was voltage while it wasintensity in the other. Again, this is a true statement but misses the important point that thedependent variable in one case was time while it was the phase in the second applet. Real-timefeedback about responses students give to such animations may help them to be more carefulobservers and place those observations in the context of some underlying principle. These areimportant problem solving and engineering design skills.ConclusionWe have demonstrated a pedagogical technique for utilizing wireless tablet computers to provideopen-ended feedback of conceptual understanding of applet simulations in an engineeringcontext. The results indicate a strong learning gain. Real-time feedback guides the instructor inaddressing
mindset beliefs while encouraging deliberate practice, self-checking, and skill improvement as students work.Mr. Zhiyi Li, Virginia Tech/Department of Computer Science I am a Ph.D. graduate student in Department of Computer Science in Virginia Tech since Fall, 2013. My research interests is computer science education. Before that, I worked as a research staff in School of Medicine in University of Virginia from 2007 to 2013. I hold a Master degree in Computer Science in Virginia Tech. Master degree in Computer Science and Chemistry in Georgia State University in Atlanta, GA. I obtained my Bachelor degree of Engineering in East China University of Science and Technology in Shanghai, China
have been designed toproduce an engaging student learning experience [4, 5]. Learner collaboration in games wasshown to be an effective method of enhancing student motivation and interest [6]. It wasdetermined that the visual nature of these games are very helpful for providing a more intuitiveview of certain classes of algorithms. The approaches above require the designing of interfacesor animations that simulates payable games. This paper designed an approach that doesn’tinvolve a complex interface designs but still motivates student’s algorithm learning throughsimple game design.A major disadvantage the aforementioned approaches is that the instructor must locate, purchase,or develop sophisticated software for each algorithm or class of
Schaumberg, IL. He joined the UTB/TSC in 2000. His areas of interest include Imaging, Visualization and Animation, Web Design and Graphics.Juan Iglesias, University of Texas-Brownsville Dr. J R Iglesias is an Assistant Professor in the Computer Science/Computer Information Systems at University of Texas at Brownsville/Texas Southmost College. He received his Ph.D. in Computer Science from New Mexico State University (NMSU), New Mexico, USA, with specialization in Databases, and the B.SC and M.S. in Computer Science from the National Autonomous University of Mexico. He has worked as an Associate Director for the Federal Electoral Institute (IFE), Mexico City, Mexico during the 1997 year. His
American Society for Engineering Education, 2015 Stimulating the Learning Process in Mathematics and Numerics using Mathematica.Abstract –The development of fast, powerful laptop computers during the last twenty yearshas greatly facilitated the solving of complex problems in a variety of scientific research areas.By using such devices, teachers and educators are able to utilize their research results in theirday-to-day work among students on campus. In my situation, teaching engineering studentsmathematics and physics at Oslo and Akershus University College, I have benefited greatlyfrom using Mathematica, an excellent programmng tool developed by Steven Wolfram andhis colleagues at Wolfram Research, Champaign, Illinois
Paper ID #33766Design and Outcome of a Course on Software-defined Radio Within theComputer Science DepartmentDr. Marc Lichtman, University of Maryland College Park I am an adjunct professor in the dept of Computer Science at UMD where I teach an undergrad elective that I created, introducing the CS students to digital signal processing, wireless communications, and software-defined radio. I do it in a non-traditional and hands-on manner, because the students are strong programmers but don’t have the same type of signals and systems background EE students do. I have a PhD in EE from Virginia Tech where I studied wireless
AC 2011-120: USING THE PROCESSING PROGRAMMING ENVIRON-MENT IN ENGINEERING EDUCATIONRyan J Meuth, University of Advancing Technology I graduated from UMR with a B.S. of Computer Engineering in 2005, after which I stayed at UMR (Now Missouri University of Science and Technology) to pursue and complete a Master’s and PhD in computer engineering. I worked for Dr. Donald C. Wunsch at the Applied Computational Intelligence Laboratory in the Department of Electrical and Computer Engineering. There I worked on the Learning Applied to Ground Robotics project, developing a ground vehicle that can not only navigate unknown terrain, but be able to learn from experience with the world. During the summers since 2006 I worked at
. These techniques include interactive exercises, immediate feedback,graphical modeling, physical world simulation, and dynamic animations and exploration. The CBImodules employed interactive multimedia modules (CD-ROM and Online Teaching-Learning- Page 8.123.1“Proceedings of the 2003 American Society for Engineering Education Annual Conference & Exposition Copyright ©2003, American Society for Engineering Education”Testing OTLT methods) that were meant to improve students’ integrative understanding of basicconcepts and to emphasize problem solving. The authors are assessing the integration of
Page 25.1010.12generally shown in many FEM software packages.Once the simulation has been solved, the user is able to save the results in the form of a text fileto the local machine. The savable results include the original node locations created by themeshing routing, the tetrahedral elements represented by four nodes, the nodal displacementscorresponding to each node, the elemental strains and stresses (both normal and shear), and thevon Mises stress invariant. The text file had been arranged so that it can be easily delimited andimported into standard spreadsheet software.III. Cluster ImplementationThe HPC cluster has much greater computing power than most personal machines, greatlyreducing the computational time required for 3D FEM
communication, on-lineclass notes, video lectures, animated instructions and simulated demonstrations. There are effortsby several engineering instructors to use the computer and Internet as a means to introduce topicsor facilitate learning. Implementation of these multimedia tools has the potential to improvestudent performance.One such multimedia tool is a computerized statistic module. These modules are animated tutorialsthat demonstrate some course topic. The modules present formal text definitions supplementedwith working examples. For instance, the module could explain the concept of statistical mean andgive the accompanying equation. Then the module could demonstrate how to calculate the mean.The modules are accessed via the course web site. The
problem-solving strategies through games and computer simulations. In R. D. Lansiquot (Ed.) Cases on interdisciplinary research trends in science, technology, engineering, and mathematics: Studies on urban classrooms (pp. 268-294). New York: Information Science Reference.[4] Cooper, S., Dann, W., & Pausch, R. (2000). Alice: A 3-D tool for introductory programming concepts. Journal of Computing Sciences in Colleges, 15(5), 107-116.[5] Cooper, S., Dann, W., & Pausch, R. (2003). Using animated 3D graphics to prepare novices for CS1. Computer Science Education, 13(1), 3-30.[6] Davies, S. P. (1993). Models and theories of programming strategy. International Journal of Man-Machine Studies, 39(2), 237-267.[7] Kuh, G. D
system are positive. It appears that we may continue to develop similar types of IntelligentTutoring Systems for other engineering subjects. It also appears that CNC Tutor‘s explanationsand feedback are a good fit for active, visual learners. Possible enhancements include theaddition of more video and/or simulations to help learners to visualize abstract concepts,IntroductionIntelligent tutoring systems (ITS) are computer-based teaching environments that incorporatemathematics, cognitive science, natural language processing, and human-computer interaction[1]. In recent years, the use of ITS in classrooms and communities has increased and they haveproved to be very effective. For example, the Cognitive Tutor developed by Carnegie Learningwhich
a process insteadof a modeling tool or software program and significantly broaden their insights into BIM beyondthe existing 3D, 4D, and 5D applications. This paper will serve as a case study of an advancedlevel BIM course in CM programs.BIM in CM EducationFrom CAD to BIMDue to the standard use of paper drawings in the AEC industry, 2D computer-aided design(CAD) drafting has been traditionally used in CM education to facilitate the curriculum acrossvarious subjects including estimating quantity and cost, developing construction sequence andschedule, and analyzing site layout and safety risks1. While being widely used as a pedagogicaltool, it often requires some degree of students’ prior experience to interpret 2D CAD drawingssince students
analysis that may include fixed, running cost, amortized cost, unit cost, and other economic considerations, (iv) describe the fabrication/Assembly/Simulation/Testing of the Model or Prototype, and (v) document the physical or computer model, test results, and design verifications.6. Ability to provide appropriate discussion, conclusions and recommendations This performance criterion is assessed by determining how well students are able to clearly (i) summarize the goals, Objectives, and indicate whether they were met, (ii) summarize constraints and codes and indicate whether they were met, and (iii) provide logical conclusions and recommendations (including strengths and weaknesses).Performance Criteria for Outcome Group 8Outcome
nations’ K-12science students [7]. Forty-one states and the District of Columbia adhere to the CCSS [8]. BothNGSS and CCSS require learners to be capable of CT practices such as creating, using, andassessing data representation models. However, like many reform movements, it has been left toteachers, schools, and districts to implement CT-based instruction and survey data shows that themajority of K-12 teachers do not feel well prepared to teach computational thinking includingbreaking computer science problems into parts and using computational artifacts [9].Virtual Reality FrameworkWeb-based VR environments show enormous promise for capturing teacher and studentattention in PD and instruction. "VR is basically a way of simulating or replicating
necessary and valuable in student learning, they canbe a source of frustration to students. This frustration can come from many different sources; onesource, as noted by Estrada and Atwood [17], is the lab documentation itself. In their survey ofstudents, they found that confusing lab documents was second only to equipment failures as asource of frustration. As a primarily simulation-based lab has minimal equipment if any otherthan computers, this supports the contention that improvements in lab documentation are aworthwhile use of instructor time in attempting to improve student lab experiences. Cognitiveload theory indicates that a student’s working memory is finite [18], and therefore the cognitiveload of switching back and forth between
recognition. He has authored or co-authored more than 60 technical journal and conference papers on these topics. He is a Senior Member of IEEE and member of ASEE. Page 25.1396.1 c American Society for Engineering Education, 2012 Understanding the Difference between Classroom Learning and Online Learning on Medical Imaging with Computer Lab ExercisesAbstractIn this paper we present a study on the effectiveness of using a computer simulation software,SimuRad, in an undergraduate Medical Imaging course. This course is offered regularly in twodifferent modes, i.e. an on-campus section in every Fall
. Page 26.1587.1 c American Society for Engineering Education, 2015 Torsion Mobile App for Engineering Education Using a High Performance Computer (HPC) ClusterAbstractEngineering students are rapidly expecting learning tools to be delivered on their tablets andsmart phones, including simulation tools for basic courses such as solid mechanics. To addressthis issue, a basic torsional stress simulation tool for mobile devices was developed andimplemented into a traditional first year solid mechanics class (Mechanics of Materials). The app,Torsion HPC, allows students to determine shear stresses for a variety of common torsional barcross sections. The app was used in class for discussion
for solution. ANSYS CFD Post allows the user to better visualize the simulation resultsthrough vectors, streamlines, plots, contours, animations etc.4. Course structure: Computational Fluid Dynamics (CFD)Thus, the proposed CFD course will be structured with a significant portion of CFD tutorial andexercise materials as introduced earlier. In this section, a brief introduction of CFD coursestructure is presented in order to shed light on course prerequisites, course description, coursetextbook, semester projects, and course evaluations.The course is proposed to develop as an elective course for senior undergraduate students,however, first-year graduate students are also allowed to take the course. To be eligible forregistration of the course
how to usethe Python programming language, Maya, and the quadratic formula to create an animation of abouncing ball. Through this, the students could visualize how the quadratic formula computesthe height of an object in free fall and how programming languages can be used to createapplications such as those used in gaming systems. To create the animation, the position of the ball should automatically be recorded foreach frame. The height formula computes the height at any given point in time given initialvelocity and gravity. The value of t will vary from 1 up to a certain number of frames. To do so,the scripting language Python is used, and a frame is recorded at every value of t. For demonstrations purposes in the Maya 3D
AC 2012-4258: ACCELERATING K-12 INTEREST IN COMPUTER SCI-ENCE USING MOBILE APPLICATION-BASED CURRICULUMSMr. Korey L. Sewell, University of Michigan, Ann Arbor Korey Sewell received his B.S. in computer science from the University of California in 2004, and his M.S. in computer science and engineering in 2007 from the University of Michigan, Ann Arbor. He currently is a doctoral candidate at the University of Michigan, Ann Arbor. He has research interests in high-performance microprocessor design, on-chip interconnects, and simulation modeling. His teaching interests include languages and tools for introductory programming, as well as computer science curricu- lum design for pre-college and college engineering
AC 2008-142: INTEGRATION IMAGE ANALYSIS PROJECTS IN ANINTRODUCTORY COMPUTATIONAL METHODS COURSE USING MATLABSOFTWARE ENVIRONMENTAbhijit Nagchaudhuri, University of Maryland Eastern Shore Abhijit Nagchaudhuri is currently a Professor in the Department of Engineering and Aviation Sciences at University of Maryland Eastern Shore. Prior to joining UMES he worked in Turabo University in San Juan , PR as well as Duke University in Durham North Carolina as Assistant Professor and Research Assistant Professor, respectively. Dr. Nagchaudhuri is a member of ASME, SME and ASEE professional societies and is actively involved in teaching and research in the fields of engineering mechanics, robotics
interests include electrocardiography, 3D modeling, and simulation of the adverse electrical and thermal effects of electrosurgical devices. He is a member of the IEEE and ASEE. Page 23.91.1 c American Society for Engineering Education, 2013 A Project Based Implementation of a Power Systems Course for Electrical and Computer Engineering Technology StudentsAbstractWestern Carolina University (WCU) is the only educational institution that offers engineeringand technology degrees in the western part of the state. As the power industry is becoming one ofthe major recruiters of our
career decisions. One male student explained: I think, in the culture of robotics... I went to RoboCup two years ago, and I did not know what I want to do in college, through participating in the competitions, you know, I want to do engineering in college. Doing this actually helped me to decide what I am going to do in the future. Page 24.852.15Another female student on the panel followed up and stated: It’s actually interesting that a lot of us are actually interested in engineering or looking at engineering and robotics, or computer science and robotics. Doing robotics at school and going to RoboCup I
students are given Tablet PCs as freshmen. Thesemachines are powerful enough for much of their work in all three classes, aside from somespecialized assignments. Because all students have machines, we do not have labs, aside fromone to house the console gaming equipment (as we describe later). Comp 441. COMPUTER GAME DESIGN AND DEVELOPMENT. This course covers concepts and methods for the design and development of computer games. Topics include: graphics and animation, sprites, software design, game design, user interfaces, game development environments. Comp 446. ADVANCED COMPUTER GAME DESIGN AND DEVELOPMENT. This course is a continuation of Computer Science 441 and is focused on the development
Paper ID #15900WORK IN PROGRESS: A Computer-Aided Design Intelligent Tutoring Sys-tem Teaching Strategic FlexibilityYang Hu, Washington State University Yang Hu obtained her Bachelor degree in major of applied chemistry in 2005. Then she continued a graduate study in polymer physics and chemistry from 2005 to 2008. After working for a year as a recycled material product manager, she came to the U.S. began the graduate study at Washington State University. She got her Master Degree in Mechanical Engineering in 2013. She currently is a Ph.D. candidate in Computer Science. She is interested in applying Reinforcement learning
holds a Ph.D. in Control and Dynamical Systems from the California Institute of Technology and a B.Sc. in Pure and Applied Mathematics from the University of Western Australia. His research is in the field of scientific computing and numerical analysis, where he works on computational algorithms for simulating complex stochastic systems such as atmospheric aerosols and feedback control. Prof. West is the recipient of the NSF CAREER award and is a University of Illinois Distinguished Teacher-Scholar and College of Engineering Education Innovation Fellow.Prof. Timothy Bretl Timothy Bretl is an Associate Professor of Aerospace Engineering at the University of Illinois at Urbana- Champaign. He received his B.S. in
AC 2012-5143: INTRODUCING A REMOTELY ACCESSIBLE OPTICALLABORATORY FOR UNDERGRADUATE STUDENTSProf. Farid Farahmand, Sonoma State UniversityDr. Saeid Moslehpour, University of Hartford Saeid Moslehpour is an Associate Professor and Department Chair in the Electrical and Computer En- gineering Department in the College of Engineering, Technology, and Architecture at the University of Hartford. He holds a Ph.D. (1993) from Iowa State University and bachelor’s of science (1989) and mas- ter’s of science (1990) degrees from University of Central Missouri. His research interests include logic design, CPLDs, FPGAs, embedded systems, electronic system testing, and eLearning. Email: mosleh- pou@hartford.edu.Mrs. Harika
community. Much of the research is stillworking out how to model emotion from one or more data sources and does not attempt toincorporate the model in an ITS. For example, Grafsgaard et al. tracked student posture, gestureand skin conductance during human-to-human, computer-mediated tutorial dialogues about Javaprogramming. They found that students’ shifts in posture and gesturing were associated withparticular types of dialogical moves by the tutor (e.g., positive feedback).Pedagogical agents are anthropomorphic characters in educational software that are usuallyrepresented by static or animated avatars and are used to deliver notifications, messages andtutorial dialogues. We found that systems combining ITS with pedagogical tutors, which
performance on core curricularmaterial. For the question, “People who like computers are weird,” there is a significant correlationbetween gender and agreement with this statement, r(70) = −0.254, p < 0.05. The four studentswho responded positively to this question were all male. Gender also correlates to responses to thequestion, “Learning to program a computer is something I can do without,” r(70) = −0.309, p <0.01. Female students, in majority, disagreed with this statement while male students agreed withit. Examining the questions that pertain to home ownership of computers and the perceivedusefulness of and computers, we note that the overwhelming majority of students, 86%, reportowning a computer at home and that 70% of students use