Paper ID #9264Credentialing MOOCs: A Case StudyMr. S. Cory Brozina, Virginia Tech Cory Brozina is a PhD student in the Engineering Education department at Virginia Tech. His research is in educational technology and data analysis.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 at Virginia Tech. His research focuses on student learning outcomes in undergraduate engineering, interdisciplinary teaching and learning, organizational change in colleges and universities
the Electrical Engineering section. Mr. Howie has worked ex- tensively in Information Assurance, Cyber Security, Information Technologies and Communications Sys- tems.Mr. Benjamin B Hannon, USCGA Benjamin Hannon is currently a cadet at the United States Coast Guard Academy and will be graduat- ing this May (2015). He is an Electrical Engineering Major and upon graduation, will report to USCGC RICHARD PATTERSON in San Juan, PR. He was born in Annapolis, MD and was a graduate of Broad- neck High School. Benjamin enjoys running Track and Field.Nicholas Williamson, United States Coast Guard Academy I am a cadet at the Coast Guard Academy graduating this year, 2015, and I am interested in being an active member of
Paper ID #19945The Firelighters: Understanding the Demand for Instructional ComputerScience FacultyJoshua B. Gross, Blackburn College Joshua B. Gross is a professor of computer science at Blackburn College in Carlinville, Illinois. His research focuses on pedagogical problems in computing, as well as employment issues in the IT industry. c American Society for Engineering Education, 2017The Firelighters: Understanding the Demand for Instructional Computer Science FacultyAbstractInstructional faculty (those whose primary responsibility is teaching undergraduates) incomputing are not well-studied, and the
, technology is not widely integrated into the learning experience. A recent surveyof ECAR shows that they wish that their professors more often use classroom technology inonline or face to face teaching (Figure 2).Figure 1: Students’ ownership of education related tech devices (a) and their importance rank to do with mobile devices (b) [2] Page 24.760.3 Figure 2: Student wished that their professors communicated more using these means [2]Classroom technology is both highly customizable and intrinsically motivating to students, it isparticularly well-suited to expand the learning experience [3]. Besides innovative
behalf of women), all at Purdue University. This year she is a visiting research scientist in the Weldon School of Biomedical Engineering, visiting faculty in the Center for Entrepreneurship, and a visiting Fellow in the Center for Education and Research in Information Security at Purdue University.Dr. Carla B. Zoltowski, Purdue University, West Lafayette Carla B. Zoltowski, Ph.D., is Co-Director of the EPICS Program at Purdue University. She received her B.S. and M.S. in electrical engineering and Ph.D. in engineering education, all from Purdue University. She has served as a lecturer in Purdue’s School of Electrical and Computer Engineering. Dr. Zoltowski’s academic and research interests broadly include the
Kee Wook Lee is a senior student at Purdue University, West Lafayette, IN, majored in electrical engi- neering.Dr. David B Nelson, Purdue University, West Lafayette David B. Nelson is Associate Director of the Center for Instructional Excellence at Purdue University. He received his Ph.D in World History from the University of California, Irvine in 2008. David has been involved in many educational research projects at Purdue, including published worked in the programming education, student engagement and academic performance in dynamics engineering courses, and educational modalities in engineering, technology and economics.Dr. Yung-Hsiang Lu, Purdue University Yung-Hsiang Lu is an associate professor in the School
Professional, EMC Information Storage and Management, IPv6 Forum Certified Engineer (Gold), IPv6 Forum Certified Trainer (Gold), and Cisco Certified Academy Instructor. Dr. Pickard received his Ph.D. in Technology Management at Indiana State University. He also holds an MBA from Wayland Baptist Uni- versity and a B.S. in Professional Aeronautics from Embry-Riddle University. Research interests include: IPv6, IPv6 adoption, wireless sensor networks, and industry-academia partnerships.John B. Southworth, East Carolina University John Brooks Southworth received a B.S. degree in electronics/computer networking from East Carolina University, Greenville, NC, in 2002 and an M.S. degree in computer networking management from East
physics as less appealing, preferring to stay in the lab, and may not apply themselves in working complex, multistep problems. (B) Some are interested in pure science and/or are planning to pursue other scientific fields (e.g., medicine). These students sometimes have little interest in the bots and programming but may do well in learning theory and taking tests.Unfortunately, most students have never done any programming or worked with spreadsheets.Some students struggle with programming beyond simple commands. Programs of any length,which required use of several subroutines and “IF…THEN” logic, were a struggle for many ofthe students. We have not emphasized programming in the course; we see it as an enablingtechnology
of Mechanical Engineering and Mechanical Engineering Technology at Eastern Washington University. He teaches courses in the areas of Robotics, Mechanics, Thermodynam- ics, Fluids, CAD, and Capstone Design.Dr. Donald C. Richter, Eastern Washington University DONALD C. RICHTER obtained his B. Sc. in Aeronautical and Astronautical Engineering from The Ohio State University, M.S. and Ph.D. in Engineering from the University of Arkansas. He holds a Professional Engineer certification and worked as an Engineer and Engineering Manger in industry for 20 years before teaching. His interests include project management, robotics /automation, Student Learning and Air Pollution Dispersion Modeling
-446.4. DeMarco, T. 1982. Controlling software projects: management, measurement & estimation. Yourdon Press, New York, NY.5. Humphrey, W. S. (1988). Characterizing the software process: a maturity framework. Software, IEEE, 5, 2 (March/April, 1998), 73-79.6. Kaner, M., and Karni, R. 2004. A capability maturity model for knowledge-based decision-making. Information, Knowledge, Systems Management, 4, 4 (December, 2004), 225-252.7. Keller, K., and Mack, B. 2013. Maturity Profile Reports (March 2013). Retrieved May 17, 2013 from http://cmmiinstitute.com/assets/presentations/2013MarCMMI.pdf.8. Kitson, D., and Masters, S. 1992. Analysis of SEI Software Process Assessment Results 1987-1991, Technical Report
purpose, the Message-Passing Interface 19, 41 (MPI) library andOpenMP can be used. As a warm-up exercise, we can assign students with matrix multiplicationbenchmark. In this problem, we assume that we have a large matrix A and B to be multiplied andthe result to be stored in matrix C. By varying the dimension of matrices A and B, as well as thenumber of processors, we can obtain a well-designed exercise where students can observe thefollowing: Writing a simple parallel program to be executed on cloud using HPCaaS Partitioning the task between the existing number of Virtual Machines (VM) allocated for this exercise Scheduling assignment task of multiplication to virtual processors Choice of static vs
an object-oriented system. Figure 1 - Example UML Class DiagramOf course, she could not see a UML diagram. Therefore, there were several major problems thathad to be overcome: a) helping her to understand what the diagrams normally convey visually, soshe can understand what the diagrams teach about program structure, b) providing a way torepresent a UML diagram that she could both read and produce, and c) providing a way for herto participate in the diagram assignments and, in particular, the peer review process.The natural idea for conveying UML diagrams was to convert them to raised-dot diagrams,where the structure is indicated by raised dots on paper and the textual elements are indicated inBraille. RCPD has a
afirst-year course. We believe that the pedagogical process used in this course is transferable toother educational contexts.References: 1. Allen, D., Allenby, B., Bridges, M., Crittenden, J., Davidson, C., Hendrickson, C., Matthews, S., Murphy, C., and Pijawka, D. (2008), Benchmarking sustainable engineering education: Final report. EPA Grant X3-83235101-0. 2. Wiggins, J., McCormick, M., Bielefeldt, A., Swan, C., and Paterson, K. (2011), “Students and sustainability: Assessing students’ understanding of sustainability from service learning experiences”, paper presented at the 2011 Annual American Society of Engineering Educators (ASEE) Conference and Exposition, 26-29 June 2011, Vancouver, Canada
Page 22.1068.5 contents. Use the GIS join operations to integrate the data and symbolize the points to create an informative map. Turn in acompressed folder with a) your map (mxd file) b) data folder containing i. your point data (txt or shp files) ii. spreadsheet with your data log. iii. Any other layers you have included c) Jpeg file with the exported image of your map. d) A short paragraph describing the accuracy of the measurements you have included. Directions for Mapping Assignment 3 This project is similar to the preceding two mapping
follows [3]: 1. The Cloud Provider signs VM with its own private key. 2. The Cloud Provider sends the signed VM to the Verification Engine. 3. The Cloud Provider sends the public key to the Cloud Consumer. 4. The Cloud Consumer sends the public key to the Verification Engine. 5. The Verification Engine verifies the authentication of VM template. Figure 2. VM template authentication using digital signaturesThe potential issues of this approach are: a) The Cloud Provider needs to protect private key from unauthorized use and disclosure. b) The Cloud Provider needs to provide its own public key in a trusted way to each Cloud Consumer. c) The Cloud Consumer needs to protect private key from
figure is the block diagram of this homework.Homework : Design a binary to decimal convertor.1-Multiply bit #i by 2^i.2-Add all the results obtained from step 1.Following figure is the block diagram of this homework. Page 24.842.6These homework could be expanded for teaching the procedure for converting a number fromother bases such as octal or hexadecimal.(b)- LabVIEW in the Data Communications coursesLabVIEW could be used to enhance teaching communication courses. It is very helpful inexplaining many important topics such as: AM, FM, and PSK, and many other communicationtopics.Homework : Design AM modulation with LabVIEW. Use the following
learning). TABLE 1. ABET student outcomesABET student outcomes(a) An ability to apply knowledge of computing and mathematics appropriate to the program’sstudent outcomes and to the discipline(b) An ability to analyze a problem, and identify and define the computing requirementsappropriate to its solution(c) An ability to design, implement, and evaluate a computer-based system, process, component,or program to meet desired needs(d) An ability to function effectively on teams to accomplish a common goal(e) An understanding of professional, ethical, legal, security and social issues and responsibilities(f) An ability to communicate effectively with a range of audiences(g) An ability to analyze the local and global
traditional REU model (A) andthe VisREU Site model (B) for student research teams. This arrangement fostered collaborationamong team members, an appreciation of the visualization process and an understanding of therole visualization plays in discovery and analysis for both the undergraduate researcher and forthe research team.Figure 1. Traditional REU student research team model (A) versus VisREU student researchteam model (B). Dashed lines in (B) indicate the REU mentoring and collaboration structurewithin the VisREU Site. Complementary outcomes of the VisREU Site are to (1) explore visualization as aconduit for collaboration, and (2) educate faculty researchers regarding the benefits ofintegrating data visualization into the systematic
Further examples can be found in the literature6,7. It is clear that each sub-convolution can beseparately processed, followed by a reconstruction stage to provide the final result. Parallelalgorithms can be developed by factorization of the Block Pseudocirculant matrix shown in (9),(12) and (13) into diagonal blocks. The general tensor product formulation for a block diagonalfactorization of the Block Pseudocirculant Matrix is6, y r = R r0 (A r0 ⊗ I N/r )D H (B r0 ⊗ I N/r )x r0 (15) 0 0 r0 0where xr0 and yr0 are the decimated-by-r0 input and output sequences and Ar0 and Br0 are thepost/pre-processing matrices, which are determined by each
]. It can also be used in Python scripts, web applications servers, or in combination with several GUI toolkits. 5. Example Compared with NumPy there is a colossal list of things one can do with SciPy. The following listing is what we use SciPy for in this instance. import numpy as np from scipy.fftpack import fft import matplotlib.pyplot as plt N = 600 T = 1.0/800.0 x = np.linspace(0.0, N*T,N) a = np.sin(50.0 * 2.0*np.pi*x) b = 0.5*np.sin(80.0 * 2.0*np.pi*x) y = a + b yf = fft(y) Y = 2.0/N * np.abs(yf[0:N/2]) X = np.linspace(0.0, 1.0/(2.0*T), N/2) import matplotlib.pyplot as plt plt.plot(x,y
Stolk, and L. Vanasupa. Collaborative Design of Project-Based Learning Courses:How to Implement a Mode of Learning That Effectively Builds Skills for the Global Engineer. in Proceedings of theAmerican Society for Engineering Education Annual Conference. 2007. Honolulu, HI.8. Sheppard, S.D. and R. Jenison. Thoughts on freshman engineering design experiences. in Frontiers in EducationConference, 1996. FIE '96. 26th Annual Conference., Proceedings of. 1996.9. Brown, B. and B. Brown. Problem-based education (PROBE): learning for a lifetime of change. in Proceedingsof the 1997 ASEE Annual Conference and Exposition. 1997. Milwaukee, WI.10. Rubino, F.J. Project based freshman introduction to engineering technology courses. in Proceedings of the
. S. Gero, "Design prototypes: a knowledge representation schema for design," AI Mag., vol. 11, pp. 26-36, 1990.23 A. K. Goel and B. Chandrasekaran, "Functional representation of designs and redesign problem solving," presented at the Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2, Detroit, Michigan, 1989.24 A. K. Goel, et al., "Structure, behavior, and function of complex systems: The structure, behavior, and function modeling language," Artificial Intelligence for Engineering Design, Analysis and Manufacturing, vol. 23, pp. 23-35, December 2008 2009
watching the video.) (a) Describe two recent “amazing” applications of Deep Learning presented by Jeremy Howard. (b) Describe the key differences between Machine Learning and Deep Learning. (c) According to Jeremy Howard, what impact will Deep Learning have on society in the future. • JupyterHub: A free package that makes it possible for students to seamlessly run Jupyter notebooks on a centralized server from within their browser. (The author was not able to get this package properly installed in time for the course.)References [1] Kangbeom Cheon, Jaehoon Kim, Moussa Hamadache, and Dongik Lee. On replacing pid controller with deep learning controller for dc motor system. Journal of Automation and Control
its ability to: (a) collect detailed information from facultyregarding the projects they are offering, (b) present the projects to the students in a media-richand sortable format, and (c) solicit student preferences and accurately record project preferences.As a result, majority of the tasks that were managed by each engineering discipline wereeliminated and replaced by an automated process that ensured accuracy and consolidated pastmultiple data streams. It is envisioned, the current platform will necessitate limited interventionfrom faculty to yield a fair and satisfactory college-wide assignment output; preferably entirelyeliminating the need for discipline-managers. In the past, discipline-managers devotedsubstantial effort towards the
the performance to be better than if Turtlebot was relying solely on the map. Thereare 3 main problems that were observed when driving Turtlebot on this robot-made map. Themaps shown in Figures 1.4a,b were previously edited in Gimp as explained earlier. Any missinggaps were filled in and small sections of the map were stitched together to create a master robot-made map. Figures 1.4 a,b Highlighting problems encountered in the robot-made mapping method The first problem encountered in this map was the stitching process. Figure 1.4a shows 2of the problems highlighted in the yellow and red boxes. The yellow box shows that the hallwayhas almost doubled in width, which occurred when Turtlebot shifted its map’s coordinate systemduring
Influencing the Choice of Hearing Aid Type. CIKM '11 International Conference on Information and Knowledge Management, pp. 11-17, Association for Computing Machinery, New York, 2011. 2. Koh, H. C., & Tan, G., Data Mining Applications in Healthcare. Journal of Healthcare Information Management, pp. 64-72, http://www.himss.org, 2005. 3. Park, I., Lee, K. H., & Lee, D. Mining Cancer Genes with Running Sum Statistics. CIKM '09 Conference on Information and Knowledge Management , pp. 35-42, Association for Computing Machinery, New York, 2009. 4. Srinivas, K., Kavihta Rani, B., & Govrdhan, A., Applications of Data Mining Techniques in Healthcare and Prediction of Heart Attacks. International
effective risk mitigation is possible. We have discussed severalapproaches to systems defense based on a combination of policy, technology and training 18 andspecified simple, yet effective strategies to disable currently known malware payload attacks,propagation and delivery vectors.References1. Dwan B. The Computer Virus — From There to Here. Computer Fraud & Security. 2000 [accessed 2014 Dec1];2000(12):13–16. http://www.sciencedirect.com/science/article/pii/S13613723001202632. Verizon. 2014 DATA BREACH. USA; 2014.3. McAfee. Net Losses : Estimating the Global Cost of Cybercrime. USA; 2014.4. ThreatScape. KAPTOXA Point-of-Sale Compromise. USA; 2014.5. Huq N. PoS RAM Scraper Malware - Past, Present, and Future. USA; 2014.6. HackSurfer. Special
of the Thirty-second SIGCSE Technical Symposium on Computer Science Education, SIGCSE ’01, pages 36–40, 2001. ISBN 1-58113-329-4.15 Steven P Miller, B Clifford Neuman, Jeffrey I Schiller, and Jermoe H Saltzer. Kerberos authentication and authorization system. In In Project Athena Technical Plan. Citeseer, 1987.16 Vennila Ramalingam and Susan Wiedenbeck. Development and validation of scores on a computer programming self-efficacy scale and group analyses of novice programmer self-efficacy. Journal of Educational Computing Research, 19(4):367–381, 1998.17 Dale C. Rowe, Barry M. Lunt, and Joseph J. Ekstrom. The role of cyber-security in information technology education. In Proceedings of the 2011 Conference on Information Technology
. V. Oorschot, and S. A. Vanstone, Handbook of Applied Cryptography, CRC Press, 1996.11. D. B. Nasr, H. M. Bahig, and S. S. Daoud, Visualizing Secure Hash Algorithm (SHA-1) on the Web, Proceedings of the 7th International Conference on Active Media Technology, pages 101-112. 2011.12. A. Salomaa, Public-Key Cryptography, Springer-Verlag, 1992.13. Schneier, Applied Cryptography: Protocols, Algorithms, and Source Code in C, John Wiley, 1995.14. D. Schweitzer and L. Baird, The Design and Use of Interactive Visualization Applets for Teaching Ciphers, IEEE Information Assurance Workshop, pages 69-75, 2006.15. J. Tao, J. Ma, M. Keranen, J. Mayo, and C.-K. Shene, DESvisual: A Visualization Tool for the DES Cipher, Journal of Computing
Paper ID #9482Cloud Computing: Is it a way to go for academia?Prof. Mudasser Fraz Wyne, National University I have a Ph.D. in Computer Science, M.Sc. in Engineering, and B.Sc. in Electrical Engineering. In my capacity as Chair of the Department of Computer Science, Information and Media Systems at the Na- tional University of San Diego, I administer 4 graduate and 4 undergraduate programs. Furthermore, I manage 7 specializations, 2 certification programs, as well as the teaching and scholarship of 14 full-time faculty members (7 Full Professors, 4 Associate Professors, and 3 Assistant Professors) and more than 115