include continued development of web-based problem-solving environmentsfor automated system design, implementation of automated cognitive task analysis within theseenvironments to facilitate continued research on design problem-solving, and development of anundergraduate-level system integration course.AcknowledgementsThis material was supported by a National Science Foundation grant no. 0238269. Any opinions,findings, and conclusions or recommendations expressed in this material are those of the authorand do not necessarily reflect the views of the National Science Foundation.Bibliography1. Hsieh, S. "Automated Manufacturing System Integration Education: Current Status and Future Directions," Proceedings of 2005 ASEE Annual Conference
? Mechatronics4 is a subject that joinselectrical engineering with mechanical engineering. Energy systems are mechatronics systems inthat they are part mechanical and part electrical and electronic. The students’ challenge was tooptimize an energy plan for the U. S. for the next 50 years. The class divided themselves intodifferent factions. Since genetic algorithms lend themselves to systems that have indefinitefactors, this was the category of algorithm that was chosen for this investigation. A population of different energy resources was compiled. For each faction, a spreadsheet wascreated which contained a detailed summary of the energy plan components. Each faction thencreated and applied a genetic algorithm to their starting plans. Genetic
. # = 0 - CR = CR, LF = LF, FF = FFFont Selection by ID # (EC ( # X or EC ) # X): Selects a soft font using its specific ID #. EC (# X - Designates soft font as primary. EC ) # X - Designates soft font as secondary. # = FontIdentification numberSpacing (EC ( s # P – Primary, EC ) s # P – Secondary): Designates either a fixed orproportionally spaced font. # =0 means Fixed spacing, # - 1 means Proportional spacingPitch (EC ( s # H – Primary, EC ) s # H – Secondary): Designates the horizontal spacing of afixed spaced font in terms of the number of characters per inch. # = Pitch in characters/inchStroke Weight (EC ( s # B – Primary, EC) s # B – Secondary): Designates the thickness orweight of the stroke that composes the characters of a font. 6. HC
and how this technique may be useful for making complex learningenvironments more navigable. The author believes advances in technology are poised tomake huge differences in the way we teach and the way students learn. Future work willinclude implementation of such tools in courses taught and comparative assessment ofstudent learning outcomes.References1. Novak, J. D.; Cañas, A. J. The Theory Underlying Concept Maps and How to Construct Them. cmap.ihmc.us/Publications/ResearchPapers/TheoryUnderlyingConceptMaps.pdf (November 20, 2008),2. Novak, J. D.; Gowin, D. B., Learning how to learn. Cambridge University Press: Cambridge, 1984.3. Milam, J. H., Jr.; Santo, S. A.; Heaton, L. A. Concept maps for web-based
/sequential circuit design, but also collectivelyfostered the student’s ability to conduct real-world design project. Preliminary assessment resultsshows that the impact of the course redesign on students’ learning outcomes is very promising.In our future work, more comprehensive assessment data will be collected and analyzed, and thefindings will be used to further improve the course redesign.AcknowledgmentThis material is based upon work supported by the National Science Foundation under Grant No.0737130. Any opinions, findings and conclusions or recommendations expressed in this materialare those of the author(s) and do not necessarily reflect the views of the National ScienceFoundation (NSF).Reference[1] A. J. Dutson, R. H. Todd, S. P. Magleby
BME Department forproviding their continuous support, resources and encouragement. We would also like to thankfaculty members affiliated with the DELTA program, the College of Engineering and theCIRTL11 group at our university for their continued support (NSF Grant No. 0227592).References1.Biomedical Engineering Design, http://www.engr.wisc.edu/bme/courses/bme200.html2. K. Sanders, P. V. Farrell, and S. K. A. Pfatteicher, "Curriculum Innovation Using Job Design Theory," HumanFactors and Ergonomics Society Annual Meeting Proceedings, vol. 50, pp. 779-783, 2006.3. Introduction to Engineering, http://www.engr.wisc.edu/interegr/courses/interegr160.html4. Bernardoni S., Nimunkar A. J., Murphy J. and Courter S., “Student-initiated design and
of the engineeringdisciplines by addressing the motivational factors that are specific to each group.AcknowledgementsThe Academic Pathways Study (APS) is supported by the National Science Foundation underGrant No. ESI-0227558 which funds the Center for the Advancement of Engineering Education(CAEE). CAEE is a collaboration of five partner universities. We would like to thank MicahLande and George Toye for all of their support from helping to develop the research question toencouraging us to think more deeply. One of the authors (SP) received support from the NSFGraduate Research Fellowship and the Stanford Graduate Fellowship.References1. S. Sheppard, Atman, C., Stevens, R., Fleming, F., Streveler, R., Adams, R., & Barker, T. (2004
6% of the S&Eworkforce, and women make up 25%. These percentages contrast sharply with thedemographics of these groups in the current overall population and workforce; by 2020 over Page 14.779.240% of college-aged students will be racially/ethnically diverse3.Currently, the U.S. engineering workforce remains 90% white and male; engineering, inparticular, has not attracted women and URMs. Baccalaureate degrees received by both URMsand women in engineering peaked in 1999-2000 and have trended downward since then 5. Arecent study conducted by Engineers Dedicated to a Better Tomorrow used the NSFWebCASPAR database to document that although
distance learning and help to change passive delivery toa more active and flexible delivery methodology. It is also a very effective means for deliveringquality distance-workshops and collaborative research-projects where participants are not fromthe same geographical area. References 1. Amirian, S., “Pedagogy &Video conferencing: A Review of Recent Literature,” First NJEDge.NET Conference, 2003. 2. Owen, R. and Bosede A., “Return on Investment in Traditional Versus Distributed Learning,” 10th Annual Distance Education Conference, 2003. 3. Kriger, T. J., “A Virtual Revolution: Trends in the Expansion of Distance Education,” American Federation of Teachers, May 2001. 4. Patcha, A. and G. Scales
. With this slightmodification, course learning objectives can now be measured much more accurately.Note that it is not necessary to use all assignment problems as an assessment tool, but it isimportant to always specify course learning objective corresponding to a given problem.This has proven to provide the student a sense of ownership of the problem, therebyencouraging and motivating the student. Once the format is set for each homework, theinstructor can change problems from year to year, however maintaining thecorresponding related course learning objective. This way, the Excel spreadsheet neednot be modified further. HOMEWORK #1 The next question(s) addresses the following course learning objective(s): • Convert any number between
atMissouri University of Science and Technology. The principal conclusion is that it is imperativeto the success of this type of program to provide a mechanism for frequently collecting feedbackin order to prioritize and schedule activities to best meet the needs of participants.IntroductionThe National Science Foundation (NSF)-funded project “A Program to Facilitate ScholasticAchievement in Computer Science, Engineering, and Mathematics” at Missouri University ofScience and Technology (Missouri S&T) ran from August 15, 2004 through July 31, 2009. Thegoals of this program were to address: (1) the decline in the number of students pursuing degreesin mathematics, computer science, and engineering, and (2) the minimal rate of low-incomestudents
orientation toward cultural differences 35 Learning self-efficacy instrument: confidence in self-directed learning25, 36, 37 Miville-Guzman Universality-Diversity Scale (MGUDS-S) survey – cultural competency38, 39 Need for Cognition Scale: self-directed learning measure40 Pittsburg Freshman Engineering Attitudes Survey (PFEAS) 41, 42 Situational Intrinsic Motivation Scale: base motivation measure 43 Student Self-Determination Scale (SDSS) 44 Student Thinking & Interacting Survey 27, 28Bland notes that quantitative data such as the IDI should be linked with qualitative information,because the IDI can show that movement is taking place along the
topics and “new engineer” workforce skills—that we are seeking toprovide for students through the Build IT curriculum. Page 14.215.14AcknowledgementThis material is based upon work supported by the National Science Foundation under grantnumber ESI-0624709. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.Bibliography1 Jonassen, D. (2000). Computers as mindtools for schools. Engaging critical thinking (2nd ed.). Saddle River, NJ:Prentice Hall.2 Chambers, J. & Carbonaro, M. (2003). Designing, Developing, and
Campbell and Campbell (2000)’s study, they concluded the perceived need of facultyand students (referred as protégé in their article) from mentoring relationships[3]. The facultymentor has perceived needs including the altruistic desire to help students (beyond the helpafforded through assigned teaching and advising), need for evidence of activities demonstratingservice to the university (for tenure and promotion decisions), and opportunity for enjoyment ofthe friendship and relationship with students provided by mentoring. On the other hand, thestudent protégé approaches the relationship with expected needs, including help with schedulingand enrollment decisions, help interpreting degree requirements, career guidance, assistance incoping with
this type is not a working prototype product but a package of deliverables includingconcepts, descriptions of user needs, and specifications for products or systems, with thoughtfuldesign of the interface and the basic structure of the product(s) or system to be built. Comingfrom a technology background the design team should show a depth of understanding of thetechnical issues facing the product design.In order to achieve high quality results, such as those described above the designers (students)need to follow a reliable design and development process that requires discipline, technical skill,and creative design work. All the attributes for successful capstone courses will be required bythe students, some to an enhanced degree.4. The case
validated “best” set hadbeen stored on behalf of all.Background and Literature ReviewThe University of California (UC) is comprised of ten universities located in Berkeley (N), Davis(N), Irvine (S), Los Angeles (S), Merced (N), Riverside (S), San Diego (S), San Francisco (N),Santa Barbara (S) and Santa Cruz (N), nicely divided into five Northern (N) and Southern (S)campuses. Two Regional Storage Facilities (RLFs), north and south, located near Berkeley andin Los Angeles, have provided storage space for older and lesser-used materials for about threedecades. For a conceptual description of the roles of the RLFs, see Schottlaender1. Recentpolicy changes have led to them being managed as persistent shared collections. This changeguarantees that
, T(r | p) T(p | p) for all r p andT(r* | p) T(p | p) when r* = p. [1-4] Many strictly proper scoring rules have been developed.Three of the most popular are given below.Quadratic (Q): Qi (r ) 2 ri r r [1,1] (2)Spherical (S): Si (r) ri / (r r)1/2 [0,1] (3)Logarithmic (L): L i (r ) ln( ri ) ( ,0] (4)The range of possible scores differs considerably. For example, logarithmic scoring holds thepossibility of an infinitely negative score. While this may seem like a defect, we will argue thatthis feature is a benefit of log scoring. Any linear
projects; rather it directs you to these resources and how onecan initiate working on projects. Although the goal of this paper is to address educators on how to promoteengineering education through NXT, but not to focus too much on the building andprogramming instructions or procedural steps involved in a robot design, as the NXT kitcomes with very clear and user friendly instructions[2][5][6]. However, the author(s)would like to cite one specific “Multi –NXT robot design” that students at University ofNorth Dakota built and programmed, because it is definitely worth mentioning. The author (s) would like to address this project in particular in two differentPhases:Phase I – To get to know the NXT kit and its programming blocks by
and Techniques for et al. Residential Buildings 4. Consequence of Climate R. H. Chaudhary Texas Section ASCE 2008 Change on the Infrastructure 5. Green Buildings – Y. R. Kanapuram ASEE Gulf 2008 Sustainable Construction Southwest 6. Sustainable Building Design S. R. Yardimalla ASEE Gulf 2008 Southwest 7. Overview of Adaptive A. P. Pakalpati Texas Section ASCE 2007 Techniques and Materials used in Sustainable Buildings 8. Effective Municipal Solid D. Siringi
Promote Growth. Journal of Engineering Education, Vol. 93, No. 4, 279, 2004.8. D. Tolfree. Commercializing Nanotechnology. Concepts–products–markets. Int. J. Nanomanufacturing, Vol. 1, No. 1, pp. 117-133, 2006.9. S. Fonash et al. Nanotechnology Education: The Pennsylvania Approach. MRS Symposia, Vol. 931, Section E, 2006.10. A. K. Lyton-Jean, H. S. Han, and C. A. Mirkin. Microarray Detection of Duplex and Triplex DNA Binders with DNA-Midified Gold Nanoparticles. Analytical Chem., Vol. 79, pp. 6037-6041, 2007.11. J. S. Lee, S. I. Stoeva, C. A. Mirkin. DNA-Induced Size-Selective Separation of Mixtures of Gold Nanoparticles. J. Am. Chem. Soc., Vol. 128, pp. 8899-8903, 2006.12. J.R. von Ehr, “Zyvex Corporation: Providing Nanotechnology
AC 2009-233: TEACHING SHIP STRUCTURES WITH SHEET METALWilliam Simpson, United States Coast Guard Academy Dr. William M. Simpson, Jr. is a faculty member in the Engineering Department at the U.S. Coast Guard Academy. He has a Ph.D. in Aerospace Engineering from the University of Maryland, a Masters in Naval Architecture and Marine Engineering from Massachusetts Institute of Technology, and a Bachelor of Science from the U. S. Coast Guard Academy. He is a registered Professional Engineer in the State of Connecticut. He served on active duty in the U.S. Coast Guard from 1965 to 1992 and had assignments in Marine Safety, Naval Engineering, Acquisition, and Research and Development
: dI (t ) 1 R 1 = ea (t ) − I (t ) − eb (t ) dt L L L Tm (t ) = K i I (t ) eb (t ) = Kω (t ) d ω (t ) 1 1 = Tm (t ) − TL (t ) Page 14.321.7 dt J Jwhere • Ki is the torque constant (Nm/A); • K is the back emf constant (V/(rad/s)); • I(t) is the armature current (A); • R is the
by supervisors and chosen by students, while many projects were integrated into thecommunity making them service learning challenges. Furthermore, most projects were funded byindustry partners and thus, the University incurred little or no research costs. Anecdotal feedbackfrom students indicated that most were inspired in their project selection by a particular pre-requisite course (and/or associated faculty member). Usually, students demonstrated a strongaptitude in the research discipline of their project indicating that they perform better in topicswith which they enjoy. We are unsure how students chose their team mate(s) as some of thegroup members had very different aptitudes, work styles and attitudes. We speculated thatstudents
to best fulfill the assignment’s outcomes within the given timeframe, while teaching students about the writing process and self-help strategies. It is also wellcited in the literature that since the 1980’s, US undergraduate writing centers have been serving agrowing population of ESL graduate students, which is the case at UI as well.77 This isproblematic because most peer tutors are undergraduates trained to meet undergraduate writingneeds and so graduate students who visit writing centers may not receive the kind of targetedassistance they need. In this study, GA’s generally rated a graduate writing center’seffectiveness in addressing the identified challenges lower than faculty did. Although notspecifically mentioned, perhaps GA’s who
Environmental Engineering (GT EnvE) ≠ Jenny Eaton, Administrative Coordinator for GT EnvE ≠ Kuo-Jen Liao, GT AEES Dialogue for Academic Excellence Committee (DAEC) ≠ Emily Lantrip, GT AEES DAECLast, but certainly not least, the authors would like to sincerely thank the entire GT EnvE studentpopulation and the GT EnvE faculty and staff who have been supportive in understandingstudent needs and concerns. Page 14.1237.15References1. Rogers, S., Noonan, J., Baek, J., Lee, S., Tezel, U., Michalski, G., Hou, C.-H., A successful student-initiated assessment method for an environmental engineering graduate program. Proceedings from ASEE's
(hrs) * Time (one day/hrs) (4)Where, W: Overall energy stored; Joule (J) = unit of energy (5) P: Number of people a day; 1J=1N.m=1kg.m2/s2 =1V.C =1W.s E: Energy recovered from one person; Watt (W) =unit for power (6) T: Time taken to store energy; and 1W= 1J/s =V.C/s=V.A Time: Time span for one day.In order to calculate the total energy stored in a day (24hrs), it was considered that 1mJ energycould be recovered per person according to the equations 5 and 6. In this case the total energystored in a battery can be calculated for 50 people as
, phasediagrams and microstructures.AcknowledgementThe authors acknowledge the support of this work from NSF CCLI Grant #0737146.Bibliography1. Boulter, C. J., & Buckley, B. C. (2000). Constructing a typology of models in science education, in Gilbert, J. K., & Boulter, C. J. (Eds.), Developing models in science education. Dordrecht, Netherlands, Kluwer Academic Publishers.2. Ben-Zvi, R., Eylon, B., & Silverstein, J. (1986). Is an atom of copper malleable? Journal of Chemical Education, 63, 64–66.3. Donovan, M. S., Bransford, J. D. & Pellegrino, J. W. (Eds.) (1999). How People Learn: Bridging research and Practice. National Academy Press, Washington, DC.4. Kikas, E. (2004). Teachers' conceptions and misconceptions
improved instructors.References1. Newborn, Timothy. (2009). “National Military Academy of Afghanistan host 1st graduation ceremony.” CSTC-A News, Combined Security Transition Command Afghanistan, Kabul.2. Photo taken by LT. Cmdr. John Gay, CSTA-photographer, 2009.3. Hamilton, S., “NMAA Command Brief,” Combined Security Transition Command-Afghanistan, Kabul,Afghanistan, May 2008.4. Epstein, J., Masters: Portraits of Great Teachers. New York: Basic Books, 1981, p. xiii.5. Ressler, S., Gash, R., Conley, C., Hamilton, S., Momand, F., Fekrat, Q.and Gulistani, A., (2008) “Designing aCivil Engineering Program at the National Military Academy of Afghanistan”, American Society for EngineeringEducation Annual Conference, Pittsburgh, PA.6. Ressler, S
relationship between two randomvariables are linear, and, therefore correlated instead of random. R1’s and R2’s correlation onthe coding of McGown level sketches is statistically significant (p-value = 0.048). R1’s andR2’s correlation on the coding Yang level sketches is also statistically significant (p-value =0.006). The relationships between R1 and R2 coding with McGown and Yang sketch codingschemes are strong, 0.881 and 0.972 respectively. Page 14.1063.9The results of the coding indicate that the vast majority of the 418 sketches were coded in thelowest 2 levels of both sketch-coding schemes. The average number of sketches in level 1 forMcGown’s