Paper ID #26401How an NSF S-STEM LEAP Scholarship Program Can Inform a New Engi-neering ProgramDr. Afsaneh Minaie, Utah Valley University Afsaneh Minaie is a Professor and Chair of Engineering Department at Utah Valley University. She re- ceived her B.S., M.S., and Ph.D. all in Electrical Engineering from University of Oklahoma. Her research interests include gender issues in the academic sciences and engineering fields, Embedded Systems De- sign, Mobile Computing, Wireless Sensor Networks, Nanotechnology, Data Mining and Databases.Dr. Reza Sanati-Mehrizy, Utah Valley University Reza Sanati-Mehrizy is a professor of
Paper ID #33301Positive Impact of an S-STEM Scholarship Program on Computer ScienceStudents’ Academic Performance and Retention RateDr. Zhijiang Dong, Middle Tennessee State University Dr. Zhijiang Dong is a Professor in the Department of Computer Science at Middle Tennessee State University. His research areas are in the fields of formal methods, system verification and validation, and computer science education. He received his BS in Mathematics from Huazhong University of Science and Technology at China, and his PhD in Computer Science from Florida International University.Dr. Joshua Lee Phillips, Middle Tennessee State
Paper ID #32306Cracks in the Foundation: Issues with Diversity and the Hiring Processin Computing FieldsStephanie J. Lunn, Florida International University Stephanie Lunn is presently a Ph.D. candidate in the School of Computing and Information Sciences at Florida International University (FIU). Her research interests span the fields of Computing and Engineer- ing Education, Human Computer Interaction, Data Science, and Machine Learning. Previously, Stephanie received her B.S. and M.S. degrees in Neuroscience from the University of Miami, in addition to B.S. and M.S. degrees in Computer Science from FIU.Dr. Monique S
founding chair of the Student Division, a Program Chair and a Director for the Educational Research and Methods Division, and the General Chair of the First-Year Division’s First-Year Engineering Experience Conference.Prof. Richard S. Stansbury, Embry-Riddle Aeronautical University Dr. Richard S. Stansbury is an associate professor of computer engineering and computer science at Embry-Riddle Aeronautical University in Daytona Beach, FL. His research interests include unmanned aircraft integration, machine learning, and aviation big data analytics. He is the ERAU lead for the FAA Center of Excellence for Unmanned Aircraft Systems, ASSURE.Dr. Mustafa Ilhan Akbas, Embry-Riddle Aeronautical University M. Ilhan Akbas is an
and Policy Analysis, Educational Policy, Journal of Student Affairs Research and Practice, and Teachers College Record.Prof. David S. Knight, University of Washington David S. Knight is an assistant professor at the University of Washington. His research examines educator labor markets, school finance, and cost-effectiveness analysis. He received his PhD in urban education policy and MA in economics from the University of Southern California and bachelor’s degrees in eco- nomics and anthropology from the University of Kansas. American c Society for Engineering Education, 2020 The CAHSI INCLUDES Alliance: Realizing Collective ImpactAbstractTo
from FIU.Dr. Monique S. Ross, Florida International University Monique Ross, Assistant Professor in the School of Computing and Information Sciences and STEM Transformation Institute at Florida International University, designs research focused on broadening par- ticipation in computer science through the exploration of: 1) race, gender, and disciplinary identity; 2) discipline-based education research (with a focus on computer science and computer engineering courses) in order to inform pedagogical practices that garner interest and retain women (specifically Black and His- panic women) in computer-related engineering fields.Prof. Zahra Hazari, Florida International University Zahra Hazari is an Associate Professor
Paper ID #22803RTTD-ID: Tracked Captions with Multiple Speakers for Deaf StudentsDr. Raja S. Kushalnagar, Gallaudet University Raja Kushalnagar is the Director of the Information Technology program in the Department of Science, Technology and Mathematics at Gallaudet University in Washington, DC. His research interests encom- pass the fields of accessible computing and accessibility/intellectual property law, with the goal of improv- ing information access for deaf and hard of hearing (deaf) individuals. In the accessible computing field, he investigates information access disparities between hearing and deaf. For
conferences in robotics, software engineering, and computer science education. He has garnered multiple international awards in innovation including the third place in Robocup world competition.Dr. Monique S. Ross, Florida International University Monique Ross, Assistant Professor in the School of Computing Information Sciences and STEM Trans- formation Institute. Dr. Ross earned a doctoral degree in Engineering Education from Purdue University. She has a Bachelor’s degree in Computer Engineering from Elizabethtown College, a Master’s degree in Computer Science and Software Engineering from Auburn University, eleven years of experience in in- dustry as a software engineer, and six years as a full-time faculty in the
underrepresentedgroups, particularly for women, Black students, and Hispanic students.AcknowledgementsThe authors would like to thank the instructors of these courses for their cooperation and supportof this study. We would also like to thank the 41 teaching assistants and section leaders whohelped distribute materials and did all the video showings. Lastly, we would like to thank thestudents who were enrolled in the course and participated in the study. There were many richdiscussions about the topics in these videos that cannot be captured by data or summarized in apaper.ReferencesBeilock, S. L. (2008). Math performance in stressful situations. Current directions in psychological science, 17(5), 339-343.Beilock, S. L., & Willingham, D. T. (2014
Center for Science and Engineering Statistics, “Women, minorities, and persons with disabilities in science and engineering: 2019,” https://ncses.nsf.gov/pubs/nsf19304/data, 2019, accessed: 2021-5-24. [4] H. S. Al-Khalifa, H. R. Faisal, and G. N. Al-Gumaei, “Teaching mobile application development in 20 hours for high school girls: A web-based approach,” in 2019 IEEE Global Engineering Education Conference (EDUCON), 2019, pp. 16–21. [5] Y. Chen, Z. Chen, S. Gumidyala, A. Koures, S. Lee, J. Msekela, H. Remash, N. Schoenle, S. Dahlby Albright, and S. A. Rebelsky, “A middle-school code camp emphasizing digital humanities,” in Proceedings of the 50th ACM Technical Symposium on Computer Science Education, ser. SIGCSE ’19. New York
IPv6, the Internet’s migration to the new protocol has beenanything but smooth. Many have expressed doubts, and some still do, that IPv6 will reach fulladoption and replace IPv4 as the Internet’s dominant protocol. However, empirical data suggeststhat Internet IPv6 adoption has entered a phase of rapid acceleration [3]. A recent study by [4]found that the number of IPv6 users on the Internet has reached the early majority level ofadoption and full adoption could occur as early as December 2024. Figure 1 shows the numberof users accessing Google over IPv6 reached 26.31% in January of 2019 [5].Figure 1. The adopter distribution normal curve partitioned into adopter categories overlaid withthe S-shaped diffusion curve [6]. The number of IPv6
Paper ID #22725Work in Progress: Designing Laboratory Work for a Novel Embedded AICourseDr. Mehmet Ergezer, Wentworth Institute of Technology Mehmet Ergezer (S’06) received the B.S. and M.S. degrees in electrical and computer engineering from Youngstown State University, Youngstown, OH, USA, in 2003 and 2006, respectively. He received the D.Eng. degree in artificial intelligence from the Department of Electrical and Computer Engineering, Cleveland State University, Cleveland, OH, USA, in May 2014. From 2003 to 2005, following his internship with U.S. Steel, he was a Graduate Assistant with Youngstown State University. In
computing. She is currently involved with an NSF-funded S-STEM project that awards scholarships to students studying computing at USF. The project implements a suite of community- building activities designed to improve scholars’ self-efficacy and develop computing identity. Sami also co-directed a project that developed system support and user-driven strategies for improving energy effi- ciency in residential buildings. Sami has served in a number of service roles at USF and in her professional community. She was chair of the Computer Science department at USF from 2013-2016. She also served on the editorial board of Sigmobile’s GetMobile Magazine from 2014-2018. She has been involved with the discipline-specific
Kokomo 2300 S. Washington St., Kokomo, IN, 46902 Abstract IntroductionThe arrival of the Internet of Things (IoT) into our The growth of the Internet, in the past decade, hasdaily lives in various forms such as home appliances enabled exponential growth of over 26.66 billionand wearable devices has dominated Internet usage. connected devices in 2019, approximately a 57.81%This dominant behavior left network practitioners increase compared to 2015 [1]. This number iswith many questions to be answered related to IoT expected to grow significantly in the coming years
Polytechnic State University San Luis Obispo Ph. D. Electrical Engineering and Information Technology, Vienna University of Technology M. S. Physics, University of Vienna M. S. Education Physics and Mathematics, University of Vienna Research Interests: Computer Science Education, Physics Simulation, Applied Computing c American Society for Engineering Education, 2020 Deep Learning and Artificial Intelligence: Project Collaboration across ClassesAbstract. Working in collaborative environments is an essential skill for computingprofessionals. In our program, students have significant team experience from previous classes;almost all of our classes in Cal Poly’s
., & LaVaque-Manty, D. (2007). Transforming science andengineering: Advancing academic women. University of Michigan Press.[6] Ceci, S. J., Williams, W. M., & Barnett, S. M. (2009). Women's underrepresentation in science:sociocultural and biological considerations. Psychological bulletin, 135(2), 218[7] Gaughan, M., & Bozeman, B. (2016). Using the prisms of gender and rank to interpret researchcollaboration power dynamics. Social Studies of Science, 46(4), 536-558.[8] Pereira, M. D. M. (2010). Higher Education Cutbacks and the Reshaping of EpistemicHierarchies: An Ethnography of the Case of Feminist Scholarship.Sociology, 44(2), 287–304.[9] Amâncio, L. (1993). Género: representações e identidades. Análise das representações
”,“crossing the chasm”, “technological S curve”, and so forth. Figure 9. Word-cloud of peer interactions within study groups Figure 10. Distance between keywords of peer discussionsLessons Learned about Peer InstructionAt the conclusion of the course, multiple course participants were interviewed to solicit theirfeedback on the P2P platform. Some interesting lessons were learned in terms of how theplatform was used in practice.Generally speaking, student feedback was mostly positive. According to students, it was“fairly straightforward” to learn to use the platform, especially since a detailed user guidehad been provided. It was helpful to view the feedback of other students, which oftentimestriggered a student to
Maturity Model (CMM) intosoftware engineering was developed by the Software Engineering Institute of CarnegieMellon University in 1987. The integrated version (CMMI) evolved from this early work.ABET’s Criteria 2000 was inexorably linked to the quality assurance fervor of the 1990’s[2-7]. However, the work involved in preparing for accreditation is enormous, and facultymembers do not always find the direct benefit of such work. As a result, some nontechnicalfaculty members have even resorted to excoriating the entire outcomes-based approach ofthe accreditation process publicly [8].The classroom instructors of many undergraduate courses are burdened with severalchallenges such as large class sizes, dwindling instructional support and the need to
$400K to ransomware hackers, 2019. Retrieved from: https://statescoop.com/georgia-county-paid-400k-to-ransomware-hackers/3. D. Kobialka, Regis University Cyberattack: What You Need to Know, 2019. Retrieved from: https://www.msspalert.com/cybersecurity-breaches-and-attacks/regis-university-cyberattack-what-you-need-to- know/4. Symantec, 10 cybersecurity facts and statistics for 2018, 2018. Retrieved from: https://us.norton.com/internetsecurity-emerging-threats-10-facts-about-todays-cybersecurity-landscape-that- you-should-know.html5. T. S. Chou, “Multi-Learning Techniques for Enhancing Student Engagement in Cyber Security Education,” American Society for Engineering Education (ASEE) Annual Conference and
future work. First, the currentsystem consists of three Python programs (or files), and the operation of the system requiressome command line inputs. It would be more convenient for a user (e.g. instructor) to use thesystem if the system could be integrated into a single application file with a Graphic UserInterface (GUI). Second, we will update the system for a more robust face recognition if acorresponding algorithm is available. Third, based on the survey, some students have a privacyconcern on face recognition. It is important to address this concern.References[1] B.K. Mohamed and C. Raghu, “Fingerprint attendance system for classroom needs,” IndiaConference (INDICON), Annual IEEE, 2012, pp. 433-438.[2] S. N. Shah and A. Abuzneid, “IoT based
authors senior capstone project partner and Paul Henriksenfor his diligence and effort in reviewing and editing this paper.References [1] M. C. et al., “Network virtualization in multi-tenant datacenters,” in 11th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’14)., 2014. [2] M. Casado, “Origins and evolution of openflow/sdn,” in Open Networking Summit, 2011. [3] M. Casado, “Keynote: Make sdn real,” in Open Networking Summit, 2017. [4] N. Mckeown, “How sdn will shape networking,” in Open Networking Summit, 2011. [5] S. Shenker, “The future of networking, and the past of protocols,” in Open Networking Summit, 2011. [6] J. H. Cox, J. Chung, S. Donovan, J. Ivey, R. J. Clark, G. Riley, and H. L. Owen, “Advancing software
will go unreported. At this point, bad actors would be able tophysically traverse the home without fear of being recorded.Although the features offered by the Google Nest Hub Max are highly utilitarian, some featurescould pose serious threats once compromised. In regard to the broadcast function of the GoogleHome app, an intruder can trigger the devices in the house and gain control over them remotely.Consider another scenario where using the Google Home app to record reminders, could bedetrimental. In this case, the intruders can gain access to personal information, such as routineschedules of the person(s) in the house, without much difficulty. A similar scenario is thecapability of the Google Home application to set-up the hub for all the
B6 1/42 B8 -1/30 B10 5/66 B12 -691/2730 B14 7/6 etc.To illustrate the usefulness of his formula, Bernoulli computed the value of s 10(1000) with littleeffort in less than “half a quarter of an hour” [Smith]. He computed s10(1000) = 91409924241424243424241924242500To achieve this end, he needed to find B0 up to B10. One can observe that the Bernoullinumbers were at one time of great value because they shortened calculations of severalmathematical functions when lengthy computations were done by
which random distribution suits best for their decision making, and how thedeparture of one node will become the arrival of the tandem nodes. Wa S AD Wa S D A Figure 3: A Tandem Queue model used for training students3.3. Input and Output Data ModelData models are vital to any simulation study. There are two significant parts of data that must beworked, understood, and documented: the inputs data and the outputs (or result). Each part needsto be studied, analyzed, and determined. The results need to be documented for the implementationof the model. Data models of the Healthcare Clinic of Figure 1 include:Input Data: • Arrival rate of the patients
release at the endof the year, Single Sign-On (SSO) configuration was not yet complete primarily due to logisticaldifficulties between IT teams. The team decided to use the old site for one final semester tocomplete more in-depth testing and help ensure a smooth transition. SSO is a critical productionfeature because it enables students to log into these applications using their Georgia Tech logincredentials, providing seamless accessibility.Spring 2020’s focus was EM development (9) and preparing IDCD for release. SSO was set upand the beta IDCD app was released on the production tenant for the Summer 2020 capstonedesign students (10). Typically, only about 60 students participate in capstone design’s ME andInterdisciplinary summer offerings as
overlooked by practitioners and researchers. Additionally, the platform has supportedworkshops organized across the country. Workshops are co-organized with organizations thatoperate large backbone networks connecting research centers and national laboratories, andcolleges and universities conducting teaching and research activities.1. IntroductionGeneral-purpose enterprise networks are capable of transporting basic data, e.g., emails,multimedia, and web content. However, these networks face many challenges when movingpetabytes (PBs) of scientific data, e.g., genomic, climate, imaging, and high-energy physics, [1].As a response, network architects have developed the concept of a Science Demilitarized Zone(Science DMZ or S-DMZ) [2] as parts of a
“veryhigh” research activity based on the Carnegie Classifications, and offer doctoral degrees in CSor computer and information science. Overall institutional enrollments ranged from slightlyabove 3,000 undergraduate students to slightly above 39,000. Participating schools aregeographically located in the Eastern (n = 3), Midwestern (n = 1), Southwestern (n = 1), orPacific (n = 2) United States. At six of the seven schools, students declare their majors uponenrollment; at the remaining university, students declare majors at the end of their second yearof coursework. No other data about “population(s) served” (e.g., student demographics,socioeconomic status, etc.) were collected, apart from the change in participation of women andmen within the CS
of papers implementing surveys started in 1994by Todd and Magleby et al. [4] that was followed up by Howe. S. et al. in 2010 [5] and 2015 [6],[7] respectively. The work from Howe, which can be found in the ASEE database, is more recentand relevant to this work. In 2015 Howe did both a qualitative and quantitative analysis ofsurvey results from 256 ABET accredited institutions executing Capstone projects in 464 distinctdepartments for a total of 522 respondents. This work looked at many aspects of the Capstoneexperience. One interesting reported observation was how various programs and institutionsvalued “process vs. product” in the final outcomes of a Capstone experience. Howe alsoexamined the number of semesters to complete, age of Capstone
Pervasive,” J. Sci. Pract. Comput., vol. 1, no. 2, pp. 67–69, 2007.[2] Q. Bui, “Will Your Job Be Done By A Machine?,” Planet Money - The Economy Explained, 2015. [Online]. Available: http://www.npr.org/sections/money/2015/05/21/408234543/will-your-job-be-done-by-a- machine. [Accessed: 25-May-2015].[3] M. Weisser, “The Computer for the Twenty-First Century,” Sci. Am., vol. 3, no. 265, pp. 94–104, 1991.[4] S. Hambrusch, C. Hoffmann, J. T. Korb, M. Haugan, and A. L. Hosking, “A Multidisciplinary Approach Towards Computational Thinking for Science Majors,” ACM SIGCSE Bull., vol. 41, no. 1, p. 183, Mar. 2009.[5] P. B. Henderson, “Ubiquitous computational thinking,” Computer (Long. Beach. Calif)., vol. 42
to evaluatethe impact of retention factors on larger private and public institutions. Machine Learning and datamining can be very rewarding as researchers can apply many different methods to institutions of all sizesand types as needed. The suggestion of establishing a centralized center supporting different kinds ofresearch to solve retention problems could impact the university’s marketing and recruitment activities aswell. Improved management of new, innovative, and existing resources could improve retention andallow for greater financial stability at Jonson C. Smith University.References[1] L. A. Spakman, W. S. Maulding and j. G. Roberts, "Non-cognitive predictors of student success in college.," College Student Journa, p. 46, Fall