Differences on Student Innovation Capabilities,” in ASME International Design and Engineering Technical Conferences, 2014.[3] T. C. Kershaw et al., “A Cross-Sectional and Longitudinal Examination of the Development of Innovation Capability in Undergraduate Engineering Students,” in Volume 3: 17th International Conference on Advanced Vehicle Technologies; 12th International Conference on Design Education; 8th Frontiers in Biomedical Devices, 2015, p. V003T04A008.[4] J. Walther, S. E. Miller, and N. W. Sochacka, “A Model of Empathy in Engineering as a Core Skill, Practice Orientation, and Professional Way of Being,” J. Eng. Educ., vol. 106, no. 1, pp. 123–148, 2017.[5] M. Kouprie and F. S. Visser, “A framework for empathy
motivate studentswithin their class by customizing course instruction and materials reflective of their students’future goals. With this additional motivation, students are more likely to use self-regulatorystudy strategies and behaviors, which has been shown to be a positive predictor of classroomsuccess [61]–[64].References[1] J. Husman and D. F. Shell, “Beliefs and perceptions about the future: A measurement of future time perspective,” Learn. Individ. Differ., vol. 18, no. 2, pp. 166–175, 2008.[2] S. E. Tabachnick, R. B. Miller, and G. E. Relyea, “The relationships among students’ future-oriented goals and subgoals, perceived task instrumentality, and task-oriented self- regulation strategies in an academic environment.,” J
idea to one (or more) of the eight fields ofMATCEMIB. Idea flexibility was then established as the number of fields of MATCEMIBthe student had used in the generation of all their ideas. Therefore, idea fluency had nomaximum range, while idea flexibility was limited to a maximum value of eight. Theevaluation of the three assessors was then checked for inter-rater reliability. Results showedthat agreement was high, with values of Cronbach‟s alpha above 0.9 for idea fluency and ideaflexibility. The values of idea fluency and flexibility for each student were then set as theaverage of the values independently allocated by the three assessors.ResultsAnalysis showed that the mean number of ideas generated for first year students was 10.53,while
engineering majors.T-SITE: A UMBC COMMUNITY OF TRANSFER SCHOLARS 2T-SITE is funded by the National Science Foundation (NSF) Scholarships in Science, Technology,Engineering, and Mathematics (S-STEM) program and managed by the Center for Women inTechnology (CWIT) at the University of Maryland, Baltimore County (UMBC). CWIT hasimplemented three S-STEM Scholars programs since 2007. The first, “Scholarships in IT &Engineering (SITE)” (DUE-0630952) served 30 students through spring 2011, 50% of whom werewomen or underrepresented minorities. CWIT’s second and third S-STEM projects are titled, “ACommunity of Transfer Students in Information Technology and Engineering (T-SITE)” (DUE-1154300) and “A
. The proposed creativity enhancing activitieswere created by Destination Imagination, a non-profit educational organization dedicated toteaching the creative process [28, 29].2. Background and MotivationCreativity is a construct that is commonly used, yet in research related terms, it evades consensusin definition [17] - [19]. This can undermine consistent findings when examining the efficacy ofcreativity enhancement and assessment. Although a single agreed upon definition has not beenestablished, Plucker, et al.’s survey of research on creativity found that there appears to be someconsensus that creativity has two basic characteristics: originality and usefulness [17]. For thisstudy, the definition proposed by Plucker, Gehetto, and Dow will
1 = Black/African American Louisiana Residency (State) 0 = Non-Resident 1 = Resident High School Rank (HSRank) 0.2 – 100 High School GPA (HSGPA) 1.59 – 4.0 ACT component scores Science Score (ACT S) 7 – 36 Mathematics Score (ACT M) 14 – 36 English Score (ACT E) 11 – 36 Reading Score (ACT R) 12 – 36ParticipantsThe participants involved in this study include first-time-in-college (FTIC) freshmen whoentered the university in any school year between 2006 and 2015 and declared an engineeringdiscipline as their major. Enrollment in a university seminar class that all FTIC freshmen
learned in their studies, altered theirview of other disciplines, and gave them the confidence to work on business ideas (new and old)after the event. While many graduates from fields considered a part of the creative class won’tstart their own businesses, the development of an entrepreneurship mindset and use of theassociated tools will be essential as they solve the grand challenges of society. Page 26.504.24ReferencesAkker, J. Van den, Koeno, G., Mckenney, S., & Nieveen, N. (2006). Educational design research. London ; New York : Routledge, 2006.Barab, S., & Duffy, T. (2012). From Practice Fields to Communities of Practice. In
forengineering design teams.Structuration TheoryThis study follows Whitbred et al.9’s approach that combines social network analysis withstructuration theory. This approach enables us to examine the structure of project teams whilealso examining the institutional and contextual factors that contribute to team climate, and to thedevelopment of group norms that affect team interactions. Structuration accounts for theinfluence of institutional factors such as rules or norms of what is “acceptable” or “appropriate”behavior within a specific social context, while also affording the actors within that contextagency to effect those structural influences. This theory envisions a reflexive relationship inwhich institutional influences constrain and enable
engineers. After interviewing 53 engineering innovators abouttheir experiences as an innovator and qualitatively analyzing the interview data, weidentified twenty unique characteristics of engineers who had demonstratedextraordinary innovative behavior (Ferguson D., 2013). This finding was corroborated bya separate focus group study (Ferguson D. et al., 2014). We then initiated a modifiedDelphi study with 150 engineering innovators drawn from academic, corporate, andentrepreneurial organizations to examine the complex constructs associated withengineering (Ferguson D, Purzer S, Ohland M, Jablokow K, & Menold J, 2014). Delphistudy participants were nominated as extraordinary engineering innovators from large,medium and small firms; from many
effective way for educators to battle this challenge. This paper describes a tool,SHAvisual, which addresses this issue for the secure hash algorithm (SHA). SHA is a family ofcryptographic hash functions that the National Institute of Standards and Technology beganpublishing in the early 1960’s. SHAvisual is designed to help students learn and instructorsteach the SHA-512 algorithm. It consists of three major components: Demo Mode, PracticeMode and Full Mode. A separate global view window helps highlight the current procedure inthe algorithm pipeline. The Demo Mode provides a simplified SHA-512 visualization and isuseful for the instructor to demonstrate important operations in the classroom. The PracticeMode is designed for students to learn the
increases. Thus we denoteproduction cost as ci (z), where the first derivative ciz < 0. In addition, let s(β, γ)denote the collaboration cost. The mathematical model for the firm’s payoff is: ΠI = b1 z − M − s(β, γ) − ci (z) (2)where b1 is a positive constant and b1 >> 0. We assume furthermore that s(β, γ)is convex with respect to both β and γ. The collaboration cost increases as the GAME THEORY APPROACH ON A UNIVERSITY-INDUSTRY COLLABORATION MODEL 7relevance γ decreases, but at a decay rate. That is, sγ < 0 and sγγ > 0. And ci (z)is also convex with respect to z.2.5. Formulation of the University’s Model. The payoff of the university fromthe collaboration
provide further insight intostudent perceptions. The following observations are noted for data summarized in Table 7: The highest survey response (96%) was noted for perceived student understanding of professional and ethical responsibility. This outcome also has the lowest standard deviation (9%) indicating a concurrence of student perception on this professional skills outcome and providing further evidence of a strong positive response.Table 5. FE Exam Ethics and Business Practice Results, 2009-2015 (n=220) FE Exam Institution CE National Avg. Ratio of Institutional Avg. Administration Avg. % Correct % Correct % Correct / National Avg. S 2009 (2) 88
necessary as sometimes we are interested inless information. The Routh Table allows us to quickly find out if there are roots in the right hand side of the s-plane and, if there are, how many. This indicates stability or instability of the closed loop system.The following steps show how to obtain the Routh Table for our specific example. 50 1+ 2 =0 𝑠(1 + 𝑠⁄20) The equation can be rewritten as: 2 𝑠(1 + 𝑠⁄20) + 50 = 0 1 1 𝑠3
-competitive markets in engineering education could arise whenever there is oneperson/organization/institution involved in providing or “consuming” a good or service. On aregional level, this could arise from engineering programs themselves if there is a paucity ofprograms for students in a certain geographical area, or for a particular technical specialty. In thisexample, there might be a small number of schools offering an engineering course of study. As aresult, students interested in engineering (or a particular type of engineering) would haveminimal options, leading to a potentially non-competitive market because the extant program(s)do not have to compete with other engineering programs to enroll engineering students. Barriersto entry for new
engineering students.2. The first part of research question two asks, how frequently was climate change a topic covered in courses taken by freshmen engineering students in high school? To answer this question, students were asked, “Please indicate whether the following topics were covered in your last high school courses. (Mark all that apply)”. One of the topics was “climate change”. Students option were binary, marking either yes or leaving blank for “Biology, Physics, Chemistry, or Other Course(s)”. The second part of research question two asks, how frequently was climate change a topic covered in courses taken by senior civil engineering students in college? To answer this question, students were asked, similar to the freshmen
, doi: 10.1080/15732471003588254.[4] L. F. Cabeza, L. Rincón, V. Vilariño, G. Pérez, and A. Castell, “Life cycle assessment (LCA) and life cycle energy analysis (LCEA) of buildings and the building sector: A review,” Renew. Sustain. Energy Rev., vol. 29, pp. 394–416, Jan. 2014, doi: 10.1016/j.rser.2013.08.037.[5] Z. Teshnizi, A. Pilon, S. Storey, D. Lopez, and T. M. Froese, “Lessons Learned from Life Cycle Assessment and Life Cycle Costing of Two Residential Towers at the University of British Columbia,” Procedia CIRP, vol. 69, pp. 172–177, Jan. 2018, doi: 10.1016/j.procir.2017.11.121.[6] N. Arena, “Life-cycle assessment applied to construction of Thames Tideway east tunnel, London, UK,” Eng. Sustain., vol. 172, no
Paper ID #30757Examining Undergraduate Engineering Students’ Perceptions of Solving anIll-Structured Problem in Civil EngineeringSecil Akinci-Ceylan, Iowa State University Secil Akinci-Ceylan is a PhD student in Educational Technology in the School of Education at Iowa State University.Dr. Kristen Sara Cetin, Michigan State University Dr. Kristen S Cetin is an Assistant Professor at Michigan State University in the Department of Civil and Environmental Engineering.Dr. Benjamin Ahn, Iowa State University of Science and Technology Dr. Benjamin Ahn is an Assistant Professor at Iowa State University in the Department of
effectivenessof the project in increasing the graduation rates in CS/CE of Hispanic and low-income students.We have also expanded the scope of the program to include the Electrical Engineering program.In accomplishing the project goals, the key components were designed to provide academic andmotivational support for student participants throughout their enrollment at the State Collegesand FAU.IMPLEMENTATION OF MAJOR PROJECT COMPONENTSIn this section, the status and progress related to each of the major project components arereported.a) Curricular refinement of gateway courses in mathematics and computer scienceDuring years 1 and 2, a team of gateway mathematics faculty from each State College incollaboration with faculty from the FAU ‘s Department of
of the parameter(s) on which to conduct the sensitivity analysiscan be considered as an indirect measure because the most relevant information is that whichprovides the best prediction of the most critical parameter (i.e., the parameter that will have thegreatest impact on the decision criterion). The online environment also tracks the informationresources visited by the student teams and the time of visitation. Data collected from a largeengineering economy course are used to evaluate the effectiveness of these assessment methods.IntroductionMaking good engineering decisions is a critical skill for every engineering discipline. Thecomplexity of decision making is tied to multiple criteria which can often be in conflict. Largevolumes of
Session 2003-1313 SPARKING Students Interest in Electrochemical Engineering Robert P. Hesketh, Stephanie Farrell, and C. S. Slater Department of Chemical Engineering Rowan University 201 Mullica Hill Road Glassboro, New Jersey 08028-1701AbstractA new course in Electrochemical Engineering was given at Rowan University using an inductiveteaching format. This format consisted of incorporating electrochemical engineering andelectrochemistry experiments into the lecture. For this class we used an
responses. Results also indicate that both engineering andscience majors are relatively confident in their level of preparedness for future research, signifiedby means above 6.0 for nearly every preparedness item. Before the summer experience, sciencestudents perceived significantly higher (p = 0.0039) recognition from their mentor(s) ascompared to engineering students, whereas in every other aspect of science identity there wereno significant differences by major in either pre- or post-summer experience items. The resultssuggest that early-stage engineering students identify less with research compared to theirscience counterparts and, subsequently, feel less prepared to conduct research; however,participation in an interdisciplinary experience
, 2008).6 Computing Research Association. Cyberinfrastructure for education and learning for the future: A vision and research agenda. (Computing Research Association, 2005).7 Boyer, E. L. The Boyer Commission on Educating Undergraduates in the Research University, Reinventing undergraduate education: A blueprint for America's research universities. (Stony Brook, N.Y., 1998).8 Mitchell, W. J., Inouye, A. S. & Blumenthal, M. S. (National Academies Press, Washington, D.C., 2003).9 Barak, M., Lipson, A. & Lerman, S. Wireless laptops as means for promoting active learning in large lecture halls. Journal of Research on Technology in Education 38, 245-263 (2006).10 Barak, M. & Rafaeli
the opportunity to immediately apply the new mathematical “tool” to an engineeringproblem. This “tool” consisted of the core mathematical concept which they learned about in thelectures and tutorials of the AEM course, and the numerical implementation that they learnedthrough the Matlab modules. For example, the first module showed the students how to solve aset of simultaneous equations which was directly applicable to the multi-loop DC circuitproblems which they were solving in their Circuit Analysis course at the same time. While in thelast module the students learned how to determine the inverse Laplace transform of rationalfunctions using the residue command in Matlab. This enabled them to work through s-domaincircuit design problems
sorting on a deeper, more meaningful level.6 Appliedresearch in engineering education has suggested that students strive to develop conceptualknowledge, but, unfortunately, do so at low cognitive levels. In a study of the learning effects ofa computer-based module on the topic of control systems10, the researchers found greater gains atlower cognitive levels of Bloom‟s taxonomy11 (Level 2: Comprehension; Level 3: Application) Page 22.1619.3than at higher levels (Level 4: Analysis; Level 6: Evaluation). Other research has identifiedmisconceptions held by engineering students regarding basic engineering concepts, like rate andenergy12, and concept
) ( (b)Figure 3.. The Robotiics-I course student s interrests in a) Roobotics, and b) A career in Roboticsbefore annd after this classThe studeents also rateed the Robotics-I activitties that increeased their robotics r undeerstanding and ainterests,, engineering g interests ass well as theiir improved skills, as shoown in Fig. 4-a-b, whereeteamworkk and engineeering designn skills, andd BEST robotics competiition along with w middle-highschool mentoring m greeatly benefittted the
student research projects and understand the have at least several months of experience before issues: the learning curve is too steep s(he) could be allowed to proceed unsupervised for safety.5 Time spent in advising / guiding Items 1- 3 above indicate that time spent in guiding undergraduates is much more poorly-prepared and unproductive graduate students, profitably spent guiding graduate is less productive than time spent guiding students, since that is counted as part enthusiastic undergraduates. Undergraduate of the Promotion/ Tenure criteria. assistants who stay on to graduate school have a
Cpr E 489 127 S. Russell Computer networking EE, ISU EE 424 43 J. Dickerson Digital signal processing CE, ISU Cpr E 305 78 A. Somani Computer system organization and design CE, ISU Cpr E 308 76 J. Davis Operating systems CE, ISU Cpr E/EE 465 37 W. Black VLSI layout and design CE, UM 24.374 84 J.F. Peters System engineering principles CE, UM 24.446 40 J.F. Peters Parallel processing EE, UM 24.771 30 J.F. Peters
properties p. Product and process reliability q. Manufacturing processes r. Quality principles s. Ergonomics3. Other Sources – After looking at program specific criteria, work done with curriculum development in 1992, and the IME Department and university mission statements, the following additional outcomes were added to the list: t. Operations Research u. Knowledge of manufacturing systems v. Working knowledge of basic and engineering sciences Page 5.685.6 w. Employability x. Attitude of Social ResponsibilityThis list was considered to be
Associate Dean of Engineering at the University of Puerto Rico atMayagüez. Address: P.O. Box 5000 College Station, Mayagüez, P.R. 00681-5000. Vocie: (787) 832-4040ext. 3823Fax: (787) 833-6965; e-mail: jzayas@exodo.upr.clu.eduJohn S. LamancusaAssociate Professor of Mechanical Engineering, and Director of the Learning Factory, Pennsylvania StateUniversity. Address: Mechanical Engineering Department, 157 Hammond Buiding, MechanicalEngineering Department, Penn State University,University Park, PA 16802. Voice: 814-863-3350; Fax:814-863-7222;e-mail: jsl3@psu.eduJens JorgensenProfessor, Mechanical Engineering Department, University of Washington, Seattle, WA 98195-2600.Voice: (206) 543-5449; Fax: (206) 685-8047; e-mail: jorgen
components of critical consciousness as criticalreflection, motivation, and action using Diemer et al.’s (2015) definitions because they providethe clearest explanation of each component and limit the use of alternative descriptors orlanguage that are not directly aligned with Freirean thought.Theoretical Expansion of Critical Consciousness Several scholars have used Freire’s (1970) work as a foundation for their work,highlighting the benefits of his scholarship but also identifying limitations in its theory andpractical application. Literature across fields confirms several ways in which criticalconsciousness is defined and operationalized. This section reviews the work of scholars frompsychology (e.g., Diemer and Montero), social work (i.e