programming language for everyone. In: WesternCanadian Conference on Computing Education. (2003)7.Harvey M. Deitel, H. M. (Editor), Deitel P. J., Liperi J. P., Wiedermann B. A., P. Liperi, J. P.,"Python, How to Program", Prentice Hall, Feb. 20028. Martelli, A., Ascher D. (eds): "The Python Cookbook", O'Reilly, 20039. Python Programming In A Day & C++ Programming Professional Made Easy (Volume 43) by Sam KeyCreate Space Independent Publishing, 2015, ISBN-13:9781511776752
responsibility have beensome significant findings resulting from this unique educational model. More research will helpvalidate and refine the effectiveness of the program but to date, anecdotal findings confirm theimportance and value of using client-centered, multidisciplinary approaches to higher education.References1. Gassert, J. D., & Enderle, J. D. (2008). Design versus research in BME accreditation [ABET requirements and why research cannot substitute for design]. Engineering in Medicine and Biology Magazine, IEEE, 27(2), 80- 85.2. Hotaling, N., Fasse, B. B., Bost, L. F., Hermann, C. D., & Forest, C. R. (2012). A quantitative analysis of the effects of a multidisciplinary engineering capstone design course. Journal of
Majors Paper presented at 2009 Annual Conference & Exposition, Austin, Texas. https://peer.asee.org/528318. Argrow, B. M., & Louie, B., & Knight, D. W., & Canney, N. E., & Brown, S., & Blanford, A. J., & Gibson, C. L., & Kenney, E. D. (2012, June), Introduction to Engineering: Preparing First-year Students for an Informed Major Choice Paper presented at 2012 ASEE Annual Conference, San Antonio, Texas. https://peer.asee.org/2160819. Sheppard, S., Gilmartin, S., Chen, H. L., Donaldson, K., Lichtenstein, G., Eris, O., Lande, M., & Toye, G. (2010). Exploring the Engineering Student Experience: Findings from the Academic Pathways of People Learning Engineering Survey (APPLES). TR
interviews with teammembers, and analyzing documents written by participants. Figure 1 below illustrates themultiple data types collected during the investigation and explains how each data source/typeinterplayed with the others to provide a detailed, real-time picture of each student’s experienceworking on a cross-disciplinary team. Observations, interviews, and document analysis yieldeda corpus of data made up of four main data types: interview transcripts (type A in Figure 1), fieldnotes and memos (type B), team meeting transcripts (type C), and individual progress reports(type D). Figure 1: Progression of data collection and the data types generated by my studyThis combination of data sources and types provided rich data on how these
number of simultaneously running guest machines is greatlydependent upon the host machine specification. Therefore, the higher end system specification ispreferred in hypervisor-based virtual machine. However, it is beneficial to run the application indifferent types of OS since it allows creating and running different type of OS in each guestmachine. Each guest machine has its own resources and OS in hypervisor-based virtual machine.3.2 Container-based virtual machineUnlike hypervisor-based virtual machine running a full OS, container-based is running on the topof the existing OS as shown in Figure 1(b), which provides the isolation using a kernelnamespace feature in Linux. The basic idea of container-based virtualization concept is tominimize
Paper ID #16411Support Model for Transfer Students Utilizing the STEM Scholarship Pro-gramMs. Lynn Olson P.E., Boise State University Lynn Olson, P.E, is the Recruitment Coordinator in the College of Engineering at Boise State. She re- ceived a Bachelor of Science Degree in Civil Engineering from Gonzaga University in 1995. She began her engineering consulting career with T-O Engineers (formerly Toothman-Orton Engineering) in Boise in 1997. In fall of 2011 she joined the staff of the College of Engineering at Boise State as an Advisor and Recruitment Coordinator. Since that time she has worked as an adjunct faculty teaching
the total bill. If the service is just fine the tip will be 15% of the total bill. Calculate the tip (Input: 2 points; Processing: 6 points; Output: 2 points) 5) Create a flowchart that requests the points scored by the B’klyn Nets and the Lakers at the end of regular time. The program should display “B’klyn Nets won!” if the Nets won, or “Lakers won!” if the Lakers won, or “Overtime needed” if there was a tie. (Input: 2 points; Processing: 6 points; Output: 2 points) 6) Create a flowchart that converts a numeric grade to a letter grade. The user should be able to enter a numeric grade from 0 to 100. The flowchart will calculate the letter grade based on: A >= 90; 80<= B < 90; 70<= C < 80
Paper ID #17355Automated Measurement of Power MOSFET Device Characteristics UsingUSB Interfaced Power SuppliesProf. Mustafa G. Guvench, University of Southern Maine Dr. Guvench received M.S. and Ph.D. degrees in Electrical Engineering and Applied Physics from Case Western Reserve University. He is currently a full professor of Electrical Engineering at the University of Southern Maine. Prior to joining U.S.M. he served on the faculties of the University of Pittsburgh and M.E.T.U., Ankara, Turkey. His research interests and publications span the field of microelectronics including I.C. design, MEMS and semiconductor
followed a four-point protocol developed by the PI, based on formalmentorship “best practices”. This four-point protocol included (a) video representationthat is representative of a career in STEM, (b) field experience that offers the studentexposure to a STEM profession, (c) a design challenge to be solved using graphicssoftware, and (d) advising sessions where students are advised on college preparatory andother related topics (Denson & Hill, 2010). Telecommunication in the 21st Century To help provide structure and a framework for the eMentorship program a websitewas developed for student participants. The site was hosted on the university’s server andtemporary IDs were developed for student participants
(Jan 1, 2015 – Dec 31, 2018) with the goals of producing significant improvements infreshman and sophomore retention rates in Chemistry, Computer Science, Engineering,Engineering Technology, Mathematics and Physics and increasing the number of female,Hispanic and African American students completing undergraduate degrees in these STEMfields.The funded NSF - IUSE project comprises the following strategies and supporting activities:1. Improve instruction by (a) establishing a STEM education active learning faculty summerinstitute and quarterly brown bag and (b) redesigning introductory CS courses.2. Establish early and motivating field-of-study and career explorations for students through a)Summer Orientation Sessions for first-year STEM
completed FE model. Figure 8 End-Effector Boundary conditionsWith all the properties and boundary conditions discussed, the FE model was simulated inHyperMesh with OptiStruct solver and results shown in Figure 9 (a) demonstrates that the structurewill endure a maximum static deflection of 0.0045in (0.1mm). Figure 9 (b) shows the von misesstresses generated in the structure due to the load. The structure generates 594.7 psi von misesstress while the permissible limit is nearly 8000 psi for aluminum providing 13.5 safety factor(SF). With the static deflection being very small, and the stresses generated well below thepermissible limit for aluminum, thereby providing for a large SF, the design is considered to besafe for
down. However, only 1.8% of students got the correctanswer for problem #26, when the pushing force is doubled. Following Newton’s second law,there is a constant acceleration since the friction force is unchanged. However, the wording ofthis option is “with a continuously increasing speed”, which sounds unrealistic to the students.Because only two students got the correct answer for problem #26, we investigated further on theselections: 38 students (34.2%) selected ‘A’ (double the speed), 44 students (39.6%) selected ‘B’(at a slightly higher but constant speed), 8 students (7.2%) selected ‘C’ and 19 students (17.1%)selected ‘D’, these last two options have a transient period. Since 74% students selected ‘A’ or‘B’, their intuitive understanding
understanding of the scope of his/her career (b) teach the students the impact theirsoftware engineering solutions have in a global context, including environmental and social (c)help develop critical thinking and (d) improve the motivation and involvement the students willhave with activities related to their future profession.Some examples of the themes developed this semester were:• Comparative analysis of the use of augmented reality for the teaching of mathematics in primary education: USA and Europe.• Comparative analysis of the use of augmented reality in projects of Architecture and Urbanism: Japan and Europe.• Comparative analysis of the use of ubiquitous computing in Medicine: USA and Latin America• Comparative analysis of
irrespective of individual course sections and other considerationsdiscussed above, scatter plots and regression lines were plotted and analyzed, results shown inAppendix B. For the entire population, a Pearson r = 0.533 was determined, still exhibiting apositive association. When segmented by delivery method, the correlation coefficients showedFTF = 0.512 and DE = 0.611. These results are in-line with the results of Table 2, anddemonstrate a decreased association attributed to the variances afore mentioned.Table 2. Pearson Coefficients by Class Section: SAP Proficiency v. SCM Content Course FTF Sections DE Sections Year Semester Students Pearson r Students Pearson r 2013
Seventh Annual 2015 Industrial, Manufacturing, and Systems Engineering Day (a) (b) Figure 2. (a) Discussion sessions, (b) Practice sessions during the presentationOn the first day of event, a technical seminar was held to address key issues currently debated anddiscussed at a broad perspective in organizations and also in defense. Four seminars were conductedrelated to energy issues in defense, energy efficiency in buildings, and in engineering leadership relatedissues. The planned workshops held on the second day of event were coordinated to address importantissues and topics relevant to sustainable manufacturing education and required leadership skills
Paper ID #16872Staying In or Getting Out: The Relationship Between Undergraduate WorkExposure and Job Satisfaction After GraduationDr. Alexandra Vinson, Northwestern University Alexandra H. Vinson is a Postdoctoral Fellow in the School of Education and Social Policy at Northwest- ern University. She received her Ph.D. in Sociology & Science Studies from the University of California, San Diego. Her research interests include professional education and enculturation in medicine and STEM fields.Prof. Reed Stevens, Northwestern University Reed Stevens is a Professor of Learning Sciences at Northwestern University. He
total answered. We defined five earnestness categories: ● Highly earnest: 80%100% ● Moderately earnest: 60%80% ● Moderately unearnest: 40%60% ● Highly unearnest: 20%40% ● Cheating the system: 0%20% B. Student earnestness through the course The average earnestness was calculated for each individual learning question for each college classification. Questions were ordered in our analysis based on the order they were presented to the student. We plotted the averages, and noticed a decline in earnestness as students progressed through questions. Two factors were considered that might have affected student earnestness: ● Tiredness factor: Easy learning questions at the end of the semester may have lower earnestness
therelationship between URM engineering majors’ participation ininternships/co-ops and perceived learning gains as measured by the NSSE.Results were statistically significant (F[4,923] = 7.46, p < 0.01, R = 0.18, R2 =0.03, Adj. R2 = 0.027), indicating that URM engineering majors who participatein internships/co-ops report greater learning gains than their same-racepeers who do not work in internships/co-ops. Other significant predictors ofURM engineering majors’ perceived learning generally and problem-solvinglearning specifically were age (b = - 0.002) and transfer status (b = -0.139).Collinearity statistics suggest that multicollinearity was not a problem for thisinvestigation and both part- and partial correlations reinforce interpretationsfrom the
Radio, 2007.2. Reed, J., “Software Radio: A Modern Approach to Radio Engineering,” Prentice Hall, 2005.3. Mao, S., & Huang, Y., & Li, Y. (2014, June), On Developing a Software Defined Radio Laboratory Course for Undergraduate Wireless Engineering Curriculum Paper presented at 2014 ASEE Annual Conference, Indianapolis, Indiana. https://peer.asee.org/228804. Wu, Z., & Wang, B., & Cheng, C., & Cao, D., & Yaseen, A. (2014, June), Software Defined Radio Laboratory Platform for Enhancing Undergraduate Communication and Networking Curricula Paper presented at 2014 ASEE Annual Conference, Indianapolis, Indiana. https://peer.asee.org/230235. Hoffbeck, J. (2009, June), Teaching Communication Systems
authors had studentspredict their performance on the post-video learning task and found that (a) students are in factoverconfident about their learning after watching video-recorded lectures, (b) in-video testingimproves students’ predictions about their actual performance on the learning task, and (c) asingle post-lecture test also helps to adjust unrealistic expectations.28 Therefore, some sort of in-video or post-video testing, or both, is recommended to check viewer expectations about theirown learning.Recommendation #5: When determining an appropriate video length, somewhere in the rangeof 5-15 minutes is recommended.There is no conclusive body of literature on the optimal length of an educational video, but ingeneral shorter is better. Guo
list. A survey was then conducted at the end of Fall 2015 semester.MethodologyData SourceEnd of Course Survey: The end of course survey consists of 42 to 55 items. It wasadministered to students in all sections near the end of the Fall, 2015 semester. Thesurvey covered various components of the course. A subset of these survey items (13items) focused on assessing student patterns of use and perceptions of the variousideation methods introduced by the instructor. These ideation method survey itemsincluded a) a checklist grid in which students were asked to indicate whether they usedeach ideation method on each of three course projects, b) Likert-type items onperceptions of the ideation methods, and c) open-ended items on the ideation
than 35%). While a goal is to be producing students with a higher than expected degree ofsuccess in Calculus 1, we are producing students whose success in Calculus 1 is comparable to © American Society for Engineering Education, 2016 2016 ASEE National Conferencethat of students who have placed into Calculus 1 via more traditional means (mainlycoursework).Table1:GradedistributionintheFall2014andFall2015Calculuscourses. A B C D DR/W F Total % ABC Fall 2014 Calculus 1 64 63 78 42 114 55 416 49% Summer Bridge Students 1
Paper ID #16176The Use of Classroom Case Studies in Preparing First-Year MathematicsGraduate Teaching AssistantsEliza Gallagher, Clemson University Although my mathematical research was in topological algebra, my first faculty position was a joint ap- pointment in Mathematics and Mathematics Education housed within the Mathematics Department at California State University, Chico. Currently the Coordinator of Undergraduate Studies for the Depart- ment of Mathematical Sciences at Clemson University, my research interests are in the field of STEM education, and particularly the development of a teacher identity among
of the team and the facilities areavailable. We believe, offering such realistic experience offers two key educational advantages:(1) turning our resource constraints into an advantage by creating a relevant experiential learningenvironment with its own set of challenges for the students to solve; (2) imbuing our studentswith attributes that are highly desired by employers, while meeting ABET requirements (seeAppendix B).Furthermore, in our approach we take advantage of entrepreneurship education to teach studentsto transform their engineering knowledge into economically relevant engineering practice. Theentrepreneurship education is explicitly designed to emphasize the interaction between designtechniques and techniques to incorporate the
Paper ID #17185Exploring the Impact of Engineering Student and Professor Expectations onthe Development of Student Engineering Identity and NavigationMr. Michael Galczynski, University of Maryland - College Park Michael Galczynski is a Keystone Instructor in the Clark School of Engineering and a graduate student in the School of Education at the University of Maryland, College Park. c American Society for Engineering Education, 2016 Exploring the Impact of Engineering Student and Professor Expectations on the Development of Student Engineering Identity and
transferring knowledge between biol-ogy and engineering is outlined in Table 1. Table 1: Plan for incorporating biomimicry into design innovation Create and disseminate evidence-based instructional resources: a. Design instructional resources that help students to identify characteristics of engineering design problems that enable bio-inspired design (making the leap Objective from engineering to biology). 1 b. Design instructional resources that facilitate the analogy mapping and transfer process of bio-inspired design (making the leap from biology to engineering). c. Disseminate the evidenced-based instructional resources through publications and
of Engineering: (a) tohave students learn and practice the engineering design process early in their engineeringeducation, and (b) to increase undergraduate retention in engineering at Rice University by 10percentage points.In regards to the first objective, student teams design a product that meets user-defined needs andrealistic constraints. Student teams move through the steps of the engineering design processfrom problem clarification to iterative prototyping. Students communicate with the client andinstructors through written reports and oral presentations. Teams are typically composed of fourto six students and are expected to work together effectively.Begun in the spring 2011 with 20 students, the course has been offered every
is felt positively. They are willing to participatemore and interact with their professors. For some students, the professor made a keydifference in their understanding of the subject matter. In the second semester, in [introduction to] algebra, I got a 5.0 [equivalent to a B] in my first test. I was happy because I was understanding it. After that, I realized that it was a professor’s influence. [The math professor] talked, explained and checked for understanding with questions. Then, there was a quiz, and then he explained and worked with examples. Moreover, he made us participate in class. He was a bit tough, he started saying, “you! Solve
time in 2013-2014 academic year and two groups completed the project (distal fibular fracture and mandibularfracture). In 2014-2015 academic years, two groups completed the projects (ulna fracture andclavicle fracture), and some student works are shown below. (a) (b) (c)Figure 1. (a) Plate design before surgical instruction given, (b) Plate design after surgicalinstruction given and (c) Size and shape comparision of two 3D printed platesFigure 1 showed that the differences in the plate design before and after the introduction of thesurgical procedure. A group designed the plate for clavicle fracture based on anatomy, fracturesites of clavicle and the engineering mechanics
between clusters andalso minimizing variance within the clusters. Promax rotation was utilized to adjust for the factthat some of the factors in our survey were correlated; more details about correlation amongfactors and utilizing rotation in a cluster analysis may be found in the literature40,41.Phase IIIn Spring 2015, students enrolled in the same sophomore level IE course in Fall 2014 wererecruited to participate in semi-structured interviews (see Appendix B) addressing their views ofthe future and how they regulate their learning. Four students volunteered for the interviews, andeach student was given a $20 Amazon card as incentive for participating. Interviews weretranscribed, and the text was analyzed with RQDA using directed content