• Hash Functions • Symmetric and Asymmetric Key • Quantum-Safe Cryptography Quantum Information • Density Matrices • Bloch Sphere • Multiple Systems and Reduced StatesIBM • Build your Ciruits Weeks 3 , 5 Hands-on PracticesQuantum • Apply your Gates &6Composer https://quantum.ibm.com/composer • Analyze Q-SphereandSimulatorIBM Labs • Jupyter Lab Weeks 3 - 7 Hands-on Practices • Matplotlib
.[14] L. Porter, D. Bouvier, Q. Cutts, S. Grissom, C. Lee, R. McCartney, D. Zingaro and B. Simon, “ A multi-institutional study of peer instruction in introductory computing.”, in Proceedings of the 47th ACM Technical Symposium on Computing Science Education, Feb. 2016, pp. 358-363.[15] L. Porter, C.B. Lee, B. Simon, Q. Cutts, and D. Zingaro, D., “Experience report: a multi- classroom report on the value of peer instruction.”, in Proceedings of the 16th annual joint conference on Innovation and technology in computer science education, Jun. 2011, pp. 138-142.[16] L. Porter, C.B. Lee, B. Simon, and D. Zingaro, D., “Peer instruction: Do students really learn from peer discussion in computing?.”, in Proceedings of the
will typically increasethe pass rate of a course. This course is also one of the first programming classes taken by transferstudents which may contribute to the high DFW rate. Future work will include a comparison ofthe DFW rates between historic offerings and those that have made use of Plickers.In conclusion using Plickers in class is a positive experience for both the instructor and the stu-dents. Since each class has a clear structure of: Plicker question, lecture, break, Plicker question,lecture/activity, quiz, students are never doing any one task for very long. This aids in keepingstudents engaged and on task.References [1] L. Porter, D. Bouvier, Q. Cutts, S. Grissom, C. Lee, R. McCartney, D. Zingaro, and B. Simon, “A Multi
tivity1 Perception Supervised Learning Interactive exercises, hands-on drone model development activity Conversational AI Programming social robot, dialogue NLP, intent recognition flow training Bias and Ethical Implications Case studies, small group discussions Bias in ML, ethical principles Reinforcement Learning Interactive robot activity, Q-learning in- Robot behavior, path following Machine troduction2 Behavior Deep Reinforcement Learning Hands-on drone
knowledge by integratingtechnological tools with pedagogical strategies. Flipped learning (FL) reverses traditionalteaching methods by providing course materials on datapath design beforehand, fostering active,self-directed learning in the classroom. The pedagogy is enriched with structured practiceexercises, enhancing students’ understanding of datapath design, along with theirproblem-solving, analytical, and critical thinking skills. The effectiveness of this method isvalidated through various assessments, including homework, exams, Q&A sessions, and studentfeedback, with a positive comparison to the instructor’s previous teaching experiences. Thisholistic evaluation confirms the efficacy of this innovative approach in improving the
operatewith high coordination and efficiency, leading to increased emotional stability and resilience to stress. The integrationof these diverse HRV measures offers a robust tool for monitoring cardiac health, stress levels, and autonomicfunction [16]. HRV Metric Formula Heart Rate Pulse({IBIi }) = 1 PN60 N i=1 IBIi q PN 1 SDNN SDNN({IBIi }) = N −1 i=1 (IBIi − IBI)2
career"?: In thisdiversity, Q&A session, mentees were encouraged to ask questions about computing careerequity, and pathways, including the available career opportunities, skillsets required, internshipinclusion in tips, and other related topics. Mentors shared their experience and their opinions oncomputing these topics. (Focus: objective v)iii) develop Mentoring Session 3 - Develop strategies to overcome barriers to reach goals: This wasstrategies to a Q&A session as well where mentees were able to ask questions related to theirbe successful perceived obstacles in computing careers, such as low sense of belonging & self-in computing efficacy, preparedness, academic struggle including
, G. L. Ramalho, and T. P. Falcão, "A systematic literature review on teaching and learning introductory programming in higher education," IEEE Transactions on Education, vol. 62, no. 2, pp. 77-90, May 2019, doi: 10.1109/te.2018.2864133[26] E. Gamma, R. Helm, R. Johnson, and J. Vlissides, Design patterns: elements of reusable object-oriented software. Boston: Addison-Wesley, 1994.[27] S. B. Merriam and E. J. Tisdell, Qualitative research: A guide to design and implementation, 4th ed. San Francisco, Ca: Jossey-Bass, 2016.[28] M. Q. Patton, Qualitative research & evaluation methods: Integrating theory and practice. Sage publications, 2014.
Q&As, 5-minute group discussions, and activitiesspanning most of the class duration. The pop-quiz style questions were included to make sure thatthe instructor was not speaking for more than 10 minutes without giving the students anopportunity to check their knowledge. Some of the questions were prepared in advance, but mostquestions were posed based on students’ perceived level of confusion when topics were presentedto them. Since computer networks use clearly defined protocols and algorithms, discussionsshould be used as tools to understand the design considerations or to solve practiceproblems.The main considerations of the author for designing full-class activities for a traditionallylecture-style course with a broad range of topics
in Engineering Education, 2014. 22(2): p. 283-296.28. Caminero, A., et al. Obtaining university practical competences in engineering by means of virtualization and cloud computing technologies. in Proceedings of 2013 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE). 2013. IEEE.29. Wang, Y., M. McCoey, and Q. Hu. Developing an undergraduate course curriculum for ethical hacking. in Proceedings of the 21st Annual Conference on Information Technology Education. 2020.30. Al Kaabi, S., et al. Virtualization based ethical educational platform for hands-on lab activities on DoS attacks. in 2016 IEEE Global Engineering Education Conference (EDUCON). 2016. IEEE.31. Willems
usefulness, UI design, technical soundness, and presentation quality including the Q&A session. Notably, the external evaluators were unaware of the feedback exploration approach used. 4. ChatGPT Feedback: For some of the checkpoints, we provided students with the pre-designed prompts. They were encouraged to use these prompts, to seek feedback from ChatGPT on their projects. These prompts were tailored to the specific requirements of each checkpoint, which enabled ChatGPT to offer both comprehensive and detailed feedback.Fig. 1 presents the detailed steps involved in the process of retaining valuable knowledgeobtained from various sources throughout the course duration to build a more specializedgenerative feedback
beoverwritten with this address.Type gdb mainType disassemble arbitrary_codeWhat is the address in memory of the first line of the arbitrary_code function?Type q to exit the debuggerTask 5 - Run main from command line, overflow the bufferNow we're back at the command line.Run the main executable../mainProvide input that is 20 characters. What happens?Provide a screen shot with your name somewhere in the screen shot, the command to run main,and the result.Task 6 - Run main from command line, craft input to main to execute arbitrary_code functionWe're going to have the program jump to our arbitrary code function.Type echo 0 > /proc/sys/kernel/randomize_va_spaceThis command turns off ASLR. Research this and describe what it is and why we need to do
International Conference on Systems Engineering, ICSEng 2020, pp. 223–233, Springer, 2021.[13] T. Inaoka, H. Shintaku, T. Nakagawa, S. Kawano, H. Ogita, T. Sakamoto, S. Hamanishi, H. Wada, and J. Ito, “Piezoelectric materials mimic the function of the cochlear sensory epithelium,” Proceedings of the National Academy of Sciences, vol. 108, no. 45, pp. 18390–18395, 2011.[14] Autodesk, “Tinkercad.” https://www.tinkercad.com/dashboard, Accessed January 2023.[15] A. H. Kioumars and L. Tang, “Wireless network for health monitoring: heart rate and temperature sensor,” in 2011 Fifth International Conference on Sensing Technology, pp. 362–369, IEEE, 2011.[16] H. Mansor, M. H. A. Shukor, S. S. Meskam, N. Q. A. M. Rusli, and N. S. Zamery
, 2020.[8] E. Sugiharti, S. Firmansyah and F. R. Devi, "Predictive evaluation of performance ofcomputer science students of unnes using data mining based on naÏve bayes classifier (NBC)algorithm". Journal of Theoretical and Applied Information Technology, 95, 4 (2017), 902.[9] S. Li and T. Liu, "Performance prediction for higher education students using deep learning.Complexity", 2021 (2021), 1-10.[10] K. Chai and D. Gibson, "Predicting the Risk of Attrition for Undergraduate Students withTime Based Modelling", International Association for Development of the Information Society(2015).[11] X. Wang, X. Yu, L. Guo, F. Liu and L. Xu, "Student performance prediction with short-termsequential campus behaviors", Information, 11, 4 (2020), 201.[12] Q
: 10.1145/3286960.3286970.[11] B. Zhong and Q. Si, “Troubleshooting to learn via scaffolds: Effect on students’ ability and cognitive load in a robotics course,” Journal of Educational Computing Research, vol. 59, no. 1, pp. 95–118, 2021, doi: 10.1177/0735633120951871.[12] L. Zheng, Y. Zhen, J. Niu, and L. Zhong, “An exploratory study on fade-in versus fade-out scaffolding for novice programmers in online collaborative programming settings,” J Comput High Educ, vol. 34, no. 2, pp. 489–516, Aug. 2022, doi: 10.1007/s12528-021-09307-w.[13] M. Ahmadzadeh, D. Elliman, and C. Higgins, “The impact of improving debugging skill on programming ability,” Innovation in Teaching and Learning in Information and Computer
with anoverview of research presentations before the actual presentation. Because of the elevatorpitches, the audience could post queries and comments before the event. When the researchvideos were shown, the Q&A session was altered to a discussion session where the teams maymore casually go through aspects of the research that weren't included in the formal presentationand respond to any questions that had been pre-posted [11].This material is based upon work supported by the National Science Foundation under GrantNo. 1849454.Project Summaries2019 Projects:IoT Device Security Assessment using Side Channel Analysis (Morgan State University)This study entails looking into IoT device flaws that allow information to leak through sidechannels
. ACM, New York, NY,USA 13 Pages. https://doi.org/10.1145/3446871.3469748 [3] A. Okrent and A. Burke. The STEM Labor Force of Today: Scientists, Engineers, and Skilled TechnicalWorkers. National Science Foundation and National Science Board, Science & Engineering Indicators. August2021. https://ncses.nsf.gov/pubs/nsb20212/participation-of-demographic-groups-in-stem. Accessed 11.16.2022.[4] U.S Bureau of Labor Statistics, U.S. Labor, Occupational Outlook Handbook, Information Security Analysts.Available: https://www.bls.gov/ooh/computer-and-information-technology/information-security-analysts.htm#tab-6.Accessed 02/26/2023.][5] Cybersecurity Supply and Demand Heat Map. cyberseek.org.https://www.google.com/url?q=https://www.cyberseek.org