2017 ASEE Gulf-Southwest Section Annual Conference Introduction of the Construction Decision Making Inventory (CDMI) to Improve Educational Experience Dr. Tulio Sulbaran Full Professor, School of Construction, University of Southern Mississippi, Hattiesburg, Mississippi, USAAbstractEach learner has different characteristics, learners are not a homogenous mass, but varyconsiderably in terms of educational background, income, age and learning experience. Thesedifferences affect how they make decision and perform as practicing professionals, educators andstudents in the Architecture, Engineering and Construction (AEC) industry. These
AC 2008-87: TEACHING MULTIBODY DYNAMICS IN AN UNDERGRADUATECURRICULUM – AN INTUITIVE AND EXPLICIT FORMALISM BASED ONPARASITIC ELEMENTSGeoff Rideout, Memorial University of Newfoundland Geoff Rideout received his B.Eng. (Mechanical) from Memorial University in 1993, his M.A.Sc. (Eng.) from Queen's University in 1998, and his Ph.D. from the University of Michigan in 2004. He is currently an assistant professor of engineering at Memorial University, teaching mechanics and design courses. He is conducting research in the area of automated generation of computer simulation models for dynamic system design
2006-1831: SECURITY EDUCATIONTim Lin, California State Polytechnic University-PomonaSaeed Monemi, California State Polytechnic University-Pomona Page 11.1109.1© American Society for Engineering Education, 2006 Security EducationAbstract:Network security and computer security are usually hot topics whenever any intrusion incidentscause system crash and loss of work time in big corporations. In engineering colleges howeversecurity is usually a topic with least or incompatible attention.The author has taught many upper division classes in college and also graduate course(s) and hasbeen trying to imbue and enhance the courses with the security
Paper ID #6836Closing the Design Cycle: Integration of Analysis, Simulation, and Measure-ments Results to Guide Students on Evaluation of DesignMr. Avik Dayal, Virginia TechDr. Kathleen Meehan, Virginia Tech Kathleen Meehan is presently an Associate Professor in the Bradley Department of Electrical and Com- puter Engineering at Virginia Tech. Her previous academic positions were at at the University of Denver and West Virginia University. Prior to moving in academia, she was employed at Lytel, Inc., Polaroid Corporation, and Biocontrol Technology. She received her B.S.E.E. from Manhattan College and her M.S. and Ph.D
AC 2012-4854: MECHANIX: THE DEVELOPMENT OF A SKETCH RECOG-NITION TRUSS TUTORING SYSTEMMs. Olufunmilola Atilola, Texas A&M University Olufunmilola Atilola is currently a doctoral student in the department of mechanical engineering at Texas A&M University. She obtained her master’s degree from the University of South Carolina, Columbia and her bachelor’s degree from Georgia Institute of Technology, both in mechanical engineering. At Texas A&M, her research areas include representations in engineering design and innovations in engineering education.Ms. Cheryl OstermanFrancisco Vides, Texas A&M University Francisco Vides is a Graduate Researcher at the Sketch Recognition Lab at Texas A&M University
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 evaluation of learning environments informed by the How People Learn framework.Mrs. Elif OzturkMs. Ke Liu, Prairie View A&M University Ke Liu, is a graduate student and Graduate Research Assistant in the Department of Mechanical Engineer- ing at Prairie View A&M University. She received her BS in Donghua University, China. Her research interests include CAD, Virtual Reality Technology and CFD
AC 2011-1800: ADMINISTERING A DIGITAL LOGIC CONCEPT INVEN-TORY AT MULTIPLE INSTITUTIONSGeoffrey L. Herman, University of Illinois at Urbana-Champaign Geoffrey L. Herman is a PhD Candidate in Electrical and Computer Engineering and a Mavis Future Faculty Fellow at the University of Illinois at Urbana-Champaign. His research interests include cogni- tive science, identifying and assessing common student misconceptions and difficulties in electrical and computer engineering topics, blended learning (integrating online teaching tools into the classroom), in- telligent tutoring systems, and music signal processing. He is a winner of the 2011 Educational Research and Methods Division Apprentice Faculty Grant. He has been
Coffman-Wolph, Ohio Northern University Dr. Stephany Coffman-Wolph is an Assistant Professor at Ohio Northern University in the Department of Electrical, Computer Engineering, and Computer Science (ECCS). Previously, she worked at The Univer- sity of Texas at Austin and West Virginia University Institute of Technology (WVU Tech). She is actively involved in community outreach with a goal of increasing the number of women in STEM and creating effective methods for introducing young children to CS concepts and topics. Dr. Coffman-Wolph’s re- search interests include: Artificial Intelligence, Fuzzy Logic, Software Engineering, STEM Education, and Diversity and Inclusion within STEM. ©American
. 2020, pp. 221–35. https://doi.org/10.1037/edu0000366. 15Leveraging Learning Styles for Enhanced Student Outcomes at USMAPashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning Styles: Concepts and Evidence. Psychological Science in the Public Interest, 9(3), 105-119. https://doi.org/10.1111/j.1539- 6053.2009.01038.xTerrence Tsui & R. Nazim Khan (2023) Is mathematics a barrier for engineering?, International Journal of Mathematical Education in Science and Technology, 54:9, 1853-1873, DOI: 10.1080/0020739X.2023.2256319Zwanenberg, N. V., Wilkinson, L. J., & Anderson, A. (2000). Felder and Silverman's index of learning styles and Honey and
Paper ID #42451Boosting Achieved-Learning Outcomes with Maritime-Specific Projects in aMachine Learning CourseDr. Paul Marty Kump, Kansas State UniversityIan August ©American Society for Engineering Education, 2024 BOOSTING ACHIEVED LEARNING OUTCOMES WITH MARITIME-SPECIFIC PROJECTS IN A MACHINE LEARNING COURSE0: AbstractIn 2022, we developed a maritime-specific course in machine learning (ML) for undergraduatemaritime engineering and naval architecture students in an effort to boost low levels of achievedstudent outcomes as articulated by the Accreditation Board for Engineering and Technology
Paper ID #39889GIFTS: Making Research Experiences Meaningful through CriticalSelf-ReflectionPeter DeCrescenzo, University of Maryland Baltimore County Author is a doctoral student in the Student Affairs program at a public research university in the Mid- Atlantic. He serves as an Assistant Director to an NSF-funded project in order to increase the number of racial and ethnic minorities who matriculate into and successfully complete high-quality degree pro- grams in science, technology, engineering and mathematics (STEM) disciplines in order to diversify the STEM workforce. His research interests are centered around
Paper ID #36696Smartphone App Developed By Students to Help CommunityMembers in CrisisThomas Rossi Thomas Rossi is a lecturer in Computer Science and Software Engineering at Penn State Behrend. His research focuses on improving the post-secondary experience for students through the use of current computing tools and technologies. Thomas graduated with his MS in Computer Science from the University of New Hampshire in 2016. © American Society for Engineering Education, 2022 Powered by www.slayte.com Smartphone App Developed by Students to Help Community Members
Paper ID #36904Motivating Students to Learn Basic Electronic Theories byAdopting Them in Different CoursesJack li JACK LI is an assistant professor of Electrical Engineering Technology in the School of Polytechnic at Purdue University Fort Wayne. He earned his BS, MS, and PhD degrees in electronics engineering. Dr. Li may be reached at lij@pfw.edu. © American Society for Engineering Education, 2022 Powered by www.slayte.com Motivating Students to Learn Basic Electronic Theories by Adopting Them in Different CourseJack Li, Purdue University Fort
strongly advocate use of in-person online teaching over face-to-face conventional teaching mode. A reason for success couldbe that the engineering students are more technology savvy so it is easier to move classes online.Alternatively, it might be because students saved commute time and used it for course work. Orbecause they were better off staying at home with less worries. Or due to availability of recordedlectures for the students to review in their own time.11. References[1]Teaching courses online from the Illinois website https://atlas.illinois.edu/teaching-online[2] Remote teaching technologies from Illinois website https://remote.illinois.edu/teaching-tools-and-technologies
ASEE-NMWSC2013-0049 Incorporating On-going Verification & Validation Research to a Reliable Real-Time Embedded Systems Course Nannan He Department of Electrical, Computer Engineering and Technology Minnesota State University, Mankato, MN 56001AbstractThis paper presents the enhancements to a senior-level and graduate-level course, Reliable Real-time Embedded Systems, in terms of introducing advanced verification and validation (V&V)approaches. Traditionally, this course covers the topics of fundamental principles in real-timeoperation systems like
responsibilities include providing support for student services, working with assessments of student services in online programs and also oversees the NSF STEM Master Scholar Program.Lori Wedig, University of Wisconsin, Platteville Lori Wedig works in the Distance Learning Center (DLC) as the Associate Outreach Specialist for the NSF STEM Master Scholars program and the Masters of Science in Engineering Graduate Scholars. She has worked in higher education for 25 years with the last 2 years working in the DLC advising the NSF STEM Master Scholar program. c American Society for Engineering Education, 2017 STEM Grown Masters Lisa Naderman
AC 2008-1190: AN INTERNATIONAL COLLABORATION FOR THE STUDY OFDEFECTS IN CASTINGSSergio Felicelli, Mississippi State UniversityJohn Berry, Mississippi State UniversityRafael Cuesta, CIDAUT, SpainRogelio Luck, Mississippi State UniversityRatessiea Lett, Mississippi State University Page 13.189.1© American Society for Engineering Education, 2008 An International Collaboration for the Study of Defects in CastingsAbstractThis work describes an international collaboration project that has been established betweenMississippi State University (MSU) and the CIDAUT Foundation in Spain. The project will befunded by the National Science Foundation (NSF) under the International
Society for Engineering Education, 2006 The Hubbert Curve: Enabling Students to Meaningfully Model Energy Resource DepletionAbstractCourses in Energy Systems (alternatively named “Applied Energy Conversion,” “EnergyConversion Systems,” or some variant) often discuss the idea of energy resource depletion interms of the exponential growth model. A typical problem is: given the current growth rate of oilproduction, in what year will known reserves be depleted? The exponential growth model,although offering reasonable results initially, becomes less accurate in the later stages of resourceexploitation as issues of scarcity, cost, and technological hurdles become important. It grosslyunder predicts how long a
enhance students’ mastery of the subject matter. While it isessential to keep the laboratory equipment up-to-date with the latest technologies 2 , it is alsoimportant to design a cost-effective 3 and flexible solution 4 and a safe operating environment inthe laboratory course.Although the electric machine laboratory has been traditionally offered in Electrical Engineeringcurriculum in many of the engineering institutions, the laboratory for electric machine drives hasnot been common. While the electric machines have not changed much in their structure andoperation, power electronic converters and machine drive technologies have been substantiallyimproved. Recently, there have been efforts to implement electric drive laboratories 5 , but
Paper ID #14630Transforming the CREDLE (Capstone Research Experience for Distance Learn-ing Executives)Dr. Malini Natarajarathinam, Texas A&M University Dr. Malini Natarajarathinam is an Associate professor with Department of Engineering Technology and Industrial Distribution. She teaches classes on strategic relationships for industrial distribution, distribu- tion information systems and new directions in Industrial Distribution. She is also the founding faculty and advisor for the Society of Women in Industrial Distribution (SWID). She works on many service learning projects with her students where they work
Student Development, 57(6), 742– 747.[2] Kallison, J. M., & Stader, D. L. (2012). Effectiveness of summer bridge programs in enhancing college readiness. Community College Journal of Research and Practice, 36(5), 340–357.[3] Tate, E. D., & Linn, M. C. (2005). How does identity shape the experiences of women of color engineering students? Journal of Science Education and Technology, 14(5/6), 483–493.[4] Chen, X., & Soldner, M. (2013). STEM attrition: College students’ paths into and out of STEM fields statistical analysis report. US Department of Education.[5] Ashley, M., Cooper, K. M., Cala, J. M., & Brownell, S. E. (2017). Building better bridges into STEM: A synthesis of 25 years of literature on STEM summer
2006-1708: EDUCATING THE BUSINESS PROCESS MANAGERS OF THEFUTURE: THE SIX SIGMA TECHNIQUESPatricio Torres, Purdue University Mr. PATRICIO TORRES, M.B.A. earned a double major: Business Administration and Law in his native country, Ecuador, S.A. In 2003, he obtained an M.B.A. degree with a major in Operations in Purdue University, Indiana. His professional experience includes Finance, Marketing and Operations. He was a Mathematics teacher in the Catholic University of Ecuador (1991-1995). He published an article in the journal "The Progressive," (Ecuador, 1998) and in the "American Society of Engineering Education," where he also presented a conference (U.S.A. 2005). A
recent decades in which terms like “carpal tunnel syndrome”and “repetitive motion stress” have become part of the cultural lexicon. But how does theengineer assure that the solution he has reached will not only be effective, but safe for theend user? Analysis of the design parameters can establish if the solution falls withinknown ergonomic parametric standards, but often the analysis falls short of optimal anddesign changes are required to accommodate unforeseen issues encountered in theimplementation of the design. A solution to this problem is to conduct 3D simulationsthat allow engineers to clearly visualize the implementation of the design in its intendedenvironment, complete with simulated users. Technology has finally advanced to thepoint
. Alejandra J. Magana, Purdue University Alejandra J. Magana, Ph.D., is the W.C. Furnas Professor in Enterprise Excellence in the Department of Computer and Information Technology and Professor of Engineering Education at Purdue University. ©American Society for Engineering Education, 2024 Evaluating the Impact of Additional Examples and Explanation on Student Outcomes in a Free Online Python CourseAbstractHelping students to learn a new programming language in a voluntary online course can be timeconsuming and difficult. Students in such a noncredit course face many challenges in learning;the content must keep their attention, and these students also need to quickly achievecompetency in
A Modified System Development Life Cycle for the Analysis of Complex Systems Using the Formal Specification of Software for a Kitchen Cooking Application Shanelle M. Harris, LeeRoy Bronner Ph.D., P.E. Morgan State University SDLC process is the waterfall Fig. 1. The waterfall is a Abstract— With the large complex problems facing 21st predictive model flow of sequential phases where the outputscentury researchers, such as Engineering Education, Retention, of stages are the inputs to the preceding stage [1
AUTOMATED HIGH SPEED ASSEMBLY MACHINE DESIGNMurat Demirci Zheng Jeremy Li, PhDGraduate Student Associate ProfessorSchool of Engineering School of EngineeringUniversity of Bridgeport University of BridgeportAbstractRecent years, automation is still important for industrial world and in the global economy. Because of theglobal competition, industries started to look for new technologies and designs in automation field. Thereis no more enough time, energy and material to catch people needs for industries in nowadays. Thus,automated systems are becoming more interesting and
Combining Take-Home and In-Person Exams to Improve Student Performance and Improve Instructor Grading Efficiency Pilin Junsangsri Marisha Rawlins Electrical and Computer Engineering Electrical and Computer Engineering School of Engineering School of Engineering Wentworth Institute of Technology Wentworth Institute of Technology Boston, USA Boston, USA1 AbstractThis paper presents a methodology to evaluate students’ performance by combining take-homeexams with in-person exams
2025 ASEE Northeast Section Conference, March 22, 2025, University of Bridgeport, Bridgpeort, CT, USA. Automated Queueing System using Facial Recognition Applying AI and Computer Vision to Queue Automation Zebin Pepin Douglas E. Dow Department of Electrical and Computer Engineering Department of Electrical and Computer Engineering Wentworth Institute of Technology Wentworth Institute of Technology Boston, Massachusetts Boston, Massachusetts Abstract— Theme parks
Paper ID #37533Leveraging the power of Python, Octave and Matlab forMachine LearningMohammad Rafiq Muqri (Professor CEIS)Seta Boghikian-Whitby (Professor and Department Chairperson)Muiz MuqriZacki MuqriSarah Muqri © American Society for Engineering Education, 2022 Powered by www.slayte.comLeveraging the power of Python, Octave and Matlab for Machine LearningAbstractThe objective of this paper is to bring awareness, instigate interest, and promote the need ofusing Artificial Intelligence (AI) and machine learning algorithms for information andengineering technology students. This paper will also attempt to review some of the
classes at localschools.AcknowledgmentsThanks to Foaad Khosmood for the suggestion of the googly eyes.Bibliography 1. A. Denker, A. Dilek, B. Sarıoğlu, J. Savaş, Y. Gökdel, "RoboSantral: An Autonomous Mobile Guide Robot," IEEE International Conference on Industrial Technology (ICIT), Seville, pp. 459-463, 2015 2. E. Saad, M. Neerincx, K. Hindriks, “Welcoming Robot Behaviors for Drawing Attention”, International Conference on Human-Robot Interaction, 2019 3. L. Ni, C. Schaefer, T. Buntin, “A Robotic Tour Guide Using a NAO T14 Humanoid with a Wheeled Mobile Platform”, 2nd International Conference on Robotics and Automation Engineering (ICRAE), 2017 4. S. Wang, H. Christensen, “TritonBot: First Lessons