Paper ID #12956Using BIM to support Habitat for Humanity: A case studyDr. Stan Guidera, Bowling Green State University Stan Guidera is an architect and a Professor in the Department of Architecture and Environmental Design at Bowling Green State University. He teaches design studios and computer modeling courses related to digital applications in design, design visualization, and computer animation. He has conducted work- shops, published, and presented papers at national and international conferences on a variety of digital design topics including design visualization, building information modeling, parametric modeling
two computer-based assessment games, each ofwhich targeted only one of the design thinking strategies (parallel design or seeking criticalfeedback) emphasized within each condition. As opposed to self-report measures or paper-and-pencil tests, the games provide process data of the choices students make while learning in newcontexts and within subject matter domains. Thus, they are a form of assessment that provides Page 26.828.2insight into students’ preparation for future learning5. In what follows, we report on the preliminary analysis of the game-based assessment ofinstruction of two design thinking strategies: seeking critical feedback
idea is well known in the field of conservationtechnology, discussed in the introduction in different ways. This includes using computer visionto identify between, say, a fox versus not a fox, or even can get down to the identification ofspecific fox individuals (Figure 2). Different wildlife cameras are currently being developed thatspecify target species, and there are many use cases in literature utilizing edge devices. We willgive one example here with that of EleTect [46]. This technique and application can be appliedto other camera-collected data, and identification between, say, fox versus not a fox or elephantversus not an elephant can be a simple task. There are specific animals around campuses orstudent dorms that would provide
’ learning styleand to determine their attitude towards PowerPoint lectures. The majority of studentssurveyed were found to be kinesthetic or read-write in their learning style. Those studentswho had experienced the animated PowerPoint presentations were much more favorabletowards PowerPoint than those who had not. Future work will compare VARK learningstyles of engineering students with those of liberal arts students and enhanced PowerPointlectures with PowerPoint that includes printed handouts.IntroductionIn order to succeed in engineering studies, students must possess certain cognitive traits: ≠ The ability to handle higher mathematics ≠ The ability to identify and formulate problems ≠ The ability to model physical situations with
(hypertext, sound, animation, simulation). Cobourn and Lindauer4 describedflexible, computer-controlled, interactive, multimedia thermodynamic modules that allowedinstructors to implement different kinds of in-class and out-of-class activities. Students haveresponded favorably to the modules. Fridman and Shelangoskie49 presented a web-based,multimedia, self-assessment tool that enabled students to become actively engaged in learningthermodynamics. The tool provided immediate feedback, which allowed students to recognizetheir weakness and gauge their own learning levels and needs.Huang and Gramoll50 described the development, implementation and functionality of highlyinteractive multimedia, online eBook designed to enhance students’ learning of
systems using these devices. These courses encompassphysics, solid-state concepts and conventional transistor circuits and systems.A variety of synchronous and asynchronous delivery methods, chosen to provide support andenable students to comprehend and appreciate this crucial component in the study of electricalengineering technology, were employed in the Active Networks I course.2,3,6,7 Asynchronousmaterial was made available through WebCT in the form of a detailed course syllabus, anextensive course schedule with links to individual assignment write-ups, lecture notes, examples,homework solutions, test solutions, and computer simulations.8 Synchronous delivery wasachieved through Centra in the form of office hours, problems sessions and
. scientific experiment. Automation Use computational tools Use computational tools (Star logo, Python code, (Probeware). …). Parallelization Dividing up data to be Solve linear and matrixial Parallel run different processed in parallel. systems. experiments. Simulation Algorithm animation. Graph variables and Simulate the movement of functions in different the solar system
, pp. 291 – 295.19 Kiss, S., (2001), “Web based VRML modeling.” Information Visualization, 2001. Proceedings, Fifth International Conference on, 25-27 July 2001 London, UK, pp. 612 – 617.20 Tamiosso, F.S., Raposo, A.B., Magalhaes, L.P., and Ricarte, I.L.M., (1997), “Building interactive animations using VRML and Java.” Computer Graphics and Image Processing, 1997. Proceedings, X Brazilian Symposium on, 14-17 Oct. 1997 Campos do Jordao, Brazil, pp. 42 – 48.21 Belfore, L.A., II and Chitithoti, S., (2001), “Multiuser extensions to the Interactive Land Use VRML Application (ILUVA).” Simulation Symposium, 2001. Proceedings, 34th Annual, 22-26 April 2001 Seattle, WA, USA, pp. 159 – 166.22
. Page 15.51.11Taraban, R., Anderson, E.E., DeFinis, A., Brown, A.G., Weigold, A., & Sharma, M.P. (2007).First steps in understanding engineering students’ growth of conceptual and proceduralknowledge in an interactive learning context. Journal of Engineering Education, 96(1), 57-68.Villareal, S., Eastwood, D., Seetharam, A., & Wynn, C. (1998). Design, development, andimpact of computer-animated simulations of diode rectifiers. Computers in Education Journal,8(4), 56-60. Wolfe, R., & Sears, A. (1996). Effective tool for learning the visual effects ofrendering algorithms. Computer Graphics (ACM), 30(3), 54-75.Wulf, W.A. (1998). The urgency of engineering education reform. The Bridge of the nationalAcademy of Engineering, 28(1), 4-8
environments. Page 22.1630.2IntroductionPervasive computing power and the high-speed Internet have altered engineeringeducation as they have altered other aspects of life. Virtual reality simulations and remotelaboratories over the Internet provide “hands-off” experiments that are able to strengthentheory and enhance student comprehension [1]. These hand-off laboratories, however, donot facilitate hands-on skills such as circuit construction and the use of measurementequipment, which are important parts of problem solving and skills that are desired forstudents’ careers. Several recent engineering education projects, including “Lab-in-a-box”[2] and “the Mobile
, the undergraduate student got familiarized withthe UMES combine and the basics of the yield monitor system. The data card thatrecorded the yield in various agricultural fields during spring harvest was then taken outfrom the cab and inserted into the PCMCIA slot of a laptop computer and downloadedinto the computer memory. The data sets corresponding to spring-wheat harvest from the“Bozman field” were isolated and mapped using SMS Advanced. SMS Advancedprovides user friendly tools for developing the yield maps to document the spatialvariation of the yield across the field. Upon extensive investigation of the raw yield datathe student identified the chief sources of error including (i) inappropriate yield records atthe edges of the field due to
. Sargent, and I. Nourbakhsh, “Community empowered air quality monitoring system,” in Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, ser. CHI ’17. New York, NY, USA: ACM,2017, pp. 1607–1619. [Online]. Available: http://doi.acm.org/10.1145/3025453.3025853[10] “Use of low-cost sensor technology to monitor air quality & engage citizens,” in SECURE Workshop, S. R. partnership for Air Pollution health Effects (SHAPE), Ed., COSLA Edinburgh, Scotland, Mar 2016.[11] R. Bonney, J. L. Shirk, T. B. Phillips, A. Wiggins, H. L. Ballard, A. J. Miller-Rushing, and J. K. Parrish, “Next Steps for Citizen Science,” Science, vol. 343, no. 6178, pp. 1436 LP – 1437, mar 2014. [Online]. Available: http
in computer graphics applications (computer-aided design, modeling, animation, and 3D fabrication) and concepts pertaining to Computer Science.Dr. Malini Natarajarathinam, Texas A&M University Dr. Malini Natarajarathinam joined the faculty of Industrial Distribution Program at Texas A&M Univer- sity in 2007. Natarajarathinam received her Ph.D. in Supply Chain Management from The University of Alabama. She received her Bachelor of Engineering (Major: Industrial and Systems Engineering) from Anna University [Tamilnadu, India], her MS in Industrial Engineering from Auburn University, her MA in Management Science and MS in Applied Statistics from The University of Alabama. She has experi- ence working with
document our methodologies in developing and integrating suchhands-on virtual learning activity in a fully asynchronous online learning environment. Thereby,our goal is to share our experiences, so that others can replicate, adapt, or expand on ourapproaches. Guided by various learning theories, merged into a framework of progressivecompetency development, a VLE was constructed that allows students to systematically developmethodological understanding and procedural application skills for the collection and analysis ofdata in a lab environment. Thereby, a simulation element was embedded into the larger didacticframework of the asynchronous online course, and provisions were implemented that allowed forongoing formative feedback. The, in this way
Eric Williamson is a rising senior student at Purdue University in West Lafayette, IN, majoring in aeronau- tical and astronautical engineering with a focus on astrodynamics and space applications. He is interested in researching improvements in engineering education and their applications to curriculum.Kenneth Park, Purdue University Kenneth Park is an undergraduate student studying Computer Graphics Technology at Purdue University. He enjoys exploring how data visualization can be used to aid in education by providing meaningful and inventive ways for students to interact with data.Prof. Michael David Sangid, Purdue University Michael D. Sangid received his B.S. (2002) and M.S. (2005) in Mechanical Engineering from
graphics applications (computer-aided design, modeling, animation, and 3D fabrication) and concepts pertaining to Computer Science.Dr. Mathew Kuttolamadom, Texas A&M University Dr. Mathew Kuttolamadom is an assistant professor in the Department of Engineering Technology & In- dustrial Distribution and the Department of Materials Science & Engineering at Texas A&M University. He received his Ph.D. in Materials Science & Engineering from Clemson University’s Int’l Center for Au- tomotive Research. His professional experience is in the automotive industry including at the Ford Motor Company. At TAMU, he teaches Mechanics, Manufacturing and Mechanical Design to his students. His research thrusts include
currently interested in engineering design education, engineering education policy, and the philosophy of engineering education.Dr. Michael S Thompson, Bucknell University Prof. Thompson is an assistant professor in the department of Electrical and Computer Engineering at Bucknell University, in Lewisburg, PA. While his teaching responsibilities typically include digital de- sign, computer-related electives, and senior design, his focus in the classroom is to ignite passion in his students for engineering and design through his own enthusiasm, open-ended student-selected projects, and connecting engineering to the world around them. His research interests are primarily experimental wireless networking and the application
the existing systems have one or more of the followingGeneration, Knowledge Based Systems, Expert Systems characteristics: • Self-contained corpus of knowledge not utilizing the I. INTRODUCTION Internet • Designs based upon using analogy or user input toO NE of the most intriguing topics in computer science research is creativity. To be more specific, can weprogram machines to be creative? In an attempt to answer this
studentsextremely happy as it gives them a sense of completing a successful design-specifically their veryown first truss bridge design! This software helps students develop an appreciation of theaesthetics, innovation and creativity involved in engineering design and also the importance ofcomputer simulations to reduce efforts spent on repetitive calculations.Conclusions and Future RecommendationsIn real-world settings engineers work in multidisciplinary teams on a variety of complexproblems. The fundamental principles of measurement and their application are crucial to thesolution of these problems. This three week module effectively introduces students to commonstructural measurements through conventional and innovative computer-integrated
potentially embarrassing manner.While the potential of computer-assisted instruction to enhance learning is unarguable, rigorousdemonstrations of its true effectiveness are in short supply, and the results of most studies thathave been carried out have not been conclusive. For example, a group at Purdue Universityevaluated the use of computer-simulation experiments in a senior-level chemical engineeringcourse.1 They found that the computer-simulated experiments led to better learning for somestudents, while others got more out of a traditional lab experiment. The authors caution againstusing instructional technology without evaluating its effectiveness.The effectiveness of any instructional software for a given student depends on a variety offactors
be accessed remotely and simultaneously by a large number of people, with the command inputs of one person affecting the command results of other people. • Physicality: people access the program through an interface that simulates a first-person physical environment on their computer screen; the environment is generally ruled by Earth’s natural laws and is characterized by scarcity of resources. • Persistence: the program continues to run whether anyone is using it or not; it remembers the location of people and things and the ownership of objects.Castronova made this definition in the video game context, but it is applicable and adaptable tothe educational context.Extensive research has been
Department Head at Texas A&M for eight years. Smith’s research is in simulation, animation, and technology utilization in teaching and learning.Mr. Timothy Allen Robinson, Pennsylvania State UniversityDr. Bugrahan Yalvac, Texas A&M University Bugrahan Yalvac is an Assistant Professor of science education in the Department of Teaching, Learning, and Culture at Texas A&M University, College Station. He received his Ph.D. in science education at the Pennsylvania State University in 2005. Prior to his current position, he worked as a learning scientist for the VaNTH Engineering Research Center at Northwestern University for three years. Yalvac’s research is in STEM education, 21st century skills, and design and
meters per second (m/s) or 5 miles per hour (MPH). Thecreated with a diameter of 4 inches. A shroud was created in computers were left to process for a considerable amount ofSolidWorks to surround the rotors. The two-bladed rotor, time, either to the finish or for an hour depending on whichthree-bladed rotor, and shroud were also turned into physical came first. During the simulation point goals were placed inobjects by the stereothiography machine as seen in figure 4a
Technologies, and Manufacturing Managementcourses. Distance learning for electrical engineering laboratories has been extensively reportedin the literature for several years 3-5. In the area of Thermodynamics, Sheyman 6 developedcomputer simulations for thermodynamics laboratory experiments. Another study on howstudents learn to design an online Thermodynamics course7 was reported, and aThermodynamics course 8 was taught using Adobe Connect and computer software. Other thanthese articles the authors are not aware of attempts to teach synchronous (live interactive)distance learning in undergraduate thermal engineering courses. This is likely because of themathematical nature, and numerous new concepts covered in courses such as Heat Transfer
7. Physical methods for surface characterization of ceramics 8. Sensor arrays, neural network and pattern recognition 9. Zeolites as sensor materials 10. Lithography process in miniaturized sensor fabricationA3. Computer Modeling Recognizing the growing importance of computational science & engineering (CSE) inmodern technological advancements, modeling and simulation forms a key module of thecurriculum. The research achievement on computer modeling and simulation at CISM isuniquely suited for adoption in undergraduate and graduate instruction because it involves thedesign and optimization of sensor materials and extensive
-voltage (I-V) characteristics of a BJT using theEbers-Moll model. The ac response of the pn junction is illustrated using animation, where theexcess carrier concentration is rapidly re-plotted at successive instants of time to illustrate boththe temporal and spatial variations. The iteration capabilities of Excel are used to accomplish the“sweeping” of the time variable. The frequency can be adjusted to see its effect on the acbehavior, although the time taken to plot a single time period is kept fixed so that the behaviorcan be observed clearly. We also carried out major revisions and enhancements of the other workbooks,particularly with regard to the GUI design. Previously, we frequently used scrollbars to adjustquantities such as doping
revise both the EE and the CpEcurriculums, especially in the early years, to have a significant active “hands-on” learning component.One possible way to achieve this goal would be to develop simulation laboratory exercises in which thestudents do their “experiments” on a computer, using for example, such tools as MatLab or MultiSim. Wehave found it very challenging to develop computer-based exercises that do not reduce the degrees offreedom provided to the students, and thus provide fewer opportunities for the deeper learning than wouldbe obtained when the students are engaged in building, testing, and debugging the circuits that they havedesigned. In part, this may be due to the fact that engineering students have a high level of
blocks of two hours). It relies on the use of advanced computational and simulationtools, such as SDRC / I-DEAS®. The pre-requisites for this course are: MECH-200 (computeraided engineering), MECH-310 (dynamics) and MECH-312 (design of mechanical components).Also, a pre-test is given in the beginning of the course in order to evaluate the level ofunderstanding that students have on these specific subjects.The course is divided in two major parts: (i) Analysis, (ii) Design with synthesis. The analysisportion consists of kinematic, dynamic and stress analyses. The dynamic analysis portion canalso include vibration and durability studies of critical components of a mechanical system.Graphical methods are used to conduct quick velocity analysis and
, field trips are crucial to fostering the linkbetween classroom learning and practical application. The hands-on experience boosted thelearning process, stimulating interest and leading to questions and answers. However, it could bechallenging to bring petroleum engineering students to the field operations due to logistical andsafety reasons.A computer simulation-generated interactive and immersive experience, virtual reality (VR), hasbecome a breakthrough in STEM [1]. Giving the impression of being physically present in thenon-physical world is made possible through it. The creation of a mechanical device called theSensorama, which offered a multisensory sensation of riding a motorcycle in a three-dimensionalworld, was one of the first
, American Society for Engineering Education 28the success experienced by multimode database teaching. The paper also discusses positive outcomes ofusing multimode teaching techniques and the rewarding impact this approach has on student learning.Supportive data for these conclusions include student GPAs and end of course evaluations.Recently, we have used additional technologies for an onsite database class which include the following:HP tablet, Internet, eCompanion, MS Office, a customized simulation package and custom applicationsoftware. These classes were computer-equipped classrooms with high speed internet connectivity. AllPCs in the