. 198.0 References1. K. Otto and K. Wood, "Product design: techniques in reverse engineering and new product design," ed: Prentice-Hall, 2001.2. L. Sass and R. Oxman, "Materializing design: the implications of rapid prototyping in digital design," Design Studies, vol. 27, pp. 325-355, 2006.3. M. Schrage, "The culture (s) of prototyping," Design Management Journal (Former Series), vol. 4, pp. 55-65, 1993.4. R. Moe, D. D. Jensen, and K. L. Wood, "Prototype partitioning based on requirement flexibility," in ASME-IDETC, 2004, pp. 65-77.5. B. A. Camburn, B. U. Dunlap, V. K. Viswanathan, J. S. Linsey, D. D. Jensen, R. H. Crawford, et al., "Connecting Design Problem Characteristics to Prototyping Choices to Form a Prototyping Strategy
7 17 300 30 G 2 3 6 20 210 4 1 S 10 200 Targets/Waypoints 5
in SoTL.References[1] A. M. Lucietto, and L. A. Russell, “STEM Educators: How They Teach,” Journal of STEM Education: Innovations and Research, no. Summer 2018, 2018.[2] C. R. Thomas, “Personality in Engineering Technology,” Journal of Engineering Technology, vol. 31, no. 2, pp. 16-20, Fall2014, 2014.[3] E. R. Kahu, and K. Nelson, “Student engagement in the educational interface: understanding the mechanisms of student success,” Higher education research & development, vol. 37, no. 1, pp. 58-71, 2018.[4] R. M. Felder, and R. Brent, “Understanding student differences,” Journal of engineering education, vol. 94, no. 1, pp. 57-72, 2005.[5] J. A. Gasiewski, M. K. Eagan, G. A. Garcia, S. Hurtado
concern Assessment Assess action taken to improve learning None; Change/ Change in/confirmation of one’s thinking (about Vague; Confirmation learning strategy or learning concern) as a result Sufficiently Goals Description of clear goal Detailed; Planning Steps Articulate action(s) to be taken Justification Explain/Justifies choices made to move forward OR Planning- Transfer Description of application of learning strategy/ Transfer skill/content to futureVI. ResultsThe levels of students’ engagement
methods to address the students’ diverse learningstyles.Our research team is currently working on developing shared MR environments to allow formore comprehensive collaborative experiences among students. So, as future work, our teamaims to refine the MR module and upgrade it from single-user to multi-user operation, allowingfor synchronized shared experiences and conducting another research study.References[1] B. Jaeger and A. Upadhyay, “Understanding barriers to circular economy: cases from the manufacturing industry,” J. Enterp. Inf. Manag., vol. 33, no. 4, pp. 729–745, 2020.[2] S. Helper, T. Krueger, and H. Wial, “Why Does Manufacturing Matter? Which Manufacturing Matters? A Policy Framework,” SSRN Electron. J., Feb. 2012, doi
, leadership, teamwork, innovation, and civic andpublic engagement. The survey aimed to understand students’ “attitudes towards professionalskills is to predict their intention to master those skills during college and enact them aftergraduation” [13, p. 1430]. This recent work is focused on helping universities develop curriculathat incorporate professional skill development within technical courses and seems particularlyuseful for engineering educators. Another option might be using the Miville-GuzmanUniversality-Diversity Scale—Short form (MGUDS-S) to determine their openness to andappreciation of cultural diversity [14].Students should be taught creativity theories and methodologies in engineering design courses toincrease creativity in
interdependence between teachers and the SLIDER Fellows and how is power distributed in the teacher-fellow relationship? • How does the relationship between teachers and Fellows, particularly related to interdependence and power, impact teachers’ instructional practices? Page 22.1470.4Research DesignTo study the relationship between Fellows and their partner teacher(s), we relied on case studydesign, described by Yin (2003) as “an empirical inquiry that investigates a contemporaryphenomenon within a real-life context, especially when the boundaries between the phenomenonand context are not clearly evident” (p. 13). In this study, it was
period. The MEA was launched in the laboratory setting which was facilitated by twoGTAs supported by four undergraduate assistants. Student teams of 3-4 students developedDRAFT 1 of their memo with procedure and results. This draft entered a double-blind peerreview process. In preparation for the peer review, students participated in a calibration exercisein which they practiced giving feedback on one prototypical piece of student work using theMEA Rubric, were provided an expert‟s review of that student work, and reflected on what theyneeded to do differently to improve their ability to give a peer review. For the actual peerreview, each student reviewed one other team‟s solution to the MEA. Each team was assigned atleast 3 peer reviewers. Each
a 4-yearinstitution, can impact a student’s “roles, relationships, routines, and assumptions” [16, p. 159].Therefore, to further examine the experiences and perceptions of transfer students withincomputer science, we leveraged Schlossberg’s Transition Theory [16], [17], a theory originallydeveloped for use in adult education and counseling. This theory outlines coping strategies thatplay a critical role in understanding an individual’s response to a transition and determining whatresources or structures could be designed to support a particular transition better. To categorizecoping strategies that would be applicable regardless of the transition or where an individual waswithin the transition, Schlossberg defined the 4 S system: situation
differently during the different stages of the design process. As such,the rubric divides the design process into three stages (i.e., Requirements/Problem Definition,Concept Generation/Development, and Technology Integration), which can be modifieddepending upon the design project, and a fourth category for the overall design.Each design stage is examined more closely using questions about the incorporation ofstakeholder considerations at that stage, 1. Did the student(s) state an intention to incorporate stakeholder concerns at this phase? 2. Did the student(s) apply a design process at this stage that could include stakeholder concerns? 3. Was the student(s) successful in integrating stakeholder concerns?These
parameters of the induction machine are: V, rated voltage, f, Frequency, p: number ofpoles; Re: Stator winding resistance; Xe: Stator leakage reactance; Rr’: Rotor winding resistancereferred to stator; s: Slip; Rr’(1-s)/s: Load resistance or effect of slip on the rotor; Xr’: Rotorleakage reactance referred to the stator; Gc: Conductance that represents iron losses; Bm:Magnetizing susceptance; and, Pm: Mechanical losses The graphic window of the torque-speedcurve is the fundamental tool of analysis of the virtual lab model, is composed of three parts: 1) Torque-speed curve; 2) Cursor adjustment of slip, load adjustment, (s); 3) Values of the variables of interest.The motor operating conditions, which can be analyzed with the model, are: a
. Vitak et al. critique the IRB process for applying strict requirements forlow-risk research [18]. While our study was low-risk, we successfully underwent the IRBprocess and received approval exempt from full board review. However, we found that twocommunity colleges would not recognize our qualifying IRB. Each college's IRB requested thatthe research study go through their college’s IRB qualification before allowing their faculty toreceive the recruitment message. In one instance, coauthor 1 asked to forward the recruitmentmessage from coauthor 2's initial postings and was told to submit the survey to coauthor 1's IRBbefore doing so. In the second instance, after someone had forwarded our survey invitation totheir colleagues, a community
approaches to enhancing programs and curricula.In this context, we argue that it is particularly important to conduct comparative internationalresearch to better understand how conceptualizations of interdisciplinary education are not onlydiscipline-dependent but also culturally and institutionally contingent. Such a comparative studycan help inform curricular design to foster students' understanding of global competence. As afirst step in such efforts, we used reflexive thematic analysis within a comparative case study[11], [30], [31] to identify interdisciplinary graduate students’ conceptualizations ofinterdisciplinary education at two universities, one in Finland and one the U.S. The researchquestion(s) associated with this work are the
periods are the focus of this work. A visualization of thismodel is presented below in Figure 1. Figure 1: Conrad et al.’s (2006, p. 257) Model of Undergraduate SocializationStrayhorn [23] argues that feelings of belonging are a fundamental human need that are alsosufficient to drive behavior. Individuals that feel cared for, supported, and that they matter tothose around them in a given environment subsequently feel that they belong in thatenvironment. Belonging takes on heightened importance during uncertain or stressful periods oftime, and in contexts where an individual feels like an outsider. For most traditional prospectivestudents, the college application process is stressful and takes place during late adolescence: acritical period
traditional linear regression and thus necessitatesa regression method that accounts for clustering within a sample. ICC values can range from 0 to1, with higher values indicating stronger intergroup correlations and indicating the need forHierarchical Linear Modeling (HLM) methods. While the interpretation of ICC depends on thecontext of the study and the research question being addressed, ICC values greater than 0.1generally indicate that there is a significant amount of clustering in the data and that HLM maybe appropriate [40]. It is also important to note that the interpretation of ICC values should bedone in conjunction with other information about the study, such as the sample size andcharacteristics, the instrument(s) used, and the research
HSGPAranges.Continuing from the insights provided by the KDE analysis, we further examine the variability inprogram complexity among universities. This part of the exploratory data analysis focuses on howthe structural aspects of university curricula influence student enrollment decisions. As highlightedin Figure 3, the distribution of program complexity varies notably between different institutions,such as University ’1’ and University ’3’. This variability is not merely incidental but indica-tive of these institutions’ diverse academic cultures and curricular frameworks. The KDE plot forUniversity ’1’, with a multi-peaked distribution, suggests a curriculum that offers a wide array ofprograms ranging from less to more complex. In contrast, University ’3’s
Paper ID #35732Engineers and AccountabilityDr. Kenneth W. Van Treuren, Baylor University Ken Van Treuren is an Associate Professor in the Department of Engineering at Baylor University. He received his B. S. in Aeronautical Engineering from the USAF Academy in Colorado Springs, Colorado and his M. S. in Engineering from Princeton University in Princeton, New Jersey. After serving as USAF pilot in KC-135 and KC-10 aircraft, he completed his DPhil in Engineering Sciences at the University of Oxford, United Kingdom and returned to the USAF Academy to teach heat transfer and propulsion systems. At Baylor University, he teaches
respondents’ gender, race, and age.Respondents were asked to rate various factors on a Likert scale – from not at all (0),barely (1), somewhat (2), moderately (3), and very (4), that influenced their decision toenroll in an aviation maintenance collegiate program. The factors were: encouragementfrom parent/ guardian; encouragement from advisor, teacher, or friend(s); the number ofjob opportunities the field offers and their level of pay; interest, passion, or aptitude insubject; and reputation of the program. The full survey is attached in Appendix A.Data Collection PlanParticipation in the survey was voluntary and this was indicated in the recruitment email.The recruitment email was sent using a blinded, private mailing list that did not identifythe
Fellow role(s) interested them and why. All of the candidates wereinterviewed and, based on those conversations, we decided to add two more Fellowship roles: The EnSURE Fellow would help organize the Engineering Summer Undergraduate Research Experience (EnSURE) program The Recruiting Fellow would assist in identifying and connecting with prospective graduate students through on- and off-campus recruiting activitiesIn addition to these six Engineering Graduate Leadership fellows, we decided to partner with theGraduate School’s Leadership Fellows program to co-sponsor two additional roles: a GraduateStudent Life and Wellness Fellow, focusing specifically on the needs of Engineering graduatestudents, and a Women in STEM
of applications that were introduced in the workshop.Upon completion of the workshop, the participants were given an eight-question exit post-trainingsurvey shown in Figure 2. There were six quantitative questions using a five point or a three-pointLikert scale as well as two qualitative questions. The two qualitative questions were also used aspedagogical tools based on experiential learning best practices. Question 7’s goal was to elicit apositive self-reflection while Question 8 reinforced learning through internalization andsummarization. 1. Exiting this workshop, I learned something new about AI concepts, applications, and ethics (1 - strongly disagree to 5 - strongly agree). 2. I have a better understanding of AI and how to
Leveraging Faculty Externship to Develop New Concentrations and Specializations in Construction Management CurriculaAbstractThis "Work in Progress" paper provides insight into a viable strategy for enhancing ConstructionManagement (CM) curricula through the integration of concentration(s) and specialization(s)within program degree paths via formalized engagement of a faculty member industry residency.Ultimately, a faculty member's industry residency aims to gain familiarity and hands-onexperience utilizing cutting-edge industry trends and best practices. It requires embedding a full-time faculty member within an industry environment during a typical summer academicsemester, reducing available faculty resources for the related degree
involved over the years teaching Mechanical, Industrial,Manufacturing, and Mechatronics Engineering Technology capstone courses at PNW.In the 1980’s and 1990’s, capstone projects were typically associated with a student’s workplaceat this university which was, at that time, focused on part-time adult learners. In the past twodecades the student body has shifted to younger, full-time students and senior capstone projecttopics, execution and outcomes have changed with the changing student body. With the shiftaway from part-time students, there are fewer adult learners in the classroom who are currentlyworking in the field. This results in a larger population of students who do not have existingaccess to industrial project experiences.Prior to this
University, India. He extensively traveled within and abroad for technical lectures viz., USA, Germany, Belarus, China, Hong Kong, Thailand, Malaysia, Singapore.Dr. Shanmuganeethi Velu, P.E., Dr. V.Shanmuganeethi, Professor, Department of Computer Science and Engineering. He has been work- ing in the domain of Education Learning Analytics, web technologies, programming Paradigm, Instruc- tional technologies and Teaching aˆ C” Learning PraDr. P. MalligaDr. Dinesh Kumar K.S.A. Dr. K S A Dineshkumar, Assistant Professor, Department of Civil Engineering. He has been working in the domain of Structural Engineering, Geographical Information System, Sustainable development, Smart City, Instructional technologies and Teaching
, how to dress, eat and hold a professional conversation at a formal meal during aninterview; and how to network and follow-up after meeting people professionally. The guestspeakers, veterans themselves, were excited to present to these highly motivated student veteransand to share their stories, and in the process, they inspired this next generation of engineers andengineering technologists.Keywords: adult learners, engineering, learning communities, STEM workforce preparationIntroductionThe goal of the National Science Foundation S-STEM project, A Pathway to Completion forVeterans Pursuing Engineering and Engineering Technology Degrees, is to provide professionaldevelopment and scholarships to student veterans who are attending Old Dominion
Water: Graduate Teaching Assistants in Introductory Science Laboratories at a Doctoral/Research University.,” J Res Sci Teach, vol. 41, pp. 211–233, 2004, doi: 10.1002/tea.20004. [2] G. Marbach-Ad, L. Egan, and K. Thompson, A Discipline-Based Teaching and Learning Center: A Model for Professional Development. 2015. doi: 10.1007/978-3-319- 01652-8. [3] D. A. Schmidt, E. Baran, A. D. Thompson, P. Mishra, M. J. Koehler, and T. S. Shin, “Technological Pedagogical Content Knowledge (TPACK),” Journal of Research on Technology in Education, vol. 42, no. 2, pp. 123–149, Dec. 2009, doi: 10.1080/15391523.2009.10782544. [4] P. Mishra and M. Koehler, “Introducing Technological Pedagogical Content
back on trackfaster by alerting teachers to potential problems. This paper proposes a Deep Learning NeuralNetworks approach that helps students select their best-fit specialization in a specific category.Deep learning is a subset of machine learning, but it can determine whether a prediction isaccurate through its own neural network- no human help is required [1]. The proposed systemwill use a dataset that contains student data that is related to the general education coursesrequired for their program, such as grades, the number of hours spent on each course's materials,the opinion of the student about the content of each course, and the course(s) that the studentenjoyed the most. Additional data will be included in the dataset such as the
] E. Salas, N. J. Cooke, and M. A. Rosen, “On Teams, Teamwork, and Team Performance: Discoveries and Developments,” Human Factors, 50(3), 540-547, 2008.[4] E. Salas, E., D. L. Reyes, and A. L. Woods, “The Assessment of Team Performance: Observations and Needs” Innovative Assessment of Collaboration, 21-36, 2017.[5] G. Wu, C. Liu, X. Zhao, and J. Zuo, “Investigating the Relationship between Communication- Conflict Interaction and Project Success Among Construction Project Teams,” International Journal of Project Management, 35(8), 1466-1482, 2017.[6] A. J. Garcia, and S. Mollaoglu, “Individuals’ Capacities to Apply Transferred Knowledge in AEC Project Teams,” Journal of Construction Engineering and Management
thermodynamics; Carnot Cycle; thermodynamic, overall, and isentropicefficiencies; effectiveness of heat exchangers; refrigeration and heat pump cycles, includingabsorption and cascade refrigeration, and other advanced cycles; air-conditioning processes ofhumid air; Reheat Rankine cycle including means to improve its efficiency; Otto and Dieselcycles; Brayton with intercooling, reheating, and regeneration; property diagrams, p-v, T-v, T-p,T-s, h-s, p-h, and Psychrometric chart.This paper examines course offerings in the fall of 2019, 2020, and 2021. The three offeringsdiffered in content delivery methods. Course in 2019 had one-third of the lectures flipped and alllabs were in person. Course in 2020 had completely flipped lectures and all instruction
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