integrate LESs into F2F and online class activities, and evaluate which combina-tion(s) of LESs can be most effective on improving student learning.3 Pedagogical Approach using LESsIn this section we present our proposed LES integration model (LESIM), a brief overview of SEP-CyLE, and a description of how LESs are integrated into the F2F and online activities of a softwaretesting class. Preliminary results obtained by comparing the midterm exam scores prior to usingLESs and while using LESs in the classroom are also presented.3.1 LES Integration Model (LESIM)Conceptually LESIM is used to improve student learning based on the model shown in Figure1. The top of the figure shows the pedagogical approaches (LESs and traditional approach) thatare
. I. I NTRODUCTIONHigh Performance Computing (HPC) stands at the forefront of engineering innovation [1, 2].With affordable and advanced HPC resources more readily accessible than ever before,computational simulation of complex physical phenomena is an increasingly attractive strategyto predict the physical behavior of diverse engineered systems [2], such as systems in nuclearsafety [3], outcome of cancer treatment [4], or multidimensional flight stresses on aircraft. Tomaintain the U.S.’s leadership position in HPC production and application [2], and to meet theneeds of the rapidly growing HPC market [5], American institutions of higher education mustproduce a sufficient supply of highly-trained HPC professionals. Sadly, at current rates
automatic alerts that are integrated with the visualizations.References:[1] Z. T. Siti Khadijah Mohamada, "Educational data mining: A review," in The 9th InternationalConference on Cognitive Science, Malaysia, 2013.[2] R. S. Baker, "Data Mining for Education," in International Encyclopedia of Education (3rdedition), Oxford, 2012.[3] C. G. Merrett, "Using Textbook Readings, YouTube Videos, and Case Studies for FlippedClassroom Instruction of Engineering Design," in Proc. 2015 Canadian Engineering EducationAssociation (CEEA15) Conf., Canada, 2015.[4] D. N. A. G. M. S. Kenneth A. Connor, "Faculty Development and Patterns of StudentGrouping in Flipped Classrooms Enabled by Personal Instrumentation," in 2017 ASEE AnnualConference & Exposition
Characteristics of World-Wide- Web Client Proxy Caches. USENIX Symposium on IT and Systems. Vol. 997. 1997.4. Murlimanohar N, Balasubramonium R, Jouppi N.P. CACTI 6.0: A Tool to Model Large Caches. HP Laboratories, 20095. Todd Austin, SimpleScalar LLC, www.simplescalar.com6. S. Przybylski, M. Horowitz, J. Hennessey. Characteristics of performance-optimal multi-level cache hierarchies. ACM SIGARCH Computer Architecture news, June, 19897. Conte T.M., Hirsch M.A., Hwu W. Combining Trace Sampling with Single Pass Methods for Efficient Cache Simulation. In: IEEE Transactions on Computers, 19988. Sugumar R, Abraham S. Set Associative Cache Simulation Using Generalized Binomial Trees. In: ACM Transaction on Computer Systems, 2005.9
classroom activities.AcknowledgementThe author is grateful for the help of undergraduate teaching assistants in the course sectionsunder study in this paper: Max Anderson, John Biggs, Zachery Eldemire, and Megan Moore.BibliographyCrouch, C. H., Watkins, J., Fagen, A. P., & Mazur, E. (2007). Peer instruction: Engaging students one-on-one, all at once. Research-based reform of university physics, 1(1), 40-95.Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 111(23), 8410-8415.Garcia, S. (2018). Improving classroom preparedness using guided
be close to initial expectations and the game was able to be played at a distancesuitable for a fun experience. This project was a success and student commented “I made anembedded systems laser tag system for my senior design project. I was able to apply what Ilearned in my engineering courses to achieve my design goals. I was able to combine suchsubjects as digital design, embedded systems, electronic systems, digital signals processing, andphysics. I also honed practical skills like soldering, putting together breadboards andprogramming in C. My professor helped me maintain a disciplined schedule to make sure Istarted early on prototypes so my final design would meet my goals”.This project was funded by NSF S-STEM Scholarship program at
/ap_21_cyber_security-fy2019.pdf4. Formal Education, The National Initiative For Cybersecurity Careers and Studies (NICCS). Retrieved from: https://niccs.us-cert.gov/formal-education#5. W. Hotalen and T. S. Chou, “A Multiplayer Peer-to-Peer Cyber Attack and Defense Infrastructure,” American Society for Engineering Education (ASEE) Annual Conference and Exposition, Salt Lake City, Utah, June 2018.6. T. S. Chou, “Labs and Three-Stage Learning Process for a Cyber Security Learning System,” International Conference on Engineering, Science and Technology (IConEST), Denver, CO, October 2019.7. N. Hempenius, Te-Shun Chou, and Lee Toderick, “Automatic Collection of Scoring Metrics in Competitive Cybersecurity Lab Environments,” The Conference
documentation. Thestudents’ feedback and their final project presentation indicate that they have pride in theirproject accomplishments and have gained confidence in their engineering abilities.References 1. Akyildiz, Ian and Mehmet Can Vuran, “Wireless Sensor Networks”, Wiley, 2010. 2. Li, Yingshu, My Thai, and Weili Wu, “Wireless Sensor Networks and Applications”, Springer, 2008. 3. Dargie, Waltenegus, and Christian Poellabauer, “Fundamentals of Wireless Sensor Networks: Theory and Practice”, Wiley, 2010. 4. Minaie, Afsaneh, et al., “Integration of Wireless Sensor Networks in the Computer Science and Engineering Curricula”, Proceedings of the ASEE Annual Conference, June 2012. 5. M. Assaf, R. Mootoo, S. Das, E. Petriu, V
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robots that are programmable in the sameprogramming language used in the class. Affordability and low maintenance costs are alsoimportant factors to long term sustainability of these activities.Our initial experience with robotics in programming classes indicate that most students enjoyrobotics and they become more motivated to learn programming. We are pleased with theoutcome and will continue using robotic activities in our introductory programming classes.References 1. Bennedsen, J. and Caspersen, M.E.” Failure rates in introductory programming.” SIGCSE Bull. 39, 2 (2007), 32–36 2. Jennifer S. Kay, “Robots in the classroom...and the dorm room,” Journal of Computing Sciences in Colleges, vol. 25, Issue. 3, Jan. 2010, pp
Paper ID #27348How to Cultivate Computational Thinking-Enabled Engineers: A Case Studyon the Robotics Class of Zhejiang UniversityDr. Jingshan Wu, Zhejiang University Postdoctoral Fellow of Institute of China’s Science, Technology and Education Strategy, Zhejiang Uni- versity; Lecturer, School of Public Administration, Zhejiang University of Finance & EconomicsMs. Yujie Wang, Zhejiang University Postgraduate of Institute of China’s Science,Technology and Education Strate, Zhejiang UniversityMs. Hanbing Kong, Zhejiang University Hanbing Kong, PhD Deputy Director, the Research Center for S&T, Education Policy, and Associate
- anguished-outraged/Hayajneh, T., Denis, M., & Zena, C. (2016). Penetration testing: Concepts, attack methods, and defense strategies. 2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT), (pp. 1-6).McGettrick, A. (2013). Toward Effective Cybersecurity Education. IEEE Security Privacy, 66- 68.Microsoft Corporation. (2014). Support for Windows XP ended. Retrieved from https://www.microsoft.com/en-us/windowsforbusiness/end-of-xp-supportMicrosoft Security Bulletins. (n.d.). Retrieved from https://docs.microsoft.com/en- us/security-updates/Mirkovic, J., Benzel, T. V., Faber, T., Braden, R., Wroclawski, J. T., & Schwab, S. (2010). The DETER project: Advancing the science of cyber
data for the REETsenior project was analyzed. Several recommendations for improving student’s outcomes aresuggested.References1. Alternative Energy Systems and Applications, by B. K. Hodge, 2010, John Wily & Sons, Inc.2. Electric Machinery Fundamentals, 5th, S. Chapman, 2011 McGraw-Hill3. Power Electronics: Principles & Applications, Jacob, J. Michael, 20024. Renewable Energy - Sustainable Energy Concepts for the Future, engenmayr, Roland andBührke, Thomas, Eds., 2008.0 Verlag GmbH and Co. KGaA., Weinheim, Germany5. Alternative Energy Systems in Building Design Gevorkian, P. (2010), New York: McGraw-Hill.6. Techniques for a Wind Energy System Integration with an Islanded Microgrid Goyal, M., Fan,Y., Ghosh, A., & Shahnia, F. (2016
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in the process. (3) Hands-on activitiesneed careful preparation and close guidance.1 IntroductionThe wireless telecommunication industry has grown tremendously since the first cellular systemwas deployed in 1983. Digital techniques were introduced in 1993 to accommodate the hugeboom in subscribers of portable telephone service in the mid 90’s. Cellular communicationssystems evolved from providing voice in the mid 90’s (2nd generation or 2G) to all-IP dataservices that are available since 2011 (4G). Advanced mobile broadband and real-time controlwill be enabled by future 5G systems. Wireless systems that provide personal andmachine-to-machine communications currently constitute a major research area of vitalimportance.Telecommunication
detection. In addition, a study on the trends of curiositylevels across the different lab’s QFT data may yield insight into whether students are improvingin their critical thinking skills and developing more curiosity in exploring a provocative orchallenging statement. We also plan to continue work with studying curiosity detection withother learners, other data mining schemes, investigating linguistic text mining methods, andother QFT or question-based datasets.References[1] D. L. Schwartz, J. M. Tsang, and K. P. Blair. The ABC’s of How We Learn: 26 Scientifically Proven Approaches, How They Work, and When to Use Them. W. W. Norton & Company, Inc., New York, NY, 2016.[2] M. J. Kang, M. Hsu, I. M. Krajbich, G. Loewenstein, S. M. McClure
examine these changes on student performance as well, and a morein-depth analysis with an automated tool needs to be conducted on how student code quality isimpacted. Also, future studies could look at developing methods to better enforce code qualityand good style practices in short exercises. In addition, future studies should confirm the Bloom’sTaxonomy level of CS exercises before their use, and perhaps they should even aim to work withother instructors to create a bank of CS exercises and come to a consensus on how to map CStopics to BT.References [1] S. Zweben and B. Bizot. The taulbee survey. Computing Research Association, 2018. URL https://cra.org/resources/taulbee-survey/. [2] Vincenzo Del Fatto, Gabriella Dodero, Rosella Gennari
expected by chance” [2, para. 1]. The second test was Kendall’s tau to show correlations between organizational successand implementation of a defined process model. Kendall’s tau is a measure of rank correlation.“Kendall-tau is a non-parametric correlation coefficient used to assess and test correlationsbetween non-intervals scaled ordinal variables. Frequently, researchers use the Greek letter τ(tau) to abbreviate the Kendall tau correlation coefficient” [5, p. 14]. Rank correlation is aninteresting method to assess and evaluate the data collection [22]. Kendall’s tau is well knownand broadly used to measure the degree of the relationship between variable [22].References1. Aasheim, C. L., Lixin, I., & Williams, S. (2009). Knowledge
Data Scientist’s Skill-Set(s)Once the talent gap in the area of data science & analytics has been identified, and many expertpredictions about the near-to-intermediate future about the continued growth in demand for therelated skills, and once the institutions of higher education in the US (as well as many globally)have taken a notice, the next question is: what are the actual, concrete key skills and knowledgethat the next-generation data scientists and analysts should have, in order to fill that gap mosteffectively? This, too, turns out to be a multi-faceted, complex question.We will briefly summarize below our own experience, stemming cf. from i) working as aSenior/Principal Data Scientist in industry (cf. high-tech/Silicon Valley) and
2007. 5. Minaie, Afsaneh, et.al., Nanotechnology in Engineering Education”, 2015 American Society for Engineering Education Annual Conference, June 2015. 6. “What is Nanotechnology?,” What is Nanotechnology? | Nano. [Online]. Available: https://www.nano.gov/nanotech-101/what/definition. [Accessed: 28-Jan-2018]. 7. P. Dockrill, “Scientists Just Developed The World's Smallest Transistor,” ScienceAlert, 07 Oct-2016. [Online]. Available: https://www.sciencealert.com/scientists-just- developed-the-world-s-smallest-ever-transistor. [Accessed: 28-Jan-2018]. 8. “VEGA3,” Tescan. [Online]. Available: https://www.tescan.com/en- us/technology/sem/vega3. [Accessed: 27-Jan-2018]. 9. M. J. Madou, Fundamentals of
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students (S-STEM), Researcher Practitioner Partnership (RPP), IUSE, and EAGER.Alexandria Benedict, University of North Carolina at Charlotte Alexandria Benedict is a graduate student at the University of North Carolina at Charlotte pursuing her Master’s in Computer Science. She is a research assistant under the RPP STEM Ecosystem Project which helps study the effects of computational thinking inside classrooms.Audrey RorrerDr. David K. Pugalee, University of North Carolina at Charlotte Dr. David Pugalee is a full professor, and Director of the Center for Science, Technology, Engineering, and Mathematics Education (STEM) at UNC Charlotte. The recipient of millions of dollars in grant- funding, Dr. Pugalee has also
80 96 120 digital circuits Others 128 64 144 48 40 390As can be seen, the science and engineering course requirements vary much more across schools,compared to the requirement of computer science courses and math courses. All schools exceptBUAA require a digital logic (or analog and digital circuits) course. It is possible that BUAA hasthe digital logic component in other courses. Overall, these schools require physics course(s) asthe science requirement. No schools require other areas of sciences such as chemistry, biology,or any other natural science courses.7. Social sciences, humanity, and arts requirementIn this section, we examine the non
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specialization areas.Database Engineering is a viable component of Software Engineering. In our UndergraduateComputer Science Degree, there is only one database course where Relational, ObjectRelational, Object-Oriented and Distributed Databases will be covered. Since the mission of thisUniversity is to graduate students with high quality education prepared for the competitive jobmarket, as part of this course work, students work on a set of assignments and implementone/two database(s) of their choice in teams. The contents represented in this paper is anexample of an assignment that student need to do in this course.Entity Relationship for University DatabaseThe following diagram (Figure 1) represents a simplified entity relationship for course
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