our custom-built Faraday cage at this stage. Figure 8: Powerline Filter Connectors for the CabinetWe drilled a hole on the outside of the cabinet to insert the powerline filter, which has a 3/4”threaded tube. We attached the powerline filter to the cage using a 3/4” nut on the inside and 4small-sheet metal-screws on the outside of the cabinet. Next, we connected the inner powerlinewires to the power strip by splicing the cable. Then we used the plug end of the cable to attach tothe outside connections of the powerline filter. Figure 9 represents the inner state of our custom-built Faraday cage at this stage. Figure 9: Internal Penetrations in the CabinetNext, we add another layer of fabric sheet to
students in this course can rely on a configuration that works and is accessiblefrom any computer with a network connection. Figure 2 shows the page to start a Jupyter Labsession and Figure 3 shows how Jupyter Lab appears.Figure 1 The Open OnDemand login page.Figure 2 Starting a Jupyter Lab session.Figure 3 Jupyter Lab with several jupyter notebooks loaded.So our current setup for this class is as follows: ● Integrated Development Environment (IDE) ○ Jupyter Lab running on the Buddy supercomputer. ● Python and Associated Libraries ○ Python 3.8.6 with current versions of numpy, scipy, and matplotlib. ● Code Sharing ○ git & github.comPedagogyIn general, this course and many others of co-author Lemley’s
was the insistence that students must learn the mathematicalunderpinnings of software packages.With regard to student software perceptions, none of the freshman or sophomores from non-engineering degrees (3 students) reported having prior experience with software before the fall of2019, whereas over 90% of sophomores in engineering degree tracks reported prior softwareexperience. About 90% of all junior respondents enrolled in these upper-division math courses,whether in engineering tracks or not, reported having prior hands-on software experience of 7some level. Furthermore, 27% of sophomore engineering students attributed part of theirsoftware
role of the D.C. link.In a typical laboratory session, each student team is given a pre-assembled bi-directional 3-phaseinverter connected to our controller. This board is the basis for the course and is used to create amicrogrid and demonstrate the advanced power electronics and controls concepts in real-lifeconditions.Creating the microgrid is as simple as connecting the three phases on two or more invertermodules and running the software. This enables the students to develop an understanding of theend-goal rather quickly, applying a real scenario and real experiment to all of the math andtheory to come in follow-on courses also currently in development.Our approach offers considerable flexibility in configuring experiments. For example, in
teams.2- How team members work is defined as the specific collaborative actions carried out bystudents while developing their projects. These actions include task division, joint taskdevelopment, collective decision-making, and individual progress review.3- How team meetings developed: This construct explores how students engage in collaborativework outside of the classroom setting. It is not derived from a theoretical perspective butdeveloped inductively based on the specific course context. The objective is to understand thesignificance students attribute to synchronous instances (such as face-to-face meetings or videoconferences) and asynchronous work (like written communication channels or collaborativeplatforms).4- How students felt while
Impact of Mental Illness Stigma on Seeking and Participating in Mental Health Care,” Psychol. Sci. Public Interest, vol. 15, no. 2, pp. 37–70, Oct. 2014, doi: 10.1177/1529100614531398.[4] L. Sheehan, K. Nieweglowski, and P. W. Corrigan, “Structures and Types of Stigma,” in The Stigma of Mental Illness - End of the Story?, W. Gaebel, W. Rössler, and N. Sartorius, Eds., Cham: Springer International Publishing, 2017, pp. 43–66. doi: 10.1007/978-3-319- 27839-1_3.[5] B. A. Pescosolido, B. L. Perry, and A. C. Krendl, “Empowering the Next Generation to End Stigma by Starting the Conversation: Bring Change to Mind and the College Toolbox Project,” J. Am. Acad. Child Adolesc. Psychiatry, vol. 59, no. 4, pp. 519–530, Apr. 2020, doi
professional acumen by further developing their interpersonal and technical skillsthrough hands-on and meaningful work.Since they were established, internships and co-ops have become a key component ofengineering culture and the stepping stone into life as a practicing engineer in the workforce.WILs have been fundamental to the development of undergraduate engineering students’ accessto mentorship [1],[4],[7],[12], learning outcomes [1]-[5],[12], persistence and academicperformance [6],[13], employability [3]-[5], and transition into the workforce [5]. In addition,several factors influence the outcomes of WILs such as student classification (i.e., first-year,second year, third year, or fourth year) [14], WILs structure [1], the amount of
was video data of dyads interacting with one another, as well asmembers of the research team and volunteer engineers and makers, during the monthlyworkshops. The data was collected through a stand-alone camera directed at each family with theuse of a Bluetooth microphone to capture audio. The amount of data collected for each familyvaried based on their attendance at these monthly workshops. We have approximately four hoursof video data from Dyad 1 as they attended January and April together. Dyad 2 attended themonthly workshops with the exception of April. This amounted to about 8.5 hours of data.Lastly, Dyad 3 attended each session for approximately 11 hours of video data. This amounts toa total of 23.5 hours of video data.Data
Paper ID #16351Vehicle Structural Analysis for Automotive Systems: An Engineering Coursefor Fundamental Automobile Body DesignDavid Schmueser, Clemson University David Schmueser joined the Clemson University International Center for Automotive Research (CU- CAR) in August 2013 as Adjunct Professor of Automotive Engineering. He received his BS and MS degrees in Engineering Mechanics, and a PhD degree in Mechanical Engineering, all from the Univer- sity of Michigan-Ann Arbor. Prior to joining the CU-ICAR staff, Dr. Schmueser worked as a research engineer at Battelle Memorial Institute in Columbus, Ohio and as a senior staff
instructors is one of the primary reasons why many CBOs have few academicenrichment programs [17].The optimal STEM/STEAM instructor to implement an OST activity need to have the followingcharacteristics: 1) Be knowledgeable in the subject area (content knowledge), 2) Be knowledgeable in the ways to learn and teach in the informal setting (pedagogical content knowledge), 3) Time availability to provide instruction in the times the schools are not in session (generally afternoons, Saturdays and breaks), 4) The cost of the instruction needs to be affordable by the CBO.From the description above, it is clear that the potential poll of instructors able to provide high-quality STEM/STEAM instruction in CBOs in their OST
processing perspective on divergence and convergence in collaborative learning. International Journal of Computer-Supported Collaborative Learning, 6(2):207–221, 2011.[17] Ulrike Cress and Joachim Kimmerle. A systemic and cognitive view on collaborative knowledge building with wikis. International Journal of Computer-Supported Collaborative Learning, 3(2):105, 2008.[18] Evren Eryilmaz, Jakko van der Pol, Terry Ryan, Philip Martin Clark, and Justin Mary. Enhancing student knowledge acquisition from online learning conversations. International Journal of Computer-Supported Collaborative Learning, 8(1):113–144, 2013.[19] C. M. Steele. A threat in the air: How stereotypes shape intellectual identity and performance. American
planning to start engineering at Loyola University Chicago (LUC), the new Director decidedto integrate social justice with engineering in the curriculum. This decision seemed a naturalextension of Jesuit universities’ emphasis on social justice. LUC’s BS Engineering Scienceprogram began the following year in August, 2015.BackgroundIn his 1968 survey for ASEE, Liberal Learning for the Engineer, Sterling Olmsted counted 93engineering schools that had initiated programs in liberal studies in the last three years. By 1973,as a result of this report, almost 200 technical colleges experimented with curricula to address thesocial implications of technology. Two curricular approaches included “humanizing”engineering through interdisciplinary education and
anode side while oxygen flows through the cathode side as shown in Fig.1. Thehydrogen molecules split into electrons and protons (positive hydrogen ions). The electrons flowthrough the external circuit, while the protons flow through the membrane to the cathode to reactwith oxygen ions and electrons, producing electricity and H2O as a by-product. Fig. 1. PEMFC Diagram.When it comes to unmanned aerial vehicles (UAVs) as an industrial application, PEMFCs cansupport much longer flight endurance than internal combustion engine and battery do. In 2006,it was reported that a 2.5 kg UAV powered by an 85 W average, Protonex Technology 110Wpeak PEM fuel cell flew for up to 3h 19min11. Later, Lyon et al. demonstrated
participation in engineering.Dr. David B Knight, Virginia Tech Department of Engineering Education David Knight is an Assistant Professor in the Department of Engineering Education and affiliate faculty with the Higher Education Program, Center for Human-Computer Interaction, and Human-Centered De- sign Program. His research focuses on student learning outcomes in undergraduate engineering, learning analytics approaches to improve educational practices and policies, interdisciplinary teaching and learn- ing, organizational change in colleges and universities, and international issues in higher education.Mr. Lee Michael Warburton, AKKA TechnologiesMr. Christopher David Ciechon c American Society for
, 2024 Unraveling the Nexus: Engineering Student Effort, Coding Protocols, and Academic PerformanceAbstract This paper explores the intricate interplay between engineering student effort and itsimpact on academic performance, building upon and refining existing research (Christensen etal., 2019; Douglas & Alemanne, 2007). The study explored the effectiveness of a 3-point codingscheme created by the research team to assess perceived effort. Additionally, it utilizes statisticalanalyses, including correlations and linear regression, to investigate the complex interplaybetween perceived effort and exam performance. While previous research has emphasized the significance of student participation
] V. Wilczynski and R. Adrezin, “Higher education makerspaces and engineering education,” in ASME International Mechanical Engineering Congress and Exposition, American Society of Mechanical Engineers, 2016, p. V005T06A013.[11] M. Tomko, M. W. Alemán, W. Newstetter, R. L. Nagel, and J. Linsey, “Participation pathways for women into university makerspaces,” J. Eng. Educ., vol. 110, no. 3, pp. 700– 717, Jul. 2021, doi: 10.1002/jee.20402.[12] A. C. Barton and E. Tan, STEM-rich maker learning: Designing for equity with youth of color. Teachers College Press, 2018.[13] S. Vossoughi, P. K. Hooper, and M. Escudé, “Making Through the Lens of Culture and Power: Toward Transformative Visions for Educational Equity,” Harv. Educ
models should incorporate a pre-course orientation program,instructor development training sessions, and design refinement to enhance student and instructoroutcomes.AcknowledgmentsThis publication is a product of a project funded in the Challenge-Based Research FundingProgram 2022 project ID # I035 - IFE005 - C1-T3 – E by Tecnologico de Monterrey. The authorsalso acknowledge the technical and financial support of Writing Lab, Institute for the Future ofEducation, Tecnologico de Monterrey, Mexico, in producing this work.In addition, the authors would like to acknowledge the leadership and financial support of theSchool of Engineering of Universidad Andres Bello, Chile. We also thank the Educational andAcademic Innovation Unit (UNIDA) for
of 26 students enrolled in the course submitted their responses. The surveyasked students to rate each question on a scale of 1 (strongly disagree/none at all) to 5 (stronglyagree/throughout most of the project). Table 2 shows the average of the results from the survey.For the entrepreneurial dimension, questions two, five, and six target creating value. Question 4is related to curiosity and questions 1 and 3 target making connections. Questions 10 and 11target the communications skills on the technical aspect of the project. Students overwhelminglyagreed that the project motivated them and gave them a better understanding of addressingcustomer’s needs and using critical thinking skills to find solutions. Students found that theyimproved a
) it was more flexible in displaying real-time results and customizing the number of allowableattempts and responses for each student; and (iii) it was free for both students and instructor ifthe number of responses in each poll was 40 or less – the class sizes in the fall 2018 offeringswere 34 and 35. Except in sessions scheduled for the exams or project workdays, poll questionswere used to quickly assess the students’ learning in a previous lesson. In total, 26 multiple-choice, 7 open-ended and 3 clickable-image questions were polled throughout the fall 2018semester for each section.Two different sources of data were collected and analyzed to evaluate whether the pollimplementation increased the interest, engagement and learning of the
mathematics (STEM) workforce pipeline is facingmultiple challenges. The first challenge is the relatively lower academic performance of USstudents in comparison to the other 35 countries of the Organization of Economic Cooperationand Development (OECD) as evidenced by the data of the Program for International StudentAssessment (PISA). According to the 2018 assessment PISA [1] which measured themathematics, science and reading skills of 15-year old students from almost 80 countries, theaverage score of US students in science was lower than six of the 36 countries OECD. Theperformance of US students in math literacy is even more concerning. The average score of USstudents in math was lower than the average math score of students from all the OECD
influence ethical decision making.IntroductionEngineers are confronted with ethical challenges on a daily basis, from navigating conflicts ofinterest to negotiating duties to clients and the public. Major engineering failures, such as theChallenger disaster and the Hyatt Regency walkway collapse, are tragic reminders of theconsequences when short-cuts are taken or responsibilities avoided in the profession ofengineering. Engineers involved in construction are faced with navigating one of the mostcorrupt industries globally. In fact, the American Society of Civil Engineers (ASCE), citing astudy by Transparency International, indicates that $850 billion, or 10% of global constructionexpenditures, are lost to bribery, fraud, and corruption each year
assess science teachers’ instructional quality, including observational measures, value-added measures, student surveys, and performance-based tasks; and (3) extending and studying the use of these knowl- edge and instructional practices measures of science teaching quality as summative assessment tools for licensure purposes and as formative assessment tools integrated within teacher education and professional development contexts. She currently serves as principal investigator on three National Science Founda- tion (NSF) research projects. One study (NSF #1621344) is designed to develop, pilot, and validate a set of performance-based tasks delivered within a simulated classroom environment in order to improve pre
by newly-hiredengineers and engineering managers’ supportive actions need to be explored to improve theengineering field’s socialization process and improve career preparation in the engineeringprograms of universities and colleges.3. Methodology3.1 Data CollectionThe study aims to detailly interpret the patterns of comparison in the specific context of theA&D industry within the U.S. Qualitative research methods are applied to focus on aparticular context and identify patterns with sufficient descriptions [31]. Since the study doesnot consider the effect of the individual factors as variables of the participants (e.g., gender,age, working experience, position, etc.), quantitative methods were not involved. The studyadopts semi
Economics 1 Construction Management 1 Statistics 1 Computer Science 1 International Studies 1 German Table 2: Academic Classification of the 12 participating students Number of Students Academic Classification 1 Fifth-year 5 Senior 3 Junior 2 Sophomore 1 FreshmanIn the second week of the Spring semester, students were
to construct an analysis model of the diffusion of DoubleFirst-rate Initiative (see Figure 1). 3 Figure 1 Prelimenary Analysis Framework for the Diffusion of Double First-rate InitiativeThe advancement of the Double First-rate Initiative is complex and unique, covering both internaldecision-making model and external diffusion model. In the internal decision-making model, localgovernments fully consider the political factors, cultural factors, economic factors and social factors,under the influence of internal motivation factors, resource or barrier factors, relevant policy factorsand policy attribute factors based on global development trends and domestic realities, so as tomake
and 2014, respectively. He has worked with Tata Consultancy Services as an Assistant Systems Engineer from 2011–2012 in India. He has worked as an Assistant Professor (2014–2018) in the department of Electrical and Electronics Engineering, KLE Technological University, India. He is a certified IUCEE International Engineering Educator. He was awarded the ’Ing.Paed.IGIP’ title at ICTIEE, 2018. He is serving as an Associate Editor of the Journal of Engineering Education Transformations (JEET). He is interested in conducting engineering education research, and his interests include student retention in online and in-person engineering courses/programs, data mining and learning analytics in engineering education
focus on a variety of aspects, including (1) supporting desired learning or development outcomes, (2) facilitating new perspectives or mindsets, and (3) improving students’ experiences in the course. Visualization Visualization focuses on articulating potential solutions to identified design problems. Such visualization can focus on expansion of the base of ideas and concepts the design team works with or expansion of the details of promising concepts. An important feature here is externalizing a designer’s internal representations and creating novel, shared representations among the design team
, Expert Systems with Applications and other conferences (over 260 refereed publications). He is currently serving as an editor of Journal of Computer Standards & Interfaces (CSI) and editor boards of International Journal of Data Mining, Modeling and Management (JDMMM) and American Journal of Industrial and Business Management (AJIBM). He is currently a Senior Member of Institute of Industrial Engineers, Society of Manufacturing Engineers and the Division Chair of Manufac- turing Division of American Society of Engineering Education (ASEE). He is also actively involved in several consortia activities.Dr. Irina Nicoleta Ciobanescu Husanu, Drexel University Irina Ciobanescu Husanu, Ph. D. is Assistant Clinical
Devices, RF circuits, Low Power CMOS and Wireless Communication.Mr. Brandon Marroquin, Sam Houston State University c American Society for Engineering Education, 2020 Design and Development of Simple Robotic Arm ASEE 2020 Conference - DELOS Division – BYOE SessionSummaryIn today’s world there is an increasing need to create artificial arms where human interaction is difficultor impossible. In this paper we describe the implementation of a simple robotic arm capable of movingand lift some objects. The development of this arm is based on the Arduino UNO. The servos act asjoints of the robotic arm which are controlled by corresponding potentiometer. We have used lowtorque servos
WIL context.3 MethodsThe interview protocol was an exploratory, semi-structured approach adapted from the ECHOmethod [21]. This approach is well suited to gathering rich contextual descriptions of theparticipants’ experiences. Participants were asked about design challenges they encountered, andprompted to identify specific examples of how people and technical factors from their designcontext affected the situation being discussed. This method of prompting minimizes recall biasby focusing the participants descriptions on concrete examples as opposed to generalizeddescriptions.The participants described in this paper worked for a unit called the Engineering Ideas Clinicwithin the Faculty of Engineering at the University of Waterloo which