competencies in Materials Science and Engineering,creating a demand for students who can engage in the computer-aided design of materials4.Meeting this new demand for computational competencies is not straightforward, as simplyadding new subject matter independent of the traditional content is not viable in already packedcurricula. To add these new competencies, we must either teach a smaller technical core to createspace for computational competencies or find ways to synergize the instruction of computationalcompetencies with the traditional content so that learning computational competenciesaccelerates learning of traditional content and vice versa.Fortunately, early research into the use of modeling and simulation tools suggests that
a range of options for each type ofsoftware. Our goal was to introduce the major capabilities of each type of software. Wealso selected these products based on ease of learning and ease of use. Our committeesurveyed the faculty in Engineering and Applied Science at UVa about the skills they feltour students should have; we also asked them which software they actually used in theirclasses, research, and consulting. Finally, we considered the demands and needs ofindustry for computer fluent engineers. We cannot provide instruction in each of theparticular software products used by industry, but we can and do educate our students inthe relevant capabilities and limitations of each type of program.2. Incoming population: a profile of our
freshmen course in the introduction to design and the senior capstone design courses.Also, the positioning of this course in the sophomore year allows for the use of more advancedconcepts than can realistically be expected for freshman while providing an introduction to theconcepts and analysis methods the students will learn as juniors. The use of CAD tools in thedesign reinforces the computer skills the students need later, particularly in capstone design, andprovides a motivation for our students who are excited by aerospace vehicles.The content of the course provides for a parallel development of CAD skills with theintroduction of aerospace vehicle concepts and analysis tools. The course includes an experiencein both spacecraft design
materials used in the module Module evaluation Assessment tools to measure learning and module effectivenessCourse module 1 – Introductory levelThis course module, referred to as CM1, targets CS2, the second course in the problemsolving sequence typically required for first year students in several computing majorssuch as Computer Science, Software Engineering, Computer Engineering, andComputational Mathematics. Students in the class are already prepared with basic idea ofcomputational thinking, programming languages and techniques, elementary datastructures, and some basic problem solving methods. They continue to learn those topicswith more complex features and typically from
; societal context for ethics cases studiesi discussion of changing pace in their chosen professions, graduate schoolj ethics case studies include recent ECE topicsk study and apply techniques in learning to use the graphical computer organization and processing; programming environment associated electronic library and internet with the RoboLab resourcesWe believe our Introduction to Electrical and Computer Engineering course acquaints students insome degree with all of the ABET Criterion 3 outcomes we expect them to have upon completionof their degrees.V. Preliminary AssessmentIt is too early to give any longitudinal
. Laboratoryassignments reinforced lecture material, and are further explained below. Grading wasdistributed as follows: Exams - 45 percent, laboratory assignments - 40 percent, attendance andassignments, 15 percent. Exam questions focused primarily on lecture information, but couldinclude questions about laboratory knowledge. Lab assignments Six laboratory assignments were used to reinforce lecture information and to give hands-on design experience. It is believed that hands-on experience is required when learning aboutcomputer-based technologies. Having students experience old (manual) ways of accomplishingmanufacturing tasks, new computer-based approaches, testing and simulating computer results,and producing final
orthographic views, house plans and plant layouts.Solid modeling is taught in CADD II (ET 3360) and Architectural concepts are taught inArchitectural CADD (CM 3320). In Advanced CAD (ET 4330), students learn advanced topicsincluding programming in AutoLISP and using different solid modeling software. Both CADDII and Advanced CAD courses have 500-level graduate components. Also, we have a 600-levelgraduate course, Advanced Technical Drafting (ETIS 6230) in which graduate students work onindependent projects. All of our undergraduate students except the Computer EngineeringTechnology majors are required to take CADD I. Elector-Mechanical and Manufacturing majorsare required to take CADD II, Architectural CADD is required for Construction majors
who attend the regular scheduled lectures andcomplete all course assignments, multiple weekly SI leader led teaching sessions, evaluation ofsessions by SI supervisors for feedback and improvement, weekly planning and coordination ofsession content between SI-leader and course instructor. Prior to the class start date, SI leadersreceive training on session preparation and teaching pedagogy, and work with SI supervisors andfaculty to continually monitor and modify session content. SI was developed around acombination of learning theories [5], cognitive development principles [6], societalinterdependence principles [7], and interpretive principles [8]. Specifically, the fouraforementioned gaps applicable to technical computing can be filled by
. Hayne made the class very interesting. The lecture slides and homework assignements were very helpful tools to help us learn the material.” “Gaining an understanding of computer architecture design gives a clear picture in the inner workings of processors and microcontrollers. I've worked on computers since I was 14 but the innerworkings of components on boards were always a mystery to me. This course brings together Discrete mathematics, digital systems, and design into a single class with a focus on design. I feel much more comfortable in my understanding of computer hardware design and searching for jobs in the related field now.” “I really enjoyed the focus on understanding concepts so that our design practices can be
capability and itsadaptability with other techniques have been evaluated empirically as effective and scalable14.The rules reduce substantially the impractical manual development process of patterns andprofiles, computing statistical patterns from the collected data.Misuse Detection:In Misuse Detection each data record is classified and labeled as normal or anomalous activity.This process is the basis for a learning algorithm able to detect known attacks and new ones ifthey are cataloged appropriately under a statistical process. The basic step known as discoveryoutliers, matches abnormal behavior against attack patterns knowledge base that capturebehavioral patterns of intrusion and typical activity. To do this, it is needed to compute eachmeasure
Tagliatela College of Engineering at the University of New Haven since August 2011. He is the PI of the grant entitled Developing Entrepreneurial Thinking in Engineering Students by Utilizing Integrated Online Modules and Experiential Learning Opportunities. Through this grant from the Kern Family Foundation, entrepreneurial thinking is being integrated into courses spanning all four years in seven ABET accredited engineering and computer science BS programs.Dr. Nadiye O. Erdil, University of New Haven Nadiye Ozlem Erdil is an assistant professor of industrial and systems engineering at the University of New Haven. She has over eleven years of experience in higher education and has held several academic positions
Session 2137 Providing a Real World Experience in the Teaching of Computer Technology By Joel Weinstein, Andrew Gilchrist IV, Kyle Hebsch, Jefferey Stevens Northeastern UniversityAbstractOne of the greatest challenges facing engineering technology educators is preparation forwhat graduates will face in the real world. Unlike the classroom, problems are notpredefined, solutions do not come from answer books and personnel are not nearly asexpert as the instructors that have prepared the students. This paper describes a courseand its methodology that helps to better prepare students for
- sponsored SUCCEED Coalition. She remains an active researcher with MIDFIELD, studying gender Page 23.1132.1 issues, transfers, and matriculation models in engineering. c American Society for Engineering Education, 2013 Tapestry Workshops: Helping High School Teachers Grow and Diversify ComputingAbstractThe Tapestry Workshop series helps high school Computer Science teachers inspire diversestudents to learn computer science. The workshops are offered to high school educators whowant to initiate, expand, or improve Computer Science instruction in their schools
Student-Owned Computing in the College of Engineering and a doctoral candidate in the Department of Industrial and Systems Engineering at NC State University. She regularly teaches the Introduction to Engineering and Problem Solving course in the First Year Engineering Program. Her research interests include faculty development and teaching and learning in the engineering disciplines. She received her MIE and BSIE degrees from NC State University. Prior to her return to NC State, she worked as a Cost Engineer in the Personal Computing Division of IBM. Page 13.772.1© American Society for Engineering
integrating computation into the undergraduate core curriculum. Falk also serves as the lead investigator for STEM Achievement in Baltimore Elementary Schools (SABES) an NSF funded Community Enterprise for STEM Learning partnership between JHU and Baltimore City Schools.Dr. Michael J. Reese Jr., Johns Hopkins University Page 26.744.1 c American Society for Engineering Education, 2015Exploring Undergraduate Students’ Computational Literacy in the Context of Problem SolvingAbstractThis paper evaluates undergraduate students’ performance during a problem-basedcomputational
life. [Criterion 3(f) and 3(h)]10. A capacity for effective written and oral communication. [Criterion 3(g)]11. In-depth education in the hardware and software subdisciplines of Computer Engineering.12. Recognition of the need for, and an ability to engage in life-long learning. [Criterion 3(i)]13. Knowledge of contemporary issues and an awareness of the changing technological environment. [Criterion 3(j)]14. An ability to use modern engineering techniques, skills, instruments, and software tools necessary for effective participation in the Computer Engineering Profession. [Criterion 3(k)]15. An appreciation of the unique concerns regarding safety required when working with electrical systems.16. A general preparedness for graduate
Session 1566 Design and Implementation of An Undergraduate Computational Fluid Dynamics (CFD) Course Kyaw Aung Department of Mechanical Engineering Lamar University, Beaumont, Texas 77710Abstract With ever increasing advances in the computers and their computing power,Computational Fluid Dynamics (CFD) has become an essential tool in the design and analysis ofengineering applications. Thus, many universities have developed and implemented a course onCFD for undergraduate and graduate engineering students. This
Paper ID #9465Enhancing Computer Science Programming Courses to Prepare Students forSoftware EngineeringDr. J. Jenny Li, Kean University Prior to joining Kean as a faculty member last month, Dr. J. Jenny Li had been a research scientist at Avaya Labs, formerly part of Bell Labs, for 13 years. She is an experienced industrial researcher with more than 70 papers published in technical journals and conferences, and holder of over 20 patents with five pending applications. Her specialties are in automatic failure detection, with particular emphasis on reliability, security, performance and testing. Before Avaya, she worked
individual learning style to the teaching resource could have important implications ina students’ learning. In addition, Pitman, Gosper and Rich (1999) report that students usedifferent course materials in different ways and to different degrees. Implementing supplementalteaching methods such as computer tutorials into the classroom may thus assist the students inachieving even more knowledge than the traditional lecture formats. Page 8.538.1 Proceedings of the 2003 American Society for Engineering Education Annual Conference & Exposition Copyright 2003, American Society for Engineering Education
a laboratory environment. The laboratoryexercises would certainly enhance experiential learning of the students. However, choosing asuitable platform to accommodate the laboratory exercises is challenging as it needs to satisfypeculiar needs of different types of designs. Field Programmable Gate Arrays (FPGAs) provide aflexible hardware platform to accommodate digital systems. FPGAs, such as the ones providedby Xilinx, are quite useful in applications requiring hardware changes to accommodate systembehavior. As such, these devices offer the opportunity to implement different computer systemcomponents conveniently in hardware using VHDL (Very high speed integrated circuitHardware Description Language). FPGAs can be easily reconfigured to
Paper ID #7754Sophomore-Level Curriculum Innovation in Electrical and Computer Engi-neeringDr. Cordelia M Brown, Purdue University, West Lafayette Cordelia M. Brown is an Assistant Professor in Electrical and Computer Engineering, and Engineering Education at Purdue University. She received her Ph.D. in Electrical Engineering at Vanderbilt Univer- sity, her M.S. in Electrical Engineering at Vanderbilt University, and her B.S. in Electrical Engineering at Tuskegee University. Her research interests include assessment of instructional methods, laboratory design, collaborative learning, and retention and recruitment issues in
to development of intelligentautonomous systems. These systems form a broader class of newly-coined cyber-physical systems or CPS.In a CPS, the cyber resources representing computing, communication and control combine andcoordinate with physical resources. For development of CPS systems, CI techniques are used withinspirations from the nature. These systems have unique ability to learn and adapt to new situationsutilizing the processes of generalization, abstraction and association with inspirations from nature [12-29]. Proceedings of the 2011 ASEE Northeast Section Annual Conference, University of Hartford Copyright © 2011, American Society for Engineering Education Application domains of CI include
“Hands-On Learningin Engineering” project were Professors J. Dempsey, J. Carroll, J. Taylor, W. Wilcox, and A.Zander. The teaching methodology for the revised ES100 course adapted the ‘integratedteaching and learning’ paradigm pioneered and developed by Drs L.E. Carlson and J.F. Sullivanat the University of Colorado at Boulder. 2 The adaptation at Clarkson is a combination oflaboratory experience woven within an introductory computer course teaching both MATLABand LabVIEW. The goals and objectives of this original proposal are listed below. These goalshave guided the ES100 course revisions throughout all of the twists and turns discussed in thispaper. Significantly, note that just recently (February, 2008), Drs Sullivan and Carlson wereawarded
interest in CS.other students similar to the one themselves were facing (shown in In addition, it will be beneficial to understand the differences inFigure 9.). 40% of the participants stated that they got new instruction format in countries where there is little genderinspiration from someone else’s idea in the group (shown in Figure imbalance in the computing fields such as in India[15] and10.). In addition, 60% of our participants agreed that the Facebook Malaysia [13]. The insights and knowledge gained from thesediscussion group helps them learn CS1511 better and kept their explorations will also be integrated in the next round of interventioninterest in the computer science (shown in Figure 11.), while 10
. Through the hand-on approach to learning and teaching both core technology and practicum, it fosters the creation of new enterprises through innovation “Sandboxes”23 where the future IoT implementers can learn to apply and benefit from local subject matter expertise. 5. Finally, because of the open-access for global content in tools, demonstrations and reference design libraries it can server as a conduit for the “give-back” of technological innovation developed overseas to aid the economic redevelopment of traditional industrial centers in the US.Approach:The basic approach to develop a scalable, state-of-the-art Computer Engineering and ScienceCurriculum with IEEE Certification of participants and ultimately ABET
, University of Illinois Urbana-Champaign Matthew West is an Associate Professor in the Department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign. Prior to joining Illinois he was on the faculties of the Department of Aeronautics and Astronautics at StanfoSascha Hilgenfeldt, University of Illinois Urbana-ChampaignProf. Mariana Silva, University of Illinois Urbana-Champaign Mariana Silva is a Teaching Associate Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. Silva is known for her teaching innovations and educational studies in large-scale assessments and collaborative learning. She has participated in two major overhauls of large
learning). The survey was distributed to students and educators in educational institutes in Kuwait. The results showed high acceptance and awareness, especially among the department heads. The lowest awareness scores were attributed to the administration's roles; therefore, a recommended training that emphasizes the importance of CT in education for the leadership positions then forming a team including the department heads to incorporate the plan into the classroom. Overall, the results of this study can guide promoting CT activities in the Kuwait education system.IntroductionComputational thinking (CT) is a mindset tool that uses computing ideas to improve reasoningthrough the processes of problem
systems design, development, and consultation firm. She joined the faculty of the School of Engineering and Computer Science at Baylor University in 1997, where she teaches a variety of engineering and computer science classes, she is the Faculty Advisor for the Women in Computer Science (WiCS), the Director of the Computer Science Fellows program, and is a KEEN Fellow. She has authored and co- authored over fifty peer-reviewed papers.Kevin Kulda, Baylor University Kevin is a Senior at Baylor University studying Computer Science and Information Systems. He is simul- taneously a Baylor Honors Student and a Baylor Business Fellow. Kevin’s senior thesis will investigate the intersection of machine learning and
generally take ownership oftheir projects, they learn material specific to their projects and beyond that taught in class, and he c mm nica e ha ma e ial hei cla ma e . Since each den jec i diffe en ,there is usually an increa ed demand n he in c ime. Thi a e e en he c eof the CFD course, the problems designed by the students, the models they employed, thechallenges faced by the instructor, and the lessons learned.IntroductionThe evolution of modern computers and simulation tools has had a profound effect on theengineering profession. Engineering problems that were once addressed by governmentresearchers or industry research and design teams using custom computer codes can now beroutinely solved
visualization of fluid flow, which can get students excited about fluidmechanics. Page 9.1370.1 Proceedings of the 2004 American Society for Engineering Education Annual Conference & Exposition Copyright © 2004, American Society for Engineering EducationThe basics of computational fluid dynamics are first introduced in a one hour lecture and thenstudents work in-groups in a computer classroom for two class hours learning how to use theCFD software (Fluent 6.1). Students are given a mixing elbow tutorial where they learn how toenter the required inputs to run a simulation, the post processing tools available to view