indispensible ingredients of a successful career in engineering, thusfulfilling some of the program educational objectives.Bibliography 1. Schuster, P., Davol, A. and J. Mello, “Student Competitions - The Benefits and Challenges,” Proceedings, 2006 ASEE Annual Conference (Washington, DC: American Society for Engineering Education, 2006). 2. Pierrakos, O., Borrego, M. and J. Lo, “Assessing Learning Outcomes of Senior Mechanical Engineers in a Capstone Design Experience,” Proceedings, 2007 ASEE Annual Conference (Washington, DC: American Society for Engineering Education, 2007). 3. Davis, D. C., Crain Jr., R. W., Calkins, D. E., Gentili, K. L., and M. S. Trevisan, “Competency-Based Engineering Design Projects
measure. The researchers intend to collect more data for thenext revision of the measure. We encourage future researchers to validate the CDFS for similarcross-disciplinary teams use.Bibliography1. Solomon, G. (2003). Project-based learning: A primer. Technology and learning - Dayton, 23(6), 20-20.2. Fruchter, R., & Emery, K. (1999). Teamwork: Assessing cross-disciplinary learning. Paper presented at the 1999 Computer support for collaborative learning Conference, International Society of the Learning Sciences.3. Agogino, A., Song, S., & Hey, J. (2007). Triangulation of Indicators of Successful Student Design Teams. International Journal of Engineering Education, 22(3), 617.4. Sage, A., & Rouse, W. (2009
objectives. A detailed questionnaire has beendeveloped and used in several courses to gather information on the opinions and reflections ofstudents on the learning opportunities offered them. In this unique survey, presented to thestudent not as a course evaluation but as survey of the student‟s opinions of his/her own learning,students are asked to evaluate their own ability to understand and apply the course knowledgeand skills objectives. Students are asked also to rate the course various learning opportunities –lectures, text, laboratories, etc. – insofar as each opportunity aided their learning in each courseobjective.The survey has provided valuable new information to the instructor to measure and meet notonly continuous improvements in
]: Ontario Institute for Studies in Education, 1967.[4] D. P. Ausubel and F. G. Robinson, School learning; an introduction to educational psychology. New York,: Holt, 1969.[5] J. Bruner, "Learning and thinking," Harvard Educational Review, vol. 29, pp. 184-192, 1959.[6] B. E. Cline, C. C. Brewster, and R. D. Fell, "A rule-based system for automatically evaluating student concept maps," Expert Systems with Applications, vol. 37, pp. 2282-2291, March 15, 2010 2009.[7] S. H. Harrison, J. L. Wallace, D. Ebert-May, and D. B. Luckie, "C-Tools Automated Grading For Online Concept Maps Works Well With A Little Help From "Wordnet"," in First International Conference on Concept Mapping, Pamplona, Spain, 2004.[8] D
Design of Sustainable Water Pumps for Burkina Faso Timothy B. Whitmoyer and David T. Vader Messiah College, Grantham, PAAbstractThe Department of Engineering at Messiah College has partnered with the Handicap s en Avant,(a center for rehabilitation and education of handicapped persons in southeast Burkina Faso) forover a decade. One of the enduring student-faculty projects spawned from this relationship is theModified Rower Pump Project. The long-term vision of this project is to provide a sustainabledesign, including construction methods, allowing local manufacturers to build water pumps aspart of their businesses. The present goals of the project are to quantify the pump’s
they will encounter as they enter the workforce.Bibliography1. S. Datar, C.C. Jordan, S. Kekre, S. Rajiv, and K. Srinivasan, "The Advantages of Time-Based New Product Development in a Fast-Cycle Industry," Journal of Marketing Research 34 (1), 36-49 (1997).2. G. Kalyanaram and G.L. Urban, "Dynamic Effects of the Order of Entry on Market Share, Trial Penetration, and Repeat Purchases for Frequently Purchased Consumer Goods," Marketing Science 11 (3), 235-250 (1992).3. D. Hall and J. Jackson, "Speeding Up New Product Development," Management Accounting 74 (4), 32-36 (1992).4. M.A. Cohen, J. Eliashberg, and H. Teck-Hua, "New Product Development: The Performance and Time-to- Market Tradeoff," Management Science 42 (2), 173
, coupled with high anxiety and low self-efficacy can lead to low teachereffectiveness and lack of interest from the K-5 students. At our institution, The College ofNew Jersey (TCNJ), it was felt that the Department of Technological Studies, housed withinthe School of Engineering, was well positioned to provide a unique K-5 academic major bycombining the T&E with the M&S components of STEM, resulting in a program breadth thatmatches well the breadth of skills needed by a highly skilled K-5 teacher.Such a program was established at TCNJ in 1998 and is formally referred to as the Math-Science-Technology or MST program. The program has substantial requirements in allSTEM areas, and takes a truly integrated-STEM approach. To the authors
is also to be collected with respect to instructor time for delivery;instructor experience; student experience; and student interaction in groups. Results will bepresented at the conference.Bibliography1. Grassman, S., “Teaching Engineering Economics via Distance Education,” Proceedings of the ASEE AnnualConference and Exposition, 2002.2. Ibrahim, W. and R. Morsi, “Online Engineering Education: A Comprehensive Review,” Proceedings of theASEE Annual Conference and Exposition, 2005.3. Kolowich, S., “Going for Distance,” Inside Higher Education, www.insidehighered.com, August 31, 2009.4. Kolowich, S., “Learning from Online,” Inside Higher Education, www.insidehighered.com, December 7, 2009.5. Thiagarajan, G. and C. Jacobs, “Teaching
. Reputation systemsA reputation system is a way of measuring the reliability of ratings. Scores assigned byreviewers and metareviewers can be factored into a student's reputation. Several algorithms[4, 5, 6] have also been published for determining reviewer reliability, based only on thescores assigned by reviewers. These algorithms consider (i) consistency of scores assignedby this reviewer with scores assigned by others to the same work, and (ii) spread, how muchthe highest score the reviewer assigned differs from the lowest score (s)he assigned. Somealgorithms also consider (iii) leniency, the tendency of a reviewer to give scores that arehigher than other reviewers. Research [6] demonstrates that these algorithms provideeffective quality control
experience to enter the high technology workforce upon completion of BS degree; and5. Perform a regular and thorough assessment of the ET2 program that will be used for the contract reporting purposes and also will be an integral part of our standard program review process.In August 2008, NSF awarded us a four-year grant from its S-STEM program to support the ET2Transfer Scholars1. In support of this project, the university will contribute $50,000 to ensurethat continuing ET2 scholars have financial support after the grant expires and help themgraduate on time. This support indicates the university’s enthusiasm, a firm commitment ofservice to our EET students, and an endorsement of the goals and objectives of the ET2 program.For AY 2008-9, the
about and can effectively use this system,researchers at Missouri University of Science and Technology, supported by the NationalScience Foundation, have set out to explore creative and effective means of teaching this systemto students. There are many segments of GIS, but for the purpose of this study we will beevaluating the transportation module created by Missouri S&T scientists and engineers tocomplement the Geographic Information System learning tool.The transportation module itself is a web-based help system that contains categories to explainhow to use many of the transportation-related capabilities of Geographic Information Systems.This module is to act as an aid to learning the application of GIS. The purpose of this study isto
-Level Diagram.Mnemonic Encoding Operation NOP 0000 Do no operation. Takes 2's complement of the number in NEG 0001 the accumulator. Takes 1's complement of the number in NOT 0010 the accumulator. Rotates the accumulator data one bit to ROR 0011 the right (with wrap-around). Transfers the data from the accumulator OUT 0100 aaaa to the selected output port
data (b) ≠ the ability to function in teams (d) ≠ understanding of professional and ethical responsibility (f) ≠ the ability to communicate effectively (g) ≠ a recognition of the need for, and an ability to engage in life-long learning (i) ≠ a knowledge of contemporary issues (j) ≠ the ability to use some of the basic techniques, skills, and modern engineering tools necessary for engineering practice (k).If these outcomes are clearly articulated and effectively assessed by the TYC program, this willhelp the program articulate smoothly with the engineering program(s) at the four-yearinstitutions. Community college programs are advised to work with their four-year partner(s) todevelop an assessment and evaluation process that
transforms for the analysis of circuits in the s-domain including Bode plots and frequency response. Also, perform Fourier circuit analysis8-11.4. Use PSpice to simulate and analyze simple electronic circuits.The abovementioned courses have a laboratory component where students build simple electriccircuits and make measurements in the laboratory by using basic laboratory equipment, computersimulation tools, and work in teams.The course objectives are in agreement with ABET Criterion 3 outcome and assessment foraccrediting Engineering programs12. Page 15.699.3Assessment Method and Information GatheringThe next sections of the paper report the
the process. The specifics of equipmentdesign and simulation for other batch unit operations (distillation, filtration, crystallization, etc.)are not covered but are left for specific operations related to the group project.As an example of the differences between unsteady, batch operation and continuous operation,consider the preheating of a batch reactor with preheating of a continuous reactor in a continuousheat exchanger. The familiar, steady-state equations for a heat exchanger are the energybalances and the heat-exchanger design equation (assuming a utility of condensing steam, forexample) Q ? m& p C p , p ΦT p ? m& s νs ? UAΦTlm F (1)where the subscript p represents the
Disassembling experience Consulting the experts and masters Experiments Books and internet information Prior knowledge and ability Investigation of the products in the marketMost of interviewees indicated that DIY was the most critical design factor for STEMin PBL, the next important factors were books and internet information.Frequency Analysis of the Contents of STEM:The contents of forum on the website of STEM were analyzed as shown in Table 4.According to the data of the forum of STEM website, the most frequent discussed wasTechnology (T); next was Science (S); and Mathematics (M) was the least discussedby students. The students of the two schools obtained similar results.Table 4 Stem content frequency analysis Schools
factor, we choose to measure the power whenthe system is set in DC MODE (Figure 3), which lead to a power factor of 1.This design was done in multiple steps using different type of hardware and software. The firststep was to obtain the value of the V (t) across the pump. In order to accomplish this task, weused the NI USB 4065 DMM, a digital multimeter which has the following characteristics ≠ Bus-powered for portability ≠ Small (7.0 by 4.1 by 1.3 in.) and lightweight (10 oz) ≠ 6½-digit resolution ≠ 7 built-in measurements - AC/DC voltage, AC/DC current, 2- or 4-wire resistance, and diode test ≠ ±300 VDC/Vrms isolation ≠ 3000 readings/s (maximum) at 4½ digitsThe second step was to measure the current flowing through
. Table 2. Summary of the Test Result Exhaust Air Mass Flow Fuel Flow Air/Fuel Item Temp (°C) (g/s) (g/s) Ratio 550 19.44 3.675 5.2910 565 22.22 3.538 6.2810 574 25.00 3.524 7.0935 B100 589 27.78 3.470 8.0054 604 30.56 3.449 8.8580 618 33.33 3.402 9.7982 468 19.44 3.538 5.4959 462
and Scale Invariant Feature Transform inParticle Filter Framework”, IEEE Transactions on Consumer Electronics, Vol. 55, No. 3, AUGUST 2009 2. Angelo Bosco, Arcangelo Bruna, Sebastiano Battiato, Giuseppe Bella, and Giovanni Puglisi “Digital VideoStabilization through Curve Warping Techniques” IEEE Transactions on Consumer Electronics, Vol. 54, No. 2,MAY 2008 3. Hany Farid and Jeffrey B. Woodward, “Video Stabilization and Enhancement” TR2007-605, DartmouthCollege, Computer Science 4. J.L. Barron D.J. Fleet S.S. Beauchemin, T.A. Burkitt “Performance of Optical Flow Techniques” Multimedia and Expo, 2006 IEEE International Conference on 9-12 July 2006 Page(s):241 – 244 5. Jen. Hsiao, C. Hsu, T. Shih, P. Hsu, S. Yeh and B. Wang “Real
the widely utilized Force Concept Inventory.Since then multiple engineering and physics disciplines now utilize concept inventories forteaching and learning assessments. The Statics Concept Inventory11 utilized in this research wasdeveloped by Paul S. Steif at Carnegie Mellon University and the co-developer was Anna Dollàrfrom University of Miami at Ohio. The 30-minute exam consists of 27 multiple choice questionscovering nine statics concepts (three questions for each topic) as categorized in Table 1. Table 1. Description of the concepts in the Statics Concept Inventory Exam A Free Body Diagram – Separating Bodies B Newton’s 3rd Law C Static equivalence of combinations of forces and
collected: gender,major(s), year in school, relevant course work, and the results of the online learning stylesassessment. The learning style assessment gave the students a numeric indicator for theirlearning preference in each category, over a range from -11 (extreme to one side), to +11(extreme to the other side). Using this information the course and lab instructors assigned elevengroups with 3-5 students in each. Groups were assigned such that they had a roughly equalrepresentation of gender and majors and had an “average” learning style for each group that wasbalanced within each of the four categories. We did not mix undergraduate and graduatestudents. It was obviously impossible to perfectly mix the groups, but the average learning styleof
Production Economics, vol 62, pp. 87-105, 1999. 2. S. C. Park, A methodology for creating a virtual model for a flexible manufacturing system, Computers in Industry, vol. 56, pp. 734–746, 2005. 3. D. Kotak, S.Wu, M. Fleetwood, H. Tamoto, Agent-based holonic design and operations environment for distributed manufacturing. Computers in Industry, vol. 52, pp. 95-108, 2003. 4. M. Bal, M. Hashemipour, Virtual factory approach for implementation of holonic control in industrial applications: A case study in die-casting industry. Robotics and Computer-Integrated Manufacturing, Vol. 25(3), pp. 570– 580, 2009. 5. S. Cavalieri, M. Macchi , P. Valckenaers, Benchmarking the performance of manufacturing control
forthe following discussion on the three great challenges of the past thirty years and the responsesobserved thereto.1983: The issue of a distinctive curricular identity for manufacturing engineering was firstopenly and cohesively articulated in the early 1980’s. The founding of the ManufacturingConstituent Committee at the ASEE conference at Southern California in 1981 was one of thecritical milestones. Another occurred at the ASEE conference in Salt Lake City in 1983, whenover coffee during a break in the sessions, the notion of a workshop to explore curricular identitywas first broached. The question formulated at that time was as direct as it was simple: “If youwant to teach someone to be a manufacturing engineer, what do you teach?” The
, which played a more significant role in sustaininginterest in engineering for women than men. When entered in the second block, theenvironmental factor, Respect/Care, had stronger predictive power for women than men(Women: ß=.343, p≤.001; Men: ß=.270, p≤.001). Negative Educational Experiences, afactor identified by Goodman et al.10, had a statistically significant effect in theregression equations for both men and women, but the effect was stronger for women(ß=-.211, p≤.001) than men (ß=.-141, p≤.001).Contrary to Fox et al.’s assertion14, the block of individual variables, particularly thefactor measuring motivation, had more explanatory power for both men and woman thanthe environmental factors. The variable, Motivation, played the most
AC 2010-171: EXCEL IN MATHEMATICS: APPLICATIONS OF CALCULUSCynthia Young, University of Central Florida Cynthia Young is a Professor in the Department of Mathematics in the UCF College of Sciences and a Co-PI of the NSF-funded S-STEM program at UCF entitled the "Young Entrepreneur and Scholar(YES) Scholarship Program" as well as the NSF-funded STEP program entitled "EXCEL:UCF-STEP Pathways to STEM: From Promise to Prominence." Dr. Young's research interests are in the mathematical modeling of atmospheric effects on laser beams. She currently has projects with the Office of Naval Research and the Naval Research Laboratory investigating atmospheric propagation in the marine
Page 15.680.10of this field – to use these concept and techniques to positively affect human health. By the timethese students become juniors and seniors, we must remind them of this ultimate goal.Incorporating real-world examples and having students tackle more abstract problems on theirown is one way to do so.1. E. Jansen, A. Mahadevan-Jansen, W. Lin, S. Brophy and M. Mackanos. Development and Implementationof an Interactive Instructional Module of Light Distribution in Tissue. 2001.2. J. Bransford, National Research Council (U.S.). Committee on Developments in the Science of Learning.and National Research Council (U.S.). Committee on Learning Research and Educational Practice., How peoplelearn : brain, mind, experience, and
1100 s. The figure also shows the solution of the Page 15.1157.6model. The model agrees well enough with the data to be useful for designing the controlalgorithm.The model was used to design a PI controller. The PI gains were selected to give a closed loopsystem with a damping ratio of ζ =1 and a desired closed-loop time constant τd.The Results Since the heater voltage is limited to 12 V, if τd is selected too small, the heater willsaturate. A Simulink model was constructed to investigate how small τd could be made withoutcausing saturation. It was found that τd close to 550 s was the smallest possible value. Figure 5shows the experimental
that you think undergraduates should be prepared for at the outset of their professional careers.Over ninety CoE alumni or alumnae responded to the email. The survey was not intended to be ascientific instrument. The organizers could determine the age, gender and engineering majorthrough alumni records, but elected not to do so. However, approximately one-half of therespondents did list their majors and years of graduation. All engineering majors wererepresented: chemical (7%), civil (32%) electrical/computer (27%) and mechanical (34%). Theyears of graduation ranged from the 1940’s to the 2000’s. The 1950’s, 1960’s, 1980’s and1990’s were the most prevalent years.Most of the respondents did not address the two questions directly
consists of a question and actual student response from a recentTransport Phenomena 1 final exam (the student was a junior):Gasoline is being pumped 17 miles through nominal 3-inch, schedule-40 steel pipe at arate of 9500 gal/hr. What horsepower will be required if the pump’s efficiency is about75%? ≠ M/ τ The average velocity in the pipe: > V ≅? ρR 2 4571856 therefore, > V ≅? 2 ? 8.9 x107 ft/s. ρ (0.1278) d >V ≅ τ