more relevant to their futureneeds as working engineers through the use of our prototyping facility.Bibliography[1] Christiansen, Donald "New Curricula," IEEE Spectrum, Vol. 29, No. 7, 1992[2] Conner, Doug "Systems Create Prototype Circuits Boards Fast," Electronic Design News, pp. 104-108, July 1992[3] Rosenblatt and Watson, "Concurrent Engineering," IEEE Spectrum, Vol. 28, No. 7, July 1991[4] Strategic Manufacturing Initiative, National Science Foundation, 1992[5] Brown, George E., Jr. (D-California) Chairman, "Report of the Task Force on the Health of Research," Congressional Records 102nd Session of Congress, July 1992[6] Gomory, Ralph "Government's Role in Science and Technology: Goals and
saw them as being totally unrelated.As the authors believe that conceptual knowledge is best developed with “hands-on” experience,major changes were again made to both the laboratories and lecturing styles in 2007. Thesechanges were made to introduce a concept of “global learning” where the laboratory experimentsundertaken by individual students are directly related to the material being covered in thelectures5. The “global learning” concept is based the best teaching method of induction, asdefined by Felder and Silverman6, 7. The pass rate for the course improved to 80% in 2007 and74% in 2009, showing an improvement for two successive cohorts.Students entering the university in 2009 were the product of both a major curriculum change anda new
design and led multi-institution teams in the development and testing of curriculum materials and assessments for engineering design learning. He is also the owner of Verity Design Learning LLC, a publisher of instructional materials for design reviews and teamwork development. He is a Fellow of the American Society for Engineering Education. Dr. Davis received his PhD in Agricultural Engineering at Cornell University.Ms. Sarah Winfree, The Ohio State University Sarah Winfree is an undergraduate research assistant in the Department of Engineering Education at The Ohio State University. She joined the University in August 2013 working towards a Bachelor of Science degree in Food Engineering. Her career includes
University Marisa Exter is an Assistant Professor of Learning Design and Technology in the College of Education at Purdue University. Dr. Exter’s research aims to provide recommendations to improve or enhance university-level design and technology programs (such as Instructional Design, Computer Science, and Engineering). Some of her previous research has focused on software designers’ formal and non-formal educational experiences and use of precedent materials, and experienced instructional designers’ beliefs about design character. These studies have highlighted the importance of cross-disciplinary skills and student engagement in large-scale, real-world projects. Dr. Exter currently leads an effort to evaluate a
approach, with hands-on related course material. Students like to havevarious tools and options available for them to learn and most importantly they should have theskills and competency that meets the requirement of the employers.Backward design approachA backward design approach (BDA) proposed and developed by Wiggins and McTighe [5] wasused to create this new course. By using this, instructors could delineate from their research andteaching goals and develop corresponding learning objectives for the course. The BDA approachis a persuasive approach for student-centered result-oriented learning. In a backward designapproach, the first step is to identify the student learning outcomes for the change. Then itmoves to the ways of assessing the
accessible tasks [15]. To address these issues, iterative teaching,real-world examples, and structured onboarding were recommended [15], [17].3.4 Results for RQ3: How is PBL being integrated into the AI curriculum?PBL effectively enhanced engagement, skill development, and ethical awareness. Lohakan andSeetao's AI kit activities provided hands-on experience with computer vision and Pythonprogramming, increasing engagement and understanding [17]. Lin et al. integrated AI into amarine science project, using robotics to connect AI principles to real-world applications [19].Gamification and role-playing games simplified ML concepts and encouraged collaboration [15].Lu and Fan used PBL in a weather prediction project, guiding students through the
Engineering Education”2. Working in small groups, RAs actively participate in a hands-on demonstration of theequipment conducted by USF undergraduate researchers.3. In the same small groups, university researchers observe and evaluate each RA as they usethe sampling equipment, in turn. The focus of this observation and evaluation is on safety,proper equipment handling, and sampling techniques. The small group interaction allows foreach RA to observe colleagues as they individually use the equipment for the first time helpingto reinforce their understanding and retention of the information.4. Following these steps, each RA is required to take a written certification examination. Theexamination covers material on reasons for sampling the selected
experiential setting.Experiential learning encourages student reflection and experimentation and offers a safe placefor students to apply concepts or techniques they have learned in the classroom, and even allowsthem a safe haven to fail [11]. These types of engagement opportunities are based in authenticscenarios. Experiential learning experiences produce transferable skills, such as communication,problem-solving, and civic behaviors [12]. Competitions, in fields such as engineering and ITpromote interest in certain disciplinary domains and encourage teamwork [13]. Employers valuethe “blend of technical and general skills and hands-on experience” [14, p. 929] that result fromexperiential learning; for this reason, employers have called for formal
these examples, bearing in mind the initial differences in their programmingproficiency. Their use was still found stimulating.Rationale for the study – The context of mathematics in engineering educationDesigning engineering education with mathematics and physics in the first two years of theprogram is not a law of nature. 4 It can hardly be argued that abstract mathematics is taught in theinitial stages of programs for pedagogical reasons. Rather, such a design reflects a Tayloristicview of industrial production transferred to education where context-free bits and pieces aredispensed by specialists to be assembled to a coherent whole in the end. 5 Most engineeringteachers claim that they need to build on a ”solid” mathematics and science base
(BEC) (pp. 1-5). IEEE.[13] Salameen, L., Estatieh, A., Darbisi, S., Tutunji, T. A., & Rawashdeh, N. A. (2020, December). Interfacing Computing Platforms for Dynamic Control and Identification of an Industrial KUKA Robot Arm. In 2020 21st International Conference on Research and Education in Mechatronics (REM) (pp. 1-5). IEEE.[14] Hadidi, R., Cao, J., Woodward, M., Ryoo, M. S., & Kim, H. (2018). Distributed perception by collaborative robots. IEEE Robotics and Automation Letters, 3(4), 3709-3716.[15] Galin, R., Meshcheryakov, R., Kamesheva, S., & Samoshina, A. (2020, May). Cobots and the benefits of their implementation in intelligent manufacturing. In IOP Conference Series: Materials Science and
& Exposition Copyright c 2005, American Society for Engineering Educationand tabulated as a function of temperature [1,7,8]. If the temperature at the inlet and outlet areknown, Eqs. (3) and (4) indicate that the work of compression can be calculated.However, an important thermodynamic process is the compression of gas from a known inlet tem-perature ̽ and pressure Ƚ to a specified outlet pressure Ⱦ , i.e. the outlet temperature is notknown. (See Fig. 1 for a schematic of the compressor and the process on a Ì -× diagram.) Thus,another piece of information is required to fix the outlet temperature. For an ideal (i.e. reversible)adiabatic compressor the process is isentropic, which implies that × ½ ×¾ . Thus, two
expectations and detailed procedures in the laboratory assignments, whichlargely reflected their prior experience with traditional laboratory handouts in which all thesteps are spelled out. The students were also concerned by the amount of time required toprepare for laboratories for which they had to do research, read technical material written forprofessional engineers, and find on occasion that they had been on the wrong track.Preparation time for inquiry-based laboratories was also a student concern in other studies[4].Our students generally had positive impressions of the collaborative aspects of the initiallaboratory discussions (Figure 2), which mirrors previously reported results[1].As a group, our students were neutral in their assessment of
, which he has sought to implement through service-learning activities.Beverly Perna, Tsongas Industrial History Center Dr. Beverly Perna is the Museum Education Specialist at the Tsongas Industrial History Center where she oversees the development of science programming related to the Industrial Revolution. She acquired her interest in engineering in her ten years on the education staff of the Boston Museum of Science and has turned that interest into a variety of teachers' workshops, including one that examines the Pemberton Mill collapse in Lawrence, MA. Page 11.879.1© American Society for
-life” project. The open-ended nature of real-life projects requires students to determinewhich skills to apply as well as how to apply them. This can be a great learning experience forstudents, but there are many challenges presented to students during the senior design project.The main challenges identified include; project and time management, lack of technical depth,and lack of structure.Engineering management is one of the biggest challenges students face during their senior designprojects. American Society of Engineering management (ASEM) defines engineeringmanagement as “the art and science of planning, organizing, allocating resources, and directingand controlling activities which have a technological component” 1. Students need to
. The goal of this paper toshare how the usage of a simple tool to perform advanced operations can improve or facilitatethe learning process of students in Mechanical Engineering. In the summer of 2014 and 2015, 84 students were enrolled in these courses. Studentsworked in teams of five to six and were assigned team projects. Courses taught includedManufacturing I, Manufacturing II and Heat Transfer. In Manufacturing I, the topics coveredincluded a description of tool machines as the main material removal process in industry, tooland machine selection and precision measurement with calipers and micrometers. InManufacturing II, the focus was on production planning, standard operating procedures, andgeometric and dimensional tolerancing. A
content and concepts [36]. The teacher’s role as a catalyst is to guide studentsto examine problems from all angles through questioning.STEM pedagogy, on the other hand, involves a large community of practice made up of smallerseparate communities of practice of the STEM enterprise. Each disciplinary domain orcommunity of practice like Science, Technology, Engineering, and Mathematics is different andhas its own unique and distinctive knowledge practices that cannot be changed. Learning in aspecific community of practice involves making sense in a social context of the particularcommunity of practice [35]. Student members of the smaller communities have multiplememberships. Margot and Kettler [36] explains that teachers and the STEM curriculum
test-bed setting, and supplemental instructor aidsare currently under development. To view and request samples of the modules, please visit thewebsite http://engr.nmsu.edu/~csm/nsf-project. This material is based upon work supported bythe National Science Foundation under Grant No. 0230643. Proceedings of the 2005 ASEE Gulf-Southwest Annual Conference Texas A&M University – Corpus Christi Copyright © 2005, American Society for Engineering Education Module Development There have been numerous recent educational research publications that suggest the needto introduce the concept of “statistical thinking” into secondary education programs, i.e
Paper ID #29435The Manufacturing Education Dilemma: Operating Efficiency vs. Produc-tivityProf. Robert Simoneau, Robert W. Simoneau has 47 years of academic and industrial experience in manufacturing and manage- ment related disciplines and holding an MS in Plastics Engineering as well as an ABD in Educational Leadership. He is an Associate Professor at Keene State College in the Technology Studies and Busi- ness Management Departments. On a leave of absence he served as a Program Officer at the National Science Foundation where he made recommendations for funding while managing the following solic- itations
Senior Lecturer at the Department of Education in Technology & Science, Technion – Israel Institute of Technology. His research interests are in science, mathematics, and engineering education with emphasis on technological learning environments, physical models, experiential learning, robot design and operation, spatial imagery, mechanical aptitude, mathematical learning in the context of engineering and architecture. Page 12.336.1© American Society for Engineering Education, 2007 Building Self-Efficacy in Robotics EducationAbstractWhile the cognitive and attitudinal aspects of
universities provide guidance on these tasks to new faculty members, but most do not. All academic programs of the 16-campus University of North Carolina system that usegraduate teaching assistants are required to provide the TAs with preliminary training. For manyyears, the North Carolina State University (NCSU) College of Engineering met this requirementby sending its new TAs to a day-long campus-wide workshop. Many of the graduate studentscomplained that the workshop was too general to be of much value—their perception was thatthe things they needed to know to be TAs in engineering were different from what TAs inhumanities and social science and business and management courses needed. Ronkowski1 presents a number of strong
, mechanical engineering and physics (optics) primarily forinnovation and design, materials science and chemistry for fabrication processes, and all thefields for applications in consumer products, instrumentation, sensors, biomedicine, etc. Thisinterdisciplinary nature of MEMS creates many challenges as well as opportunities in theacademia for introducing the subject at both graduate and undergraduate levels.We have recently introduced an undergraduate senior level MEMS course as a technical electiveprimarily for electrical (EE) and mechanical engineering (ME) students. Topics covered includemicromechanical structures, materials for MEMS and their thermal, electrical and mechanicalproperties, principles of microfabrication, micromechanics
Paso (UTEP). He received his M.S. degree in Industrial Engineering (con- centration on manufacturing systems and decision sciences) from the University of Wisconsin at Madison in 1993 and 1995 respectively and Ph.D. in Industrial Engineering from the University of Iowa in 1999. Dr. Tseng is also a Certified Manufacturing Engineer from Society of Manufacturing Engineers since 2002. Dr. Tseng is specialized data mining, knowledge management, decision sciences and statistical analysis, specifically in the area of IBDSS. Over the years, he has served as principle investigators spon- sored by NSF, NIST, NASA, DoEd, , KSEF and industry like LMC, GM and Tyco Inc. Dr. Tseng delivered research results to many refereed
transformative work in the area of maker education.Figure 1. The SMU Maker Education Project’s mobile makerspace, the MakerTruck.During the second year of the project, we launched a mobile makerspace, the MakerTruck. TheMakerTruck is a former delivery truck retrofit by SMU engineering students to include a suite ofhigh-tech and low-tech tools and materials helpful for creating personalized artifacts. Some ofthe items on the MakerTruck include: a laser cutter, a vinyl cutter, a 3D printer, hand tools, andcrafting materials. Once operational, we began deploying the MakerTruck in the community todeliver unique maker-based experiences to educators and students at K-12 schools. (See Figure 1for images of the outside (left side) and inside (right side) of the
A Reflexive Course for Masters Students to Understand and Plan Their Own Continuing Professional Development Llewellyn Mann, David Radcliffe Catalyst Centre for Society and Technology The University of Queensland AustraliaAbstractContinuing Professional Development (CPD) is seen as a vital part of a professionalengineer’s career, by professional engineering institutions as well as individual engineers.Factors such as ever-changing workforce requirements and rapid technological change haveresulted in engineers no longer being able to rely just on the skills they learnt at university orcan pick up on
, manufacturing and design area, are from the University of Texas at Austin. Additionally, Dr. Austin Talley holds an undergraduate degree from Texas A&M University in Mechanical Engineering. His research is in engineering design theory and engineering education. He has published over 30 papers in engineering education journals and conference proceedings. He has worked to implement multiple National Science Foundation (NSF) grants focused on engineering education. He has been an instructor in more than ten week long summer K-12 teach Professional Development Institutes (PDI). He has received multiple teaching awards. He has developed design based curriculum for multiple K-12 teach PDIs and student summer camps
Session XXXX An Improved Genetic Algorithm Using Intelligent Symbolic Regression Mohammed Shahbazuddin Mechanical Engineering Department, University of Louisiana at Lafayette Dr. Terrence. L Chambers Mechanical Engineering Department, University of Louisiana at Lafayette AbstractIn this paper, an optimization technique based on intelligent symbolic regression is presented.Intelligent symbolic regression methodology seeks to replace
material covered.This can be accomplished by reducing the amount of writing by the professor and copying by the students.Specifically, it is recognized that copying complex diagrams, computer programs, and lengthy equations andtext diverts both the professor and the student from the task of teaching and learning. Therefore, technologyshould be employed to eliminate this copying, while retaining the type of note taking that is vital to learning andthe retention of knowledge. Secondly, what is expected in the classroom should be changed by modi@ing the classroomenvironment. If every classroom has only a blackboard, it is not surprising that most instructors will use theblackboard. On the other hand, if every classroom is equipped with an
; confederation and linking / mashable software fluency / manipulate multidisciplinary model (M = 3.94, SD = 0.73).Of the top five, two are not explicitly BIM specific skills but rather prerequisite skills required tocomplete a BIM model. Understanding hidden materials and validation of model accuracy willrequire the construction manager to understand how the project is actually put together, the“hands-on” component of construction. This is what the researcher considers “traditional”construction management education. In examining the highest scoring item, BIM quantity take-off and verification, this skill requires both BIM knowledge to use the computer model tocomplete a take-off and traditional math skills to verify the take-off quantities
and a timely assessment of course improvements. This methodology iseasily adaptable to any lab course and can indicate where limited time and resources should bedirected for maximum impact.IntroductionLaboratory classes are a key component of mechanical engineering programs. Although theyhave proven educational benefits, and are generally required for accreditation, they represent asubstantial commitment of space, resources, and personnel. Because of the effort and financialinvestment involved in developing new lab experiments, it is easy for labs to stagnate andbecome out of date. Virtual labs and simulations have been used to combat this in many casesbut hands on and open ended experiments still have immense value for student learning.In
1 NRN. Appropriate applications of science (physics/chemistry) 5 4 3 2 1 NRO. Appropriate applications of engineering/technology 5 4 3 2 1 NRP. Appropriate applications of materials/material science 5 4 3 2 1 NRQ. Appropriate applications of methods/processes 5 4 3 2 1 NRR. Proper process of conducting an experiment/research 5 4 3 2 1 NRS. Proper process of analyzing and