forinformation extraction at various levels and resolution. Machine learning [3] promises toprovide solutions for compression, parameterization and interpretation of sensor data. Variouslevels of the system are employed to learn from the sensor data and further to carry out apredefined set of objectives such as classification or clustering of the data.In this paper, we describe the development of an online learning environment that supportsmodules and laboratories for training undergraduate students in multiple disciplines in sensorsand machine learning. This project is part of an NSF IUSE module development grant anddescribes a variety of sensor systems, their properties, and the process of interpreting signalsusing classification algorithms. We have
Engineering Profession n/a I am familiar with what a practicing engineer does. n/a6a. Exposure to Project-Based Learning Methods (Individual n/a Projects) Since September, what percentage of your classes used the following n/a teaching methods? Individual Projects:6b. Exposure to Project-Based Learning Methods (Team Projects) n/a Since September, what percentage of your classes used the following n/a teaching methods? Team Projects:7. Collaborative Work Style .61 I prefer working as part of a team to working alone. .46 I am a collaborative person
growing global environmental concerns overtheir use for the generation of electric power have increased the interest in the utilizationof renewable energy. This also raises the needs for engineering and sciences programs toprovide training in the areas of renewable energy technology. New programs, courses andsupport laboratories need to be developed and implemented. This paper describes thedevelopment of a design module that forms part of a project-based course in solar-windenergy systems taught at one of the author’s former institution during the Winter 2006term. Course materials were developed during the summer 2005 and fall 2006. Thismodule, which is part of the course-support laboratory, consists of a decision supportsoftware application used
they would with traditional techniques.” Bowen 13 describes an introductory class incomputing that is focused on MATLAB as a replacement for FORTRAN. As Bowen observes,“Inclusion of computer programming early in the curricula has been seen by the CivilEngineering faculty as a way of improving the students' skills in logical reasoning, application oftechnical knowledge, and quantitative problem solving.” The students “write MATLABprograms as an integral part of a structural design project where groups of students competeagainst one another to produce a truss-style balsa wood bridge having the highest profit.Throughout the semester a series of homework assignments require students to write MATLABprograms that calculate separate bridge
outcomes. Students develop an electronic portfolio that includes samples oftheir most important learning experiences which may be projects, term papers, extracurricularexperiences, as well as capstone and internship reports. The electronic portfolio is regularlyreviewed and assessed by faculty members to monitor student progress and assess theirachievement of various learning outcomes. A course-outcome matrix is developed for programassessment. The matrix includes a list of all IS courses, their learning outcomes and the expectedachievement levels for these outcomes. At the end of a semester, all courses are analyzed fortheir effectiveness in covering various learning outcomes. The results of this analysis are used toidentify courses that seem
currently the Project Director of RAMP-UP, a K12 math outreach program funded by the GE and the National Science Foundations. She obtained her BS degree in engineering management with a minor in mechanical engineering from the University of Missouri-Rolla in 1983. After over 10 years with IBM, she resigned to concentrate on raising her children, partnering in a science education business (Science Surround) and consulting for NC State University’s College of Engineering.Karen Hollebrands, North Carolina State University KAREN HOLLEBRANDS is an Assistant Professor of Mathematics Education at North Carolina State University. She completed her Ph.D. in Mathematics Education at The Pennsylvania State
AC 2007-1671: THE NATIONAL CENTER FOR ENGINEERING ANDTECHNOLOGY EDUCATION: SUPPORTING TEACHER PROFESSIONALDEVELOPMENTKurt Becker, Utah State University Kurt Becker is a Professor and the Department Head of Engineering and Technology Education. He is the Co-Principal Investigator for the National Science Foundation (NSF) funded National Center for Engineering and Technology Education and Principal Investigator for the NSF funded project: Communities of Effective Practice: A professional STEM Development Partnership Model for Teachers of American Indian Students. His areas of research include adult learning cognition, engineering education professional development and technical training. He works
Harvard University and B.S. from Rice University. He is a Chairman of Physics Department at Suffolk University. His research interests include neural networks, wireless motes, and ellipsometry. He has a strong commitment to teaching and integrating innovative technology to better reach his students, from streaming video and electronic writing tables for distance learning to using wireless mesh-networking devices in undergraduate research projects. His academic awards include C.W. Heaps Prize in Physics and Phi Beta Kappa from Rice University, Woodrow Wilson Fellow at Harvard University, and Carnegie Foundation Massachusetts Professor of the Year in 2005.Chris Rogers, Tufts University
address this problem. At Southern Illinois University in Carbondale, the College ofEngineering has adopted an “Introduction to Engineering Course” that is required of all freshmenmajoring in engineering. The course is described as a “lecture-laboratory course” that “allows Page 13.614.2students to work with hands-on projects that will teach the usefulness of mathematics and basicengineering concepts.” Another goal is to have students “better understand how fundamentalprinciples of science and engineering are useful in the profession.” An additional dimension ofthe work at SIU-C is to have students perform basic math computations with data
wecontinually improve our engineering curriculum.After reviewing the ABET standards, we determined that as a future-oriented university valuingthe worth of sustainability education, we must evaluate engineering courses to see howsustainability might be most effectively or most creatively introduced into the currentengineering curriculum, i.e., what the most effective pathways of learning might be. However,engaging in such a project requires a rigorous self-reflection process by all the stakeholders—faculty, staff, students, administrators—to successfully implement such curricular changes.Assessment of stakeholder attitudes is therefore critical to a study such as this.This paper will report on a research project that will: 1) extend the idea of
Institute.Allen White, Rose-Hulman Institute of Technology Allen White is an Assistant Professor of Mechanical Engineering at the Rose-Hulman Institute of Technology; he co-developed and co-taught the kinesthetic active supplemental learning opportunities for this project. Allen’s educational research interests include engaging kinesthetic learners and project-based learning. Allen has six years of industrial experience at Honda of America Manufacturing and Honda R & D North America.Glen Livesay, Rose-Hulman Institute of Technology Glen Livesay is an Associate Professor of Applied Biology and Biomedical Engineering at the Rose-Hulman Institute of Technology; he co-developed and co-taught the
-term exams (15% each) and a final exam (25%). The final exam is comprehensive. All students take the exams face-to-face on campus in the evening. The exams were computer based for all the students.5. Final Project (12% of course grade): Students are required to complete an online Project that is similar in nature to the Home Activities. The Project consists of three parts: Page 13.436.6 Part 1: Appliances Part 2: Lighting Part 3: Insulation.Results and DiscussionThe student learning performance was evaluated using the rubric previously described. Theresults are shown in Table 2. The timed quizzes consisted of 12-15
components of the system communicate with each other.Solid modeling was used to prove the concept of the physical system and optimize theconfiguration. In this phase of the project, hands-free imagery was achieved to be used by anoperator completing central vessel catheterization.The hands-free system provides the operator with the ability to use medical imaging to moreeasily and accurately find central vessels in clinical applications, and initiates the infrastructurefor future, fully automated catheterization which will be required for autonomous surgicalprojects such as the DARPA Trauma Pod Concept1. Another research group at the University ofWashington has been working on a remote, telerobotic operating room for use in militaryapplications
precluded the linkage of aresponse to a specific company.All of the respondents are working for the construction companies-holding the seniormanagement position either for the company and/or for the projects. Average workingexperience for the respondents in the construction industry is about 13 years. Questionsregarding respondents’ profile are shown in Figure 2. Page 13.741.4Figure 1: Systematic Approach to Determine Objectives and OutcomesThe Survey InstrumentThe survey instrument selected from listed IUGREEE 172 skills, knowledge descriptors, andexperiences that were mapped into the ABET 2000 Criterion 3 eleven outcome categories. Therespondents were
on their undergraduate major. This poses significant challenges tograduate faculty teaching these courses and mentoring these students with diversifiedbackgrounds.This paper focuses on our experiences and observations with the course content and structure,teaching methods, evaluation and student performances in these courses with diversifiedgraduate students and their mentoring for the past 3 years. The performances of the students inthese core courses based on the evaluations through tests, projects, etc., using the data collectedfor the past 3 years are correlated to their background and analyzed. Our experiences andobservations of the technical and interdisciplinary maturity from the time of the admission andthe graduation of the students
] compiled a subjective assessment of common mistakesin finite element analysis routinely performed in many industrial sectors. After 5 years ofcollecting anecdotal evidence in both teaching undergraduates and advising capstonedesign projects, we found this list to be nearly inclusive of the most common and moreserious errors encountered by novice users of the finite element method. Here, we addseveral additional mistakes commonly observed in the classroom and in capstone designnumerical analyses and present the augmented list in Table 1. While it may come as nosurprise that novice users commit many, if not all, of these errors, they appear toroutinely and repeatedly encounter a particular subset of them. TABLE 1. COMMON MISTAKES IN
effort was put into creating. Fifth, the wide variety of high school coursecurricula that have been impacted by the project.3 Event Description An average of approximately 18 local high schools participate in this event each year for thepast 3 years, with a peak of 450 active participants in 2007 and 1,968 participants since 2001. Therehas been a year over year increase of approximately 20% for the seven year life of the event (seeFigure 4). Snow cancellation and rescheduling resulted in a reduction in the number of participantsin 2007. The competition held each winter in the Nutter Center in Dayton, OH pits teams of fourtrebuchets against each other (four trebuchets on each side) in a single elimination tournament. Schools design
14.1306.1© American Society for Engineering Education, 2009 Use of the Knowledge and Skill Builder (KSB) Format in a Senior Mechanical Engineering LaboratoryOverviewThis paper discusses the use of the Knowledge and Skill Builder (KSB) format in HofstraUniversity's ENGG 170 laboratory course during the Spring 2008 semester.The current investigation is a fifth-year research project of the NSF-funded MSTP 1, 2Project, "Mathematics Across the Middle School MST Curriculum" . KSBs werepreviously used by the author in a sophomore level Measurements and Instrumentation 3Laboratory course (ENGG 160A) . The success of the KSBs in that
AC 2009-914: IMPROVING STEM DOCTORAL STUDENTS’ RELATIONSHIPSWITH THEIR ADVISORS: WEB-BASED TRAINING IN INTERPERSONALPROBLEM SOLVINGJessica Rohlfing, Arizona State University Jessica E. Rohlfing is a Ph.D. student in Counseling Psychology at Arizona State University. She currently works as the lead research assistant of evaluation on CareerWISE, an NSF-funded project aimed at strengthening women doctoral students' persistence in STEM fields. She earned her M.S. in General Psychology from DePaul University, and she has BS degrees in psychology and sociology from Iowa State University. Her broad research interests include interpersonal theory and the examination of the interpersonal
AC 2009-953: NONPARAMETRIC, COMPUTER-INTENSIVE STATISTICSCOURSE MODULES FOR ENGINEERSDavid Mukai, University of WyomingTrent McDonald, West Inc. Consulting Statistican and Senior Manager, West Inc. Page 14.911.1© American Society for Engineering Education, 2009 Non-Parametric, Computer-Intensive Statistics Course Modules for EngineersAbstractThis NSF CCLI project develops materials for a new course in non-parametric computer-intensive (NPCI) statistics. This course is distinctly different from existing undergraduatestatistic courses in that the NPCI methods do not depend on assumed distribution functions (non-parametric) and rely
role of the engineer, three themes have been identified forconsideration: competitiveness and collaboration; environmental sustainability; andinternational development. Through a thorough consideration of these themes, andconsultation with individuals and groups in education and industry, a list ofcompetencies, defining the global engineer, was formulated: ≠ Strong technical competency ≠ Use of creativity in problem solving ≠ An ability to see engineering projects in the context of multiple disciplines ≠ A recognition of the business implications of engineering work ≠ A recognition of the social implications of engineering work ≠ An ability to work outside of one’s trained discipline ≠ Adaptability, in type, scope
Dr. Masatak Okutsu is a postdoctoral researcher in Purdue University School of Aeronautics and Astronautics. He provides expertise in Space Mission Design and is a co-instructor in the Introduction to Aerospace Design during past semester. Dr. Okutsu is leading the project development of AeroQuest Serious Game.Daniel Delaurentis, Purdue University Dr. Daniel DeLaurentis is an assistant professor in Purdue University School of Aeronautics and Astronautics. His research interests and specializations are in the area of Aeronautical and Systems of Systems expertise. He is lead instructor of the Introduction to Aerospace Design course
their respective home university, so that no exchange offunds was involved. Whereas the homework and assignments were given and corrected by thelecturing instructor, the local instructor coordinated the course and assigned grades to studentsaccording to the norms of his or her institution. The final examination for the first courseconsisted of joint projects completed via collaboration among students from differentinstitutions. The results of the project were presented at a national conference on glass where thestudents met with their classmates for the first time.In summary, the concept of MITT has been successfully demonstrated for teaching highly
extractionbased on potential speedups makes this scheme relatively limited in exploiting potential use ofHW components. Further, the assumption that HW and SW components execute in aninterleaved manner, and not concurrently, results in a system that under-utilizes its resources.The Processor Kernel DesignThe EFP10K20 FPGA device that is used for the engineering prototype project has over20,000 gates, 1,152 logic elements (LEs), and 6 embedded array blocks (EABs). Each EABprovides 2,048 bits of memory.The UP1 Boards provide the following resources for the FLEX 10K device which has beenused for the project. The pins from the FLEX 10K device are pre-assigned to switches andLEDs on the board.• JTAG chain connection for the ByteBlasterMV cable• Socket for
development, how to better project and manage cost, schedule andperformance of a project, how to do strategic planning for the organization, and how to improvefunctional team building and interpersonal skills, motivation and entrepreneurship. Somemarkets may desire the degree to promote more broadened technical skills in areas such asstatistical and economic analysis, systems modelling and design of experiments. In some casesthe functioml area degree may need overall specialty courses, such as, logistics, human factors,expert systems or reliability that are being served by the engineering management program. ALL Engineers - Scientists Industry - Government Orgn’s
information flow between instructors from different departments encouragesfaculty learning by pushing the instructors beyond their own discipline. This paper illustratessome of the course details employed between three engineering departments to advance andenrich a multidisciplinary controls engineering course. Advantages to empowering amultidisciplinary faculty are also described. The techniques described allow the students tobenefit from the work of a multidisciplinary faculty team and enrich the students’ understandingby bringing in real world projects and examples.IntroductionIn 2005 the National Academy of Engineering in “Educating the Engineer of 2020,” stated manyideas of co-teaching, just in time teaching, and multi-disciplinary teaching.1
Filters 9 Resistance/Capacitance Sensors Op-Amps 10 Linear Variable Differential Transformers, Strain Gauges Thermocouples, Thermistors 11 Accelerometers, Exam Thermocouples and Multi- channel Data Acquisition 12 Piezoelectric and Semiconductor Devices, Accelerometers Experimental Design 13 Electrical Noise LVDT “Design” Project 14 Standards and Codes, Review LVDT “Design” Project 15 Optional Topics No Lab 16 Final
Figure 1 and Table 1. Figure 1: Projected ten-year job growth Biomedical Engineering 23% All Occupations 7% 0% 5% 10% 15% 20% 25%Figure 1: Data from the Bureau of Labor and Statistics indicate that projected ten-year jobgrowth in biomedical engineering (23%) over a ten year period from 2014-2024 is significantlyhigher than the expected job growth for all occupations (7%) Table 1: Quick Facts: Biomedical Engineers 2015 Median Pay $86,220 per year; $41.45 per hour Typical Entry-Level Education Bachelor's degree
Paper ID #18471The Variation of Nontraditional Teaching Methods Across 17 UndergraduateEngineering ClassroomsMr. Kevin A. Nguyen, University of Texas, Austin Kevin Nguyen is currently a doctoral student in the Science, Technology, Engineering, and Mathematics (STEM) Education program at University of Texas at Austin. He has a B.S. and M.Eng in Environmental Engineering both from Texas Tech University. As an engineering and STEM education researcher, he draws on a variety of social science research methods from ethnography to regression modeling. He is currently working on two projects: engineering faculty’s use of active
lastiteration, the 2017 Report Card for America’s Infrastructure, America’s cumulative GPA forinfrastructure received a D+, which is the same as it was in 2013 although grades improved inseven infrastructure categories. The 2017 Report Card demonstrates that when investments aremade and projects move forward, the grades rise. In addition to this national Report Card,ASCE’s sections and branches also prepare state and regional Infrastructure Report Cards on arolling basis, to localize these public education and advocacy efforts to the state and local levels.Nearly half of the states have a recent Report Card.Infrastructure Categories, Grading Scale, and Key CriteriaThe 16 categories graded in ASCE’s Infrastructure Report Card include Aviation, Bridges