NSF S-STEM grant to increase the recruit- ment, retention and development of underrepresented populations in electrical and computer engineering. She has approximately 20 peer-reviewed publications with two in the Computers in Education Journal. She also recently published a book on Mobile Robotics for Multidisciplinary Study.Dr. Monica Farmer Cox, Purdue University, West Lafayette Monica F. Cox, Ph.D. is an Associate Professor in the School of Engineering Education and is the Inaugu- ral Director of the College of Engineering’s Leadership Minor at Purdue University. She also serves as the Executive Director of the International Institute for Engineering Education Assessment (i2e2a). She ob- tained a B.S. in
. An interesting observation regarding these last result was detectedthrough students’ comments during the self-assessment stage: in these teams with lowerperformances, the commitment level of some team member(s) was not the adequate throughoutproject development, which was reflected on the quality of requested deliverables, including thefinal presentation.The Consensual Assessment Technique (CAT) is a powerful tool used by creativity researchersin which panels of expert judges are asked to rate the creativity of creative products such asstories, collages, poems, and other artifacts18, 23. In our case, experts in the domain (chemical,food, and environmental engineering teachers and senior undergraduate students) in question(material balances
Ethics, pro- fessionalism, and Education. Dr. Barakat is currently the chair of the Technology and Society (T & S) Division and the ASME district B leader. He is the current secretary/treasurer of the ASEE Ethics Division. Page 24.69.1 c American Society for Engineering Education, 2014 A Model for Engineering Ethics Education Leveraging Workplace Experiences through a Co-op ProgramAbstractEducating engineering student about professional ethics involves multiple challenges. Thesechallenges can be extrinsic such as finding a proper place, timing, and quantity
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achievement and gender affect the earnings of STEM majors? Apropensity score matching approach. Research in Higher Education. doi 10.1007/s11162-013-9310-y.4 Thomas, S. L., & Zhang, L. (2005). Post-baccalaureate wage growth within 4 years of graduation: The effects ofcollege quality and college major. Research in Higher Education, 46(4), 437–459.5 Carnevale, A. P., Smith, N., & Melton, M. (2011). STEM: Science, technology, engineering, mathematics.Washington, DC: Georgetown University, Center on Education and the Workforce.6 Langdon, D., McKittrick, G., Beede, D., Khan, B., & Doms, M. (2011). STEM: Good jobs now and for the future(ESA Issue Brief No. 03-11). Washington, DC: U.S. Department of Commerce.7 Hoachlander, G., Sikora, A. C
and Senior Project Courses, Paper 7199, 120th ASEE Annual Conference.3. Todd, R. H., Magleby, S. P., Sorensen, C. D., Swan, B. R. Anthony, D. K. (1995). A survey of capstone engineering courses in North America. Journal of Engineering Education, (84)2, 165-174.4. McKenzie, L. J., Trevisan, M. S., Davis, D. C., and Beyerlein, S. W. (2004). Capstone design courses and assessment: A national survey. Proc. American Society for Engineering Education Conf. Salt Lake City, UT.5. Howe, S., (2008). Focused follow-up to 2005 national capstone survey. Proc. American Society for Engineering Education Conf. Pittsburgh, PA.6. Duston, A. J., Todd, R. H., Magleby, S. P., Sorensen, C. D. (1997). A review of literature on teaching engineering
n2 x2 s2 Grading Plan 17 89.7 6.5 18 80.6 11.2 Stormwater Plan 17 87.8 6.8 18 71.3 12.5 n = sample size, x = mean, and s = standard deviationThe results appear to show a drop in graded performance on the embedded indicators. Astatistical t-test analysis27 was conducted to confirm the change in performance. Assuming thatthe population distributions are normal and the standard deviations (σ1 = σ 2) are approximatelyidentical (+/- factor of 2), the null hypothesis is that the means are identical ( x 1 – x 2 = 0).Comparing the EDP Grading Plans from 2011 and 2012Pooled estimate of the σ2 is determined as follows
somewhat reduced the amount of material included in the lectures. Table 2. Path generation module. Topic Content 1 Kinematics: A brief review of Kinematic relationships between position, velocity, basic concepts acceleration; graphical representations; examples 2 Common motion profiles 2.1. Trapezoidal velocity profile Derivation of kinematics formulas for position, velocity and acceleration profiles; examples using Excel 2.2. S
percentages:Figure 4 – Percentages of students versus their time to graduation, by gender and whether theygained work experience while at GTAgain, we can see that gender doesn’t change things much at all – students who gain workexperience while at GT overwhelmingly delay their graduation by at least 2 semesters.3. Predictive ModelNext we seek to develop a statistical formula that will provide an estimate of a student’s time tograduation, in semesters, based on whether the student engages in some of the behaviorsanalyzed in this paper and in our earlier work: - Citizenship and residency status, - Whether the student will be a student-athlete at any time during their studies, - Whether s/he will receive a poor grade (D, F, or Withdrew), AP credit
questions: what information isrelevant to the studied attack, where related fingerprint items can be located, and whatinformation each piece of fingerprint can indicate. Also, an evidence tree can provide thecontextual information to correlate attack operations by examine the fingerprints theyproduce. Furthermore, the contextual information provided to an incident tracking softwaremay have the potential of automating attack reconstruction. Page 24.1075.11References[1] Biggs, S. and Vidalis, S. (2009). Cloud Computing: The Impact on Digital Forensic Investigations. InProceeding of the International Conference on Internet Technology and Secured
Glass Interior Operating Conditions: 4.0 Passive System: Insulated Basin 80 Glass Exterior Avg. Wind Speed = 6.4 m/s Passive System: Uninsulated Basin Water Avg. Outside Air Temperature = 30.95 o C Active System: Insulated Basin Distilled Water Yield Rate, L/m2/day Ambient Air Glass Inside Temperature = 37.12 o C
prior art, customer objective(s), customer requirements,design economics, drawings, analytical results, engineering changes, test reports, and an openissues list4. Patent search results may also be included. As the design develops, the presentationshould provide insights into design activities, design alternatives considered and selected,technical/economic trade-off analysis and justifications, and conclusions21. Often the TDR process includes oral presentations. During oral presentations, designassumptions, analysis, alternatives and design methods are challenged during question andanswer (Q&A) portions of the TDR. Duesing4 (2004) states that it is “…critical that engineersexplain their concepts and designs to an engineering and
teaching practices anda five-minute video commentary of their classroom implementation of the topics (if applicable)according to the National Board aligned prompt(s) in each unit (see Appendix A for an examplerequirement and prompt). For more information on the T2I2 professional development materials,please refer to Ernst, Clark, DeLuca, & Bottomley, 20138.Pilot teachers may exercise a great deal of freedom when using the T2I2 system. First, there is noset order for how teachers go through the content. Even though Learning Objects are grouped byUnit, they do not have to be read in any particular arrangement. This allows teachers to chooseareas that interest them the most to read first. Second, although teachers must submit all of theirUnit
. Christensen described growing need forboth “top quality engineering scientists” and “engineering statesmen,” arguing that the lattershould be “trained to have the breadth of social knowledge and technical excellence to transferAmerican know-how in civil engineering to underdeveloped countries.”8 Christensen clearlytook the position that some of this know-how should be developed at the undergraduate level,adding that “[t]he 20 per cent of humanistic activities so widely accepted is only a start towardwhat is needed.” S. S. Steinberg, Dean of Engineering at the University of Maryland, took asimilar position. Discussing how American engineers might support Truman’s “Point Four”program – which aimed to provide technical assistance to developing countries
that girls were not interested in long lectures.They were, however, very interested in hands-on activities and being able to communicate andbond with the female college students. It was also found that girls were most interested inspeakers who talked about their profession in the context of how it makes the world a betterplace, how it enhances the quality of their family life and how they manage family and work.Parents were very interested in opportunities available for their child to explore STEM fields,financial considerations for college, and the parent role in their child’s STEM education.Months prior to the event, the lead from SPAWAR Systems Center Pacific would meet with thestudent organization(s) from the hosting university (e.g. San
% Average B1 B2 B3 B4 B5 B6 B7 B8Figure 6. Comparison of stages for the VBioR teamsFigure 7 shows the proportion of words spoken in the DMM by person, including the coach andall three students. All of the VBioR teams had three students. There is variation from team toteam according to team preparation and prior knowledge, team dynamics and the team’sinteraction with the coach. For example, in team B4’s coaching session only two of the studentstalked during the meeting and the coach spoke more than 80% of the words. By comparison,with team B2 the coach spoke much less, around 60% of the words, while the three studentsspoke more substantial amounts of 10% to 15% each. 100% 90% 80% 70% 60
inward Preference to focus on the present, the The preference we use Sensing (S) details, and personal to take in information knowledge Sensing (S) or and determine the Intuition (N) Preference to focus on kind of information we prefer to trust the future, the big
stakeholders’ social interaction and software productivity from an SIF perspective.Dr. Nan Niu, Mississippi State University Nan Niu is an Assistant Professor of Computer Science and Engineering at Mississippi State University. He received his Ph.D. in Computer Science in 2009 from the University of Toronto, where he specialized in requirements engineering for software product lines. His current research interests include informa- tion seeking in software engineering, requirements engineering, program comprehension, and software engineering education. He is a member of ASEE and a senior member of IEEE.Dr. Donna Reese, Mississippi State University Donna S. Reese received her BS from Louisiana Tech University and her MS and
usto reallocate staff resources from grading to providing walk-in clinic hours to serving studentswho did have difficulties.A typical year's operation saw over 122,000 problems graded automatically – not including theadditional grading resulting from student retries. We attempted to keep the entire class on asingle schedule of due dates, but this imposed significant swings in the load on the autogradingsystem. Fortunately our system administrators were able to deploy adequate server power tohandle our size class. Nevertheless, system performance requires careful attention in courseswhere significant resources are needed for autograding.Lessons learned from the first version of the course – limitations of the original formatMaple T.A.'s grading
0.250 1.284 0.076 *** Family arranged for science tutoring 0.643 1.903 0.190 ***Predictors Father – Engineer -0.507 0.602 0.181 *** Mother – Engineer - - - n/s Sibling – Engineer 0.798 2.222 0.142 *** Other relative – Engineer 0.456 1.578 0.094 *** Mother/female guardian contributed to career
a National Science Foundation Scholarships inScience, Technology, Engineering, and Mathematics (S-STEM) grant, the program involves acollaboration among STEM faculty, college staff, administrators, student organizations, andpartners in industry, four-year institutions, local high schools, and professional organizations. Inaddition to providing financial support through the scholarships, student access to academiccapital is increased through an intensive math review program, tutoring, study groups,supplemental instruction, and research internship opportunities. Access to cultural and socialcapital is increased by providing scholars with faculty mentors; engaging students with STEMfaculty, university researchers, and industry professionals
topic of free-body diagrams (Week 4 and Week 5), and (4) in-class individual and pair work on creating free body diagrams (Week 4).Our primary research focus is to investigate under what conditions (e.g., student background andinterests, prior experience, course content) do variation in the substance and style of web-basedexercises during the introductory course in mechanics impact student self-efficacy andachievement? Is there variability among our observed variables? Furthermore, can we removeredundancy or duplication from our set of correlated variables? Thus we used Factor Analysis topotentially identify latent independent variable(s) associated with the Self-Efficacy Confidenceand Difficulty measures in Figure 4. We will explore how
tura tura tura ion trac -Struc i -S truc i -S truc Relat e d Abs P re Un Mul t end Ext Figure 1. Variations in CEE seniors’ sustainability knowledge (n = 63). Page 24.583.11Table 3. Examples of student sustainability definitions
Page 24.209.1 c American Society for Engineering Education, 2014 Assessing the Role of 21st Century Skills on Internship Performance OutcomesAbstract Internships prepare students for the workplace by giving them opportunities to develop relevantskills. The Committee on the Assessment of 21st Century Skills of the U. S. National Research Council(NRC), the operating arm of the National Academy of Sciences (NAS), has been developing definitionsof workplace skills enabling individuals to face 21st Century challenges. In 2010 the Committeedefined three categories of skills underpinning a broad range of jobs: cognitive, interpersonal, andintrapersonal. The goal of this paper is
. King, C. J. Restructuring engineering education: Why, how and when? Journal of Engineering Education 101, 1–5 (2012).5. Engineering and Social Justice: In the University and Beyond. (Purdue University Press, 2011).6. National Center for Education Statistics. Table 205. Total fall enrollment in degree-granting institutions, by level and control of institution, attendance status, and sex of student: Selected years, 1970 through 2010. Digest of Education Statistics (2011). at 7. Malcom, L. E. in Understanding community colleges (Levin, J. S. & Kater, S. T.) 19–35 (Routledge, 2013).8. National Science Foundation. Table 4-3. S&E and S&E technologies associate’s degrees awarded, by sex, citizenship, race
mixed-mode (MPI-OpenMP) parallel implementation, including performance and scalability studies, carried out inour 16-node, 64 processor cluster.Based on the prime factor decomposition of the signal length this algorithm, which is based on ablock diagonal factorization of the circulant matrices, breaks a one-dimensional cyclicconvolution into shorter cyclic sub-convolutions. The subsections can be processed,independently, either in serial or parallel mode. The only requirement is that the signal length, N,admits at least an integer, r0, as a factor; N = r0.s. The Argawal-Cooley Cyclic Convolutionalgorithm, has a similar capability but requires that the signal length can be factored intomutually prime factors; N = r0.s with (r0,s) = 1. Since the
support, and customer service management. His interests include solid modeling applications, virtual and augmented reality, visualization techniques, innovative teaching methods, and distance learning. c American Society for Engineering Education, 2014 Information Visualization for Product Lifecycle Management (PLM) DataAbstractEnabling users to explore the vast volumes of data from different groups is one of productlifecycle management (PLM)’s goals. PLM must solve such problems as isolated “Islands ofData” and “Island of Automation”; the massive data flow of distanced collaborative design,manufacturing, and management; and the incapability of interpreting and
sin π x Sa ( x) = Sinc(x ) = x πx S inc( x ) = Sa ( π x ) rect ( x) = 1 if x ≤ 1 2; = 0 otherwise Re {a + jb} = a (a + jb)∗ = (a − jb) 3d : aib = ax bx + a y by + az bz 2d : a ib = ax bx + a y by u = uu ∗ j = −1
people interact with their environmentand how they can be enabled by the environment to undertake highly complex tasks thatwould usually be beyond the abilities of the unassisted individuals”32. Vygotsky firstexamined activity theory in the 1930’s. Later, Hutchins and many others have contributed Page 24.1222.5to research in distributed cognition32-38. Additionally, there have been studiesinvestigating why computers enhance student learning and results indicated that taskengagement increases at conceptual levels, student self-regulation increases, andexploration is encouraged35. There is also research to support that peers and socialinteractions are