Process Office, 2003-2009. Dr. White left MITRE in July, 2010, to offer a consulting service, CAU-SES (”Complexity Are Us” - Systems Engineering Strategies).Dr. S. Jimmy Gandhi, California State University, Northridge S. Jimmy Gandhi is currently an assistant professor in the Manufacturing Systems Engineering & Man- agement (MSEM) Department at California State University, Northridge. He teaches courses in quality management, entrepreneurship and systems engineering. Prior to coming to Cal State, he was with the School of Systems and Enterprises at Stevens Institute of Technology and also taught at the Zicklin School of Business at Baruch College, which is part of the City University of New York (CUNY). Dr. Gandhi
management, and engineering education. Prior to her academic position, she spent seven years working in industry including two years at NASA’s Kennedy Space Center.Mrs. Julie Phelps, Missouri S&T, Educational Technology Julie Phelps has a B.S. in Education from The University of Missouri, Columbia and a M.A. in Informa- tion & Learning Technology from The University of Colorado - Denver. She has 17 years of teaching experience and has facilitated professional development for K-12 teachers for 10 years. Since 2010, she has been applying her experiences with teaching, technology, and professional development into higher education as an instructional designer. At Missouri S&T, she assists faculty in course
Paper ID #6637An understanding of psychology to enhance organizational strengthLiana Bayatyan, Baruch College, City University of New York (CUNY) Liana Bayatyan relocated to New York City from Yerevan, Armenia in 2000. Since 2006, Bayatyan has been pursuing interests in the field of psychology. Currently, Bayatyan is a research assistant at the Mangels Dynamic Learning Lab, City University of New York (CUNY) and an assistant cognitive therapist at the Center for Cognition and Communication.Dr. S. Jimmy Gandhi, California State University, Northridge S. Jimmy Gandhi is currently an assistant professor in the Manufacturing
Paper ID #7664Modifications of Engineering Management Program at California State Uni-versity NorthridgeAlireza Kabirian, California State University Northridge Alireza Kabirian is currently an assistant professor of Engineering management at California State Uni- versity Northridge. He obtained a Ph.D. in Industrial Engineering from Iowa State University in 2009. After graduation, he taught in the Business School of the University of Alaska Anchorage for two years before leaving the Last Frontier to join CSUN. His research areas are focused on Operations Research, Applied Statistics, and Engineering Education.Dr. S
become more competitive in the internationalmarket resulting in the obvious domestic benefits. Another is the impact on the environment.Even a small increase in overall efficiency of U.S. commercial and industrial buildings wouldreduce the U.S.’s carbon footprint significantly.Currently, the U.S. workforce is not adequately trained in the area of energy efficiency. TheDepartment of Energy recognizes this fact and is attempting to remedy this with programs suchas the Energy Efficient Buildings Hub and the continued support and recent expansion ofIndustrial Assessment Centers 2. However at the present time, those providing "energyefficiency" services are typically either too technical in their approach such as researchers andprofessors; or possess
). Informal and incidental learning in the workplace In M. C. Smith & N. DeFrates-Densch (Eds.), Handbook of Research on Adult Learning and Development. New York: Routledge.[2] Cross, J. (2007) Informal Learning: Rediscovering the National Pathways That Inspire Innovation and Performance. San Francisco: John Wiley & Sons.[3] Dreyfus, S. (2004). The Five-Stage Model of Adult Skills Acquisition. Bulletin of Science Technology & Society, 24(3), 177-179. DIO:10.1177/0270467604264992[4] Dreyfus, S. E. & Dreyfus, H. L. (1980). A five-stage model of mental activities involved in directed skills acquisition, paper to Air Force Office of Scientific Research. pg. 3
University of Hertfordshire, (b) LEED Building site with sample features, (c) PFNC Design for an $8,000 home using shipping containers for low income families in Mexico, and (d) Thinnest house in the world designed by Polish architect J. SzczensyStudents are then asked to consider the typical home designed in the 1950’s, such as the one inFigure 4. During this time, home designs have one bathroom for the use of the entire family.When this is placed in contrast to the number of bedrooms and baths in their Dream Home,students are asked, “Why do they need so many bathrooms?” given that people today are notdifferent physically from those in the 1950’s. Students quickly realize that the needs of theindividual have not
age where largeamounts of data are being collected with a growing need for those that can make “data-drivendecisions” [3]. McKinsey Global Institute, a business and economic research firm, claims thatwith the growth of digital data, the United States is going to need an additional 140,000 to190,000 analysts and more than 1.5 million managers capable of performing data analysis [4].Additional calls have been made for more statisticians in the federal system, working in placessuch as the Bureau of Labor Statistics or the United States Census Bureau [5].These pleas are not new, however; even in the early 1980’s authors were writing about the needto make the field of statistics as a separate discipline [6] and recognizing the growing need
analysis. Themodel has been modified to develop a Cost "S" Curve from the traditional point estimate valuebased upon the triangular distribution and using three parameters, H/L ratio, the percentile valuefor the point estimate and the percentile value for the most likely cost. This approach eliminatesthe need for the traditional triangular distribution parameters of the high with a specifiedpercentile, the low with a specified percentile, and the mode. It is difficult to get estimates of thehigh and low values associated with percentiles, whereas the H/L ratio is easier to obtain forestimates. The results from the model include the lowest cost, the most likely cost, the mediancost, the mean cost, and the highest cost estimate as well as the cost
. (2005). A dynamic, systematic method for developing blended learning. Education, Communication & Information, 5(3), 221–232.4. Bassett, E., & Gallagher, S. (2005). Students prefer hybrids to fully online courses. Recruitment & Retention in Higher Education, 19(8), 7–8.5. Gecer, A., & Dag, F. (2012). A blended learning experience. Educational Sciences: Theory & Practice, 12(1), 438–442.6. Musawi, A. S. A. (2011). Blended learning. Journal of Turkish Science Education (TUSED), 8(2), 3–8.7. George-Palilonis, J., & Filak, V. (2009). Blended learning in the visual communications classroom: Student reflections on a multimedia course. Electronic Journal of e-Learning, 7(3), 247–256.8. Scherrer, C. R
in front of the class. The classdeliverables for the Measure phase, which are summarized in Table 4 was due during the fifthweek of the class. Deliverable Description CTQ Matrix Define the customers Capture the voice of the customers Translate the voice(s) to the customer need(s) Kano Model Rank the customers’ needs based on level of priority Must haves More is better and delighters Page 23.957.8 As is process
applied probability itself, butalso for the nature of problems. They should understand structuring problems and posing problems.They should be informed that there is a spectrum of problems, ranging from well-structuredproblems with definite answers and clear boundaries, such as are found in traditional textbooks (andnowhere else), and open-ended, ill-structured problems, such as are found in the engineeringworkplace. The essential and unique point is that learners s must pose, clarify, and define problems,not simply solve them.And, at the same time, learners should practice metacognitive skills such as reflecting on how theyare building these schemes. Metacognitive activities are manifold and not easy to classify. Howeverthere is widespread
Distinguished IE professor in 2003 and 2010, and as Distinguished Industrial Engineer for the Year 2010 by the College of Engineers and Land Surveyors of Puerto Rico.Dr. Alexandra Medina-Borja, University of Puerto Rico at Mayaguez Alexandra Medina-Borja earned her Ph.D. and M.S. in Industrial and Systems Engineering from Virginia Tech. and holds a Production Engineering degree from the Federal University of S˜ao Carlos in S˜ao Paulo, Brazil. Medina-Borja has concentrated her work in areas related to the effective design and analysis of service delivery systems. Her main research contribution has been to advance a model for the performance evaluation of nonprofit social services by adapting Data Envelopment Analysis formulations
: Author.4. Hesli, V., Fink, E., &Duffy, D. (2003). Mentoring in a positive graduate student experience: Survey results from the Midwest region, Part I. PS: Political Science and Politics, 36(3), 457-460.5. Wankat, P. C. & Oreovicz, F. S. (2005). Teaching prospective engineering faculty how to teach. International Journal of Engineering Education, 21 (5), 925-9306. Torvi, D. A. (1994). Engineering graduate teaching assistant instructional programs: training tomorrow's faculty members, Journal of Engineering Education, 2-5.7. Shannon, D. M., Twale, D. J. & Moore, M. S. (1998). TA teaching effectiveness: The impact of training and teaching experience. The Journal of Higher Education, 69, 440-466.8. DeChenne, S.E
the part of the student. Inthe near future, we would like to extend our research to the entire program in order to ascertainthe level of satisfaction across a wider cross-section of students.References1. I. E. Allen and J. Seaman, “Going the Distance: Online Education in the United States, 2011”, Babson SurveyResearch Group, http://sloanconsortium.org/publications/survey/going_distance_2011 , 2011 Page 23.1183.102. R. Lytle, “Study: Online Education Continues Growth”, US News- Education,http://www.usnews.com/education/online-education/articles/2011/11/11/study-online-education-continues-growth,November 11, 20113. S. R. Hiltz, R
clínica de parasitología," in Encuentros en educación superior y pedagogía 2005, Cali, Universidad del Valle, 2007, pp. 45 - 51.[5] A. Kaufman, S. Mennin and R. E. Waterman, "The New Mexico Experiment: Educational Innovation and Institutional Change.," Academic Medicine, vol. 64, pp. 285 - 294, 1989.[6] D. Guerrero, Modelo de aprendizaje y certificación de competencias en la dirección de proyectos de desarrollo sostenible, Madrid: Tesis Doctoral (no publicada), 2011.[7] J. W. Thomas, A Review of Research on Project-Based Learning, San Rafael, California: The Autodesk Foundation, 2000.[8] B. F. Jones, C. M. Rasmussen and M. C. Moffitt, "Real-life problem solving.: A collaborative approach to
questionresponse itself.Overall, clickers have shown potential to keep students engaged in the learning process andprovide a means to quickly assess learning success. Students are prompted to connect the newconcept(s) to those learned previously and demonstrate their mastery of it. This allows thestudents and the instructor to rapidly discover whether the introduction of a new concept wassuccessfully scaffolded onto prior knowledge by a critical portion of the class. If the answer is no,the instructor can return to the concept with a clarification or another example. If the answer isyes, the instructor may move on, but the students who privately know they were not correct are
Classes,” Journal of Asynchronous Learning Networks, Volume 5, Issue 2 (September 2001).2. Descoteaux, T., Muckerman, D., and Sabol, S., “The Importance of an On-Campus Residency Experience in Distance-Education Programs,” Proceedings of the 2009 American Society for Engineering Education Annual Conference and Exposition.3. McElrath, E., and McDowell, K., “Pedagogical Strategies for Building Community in Graduate Level Distance Courses,” MERLOT Journal of Online Learning and Teaching, Volume 4, Number 1 (March 2008).4. Ozelkan, E., and Galambosi, A., “Benchmarking Distance Education in Engineering Management Programs,” Proceedings of the 2009 American Society for Engineering Education Annual Conference and Exposition.5
majority of theworkforce for the aerospace industry in the San Fernando Valley, which highlights the necessityof incorporating the latest topics such as green engineering into the curriculum of the College ofEngineering.5.Bibliography(2008, May 22). Retrieved from USAToday: http://usatoday30.usatoday.com/money/industries/environment/2008-05-20-green- companies_N.htm(2013). Retrieved from Institute for Sustainability: www.csunsustainability.orgSustainable Engineering. (2013). Retrieved from http://csunsustainability.org/curriculum/sustainable-engineering/Lele. (2009). Getting serious about Green manufacturing. Frost and Sullivan.Northridge, C. S. (2012).Sandy Glatt, R. H. (2009). Energy Efficiency as a Resource: Midwest area
Economics: • Interest rate formulas • Decision making using Net Present Value Probability and Statistics: • Random variables • Means, variances, and standard deviations • Addition and multiplication laws of probability • Random variables • Conditional probabilities • Distribution and density functions Operations Research: • Decision variables • Objective functions • Optimal solution(s) • Linear programs • Integer programs • Average wait in a queue • Average Length of a queue Production Planning and Control: • Forecasting • Economic Order Quantities and Newsboy Models