MatLab Marina vs. those that did not. The pre and posttest scores were analyzed using average normalized gains15 .Figure 3 shows the average normalized gains for the three sections (labeled as A, B and C) at Page 23.1395.5Armstrong that incorporated MatLab Marina (MM) in the curriculum. It can clearly be observedthat the learning gains are significantly higher in the concepts that include an extensive set of ASEE 2013 Annual Conferencetutorials in MatLab Marina. Concepts such as vector evaluation, curvefitting and structures haveyet to be developed in the VLE
Images ·· end_if ·· end_if·· end_if end_if end_ifend_if : :Smart Robotic Warehouse: A vision system was adapted to a simulated smart robot warehouse.This smart robot warehouse is composed of vision system with a camera installed on the ceilingto observe objects on the floor, in this case toy cars, and obstacles. The three toy cars aredifferent colors; red, blue, and green. In this case the obstacles are black so that the vision systemcan recognize the difference between the toy cars and the obstacles. After that, it develops a pathhaving each car move from point A to point B and produces X and Y
havingduplicated of same machines. The objectives of this paper are to: a) Compare the Traditional and Group Cell approaches for university students b) Presents an example of machining laboratory exercise.Literature ReviewIn education, hands-on laboratory practice is the key to effective learning. "I hear and I forget. Isee and I remember. I do and I understand" was preached by the famous teacher and philosopherConfucius (551–479 BCE) during Spring-Autumn period of Chinese history. Leighbody andKidd also concluded "learning requires active experiences" in their survey3.Nowak4 ranked teaching strategies and learning activities within technology education. Thehighest ranked strategy was the one with product-oriented and laboratory-based content
Proceedings of the 2011 Conference on Information Technology Education, West Point, NY: 9- 14.[2] ASES_EWC (2010). "Engineering & Technology Enrollments, Fall 2010 — Engineering Workforce Commission." Retrieved January 23, 2012, 2012, from http://www.ewc-online.org/.[3] Crookston, B. B. (1972). "A developmental view of academic advising as teaching." Journal of College Student Personnel 13: 12-17.[4] Pardee, C. F. (1994). "We profess developmental advising, but do we practice it?" NACADA Journal 14: 59-61.[5] Schneider, A. (1998). "Harvard faces the aftermath of a graduate student's suicide." The Chronicle of Higher Education 45(9): A12-A14.[6] Waterfall, E., E. Albrecht, et al. (2008). Developmental Advising – Exploring the
, 2011. Retrieved Mar 16, 2012 from http://csunplugged.org/. [3] Blum, L., and Cortina, T. J. CS4HS: an outreach program for high school CS teachers. In Proceedings of the 38th SIGCSE technical symposium on Computer Science Education (New York, NY, USA, 2007), SIGCSE ’07, ACM, pp. 19–23. [4] Blum, L., Cortina, T. J., Lazowska, E., and Wise, J. The expansion of CS4HS: an outreach program for high school teachers. In Proceedings of the 39th SIGCSE technical symposium on Computer Science Education (New York, NY, USA, 2008), SIGCSE ’08, ACM, pp. 377–378. [5] Bruckman, A., Biggers, M., Ericson, B., McKlin, T., Dimond, J., DiSalvo, B., Hewner, M., Ni, L., and Yardi, S. “Georgia Computes!”: improving the computing education
theidentification of the characteristics of everyday engineering workplace problem which makethem constraint rich. This information can be used in the design of more authentic problems forstudents 9which will better prepare the students for workplace engineering problems. Engineersfrom a professional society were asked to share information about typical problem they solved.From this study twelve themes emerged (see Table 2) which can help define some of theparameters of workplace engineering problems as well as (a) the types of problems we mightgive students to work on and (b) the different ways that students might frame or treat the designtasks that we give them (i.e. different ways that students might understand and approach the taskfor the Mathematics
Paper ID #6781Broadening Participation: A Report on a Series of Workshops Aimed atBuilding Community and Increasing the Number of Women and Minoritiesin Engineering DesignDr. Katherine Fu, MIT Kate Fu is Postdoctoral Fellow at MIT and Singapore University of Technology and Design (SUTD). In May 2012, she completed her Ph.D. in Mechanical Engineering at Carnegie Mellon University. She received her M.S. in Mechanical Engineering from Carnegie Mellon in 2009, and her B.S. in Mechanical Engineering from Brown University in 2007. Her work has focused on studying the engineering design team process through cognitive studies
Po, Y. (2006). UCLA Community College Review: Reverse Transfer and Multiple Missions ofCommunity Colleges. Community College Review, 33(3/4), 55-70.Prevost, A., Nathan, Mitchell J., Stein, B., Tran, Natalie, & Phelps, A. (2009). Integration ofMathematics in Pre-college Engineering: The search for explicit connections. Presented at theAmerican Society for Engineering Education Annual Conference 2009, Austin, TX.Reason, R. D. (2009). An examination of persistence research through the lens of acomprehensive conceptual framework. Journal of College Student Development, 50(6), 659-682.Rethwisch, D.G., Chapman, M., Schenk, T., Starobin, S., and Laanan, F.S., (2012) A Study ofthe Impact of Project Lead The Way on Achievement Outcomes in Iowa
, Government, Healthcare & Higher Education, Vancouver, Canada, October, 20055. Hofstede, Geert, Geert Hodstede Analysis, Retrieved January 2013 from http://www.geert- hofstede.com/hofstede_dimensions.php6. Prince, M., “Does Active Learning Work: A Review of the Literature,” Journal of Engineering Education, pp 223-231, 2004.7. Bhushan Trivedi,B. and Petrierackin, M., “Beginning to Apply IUCEE Effective Teaching Strategies in India: An Experience in a Master of Computer Applications Program,” Proceedings of the 2009 ASEE Annual Conference & Exposition, Austin, TX, June 2009.8. Mazur E., “Peer instruction: getting students to think in class” in: The Changing Role of Physics Departments in Modern Universities
homework score is also correlated with the final course grade.For example, when a student earned an “A” on the course, his/her homework score was above 90in average. Similar conclusion can be made for those students who scored “B,” “C,” “D,” and“F.” Many TAMIU students work very hard in their courses, yet a regular class time may not besufficient to create and interactive environment to address all the problems that students mayhave for the course. This situation is true for the classes where the student number is greater than40. Therefore, innovative methods must be devised and implemented to improve the retentionand class performance in mathematics, engineering, and physics. Table 3. Correlation between homework and
-biological-agricultural. Accessed December 2012.5. N. Hotaling, B. Burks Fasse, L.F. Bost, C.D. Hermann, and C.R. Forest. A Quantitative Analysis of the Effects of a Multidisciplinary Engineering Capstone Design Course. Journal of Engineering Education 2012; 101(4): 630-356.6. A.M. Kelly, E. Curtis, J. McCoy, D.D. Schulte, and D. Jones. Application of Data Management Tools for ABET Accreditation. Proceedings of the American Society of Engineering Education, 2012.7. B.S. Bloom. Taxonomy of Educational Objectives, and the classification of educational goals - Handbook I: Cognitive Domain. New York: McKay, 1956
determine theircareer choice in the engineering fields. The participating 27 students were selected according to(a) their content questionnaire scores administered to 145 students in 34 different locations (b)personal interest essays, and (c) phone interviews. At the camp, the students took (a) a computerprogramming course, (b) a basic electronics course, and (c) proteus, pic, and microC trainingsessions. The students in pairs designed, built, tested, and modified their robots through practicalimplementations. They were given a variety of design challenges in each practicalimplementation. In the camp, invited researchers presented about their research and interest inRobotics and showed interdisciplinary perspectives of Robotics activities in the
-surveys and participate in an exit interview at the end of the semester. The inventory wasdeveloped by NUE team members with expertise in nanotechnology undergraduate education.Inventory items are clustered across five domains, including: (a) Nanoscale dimension andbasics, (b) Synthesis methods, (c) structural characterization, (d) Carbon-nanostructure andBioengineering, and (e) Device applications. The exit interview was recorded and is in theprocess of being transcribed. A preliminary comparison of the pre- and post- data review of pre-/post- assessment data suggests that students experienced positive change-in-learning related tocourse content in all the five categories.INTRODUCTIONThe design and development of advanced materials, devices and
research collaborations between FSU, Pitt, UNIFEI, and UFPR 3.2 Create self-sustaining research collaborations between U.S. and Brazilian engineering faculty at the consortium universities 3.3 Create long-term teaching collaborations between U.S. and Brazilian engineering faculty at the consortium universitiesExpected U.S. Student OutcomesAfter completing the FIPSE-SEAEP exchange program, it was expected that studentswill: a. Be able to demonstrate proficiency in the Portuguese language (in oral and written form) b. Be able to explain and recognize the cultural differences between Brazilian and U.S. engineers c. Be able to explain the implications of designing and fabricating engineering products
necessarily reflect the views of the National Science Foundation.Bibliography1. Wiggins, G., & McTighe, J. (2005). Understanding by design (2nd ed.). Upper Saddle River, NJ: Pearson.2. Luft, J., Kurdziel, J., Roehrig, G., & Turner, J. (2004). Growing a garden without water: Graduate teaching assistants in introductory science laboratories at a doctoral/research university. Journal of Research in Science Teaching. 41(3), 211-233.3. Travers, P. L. (1989). Better training of teaching assistants. College Teaching. 37, 147-149.4. Mena, I. B. (2010). Socialization experiences resulting from engineering teaching assistantships at Purdue University. Doctoral Thesis, Purdue University, West Lafayette, IN.5. Verleger, M., & Velasquez, J
. F., "What Makes a Good Case? Some Basic Rules of Good Storytelling Help TeachersGenerate Student Excitement in the Classroom." Journal of College Science Teaching 27(3): 163-165,(1997).8. Jeannot, M. A., Case Study, “Baffled by the Baby Bottle”,Department of Chemistry, St. Cloud StateUniversity, http://sciencecases.lib.buffalo.edu/cs/files/baffled_notes.pdf9. Chen, K., Vanasuapa, L., London, B., savage, R., “Infusing the Materials Engineering Curriculumwith Sustainability Principles”, ASEE, 2006.10.. Herreid, C.F., “Can Case Studies Be Used to Teach Critical Thinking?”, Journal of College ScienceTeaching, Vol. 33, No. 6, (May 2004).Appendix:Case study 1: Fore! Nice breeze, beautiful water
. Graham has served as principal investigator on research projects addressing GIS technology and ed- Page 23.908.1 ucation, including projects on a) the development of a GIS carbon footprint model and b) anti terrorism and airborne contaminants, which recently were presented at the ESRI International GIS Users Confer- ences. From 2006 to 2013, Dr. Graham has presented his research at state, regional and international conferences. Dr. Graham has received several awards including National Black Herstory Task Force c American Society for Engineering Education, 2013
thequiz format is that it will help student learning by (a) prompting students to keep up withmaterial as it is being taught in class and (b) reduce text anxiety / pressure on the students, bydistributing the evaluation into smaller parts. Each quiz is worth 11% of the grade in the QuizMethod, and each examination is work 27.5% of the final grade in the Examination Method. Bymaking each testing instrument worth a lower percentage, it is thought that students will feel lesspressure when taking each quiz. However, this may also reduce the level of effort that studentsplace on preparing for each quiz. In addition, the Examination Method may prepare studentsbetter for the longer (2 hour) final examination, although students should be familiar with
categorized into three categories with four to seven specifictypes of technology included for each category:(1) Seating and Room Layout a. Lecture style seating arrangement b. Group tables arrangement c. Pods or node chairs d. Web-based learning – partial face-to-face e. Web-based learning – completely online(2) Boards & Projection Page 23.541.2 a. Chalkboards b. White boards c. Computer projection w/ instructor notes d. Document Camera(3) Video and Lecture Capture. a. Mobile computing: handhelds, Smartphones, tablet PCs, laptops, + b. Fixed Lab Computing c. Video capture
, N=11). RHIT does have a Code of Ethics by which studentsare expected to abide.At the second institution, the University of Notre Dame (UND), in addition to the 8 questionsasked in the RHIT survey, the ethics survey was expanded to include questions for comparison toliterature surveys, in particular a survey from the Center of Academic Integrity10 and a journalarticle from McCabe5. The ethics survey written and delivered to the students is available inAppendix B. At UND, a total of 126 students were polled: 68 second year, 55 third year, 3 fourthyear students. These students were primarily chemical engineering (ChE) students (124 ChE, 2computer science/engineering). The surveys taken in computer methods (CBE20258), processcontrols (CBE30338
were designed to assess student learning andthe effectiveness of the new course design. In order to evaluate the student background inLLL (step 1), a survey was administered at the beginning of the semester. A copy of thesurvey is presented in Table 1. Page 23.223.4Table 1. Survey questions used to evaluate the student background and understanding of Life-long learning. Q-1 From the following four options, select the one that describe your personal knowledge of the concept of “Life-long learning”? A. Extensive B. Moderate C. Limited D.No idea Q-2
bilinearly interpolating vectors usingthe Runge-Kutta fourth order method.Figure 2. Three visual forms of field-line representation: line, tube, and animated arrow.Line Drawing. Figure 2 shows an example streamline with all three forms of visualrepresentation we provide for field-lines: line, tube, and animated arrow. The first two formsshow the entire streamline statically, while the last one dynamically conveys a vector direction aswell as its magnitude along the streamline in an animated fashion. We utilize OpenGL functionsfor all the drawing. (a) (b)Figure 3. (a) 2D texture for tube drawing where the blue dashed line indicates a segment of thefield-line. (b) Maintaining the constant edge width
. Page 23.1366.5 Diagram A B C D E F G 1. Correct system structure N N Y N Y N Y 2a. Species balance N Y Y N Y Y Y 2b. Correct species N N Y N N N N 3a. Number of data missing 3 5 4 4 2 2 1 3b. Located efficiently Y Y Y Y Y Y N 4. Streams labeled N Y Y Y N N N 5. Free of distractions N Y Y N
(Treffinger et al., 1992). Page 23.613.5Creative problem solving, as a discipline, was originated by Osborn (1963) and furtherdeveloped by Parnes (1967) and other members of the Creative Education Foundation(Torrance and Safter, 1999). According to the Osborn (1963) and Parnes (1967) model,creative problem solving occurs in the following consecutive steps: (a) sensing problemsand challenges, (b) recognizing the real problem, (c) producing alternative solutions, (d)evaluating ideas, and (e) preparing to put ideas into use.The first step in the creative thinking process involves sensing problems and challenges,which simply implies that the problem solver
least 15 years old, with some dating back as far as 1986 in essentially thesame form. In Fall 2010 the course was taken over by instructor B, but otherwise retained thesame format, lab experiments, and project.It was clear at the end of Fall 2010 that the lab handouts were extremely dated and confusingto the students. For example, the handouts instructed students to bring a floppy disk to lab,despite the fact that this technology is clearly out of date and no longer used. Because of thisand in response to student feedback, instructor B kept the same lab experiments for Spring2011, but completely rewrote and updated the lab handouts in order to clarify objectives andanalysis questions. Instructor B also increased the number of active lecture
Development of a New Power Electronics Curriculum Relevant to Tomorrow’s Power Engineering ChallengesI. IntroductionThis paper presents the results of an effort to develop a new power electronics and electric ma-chines curriculum at two collaborating academic institutions, namely, Purdue University, WestLafayette, Indiana 1, and Iowa State University, Ames, Iowa 2, hereinafter referred to as Institu-tions A and B, in a bid to enhance the relevance of this subject to the undergraduate population.This is achieved via identifying the role of power electronics and machines in addressing tomor-row’s grand engineering challenge of sustainable energy use. This is a timely and important top-ic because of the increased demand for highly
more interested My classmate & I work together to help each other to understand materialCollaborativelearning I believe I will get better grade by participating in group work I would like to practice this type of group study in my other courses I learn more effective and understand material better by: a. Instructor solving examples in class (traditional method)Studentsoverall b. Instructor giving comments andpreference answer questions while we are solving problems in group (Group assignment done in class
are analyzed. Listed in thefollowing are the articulated benchmarks set to evaluate the attainment of each programoutcome:Metric 1: The percentage of the IT 495 students who receives a grade of 2 or higher (out of 3point) on the learning statements and supporting evidence for the designate program outcome.Metric 2: The percentage of the students who receive a grade of B or higher on two selectedcourse embedded assessments that measure the related program outcome. Page 23.1299.6Metric 3: The mean of the graduates’ perceptions of their achievement of the related programoutcomes (data collected from the exit survey).Metric 4 (Reference): The mean of
between stages (eg. A-> B) as shown in thefollowing figure8,9,10,33: Figure 2: Modeling Schema8,9,10,33This proposal explicitly incorporates two important elements: the inclusion of a physical domainwhich is modeled (probably an extra-mathematical, biological, or chemical domain) and theimportance given to the pseudo-concrete domain32 as the difficult transition for students but keyin the modeling process (real model). It is important to note that the mathematical model isunderstood as the different graphical representations of the ED: solution graph, the DE itself asan analytical model, and a table of data that can eventually be modeled by a DE and / or itssolution.The literature analysis has made it clear that
Page 23.245.4students into high and low academic GPA. While a letter grade of B equates to a 3.0, acumulative GPA of 2.5 was identified as the cut-off for high achieving students as thisGPA is the highest GPA requirement for entrance into an engineering discipline from thecommon freshman engineering curriculum. A low GPA is classified as less than 2.5 asthese students are prohibited from advancing through the curriculum in severaldepartments.FindingsWhen looking at the distribution of cumulative GPA’s of students who attrite, we foundthat 44% of students over a 3.0 and 67% over a 2.5 attrite from engineering. Additionally,we found that these students attrite between their second (first year, spring semester) andthird (second year, fall