learning research in the STEM academic discipline of engineering education, specifically targeting the development of better teaching methods for engaging students in the applications of electromagnetic theory. This research has been culminated in the development of a laboratory component for the undergraduate engineering electromag- netics course at Penn State. The laboratory activities were designed to give students as many chances as possible to gain hands-on experience with real-life tools, measurement devices and analysis techniques.Dr. Julio Urbina, The Pennsylvania State University - University Park JULIO V. URBINA, Ph.D is an Associate Professor in the School of Electrical Engineering and Com- puter Science at
courses at undergraduate and graduate levels. His tremendous re- search experience in manufacturing includes environmentally conscious manufacturing, Internet based robotics, and Web based quality. In the past years, he has been involved in sustainable manufacturing for maximizing energy and material recovery while minimizing environmental impact.Dr. Michael G Mauk P.E., Drexel University Michael Mauk is Assistant Professor in Drexel University’s Engineering Technology program.Prof. Tzu-Liang Bill Tseng, University of Texas, El Paso Dr. Tseng is a Professor and Chair of Industrial, Manufacturing and Systems Engineering at UTEP. His research focuses on the computational intelligence, data mining, bio- informatics and
, becausetransmissions are complicated entities and slightly too advanced for the MCD students, andbecause of the severe lack of information on the transmission chosen. MCD students did notreceive a print nor dimensions from the ME capstone students. After researching on the Internet,dealerships, mechanic shops, and even Chrysler, they had to reverse engineer one of the lab's rearwheel drive transmissions that was the correct size. Students also used the hp ratios to determineif they had overcome the built-in safety factor of the transmission.The project was brought to fruition on paper during the last week. The SUV was designed,analyzed and simulated. Only one component, the brake hub, was used to design allmanufacturing plans and processes (lathe programs and
of signal recovery and minimization of noise effects.Educational modules teaching lock-in thermography (as well as lock-in PL and ELoptical imaging) of solar cells may be regarded as the capstone topics of the Solar Cellimaging program proposed here. Students will be working at the state-of-the-art.Finally, at a perhaps more practical and mundane application level, we show somethermal images of solar modules in the field (Figure 13), as a way of detecting hot-spots, shunts, and aberrant solar cell performance. The program thus exposesstudents to imaging from raw materials inspection (multicrystalline silicon ingots) to theend-application of inspecting and maintaining solar modules mounted on roofs forexample. Such imaging in the field plays
, century, digital activities had become very common, with about 9 of10 TE programs reporting the use of computer-based instructional activities. On average, about40% of instruction “used a computer as a tool to complete an activity or project, solve a problem,etc. and more than 6 programs in 10 reported Internet access in the TE laboratory. Conventional labs with equipment for processing wood, metal, and plastic materials wereregularly being converted into “modular Technology Education1” labs. While only 16.4% ofrespondents selected described their labs as fully “modular” about half of the respondents(48.5%) indicated their programs had at least some vendor-created modular work stations,” andnearly three quarters (72.5%) were utilizing some
the solution, wepropose an improved approach where students design and implement at least some of theirProblem-Based Learning: A Tale of Three Courses 9system’s functional blocks. These changes are a result of a curricular redesign and prompted bythe PBL workshop mentioned in this paper’s introduction. There are two main challenges in this endeavor. One is that in SDR applications,implementation means programming, a skill that has proven difficult for a large portion of ourstudents. We intend to ameliorate this problem by having a concurrent bridge programmingcourse. The second is that more active problem solving involves a rearrangement of theremaining lecture sessions that cover the
HE supports; using thesecryptographic operations to write applications at the program level; solving real-world problemsby utilizing HE. Of course, we provide both the HE library and APIs to students.Learning Outcomes Upon completion of the lab, students can use HE cryptographic operationsat the command-line and program level; and solve real-world problems with the HE cryptosys-tem.KA: KU Data: Privacy, Component: Procurement, and Human: Usable Security and Pri-vacy.3.2.4 Developing Mobile Malware (Malware Dev Lab) This lab walks through the process of developing a piece of mobile malware from scratch.Students should learn how to 1) design and develop a piece of malware that sends text mes-sages to all the contact list of the user’s
receiver) and fancy applications (such as recoding andanalyzing the remote car key signal), making the lab more interesting to students. SAMPLE LABS AND RESULTSIn this section, we present two sample labs, i.e., Lab 3—Building an AM Radio and Lab 8—WLAN MAC Protocols. Selected results are provided to demonstrate the procedure and goals.Lab 3: Build an AM RadioIn this lab, students implement an AM receiver using GNU Radio and USRP to receive frombroadcast AM radio stations and to play out the received program via the sound card and speakerin the computer. The core of this AM receiver is the AM demodulator built in Lab 2.The full AM radio diagram is shown in Fig. 8. The main blocks of the AM receiver include theUSRP
. He is the recipient of the 2012 ASEE Mid-Atlantic Section’s Distinguished Teaching Award.Dr. Craig J. Scott, Morgan State UniversityProf. Kenneth A. Connor, Rensselaer Polytechnic Institute Kenneth Connor is a professor in the Department of Electrical, Computer, and Systems Engineering, where he teaches courses on plasma physics, electromagnetics, electronics and instrumentation, electric power, and general engineering. His research involves plasma physics, electromagnetics, photonics, en- gineering education, diversity in the engineering workforce, and technology enhanced learning. Since joining the Rensselaer faculty in 1974, he has been continuously involved in research programs at such places as Oak Ridge National
engineering education work has resulted in her receiving the 2013 UNC Board of Governors Teaching Excellence Award, which is the highest teaching award conferred by the UNC system for faculty. In 2014, she was also the recipient of the ASEE Dupont Minorities in Engineering Award.Dr. Sirena C. Hargrove-Leak, Elon University Sirena Hargrove-Leak is an Associate Professor in the Dual-Degree Engineering Program at Elon Uni- versity in Elon, NC. The mission and commitment of Elon University have led her to explore the schol- arship of teaching and learning in engineering and service-learning as a means of engineering outreach. Hargrove-Leak is an active member of the American Society for Engineering Education. With all of her
undergraduate and graduate levels. His tremendous re- search experience in manufacturing includes environmentally conscious manufacturing, Internet based robotics, and Web based quality. In the past years, he has been involved in sustainable manufacturing for maximizing energy and material recovery while minimizing environmental impact.Dr. Irina Nicoleta Ciobanescu Husanu, Drexel University (Tech.) Irina Ciobanescu Husanu, Ph. D. is Assistant Clinical Professor with Drexel University, Engineer- ing Technology program. Her area of expertise is in thermo-fluid sciences with applications in micro- combustion, fuel cells, green fuels and plasma assisted combustion. She has prior industrial experience in aerospace engineering
routinely deal with large problems, and haveexcellent analytical skills. They are trained in working with interdisciplinary teams, andare taught to consider multiple options before selecting one for final work—a core ideaembodied in NEPA. Yet engineers are rarely exposed to the notion of broaderparticipation in a democratic society. If given the option, most faculties around theUnited States choose to add more technical specialization to a program of study, thatoften have a very short half-life with regards to an individual’s career, instead of fillingout the budding professional with an ensemble of “softer” skills, such as negotiationskills, or an explanation of how one participates in their government.My own experience as a professor in
telehealth practices. Her work in promoting diversity, equity, and inclusion in higher education led to the successful building and passing of the religious accommodation law in the State of Washington, which provides alternative exam testing accommodations for students due to religious observances. Dr. Hussein is the recipient of the 2021 Innovative Program Award from the Electrical and Computer Engineering Department Head Asso- ciation (ECEDHA), for founding the RHLab, as well as the 2022 IEEE Region 6 Outstanding Engineering Educator, Mentor, and Facilitator in the Area of STEM Award, recognizing her contributions to advanc- ing students’ success, mentorship, empowering under-represented communities, and promoting
Session 3438 Reverse Engineering and Rapid Prototyping: A Senior Level Technical Elective for Mechanical Engineering Technology Students and Much More. David R. Forsman Penn State Erie, The Behrend CollegeAbstractStudents in the Mechanical Engineering Technology (MET) program at Penn State Erie, theBehrend College are highly versed in application oriented computer techniques for problemsolving. Nine years ago, a senior level technical elective was developed that would allowstudents with an interest in CAD modeling and design extending beyond
design education.Prof. Marnie V. Jamieson, University of Alberta Marnie V. Jamieson, M. Sc., P.Eng. is an Industrial Professor in Chemical Process Design in the Depart- ment of Chemical and Materials Engineering at the University of Alberta and holds an M.Sc. in Chemical Engineering Education. She is currently the William Magee Chair in Chemical Process Design, leads the process design teaching team, manages the courses and industry interface. Her current research focuses on the application of blended and active learning to design teaching and learning, program content and structure, student assessment, and continuous course improvement techniques. She managed and was a key contributor to a two-year pilot project to
, National Science Foundation, ConstructionIndustry Institute, Business Roundtable, Texas Transportation Institute, etc.). Her research interests includecomputer applications to constructibility and organizational learning, including computer aided design, virtualreality, multi-media, and knowledge base systems modeling. Dr. Fisher was the former director of the EngineeringManagement Program in the department of industrial engineering at the University of Houston. She is currently the Page 6.964.12AGC chaired professor at the University of New Mexico, where she is an associate professor in the department ofcivil engineering
influences and motivates their learning. As engineering is a “practicing profession” [3]where theories from mathematics and physics are applied to solve real world problems,experience in a research lab can serve as a vital component of an undergraduate’s education.Through research, students learn how engineering knowledge and applications are created anddevelop skills that are not learned in their courses [4]. Engineering students report that engagingin undergraduate research greatly increases their technical skills and knowledge [5] and helpselucidate career goals [6]. Moreover, undergraduates report that their research experiencesdeepen their engagement in learning, amplify their motivation to learn, and increase independentthinking [7
pictures, links to other Web sites, video, sounds, Java programs, etc. The completed docu-ment is posted to the web, and instantly accessible to students. A special note, HTML, Java,VRML and Internet Protocols are standardized across all current computer platforms and manygenerations of hardware.1.3 Application Software for StaticsComputer software is not normally suited to a problem solving course like Statics. But, we foundsome professional software tools that are well suited to mechanisms (Working Model) and math-ematics (MathCAD).1.3.1 Working ModelWorking Model (see figure 1) has been designed to allow sketchpad entry of mechanical mecha-nisms, and then simulation of the dynamics. The user begins by defining objects and properties.This is
dramatic effect that the new software has had on theway that mechanical drawing and engineering design are taught at Daniel Webster College(DWC). The two year design experience at DWC is more extensive than the design experiencethat students normally have during the first two years of most four-year engineering programs.The evolution of this design experience will be presented. Three of the presenters of this paperare students. Two will present robotic arm projects; the third will present a supersonic gunproject.I. IntroductionDaniel Webster College offers B.S. degrees in a variety of majors; however, the currentengineering degree programs are two-year transfer programs. The College has severalarticulation agreements with ABET-accredited
mathematical method based on the principles of linear programming theory andapplication. It enables one to assess how efficiently a firm, organization, agency, or such otherunit uses the resources available (inputs) to generate a set of outputs relative to other units in thedata set15,16. Within the context of DEA, such units are called Decision Making Units (DMU). ADMU is said to be efficient if the ratio of its weighted outputs to its weighted inputs is largerthan to the similar ratio for every other DMU in the sample16. The weights used are DMU-specific and during the application of DEA they are chosen by each DMU to maximize its ownefficiency rating. The selection of the weights is only subject to limitations that they should bepositive (or in
model instructors and instructional designersmight choose to design a blended environment, they go through each of the ADDIE phases.The Analysis phase is the foundation for all other phases of instructional design11. Its main focus Page 14.363.2is to identify what is needed or what needs to be done differently. The instructional designerdevelops a clear understanding of the "gaps" between the desired outcomes and the audience'sexisting knowledge and skills12, identifies the instructional needs, determines the learnercharacteristics, and develops the program goals and purposes12. In the Design phase, the results from the analysis are used to
instructors to transition through these online-related decisionsin an uncertain and fast-changing environment at a speed that was unprecedented [4]. Unlikeonline learning, the transition to ERT had limited time for the planning and design processesthat are required for effective online learning [3]. The duties of transitioning courses for ERTincreased instructors’ workload [3], including redesigning assessments, as more emphasis wasplaced on formative assessments rather than summative [5]. Instructors were also required toacknowledge interpersonal matters such as access to reliable internet and students’ personalresponsibilities when they returned to their homes [5].Research about instructors’ experiences during the pandemic have started to emerge
order to apply them to teaching em- ployees as he seeks to begin a startup in the next three years.Prof. Rasim Guldiken, University of South Florida Dr. Rasim Guldiken is an Associate Professor and Graduate Program Director of the Mechanical Engi- neering Department at USF. His educational education interests lie in open courseware for courses in fluid mechanics, metacognitive activities, and flipped learning. Since joining USF in 2008, he has taught Fluid Mechanics and differential equation courses to 2100+ students and was invited to attend the ASEE Na- tional Effective Teaching Institute (NETI). He has been recognized internationally for his teaching efforts with awards such as 2021 USF STEM STEER Scholar, 2020
the students learning and is generally difficultto achieve in online courses. Equally important, the situation in which online learning isimplemented counts too because there is a difference between emergency remote teaching andonline learning.As established in [5], adequate online learning takes about six to nine months to plan and buildfor a successful online class. Lastly, each student has different needs and has access to differentresources such as a stable internet connection, appropriate technology, and a quiet place to studyand join classes. According to [6] in online programs, the differences in students' gender, age,and prior experiences, to mention a few, influence not only the students' choice for a remote classbut also their
question types can be found in Figure 1. However, theinstructor still needs to create an online account in Poll Everywhere website and edit the questionsbefore the class. Once the account is set up, an ID number together with code and a web link shouldbe assigned to the instructor and keep the same for all the questions as shown in Figure 2. By eithertext the code to the assigned ID number via cell phone or go the weblink and vote via any deviceswith internet access, the students should be able to enroll in the polling system successfully. A freeversion of Poll Everywhere service is using for this paper. Although it can accept up to 50responses for the same question, the participants’ names are not recorded, in other words, theresults are
whichmessages. In practice, however, this is made difficult by social network interface design thatmakes audience segmentation cumbersome, by algorithms that make it difficult to predict whosees what information, by a CEO who believes the age of privacy is over9, and by social pressurefrom existing contacts. Another solution, which has worked on the Internet for a while, is that ofpreserving anonymity by posting information identified with only a user name. This age ofanonymity on the Internet is over, however. In fact, anonymity is against the terms of service ofmajor social networking sites such as Facebook and Google+ and defeats the very purpose ofusing LinkedIn. Besides, anonymous postings cannot help an individual present a professionalimage to
broken down into four parts: setting goals,delivering instruction, assessing learning, and making corrections. Page 5.466.2In setting goals for the coursework we applied Bloom’s[1] cognitive learning model Thefollowing table briefly describes Bloom’s six levels of learning. Bloom’s Taxonomy of Cognitive Objectives Level 1: Knowledge: Student can recite, recognize and differentiate facts on a given subject. Level 2: Comprehension: Given cues, students can paraphrase, translate, interpret, extrapolate, and otherwise use facts. Level 3: Application: Without cues, students can
of the faculty may be judged by such factors as education, diversity ofbackgrounds, engineering experience, teaching experience, ability to communicate, enthusiasmfor developing more effective programs, level of scholarship, participation in professionalsocieties, and licensure as professional engineers (Criterion #5).The paper presents the experience in teaching the course renewable energy systems incorporatedwith life cycle assessment education component18-24. The class was taught for 10 weekly lecturesof 3-hour each which represent 11 weeks on a regular quarter. The course learning outcomes are:1. Understand the main sources of energy, energy efficiency, and their primary applications in theUS and the world, 2. Describe the challenges and
othercategories.Although many “new” BIM related construction management skills and competencies,“traditional” skills and competencies are a top response in each respective category. Withinthese “traditional” skills was the reinforcement of soft skills. BIM is a collaborative projectmanagement system so many soft skills are more important than with traditional projectmanagement systems. BIM requires some efficient communication along with strong soft skills,an area reinforced by the findings of this research.As BIM diffuses into the construction community, social systems interested in increasing BIMusage should augment “traditional” skill sets with the “new” BIM related skills andcompetencies. Any academic programs seeking to implement BIM related topics into
promote the use of Project-Based Learning (PBL) in engineering,nor even promote the use of projects within engineering science courses. There are alreadymany excellent papers that justify the benefits of PBL1,2,3,4. This paper was written to assist newfaculty, or those new to PBL, to design appropriate projects for a course.The original motivation for this work came from the re-development of curriculum at sevenAtlantic Canadian universities that share a common two year engineering program which leadsto completion of two more years at Dalhousie University. All seven have begun to implement adesign-project core of courses throughout all common semesters in the first two years. Changehas been initiated as a result of new accreditation guidelines