Hamilton, T., Sustainability by design: a reflection on the suitability of pedagogicpractice in design and engineering courses in the teaching of sustainable design. European Journal of EngineeringEducation, 32:2, 135–142, 2007.5. Helms, M., Vattam, S., & Goel, A. (2008) Compound Analogical Design, or How to Make a SurfboardDisappear. In B.C. Love, K. McRae, & V.M. Sloutsky (Eds.) Proceedings of the 30th Annual Conference of theCognitive Science Society (pp. 781 – 786), Washington D.C.:Cognitive Science Society6. Vattam, S., Helms, M., Goel, A., Yen, J., & Weissburg, M. (2008) Learning About and Through BiologicallyInspired Design. To appear in Proceeding from the 2nd Design Creativity Workshop Atlanta, GA.7. Vattam, S., Helms, M
job.However, the risk adverse individuals may conclude that the worst and most likely cases arebelow their current salary and decide to accept the new offer. Table 2: Example of level 2 task solutionCo m m ission % 2%Cu rre nt S a la ry $5,000Ba se S a la ry $3,000Bre a kEve n (L S L ) $2,000 M o st Like ly Ca se Be st Ca se W o rst Ca seRe ve n ueRental F ee per Unit $2,100 $2,500 $2,000Units under Leas e 85 100
multiple and innovative approaches.AcknowledgmentsThis material is based upon work supported by the National Science Foundation underGrant No 0717624 and 0836981, and the Research for Undergraduates Program in theUSF College of Engineering. Any opinions, findings, and conclusions orrecommendations expressed in this material are those of the author(s) and do notnecessarily reflect the views of the National Science Foundation. We want to thank Dr.James Eison of the USF College of Education who helped in designing the assessmentinstrument for external evaluation.References 1. Maple 12, Advancing mathematics. http://www.maplesoft.com/, accessed January 2009. 2. MATHCAD 13, The industry solution for applying mathematics. , accessed
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considers these findings and discussion inrelation to their own programs of engineering. Page 14.983.13References1 Malasri, S., K. Madhavan, and J. Ventura. Should engineering faculty be registered? inMid-South Annual Engineering and Science Conference. 2000. Memphis, Tennessee:Christian Brothers University.2 Madhavan, K. and S. Malasri, Professional registration of engineering faculty. Journalof Professional Issues in Engineering Education and Practice, 2003. 129(3): p. 122-124.3 Harichandran, R., Faculty hiring trends at small- to medium-sized research-intensiveCEE departments and balancing the needs of research and practice, in American Societyfor
been studiedwithin this framework.Identity and Career Choice With roots in Erik Erikson’s 20 foundational theory, career choice has remained connected todiscussions of identity development. In Erikson’s theory 20 successful resolution of the identitycrisis phase of development marks the end of childhood and the beginning of adulthood. Crisisresolution includes selecting and committing to a vocation 20, 21. Marcia 22 operationalizedErikson’s theory as a four-staged model with the lowest stage representing no identity crisis andno career choice and the highest stage incorporating resolution of identity crisis and careercommitment. In this theory, identity and career choice are tightly linked. In the 1970’s and 1980’s, many identity studies
work.BackgroundThe eleven middle and high school teachers who participated in the RET site during the summerof 2008 spent six weeks conducting research under the mentorship of an engineering facultymember. Teachers typically interacted with a graduate student(s) or a post-doctoral fellow on aday-to-day basis. Program deliverables included several short presentations on researchprogress, a scientific poster for their classroom describing their research project, and the creationof a teaching module related to their engineering research project, which teachers were toimplement during the subsequent academic year. Professional development activities took placeonce or twice per week during the summer program. Some of these sessions were directly relatedto
solution” (Interview One) and how she “struggle[s] with like, what is best” (InterviewTwo). This emphasis on a “best” solution type is in contrast with Chris’ approach to workingwith whichever solution type the individual team had chosen, and giving feedback tostrengthening that particular solution type. In his interview, Chris recognized that when he was anew TA, he also was tempted to “advise [every team] to do the exact same thing” (InterviewTwo), which suggests that it may be common for new TAs to advise teams to adopt the “best”solution type, rather than helping teams to fully develop a strong solution for whichever solutiontype they had chosen.Robin, as a new Teaching Assistant, often identified with the role of grader. An
5 3 3 4 7 6 6 TIPS 0 27 0 9 4 10 6 7 TOTAL # CONCEPTS 96 71 100 89Note from the table that the students were also asked to rate the “innovativeness” of each of theCG techniques. While this is quite subjective, it is interesting to note that each team chose adifferent CG method as most innovative (red 10’s in the table). There are some observabletrends in the innovation data. The 6-3-5/Morphological Analysis, Design by Analogy/WordTrees and Far-Field Analogies ranked high while Transformational Design/Mind maps rankedlower. However, the relative dissimilarity of the ranking
-mail: dkueker@vivayic.comPam Newberry, Project Lead the Way The Director of Strategic Curriculum Initiatives for Project Lead The Way, Inc. Prior to joining Project Lead The Way, Inc., in July 2002, she served as the Associate Director for the International Technology Education Association?s Technology for All Americans Project for five years. She taught technology education and mathematics for 10 years. During that time, she was an Albert Einstein Fellow in 1996 and received the Presidential Award for Excellence in Mathematics Teaching in 1994. Address: 177 Stone Meadow Lane, Wytheville, VA 24382 Telephone: (276) 228-6502 E-mail: pampltw@embarqmail.com
addition to their social status, their training and experience allows themto implicitly know where the boundaries are and what is appropriate in a complexmultidimensional and multivariable problem solving. Architectural historians and the generalpublic, on the other hand, are considered better long term arbiters. Many of the buildings thatreceive architectural awards and recognition by professional peers sometimes fade, or in extremecases are considered failures, by architectural historians and the general public. The Pruitt-IgoeHousing Project in St. Louis, designed in the early 1950’s, which won many architectural awardsbut was ultimately demolished less than twenty years later was considered a failure by thegeneral public and architectural
innovation as the core ingredient of theirfuture economic development. As Alan Wolf, member of the NRC-Committee on ComparativeInnovation Policy points out, China’s drive toward innovation has been an unmistakable messageof its top leaders for several years: “In today’s world, the core of each country’s competitive strength is intellectual innovation, technological innovation and high-tech industrialization.” [Jiang Zemin] “[We should give] priority to independent innovation in S&T [Science and Technology] work, take efforts to enhance S&T innovation capability, increase core competitiveness and [strive to make] S&T innovation with Chinese characteristics a reality … …We must aim to be at the forefront
AC 2009-1904: ON THE SUCCESSFUL IMPLEMENTATION OF AN NSF-FUNDEDBRIDGE TO THE DOCTORATE PROGRAM IN STEM DISCIPLINESTony Mitchell, North Carolina State University Tony L. Mitchell, Lieutenant Colonel United States Air Force, Retired, received his B.S. degree in Mathematics from North Carolina A&T State University, the M. S. in Information and Computer Science from Georgia Tech, and Ph.D. in Electrical and Computer Engineering from North Carolina State University. Currently he is Assistant Dean, Engineering Student Services, Director, Minority Engineering Programs, and Associate Professor of Electrical and Computer Engineering at North Carolina State University in Raleigh. Previous educational
biological modeling approach to someone who already has a solid background in mathematics, cell biology, and physiology. You must provide your “student” with the known mechanisms of a particular disease (with which you yourself are already very familiar), and then teach this person to determine the appropriate length scale at which to model the disease process (e.g. cellular, molecular, tissue, etc.) and to identify functional modules in which to compartmentalize the model. Rate your current confidence level at accomplishing this task on a scale of 1-5 (5 being “extremely high confidence”).8. Would you feel comfortable picking up a book(s), researching journals, and integrating information across multiple length scales to set
Sundial (1500BC) – Early Civilizations Cell Phone (1990s) – German Reunification Water Clocks (1400BC) – Thebes, Egyptian Capital Personal Computer with Clock (1980s) - Poland’s Soldarity Movement Sand Hourglass (300BC) – Construction of Great Wall of China Timex Wrist Watch (1950’s) – Space Race Begins Weight Driven Clocks (1270 AD
part American universities have neither kept up with the paradigm shift in engineering for innovation nor with the changes required in professional graduate engineering education to reflect the modern process and practice of engineering for technology innovation during the last four decades. Emphasis on attracting federal funding for academic basic scientific research began during the late 1960’s, intensified in the 70’s, 80’s, and 90’s to the present day ─ resulting in the subsequent build- up of a generation of excellent research-oriented faculty at most engineering schools who are expert at scientific research, who can attract federal research funding, but who are not that proficient, experienced, interested, or rewarded in
IEEE International Multi-Topic Conference, pp. 111-117, Lahorse University, Pakistan, December 2001.2. Merkel, C., and Fisher, D., “A Quick and Easy PLC Learning Experience for Mechatronics”, proceedings of the ASEE Annual conference, pp. 895 – 906, Chicago, IL, June 2006.3. Chiou, R., Kwon, Y., Rauniar, S., and Sosa, H., “Internet-based Robotics and Mechatronics Experiments for Remote Laboratory Development”, proceedings of the ASEE Annual conference, pp. 1363-1379, Honolulu, HI, June 2007.4. Lee, C., and Park, S., “Sensor-Based Robot Control Laboratory”, proceedings of the ASEE Annual conference, New Orleans, LA, June 1991.5. Marsico, S., “Incorporating a Flexible Manufacturing System into a Design Course
. Barrows, Howard S. (2000). Problem-Based Learning Applied to Medical Education, Springfield, IL: SIU School of Medicine.4. Boud, D., Feletti, G. (1991). The Challenge of Problem-based Learning. London: Kogan.5. Boylan, H. R. (2002). What Works: Research-Based Best Practices in DevelopmentalEducation. Boone, NC: National Center for Developmental Education.6. Boylan, H. R. (1999). Exploring alternatives to remediation. Journal of DevelopmentalEducation, 22(3), 2-4, 6, 8, 10.7. Boylan, H. R. (1999). Harvard Symposium 2000: Developmental education: Demographics,outcomes, and activities. Journal of Developmental Education, 23(2), 2-4, 6, 8.8. Boylan, H., Bliss, L., & Bonham, B. (1997). Program components and their relationship tostudent
My instructor seems well-prepared for class. 4.8 My instructor has an effective style of presentation. 4.3 I am generally pleased with the text(s) required for this course. 4.7 Course assignments are interesting and stimulating. 4.3 My instructor is actively helpful when students have problems. 4.9 My instructor is readily available for consultation. 4.8 I would enjoy taking another course from this instructor. 4.9 My instructor displays enthusiasm when teaching. 4.9 My instructor motivates me to do my best work
. 39.3. Clark, J., 2000, “Collaboration Tools in Online Learning Environments,” ALN Magazine, 4(1).4. Hiltz, S. R., Coppola, N., Rotter, N., Turoff, M., and Benbunan-Fich, R., 2000, “Measuring the Importance ofCollaborative Learning for the Effectiveness of ALN: A Multi-measure Multi-method Approach,” ALN Journal,5(2).5. Lowyck, L. and Poysa, J., 2001, “Design of Collaborative Learning Environments,” Computers in HumanBehavior, 17(5-6), pp. 507-516.6. Hughes, S. C., Wichersham, L., Ryan-Jones, D. L., and Smith, S. A., 2002, “Overcoming Social andPsychological Barriers to Effective On-line Collaboration,” Educational Technology & Society, 5(1), pp. 86-92.7. Bishop, P., Cox, B., Fothergill, R., Kyle, J., Lawson, D., Mitchell, M., Rathbone, J
running multiple sections of the course. Responsibilities include ordering books for thecourse, training of first-time faculty during the summer, recommending and implementingchanges in course materials, purchasing equipment and supplies for the course, posting allmaterials to BlackBoard, and meeting with other instructors throughout the semester.The course coordinator schedules and determines the frequency of group meetings with allfaculty involved in teaching EAS107P. She is also able to work with specific faculty to addressany problems associated with his/her particular section(s). Feedback from the faculty is used todetermine whether problems have persisted (and why) or have been successfully remedied.Scheduling of multiple sections of
underrepresented students. Although special consideration is given toapplications from these three recruitment pools, specific applicant attributes and experiences arealso considered. The E3 RET application solicits personal information on the following: 1)teaching experience (including years of experience, subjects/courses taught - STEM subjectrequired) and Texas teaching certification(s); 2) education level (degree(s) and major discipline);3) past participation in other professional development programs, 4) past research experience, ifany; and 5) engineering knowledge base (e.g., personal awareness of types ofengineering/engineers, examples of engineering solutions that affect daily lives). Theapplication essay requests additional information such as
due dates. The EGR 481 syllabus is as follows:Course Syllabus: EGR 481 - Fall 08 Project Design Principles and ApplicationsProfessor’s name: Dr. S. MonemiOffice location & phone: 9-527, 909-869-2520Email: ssmonemi@csupomona.eduClass time and location: MW 1:00-1:50 PM, Room 9-329Course prerequisites: Upper division standingOffice Hours: Monday, Tuesday, Wednesday 8:00 - 10:00 AMTextbook: Class notes and handoutsCourse Description: Completion of a capstone senior design team project under faculty supervision. Results are presented in a formal report.Course Coverage: Learn how to design, develop, and analyze
self-efficacy in engineering education, Journal of Engineering Education, 90(2), 247-251.[9] D. J. Ahlgren and I. M. Verner (2007). Building Self-Efficacy in Robotics Education. Proc. of 2007 ASEEAnnual Conference, Honolulu.[10] S. Bhandari, P. Gautam, D. Ahlgren. “Implementation of RF communication with TDMA algorithm in swarmrobots”. Proc. IEEE International Conference on Technologies for Practical Robot Applications, 2008, pp. 68-73[11] K. Nepal, A. Fine, N. Imam, D. Pietrocola, N. Robertson, D. Ahlgren. “Combining a Modified Vector FieldHistogram Algorithm and Real-time Image Processing for Unknown Environment Navigation”. Proc. IS&T/SPIE21st Annual Symposium, San Jose, January 2009
extent. As mentioned before, several assessmenttools have been identified such as classwork/homework, quizzes/exams and projects.Sincere attempt is made to refer to the CLOs while designing the contents of theassessment tools used. For example, each exam question clearly stated the concept beingtested in that question, and to what extent that question addresses the CLO(s) and how itmaps the PO(s). Students were informed where this information will be used. The statedCLO(s) is/are assumed to be satisfied based on their achieving a certain grade on thatquestion. This is repeated for all assessment tools used in this course, particularly for thefinal project, in which the students used math and CAE tools to a great extent. At first, itlooks like
Cp ? (1) 1 τAU ♣3 2To assess the rotors, the performance curves (i.e., Cp versus rotational speeds of completedturbines) were measured at distinct load points for two different wind speeds (5 m/s and 3 m/s).The score that a design received was calculated as the average of the maximum Cp valuesdetermined from the two performance curves.A numerical grade was assigned to the technical performance based on the turbine’s averagemaximum Cp value. Initially, the following algorithm was proposed: An unoptimized wind