed in CE 493 at present are shown in Table 3. Outcomes b, h, m, and n
5.14 0.00 0.250 0.899 0.500 0.883 0.750 0.894 1.00 0.879 1.25 0.936 1.50 0.980 1.75 1.00 2.00 1.04 2.25 1.05 2.50 1.09 2.75 1.13 3.00 1.12 3.25 1.13 3.50 1.14 3.75 1.12 3.25 1.31 The Fermentation produced 1000 g of a solution containing 0.13% alcohol. (a) Prepare a graph of ln(cell concentration) vs. time. (b) What is the lag time for the fermentation? (c) At
) (b) (c) (d)Figure 2. (a) Cole-Parmer 8890 was used to prepare inks for catalytic layers. (b) Carver AutoSeries hot press auto "C" (model 3889) was used to prepare membrane electrode assemblies(MEAs). (c) VWR vacuum oven was used to dry the MEAs. (d) Fuel cell test system 850e,Scribner Associates (with Back Pressure module), was used to test PEMFCs.Wind Power Systems Control ProjectThe main objective of this project is to educate undergraduate student researchers on developinga power system control technique for remote area application involving wind turbines. Thepower system including wind turbine has an uncertain source of power which depends on thespeed of wind. To feed sensitive loads
end of chapter problems in a textbook. Finally, Smith remarks: “During the past 90 years, nearly 600 experimental and over 100 correlational studies have been conducted comparing the effectiveness of cooperative, competitive, and individualistic efforts. These studies have been conducted by a wide variety of researchers in different decades with different age subjects, in different subject areas, and in different settings. More is known about the efficacy of cooperative learning than about lecturing, the fifty-minute class period, the use of instructional technology, or almost any other aspect of education. Cooperation among students typically results in (a) higher achievement and greater productivity, (b) more caring
applications may provide further insight.ConclusionsThis paper reviewed the historical underpinnings of cloud computing along with an overview ofthe technology background of cloud computing. The final sections of the paper described theresults of an action research project that was implemented to address the implementation of acloud computing application in an undergraduate information systems class.Bibliography1. Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R. H., Konwinski, A., et al. (2009). Above the Clouds: A Berkeley View of Cloud Computing EECS Department, University of California, Berkeley.2. Editions and Pricing. (2009). Retrieved from http://www.salesforce.com/crm/editions-pricing.jsp3. Hayes, B. (2008). Cloud computing
in charge of the challenge, and they select atleast one ‘A’, ‘B’ and either ‘C’ and ‘D’ or ‘Redo’ exemplars. These papers areanonomyzed, annotated and posted for all T.A.s as examples of the work standard for thepaper. While this is very time consuming, it does ensure consistency to a much greaterdegree than previously demonstrated in the course.In the first year of the new evaluation format, a sample set of papers were evaluated bycoaches using the exemplars, and then compared, on four separate occasions. The firstgroup of papers, (the second report of the first semester) showed a discrepancy of ~2letter grades (A – B+, for instance). While a direct comparision to the numeric system isimpossible, using the departmental average of 15% for
engineering proposal consisting of a problem statement, project objectives, preliminary B.O.M and a plan of action. This is due one week after the project is assigned. 2. Project Progress Updates: The students provide a weekly update to the instructor and their team either via email or through pre-scheduled meetings. Altogether 9 updates are required. In these updates the teams are required to communicate the following: a. What happened the past week? b. What will happen this week? c. What are the major issues the team is facing? 3. Project Report: At the end of the term the teams submit a comprehensive project report. This report provides the details of how the project is executed. It
complemented by media based instruction to facilitate thelearning of engineering fundamentals with minimal time. The authors intend to repeat thisexperiment over another several years. Experimental results will be shared with the academiccommunity in the future through appropriate publications.References1. P. Cohen, B. Ebeling and H. Kulik, “A meta-analysis of outcomes studies of visual-based instruction,” Educational Communications and Technology Journal, vol. 29, no. 1, pp.26-36, March, 1981.2. J.V. Powell, V.G. Aeby Jr. and T. Carpenter-Aeby, “A comparison of student outcomes with and without teacher facilitated computer-based instruction,” Computers & Education, vol. 40, no. 2, pp. 183-191, February, 2003.3. H. L. Chen, L. R
surrender of the claim that science is true. We may be living nearer thanwe suppose to the end of the Scientific Age.”2 Page 15.1367.18Bibliography, Appendix B:1. White, L., “The Historical Roots of our Ecological Crisis.” Science, vol. 155, p.1203-1207, 1967.2. Lewis, C.S., Miracles: a preliminary study, Collins, London, p. 110, 1947. Page 15.1367.19
graduates have:a. an appropriate mastery of the knowledge, techniques, skills, and modern tools of their disciplines,b. an ability to apply current knowledge and adapt to emerging applications of mathematics, science, engineering, and technology,c. an ability to conduct, analyze and interpret experiments, and apply experimental results to improve processes,d. an ability to apply creativity in the design of systems, components, or processes appropriate to program educational objectives,e. an ability to function effectively on teams,f. an ability to identify, analyze and solve technical problems,g. an ability to communicate effectively,h. a recognition of the need for, and an ability to engage in lifelong learning,i. an ability to understand
(16)The linear natural frequencies and mode shapes can be found by assuming solution forms: λ1 ? A sin ∗ s Τ + , λ 2 ? B sin ∗ s Τ + (17)Substituting into equations (16) gives: A 1 − χ / s 2 − B ] /χ _ ? 0 A ] /χ _ − B 1 − χ / s 2 ? 0 (18)For non-zero solutions, the determinant of the coefficients must be zero. This gives a polynomialin s , from which the natural frequencies can be obtained. Equations (18) give the associatedmode shapes
engineering laboratories with accessavailable to all faculty and students, mainly for classroom use. Many electrical/computerengineering leading industries use MATLAB and its toolboxes.Waves on Transmission LinesIn a transmission lines first approach towards teaching electromagnetics, students are first (a) (b) Figure 1: MATLAB movie snapshots taken (a) just before and (b) just after wave is incident on the load. The incident wave is blue and reflected wave is red. Page 15.509.4exposed to wave behavior on transmission lines
been designed for students to investigate the effect ofmixing time, particle size and loading configuration in a statistical design. The experiments anddata analysis are conducted over multiple class periods, and students are exposed to experimentaldesign strategies. A 5 L constant frequency V-mixer is used for laboratory experiences incourses, projects and research. Figures 1a and b show the mixer and the loading operation for amixing experiment.Figures 1 a) 5 L V-mixer b) Loading mixer for experimentFactorial and response surface Box-Behnken experimental designs are used and students assessthe efficacy of experimental design strategies. Variables studied include particle size and particlesize difference, mixing time
D D M M M Presentation Figure 1: Signature writing assignments mapping for MS in Wireless Communication Program CIS601 CIS602 CIS603 CIS604 CIS606 CIS607 CIS608 CIS609 CIS620 CIS620 A B Periodic progress ID M report Cover letter for a report I D D D D D D D M M or proposal Business
electroniccomponent. The substrate surface is then augmented with micro-machining to produce a matrixof micron sized posts. Finally, these posts can be chemically augmented to further improve theirinteraction with the fluid of choice. (A) (B) (C) Copper Substrate Micro-pin-fins Chemically augmented postsFigure 1: Schematic of a (A) traditional copper substrate heat sink, (B) substrate with micro-pin-finsmachined into surface, and (C) final augmented design with chemically enhanced posts. The surface enhancement is one part of the optimized design solution
. These include establishing and maintaining a robust understanding ofmath and science, learning how to include the approximations of real life, searching for relevantinformation, creating a conceptual and subsequent mathematical model, using data within themodel, testing the model results and further, and providing insight and validation on the obtainedtest results. It is expected that a particular level of self-efficacy is essential in overcoming thefear or anxiety that novice modelers experience in approaching an assigned task. b. Modeling in EngineeringBroadly defined, the term model refers to a simplified or idealized description or conception of aparticular system, situation, or process, often in mathematical terms, that is put forward
just guesses on each question. a) What is the range of the random variable X, the number of questions the student answers correctly? b) Construct the probability mass function for the random variable X, the number of questions that the student answers correctly.Note that the question allows students to build upon material that they have already studied andmastered. Namely, the students build upon their knowledge of statistical independence, thecounting technique known as a combination, and the concept of a probability mass function. Allof these topics were covered prior to introducing this new topic. After dealing with this familiartype of question, the next question in the sequence becomes
Society for Engineering Education Annual Conference, June 22 - 25, 2008, Pittsburgh, PA.17. Gustafson, R. J. and B. C. Trott. 2009. Two Minors in Technological Literacy for Non-Engineers, Proceedings of the American Society for Engineering Education Annual Conference, June 15-17, Austin, TX.18. Krupczak, J. J., S. VanderStoep, L. Wessman, N. Makowski, C. Otto, and K. Van Dyk. 2005. “ Work in progress: Case study of a technological literacy and non-majors engineering course,” Proceeding of the 35th ASEE/IEEE Frontiers in Education Conference, October 19-22, Indianapolis, IN.19. Pintrich, P. R., D. Smith, T. Garcia, and W. McKeachie. 1991. A Manual for the Use of the Motivated Strategies for Learning
activity must require students to create a solution to a problem that extends them beyond what they have been taught in coursework at their level in the program. 3. The activity must involve diverse aspects of the program as defined by program outcomes. These are: a. At least 3 program outcomes from those identified as technical b. At least 4 program outcomes from those identified as non-technical.The intent of the program is to provide students with the opportunity to work on as many of theseproblems as possible and to have them experience problem solving that integrates all programoutcomes by the time they have finished the program.Traditional methods –Capstone ProjectsA Capstone Engineering Education survey was
these outcomes. The Page 15.1195.4common lists of outcomes for engineering and for engineering technology are listed below.Engineering Degree Programs: EAC of ABET Accreditation Criteria Criterion 3. Program Outcomes Engineering programs must demonstrate that their students attain the following outcomes: (a) an ability to apply knowledge of mathematics, science, and engineering (b) an ability to design and conduct experiments, as well as to analyze and interpret data (c) an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental
among the various toolswithin the machine learning community. During the past decades it has been widely usedin technical applications involving prediction and classification, especially in areas ofengineering, business and medicine22,23. The neural network model is especially attractivefor modeling complex systems because of its favorable properties: universal functionapproximation capability, accommodation of multiple non-linear variables with unknowninteractions, and good generalization ability24. More modeling details on applying NN topredict student retention in engineering can be found in Imbrie et al.4.C. Retention ModelsFive different forms of retention models (A, B, C, D and E as shown in Table 1) wereused in this study to evaluate the