Conference Session

Potpourri

Collection

2017 ASEE Annual Conference & Exposition

Authors

Joshua B. Gross, Blackburn College

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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

Conference Session

Emerging Computing and Information Technologies I

Collection

2016 ASEE Annual Conference & Exposition

Authors

Justin L. Hess, Purdue University, West Lafayette; Lorraine G. Kisselburgh, Purdue University; Carla B. Zoltowski, Purdue University, West Lafayette; Andrew O. Brightman, Purdue University, West Lafayette

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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

Conference Session

Curricular Issues in Computing and Information Technology Programs II

Collection

2017 ASEE Annual Conference & Exposition

Authors

Jennifer Leaf, Eastern Washington University; Robert E. Gerlick, Eastern Washington University; Donald C. Richter, Eastern Washington University

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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

Conference Session

Curricular Issues in Computing and Information Technology Programs I

Collection

2016 ASEE Annual Conference & Exposition

Authors

Hassan Rajaei, Bowling Green State University; Saba Jamalian, Bowling Green State University

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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

Conference Session

Emerging Computing and Information Technologies I

Collection

2015 ASEE Annual Conference & Exposition

Authors

Forough Sheikh-Ansari, Purdue University; Baijian Yang, Purdue University, West Lafayette

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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

Conference Session

Curricular Issues in Computing and Information Technology Programs II

Collection

2017 ASEE Annual Conference & Exposition

Authors

Vetria L. Byrd Ph.D., Purdue University; Camilo Vieira, Purdue University, West Lafayette (College of Engineering)

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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

Conference Session

Potpourri

Collection

2017 ASEE Annual Conference & Exposition

Authors

Stephen Andrew Wilkerson P.E., York College of Pennsylvania; Jason Forsyth, York College of Pennsylvania; Cara Sperbeck, York College of Pennsylvania; Matthew Jones, York College of Pennsylvania; Patrick David Lynn, York College of Pennsylvannia

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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

Conference Session

Information and Network Security

Collection

2015 ASEE Annual Conference & Exposition

Authors

Ching-Kuang Shene, Michigan Technological University; Chaoli Wang, University of Notre Dame; Jun Tao, Michigan Technological University; Melissa Sue Keranen, Michigan Technological University; Jun Ma, Michigan Technological University; Jean Mayo, Michigan Technological University

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. 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

Conference Session

Emerging Computing and Information Technologies II

Collection

2016 ASEE Annual Conference & Exposition

Authors

Yujian Fu P.E., Alabama A&M University; Md Hossain Shuvo, Alabama A&M University

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the robot around. Tomove the robot, every button is assigned with an action listener and when they are pressed thecommand is send to the robot which has also been implemented using LEJOS API. Beforemoving the robot, the actuators of the robot needs to be initialized. As our robot has threemotors- A, B, C which are marked as left, right and back motors and all three motors needs to beinitialized before moving. left = con.ev3.createRegulatedMotor("A", 'L'); right =con.ev3.createRegulatedMotor("B", 'L'); back = con.ev3.createRegulatedMotor("C", 'L');After that, the robot is moved in different directions as follows © American Society for

Conference Session

Emerging Computing and Information Technologies II

Collection

2016 ASEE Annual Conference & Exposition

Authors

Mahmoud K. Quweider, University of Texas - Rio Grande Valley; Fitratullah Khan, University of Texas - Rio Grande Valley

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should demonstrate the following learning outcomes out of the course outcomes: a. Provide an understanding of how a computer draws the fundamental graphics primitives - lines and filled polygons in both 2-D and 3-D. b. Use the facilities provided by a standard API to express basic transformations such as scaling, rotation, and translation. c. Implement simple procedures that perform transformation and clipping operations on a simple 2-dimensional image. d. Discuss the 3-dimensional coordinate system and the changes required to extend 2D transformation operations to handle transformations in 3D. e. Explain the concept and applications of each of these techniques

Conference Session

Curricular Issues in Computing and Information Technology Programs II

Collection

2017 ASEE Annual Conference & Exposition

Authors

Cheryl Xu, Florida A&M University/Florida State University; Seyed Mousavinezhad, Idaho State University

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These 2 equations are put in standard form: 9V1 – 4V2 = -280 V1 – 2 V2 = 35 With solutions obtained as V1 = -50 V , V2 = -42.5 V .At this time it is pointed out that the system of equations above can be put in matrix formAX = B and solved, for example, using Matlab:>> % Nodal Analysis, Spring 2017>> A=[9 -4;1 -2];>> B=[-280;35];>> inv(A)*Bans = -50.0000 -42.5000>>Once node voltages are computed, students can check the balance of power:Absorbed powers:P5Ω = 11.25 W (this is the 5Ω between nodes 1 and 2)P’5Ω = 361.25 W (the 5Ω resistor between node 2 and the ground)P4Ω = 625 WΣ Pabs. = 997.5 WP14A = (-14

Conference Session

Curricular Issues in Computing and Information Technology Programs II

Collection

2016 ASEE Annual Conference & Exposition

Authors

Yujian Fu P.E., Alabama A&M University; Peter J. Clarke, Florida International University

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&MUniversity (FAMU) [5]. The NSF Course, Curriculum, and Laboratory Improvement(CCLI) Phase I project had the following objectives: (a) create learning materials ontesting tools, (b) increase the number of students who have access to testing tool tutorials,and (c) train instructors on how to use testing tools and WReSTT in the classroom.WReSTT-CyLE is a NSF Transforming Undergraduate Education in Science (TUES) IIproject that aims to provide a cyberlearning environment that facilitates the improvementof students’ conceptual understanding and practical skills in software testing. The maingoals of this project are to create new learning materials and develop faculty expertise tosignificantly increase the number of undergraduate students that

Conference Session

Curricular Issues in Computing and Information Technology Programs II

Collection

2016 ASEE Annual Conference & Exposition

Authors

Christina Frederick, Embry-Riddle Aeronautical University - Daytona Beach; Lulu Sun, Embry-Riddle Aeronautical University - Daytona Beach; Caroline Liron, Embry-Riddle Aeronautical University - Daytona Beach; Matthew A. Verleger, Embry-Riddle Aeronautical University - Daytona Beach; Rachel Marie Cunningham, Embry-Riddle Aeronautical University - Daytona Beach; Paula Sanjuan Espejo, Embry-Riddle Aeronautical University - Daytona Beach

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Paper ID #14660Implementation and Evaluation of a Second Language Acquisition–BasedProgramming CourseDr. Christina Frederick, Embry-Riddle Aeronautical University - Daytona Beach Dr. Frederick is currently a Professor and Graduate Program Coordinator in the Human Factors and Systems Department at Embry-Riddle Aeronautical University in Daytona Beach, Florida. Dr. Frederick received her Ph.D. in 1991 from the University of Rochester with a major in Psychological Development. She previously taught at the University of Rochester, Southern Utah University and the University of Central Florida. In 2000, Dr. Frederick joined the

Conference Session

Emerging Computing and Information Technologies II

Collection

2017 ASEE Annual Conference & Exposition

Authors

Hassan Rajaei, Bowling Green State University; Ramin Khakzad

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Paper ID #19699A Real-World Example for Student Learning: BTSU Cafeteria SimulationDr. Hassan Rajaei, Bowling Green State University Hassan Rajaei is a professor of computer science at Bowling Green State University, Ohio. His research interests include cloud computing, High Performance Computing (HPC), distributed simulation, parallel and distributed processing, communication networks, wireless communications, and virtual training envi- ronments. Rajaei received his Ph.D. from Royal Institute of Technology, KTH, Stockholm, Sweden, and he holds a M.S.E.E. from the University of Utah, and a BS from University of Tehran.Mr

Conference Session

Curricular Issues in Computing and Information Technology Programs II

Collection

2015 ASEE Annual Conference & Exposition

Authors

Mohamed Abdelrahman, Texas A&M University-Kingsville; Mohamed Abdelsalam Salem, Text Scope; Mais Nijim, Texas A&M Kingsville

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Paper ID #12420Towards an integrated Hardware And SOftware Book (HASOB)Prof. Mohamed Abdelrahman, Texas A&M University-Kingsville Dr. Abdelrahman is currently the Associate Vice President for Research and Graduate Studies and a Professor of Electrical Engineering at Texas A&M University Kingsville. Dr. Abdelrahman has a diverse educational and research background. His research expertise is in the design of intelligent measurement systems, sensor fusion and control systems. He has been active in research with over 80 papers published in refereed journals and conferences. He has been the principal investigator on

Conference Session

Curricular Issues in Computing and Information Technology Programs II

Collection

2016 ASEE Annual Conference & Exposition

Authors

Tanya Stanko P.E., Innopolis University; Marat Valiev, Innopolis University; Daniel Martin Johnston, Innopolis University

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Paper ID #15528Case Study: The Unified State Exam and Other Admission Tests as a Predic-tor of Academic Performance at the IT UniversityDr. Tanya Stanko P.E., Innopolis University Tanya Stanko is a Vice-Provost of Education at Innopolis University. She specializes in launching new Universities from scratch, including setting up curricula and polices, recruiting faculty and students. She holds PhD in Computational Aeroacoustics from the University of Leeds and worked as researcher at Technical University of Munich. Her current research interests include investigation of the professional competencies, gender diversity in

Conference Session

Curricular Issues in Computing and Information Technology Programs I

Collection

2016 ASEE Annual Conference & Exposition

Authors

Masoud Naghedolfeizi, Fort Valley State College; Sanjeev Arora, Fort Valley State University; Nabil A. Yousif, Fort Valley State University; Xiangyan Zeng, Fort Valley State University

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Paper ID #17134Computer Science Curriculum Redesign at Fort Valley State UniversityDr. Masoud Naghedolfeizi, Fort Valley State College Dr.Masoud Naghedolfeizi is a senior professor in the Department of Mathematics and Computer Science at Fort Valley State University. His academic background includes a B.S. in Mechanical Engineering with minor in instrumentation and control, an M.S. in Metallurgical Engineering, and M.S. and Ph.D. in Nuclear Engineering. Dr. Naghedolfeizi’s research interests include instrumentation and measurement systems, applied articial intelligence, information processing, and engineering education

Conference Session

Topics in Computing and Information Technologies I

Collection

2015 ASEE Annual Conference & Exposition

Authors

Wei Zheng, Jackson State University; Jianjun Yin, Jackson State University; Yanhua Cao, Jackson State University

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interaction scaffolding that specifies roles, sequences group activities, and provides question prompts for social interactions among student team members to effectively engage them in task-related social interaction. The other is the cognitive cooperation scaffolding that guides students’ cognitive processes relating to the specific learning tasks at hands. Detailed description of the two types of scaffolding can be retrieved from the previously published ASEE conference paper 21. Table 2 Different students’ team groups and corresponding instruction (input variables) Team Groups Instructional Materials Provided to Students A Collaborative learning requirements only B Collaborative

Conference Session

Emerging Computing and Information Technologies I

Collection

2017 ASEE Annual Conference & Exposition

Authors

Mudasser Fraz Wyne, National University; Abdulbaset Abdulaziz Gaddah A.G., University of Umm Al-Qura; Shakil Akhtar, Clayton State University

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! A matter of Identity?”, In proceedings of 1st International Conference on Learning and Teaching in Computing and Engineering, pp. 114-121, Los Alamitos, USA, 2013.2. Verginis, I., Gogoulou, A., Gouli, E., Boubouka, M. and Grigoriadou, M., “Enhancing Learning in Introductory Computer Science Courses Through SCALE: An Empirical Study”, IEEE Transactions on Education, VOL. 54(1), February 2011.3. Isong, B. “A Methodology for Teaching Computer Programming: first year students’ perspective”, International Journal of Modern Education and Computer Science, Vol. 9, pp. 15-21, 2014.4. Kanellopoulos, D., Sakkopoulos, E., Lytras, M. and Tsakalidis, A. “Using Web-Based Teaching Interventions in Computer Science Courses”, IEEE

Conference Session

Curricular Issues in Computing and Information Technology Programs I

Collection

2015 ASEE Annual Conference & Exposition

Authors

Alireza Kavianpour, DeVry University, Pomona; Simin Shoari; Behdad Kavianpour, University of California, Irvine

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+ √y 2 =1 ( ab b2 −y 2 ) ( cb b2 −y 2 ) 2 x2 A2 + By 2 = 1 where √ √ A = ab b2 − y 2 , B = cb b2 − y 2 2 2 The elliptic disk Ax 2 + By 2 = 1 has the area of πAB. Thus the secondmoment with respect x − z plane, mxz , can be calculated as follows: +∞ +∞ +∞ +b mxz = y 2 dxdydz = πABy 2 dy = −∞ −∞ −∞ −b 2acπ +b

Conference Session

Potpourri

Collection

2016 ASEE Annual Conference & Exposition

Authors

Roxanne Moore, Georgia Institute of Technology; Douglas Edwards, Georgia Institute of Technology; Jason Freeman, Georgia Institute of Technology; Brian Magerko, Georgia Institute of Technology; Tom McKlin, SageFox Consulting Group; Anna Xambo, Georgia Institute of Technology

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Science Foundation (CNS #1138469, DRL#1417835, and DUE #1504293), the Scott Hudgens Family Foundation, and the Arthur M. BlankFamily Foundation.References[1] J. M. Wing, “Computational thinking and thinking about computing,” Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol. 366, no. 1881, pp. 3717–3725, 2008.[2] M. Guzdial and E. Soloway, “Teaching the Nintendo generation to program,” Commun. ACM, vol. 45, no. 4, pp. 17–21, Apr. 2002.[3] A. Bruckman, M. Biggers, B. Ericson, T. McKlin, J. Dimond, B. DiSalvo, M. Hewner, L. Ni, and S. Yardi, “‘Georgia computes!’: improving the computing education pipeline,” in Proceedings of the 40th ACM technical symposium on Computer

Conference Session

Emerging Computing and Information Technologies II

Collection

2017 ASEE Annual Conference & Exposition

Authors

Mohammad Rafiq Muqri, DeVry University, Pomona; Javad Shakib, DeVry University, Pomona; James R. Lewis, DeVry University, Pomona

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Instrumentation SetupThe Bioinformatics offers a representation of medical data (e.g., nucleotide and amino acid sequences—DNA) in a quantitative and precise (almost exactly) using discrete representation. In this lab, we willexplore the sequence of the typical chain nucleic acid molecules containing adenine, guanine, cytosine,and thymine/uracil specific to DNA, RNA, and proteinThe BioMedical instrumentation setup depicted above is used in conjunction with The Silver(Ag)-Silver Chloride (AgCl) electrodes, a high-performance bio-potential amplifier with built-inhardware filter from iWorx, IV, National Instrument Elvis II+, and Laptop/PC runningBiomedical Workbench, LabVIEW, and MATLAB.The only new addition is Raspberry PI 3 Model B Python Module: it uses

Conference Session

Curricular Issues in Computing

Collection

2017 ASEE Annual Conference & Exposition

Authors

Tony Andrew Lowe, Purdue University, West Lafayette (College of Engineering); Sean P. Brophy, Purdue University, West Lafayette (College of Engineering)

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studies are potentially limited because they primarily engage self-selectingstudents in extra-curricular study groups, and thus may include be selecting motivated studentswho rather than simply effects of PLTL. One of the additional hopes of this paper is to inspireempirical research, perhaps even retrospective views of courses such as this study, to further theunderstanding of peer learning in the classroom.References[1] L. Vygotsky, Thought and language. Cambridge, MA: MIT Press, 1962.[2] N. Salleh, E. Mendes, and J. Grundy, “Empirical Studies of Pair Programming for CS/SE Teaching in Higher Education: A Systematic Literature Review,” IEEE Trans. Softw. Eng., vol. 37, no. 4, pp. 509–525, 2011.[3] L. Porter, C. Bailey-Lee, and B

Conference Session

Curricular Issues in Computing and Information Technology Programs I

Collection

2016 ASEE Annual Conference & Exposition

Authors

Alka R Harriger, Purdue University, West Lafayette; Mayari I. Serrano, Purdue University, West Lafayette

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also include socialactivities to show that college can be fun, too.The Computer and Information Technology department actively participates in these outreachprograms. A variety of activities designed by faculty, undergraduate, and graduate students havebeen used in these sessions over the past ten years. Some example sessions included the use ofthe following tools: 1. Web page development (static HTML to dynamic ASP.NET) 2. Social media tools through a Twitter-enabled game 3. Programming languages a. Alice b. Scratch c. Scratch 4 Arduino d. C# 4. Physical computing a. Arduino board b. Phoenix Contact Nanoline microcontrollerThe remainder of this paper will present the

Conference Session

Potpourri

Collection

2017 ASEE Annual Conference & Exposition

Authors

Jacob Bailey, University of Illinois, Urbana-Champaign; Matthew West, University of Illinois, Urbana-Champaign; Craig Zilles, University of Illinois, Urbana-Champaign

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. The critical role of retrieval practice in long-term retention. Trends in Cognitive Sciences, 15:20–27, 2011.[5] D. Rohrer, K. Taylor, and B. Sholar. Tests enhance the transfer of learning. Journal of Experimental Psychology Learning Memory and Cognition, 36:233–239, 2010.[6] K. E. Train. Discrete Choice Methods with Simulation. Cambridge University Press, second edition, 2009.[7] M. West and C. Zilles. Modeling student scheduling preferences in a computer-based testing facility. In Proceedings of the Third (2016) ACM Conference on Learning @ Scale, pages 309–312, 2016. doi: 10.1145/2876034.2893441.[8] C. Zilles, R. T. Deloatch, J. Bailey, B. B. Khattar, W. Fagen, C. Heeren, D. Mussulman, and M. West. Computerized testing: A

Conference Session

Emerging Computing and Information Technologies II

Collection

2015 ASEE Annual Conference & Exposition

Authors

Candido Cabo, New York City College of Technology/City University of New York

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26.1295.5adequate performance (equivalent to a passing grade or C).Figure 1. Average sttudent perforrmance (0-10) in seven ttypes of proggramming coonceptassessmeents (first two categories in Bloom’s taxonomy). n = 62. Dasshed horizonntal line markks alevel of acceptable a peerformance.Figure 2. 2 Percent of students perrforming adeequately (>= = 7 which is equivalent too a passing Page 26.1295.6grade, 70 0% or C) in the t seven diffferent progrramming connceptual cateegories.Average values can be b distorted byb very good d performannce of some

Conference Session

Curricular Issues in Computing and Information Technology Programs I

Collection

2017 ASEE Annual Conference & Exposition

Authors

Dennis K. Njeru, Utah Valley University and Novarad Corporation; Afsaneh Minaie, Utah Valley University

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. Leung, YP. Lee, HY. Chan, and MH. Tang, "Fetal biometry by an inexperienced operator using two- and three-dimensional ultrasound," Ultrasound in Obstetrics and Gynecology, vol. 35, no. 5, pp. 566--571, 2010.7. Ioannis Pratikakis, Christian Barillot, Pierre Hellier, and Etienne Memin, "Robust Multiscale Deformable Registration of 3D Ultrasound Images.," International Journal of Image and Graphics, vol. 3, no. 4, p. 547, 2003.8. Aaron. Fenster, B. Downey Dónal, and Neale Cardinal H., "Three-dimensional ultrasound imaging," Physics in Medicine and Biology, vol. 46, no. 5, p. R67, 2001.9. Charles E. Kahn Jr, John A. Carrino, Michael J. Flynn, Donald J. Peck, and Steven C. Horii, "DICOM and Radiology: Past, Present, and Future

Conference Session

Curricular Issues in Computing

Collection

2017 ASEE Annual Conference & Exposition

Authors

Joshua Levi Weese, Kansas State University; Russell Feldhausen, Kansas State University

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- in-schools/report/19. Seehorn, D., Carey, S., Fuschetto, B., Lee, I., Moix, D., O'Grady-Cunniff, D., . . . Verno, A. (2011). CSTA K-12 Computer Science Standards. New York: Association for Computing Machinery. Retrieved March 31, 2016, from http://csta.acm.org/Curriculum/sub/CurrFiles/CSTA_K-12_CSS.pdf20. Seiter, L., & Foreman, B. (2013). Modeling the Learning Progressions of Computational. Proceedings of the ninth annual international ACM conference on International computing education research - ICER '13, (pp. 59-66).21. Snow, E., Haertel, G., Fulkerson, D., Feng, M., & Nichols, P. (2010). Leveraging Evidence-Centered Assessment Design in Large-Scale and Formative Assessment

Conference Session

Computing & Information Technology Division Technical Session

Collection

2016 ASEE Annual Conference & Exposition

Authors

Mayari I. Serrano, Purdue University, West Lafayette; Alejandra J. Magana, Purdue University, West Lafayette; Baijian Yang, Purdue University

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. As illustrated in Figure 1, the focus ofthis problem-based activity is to promote students’ learning in the core concepts related toHyper-Text Transfer Protocol Secure, or HTTP over SSL. The learning objectives for thisparticular activity are: (a) review firewall, network design and web server configurationprocesses; (b) identify differences between HTTPS and HTTP; (c) migrate a website from HTTPto HTTPS; (d) acquire, activate and install certificates; (e) identify potential vulnerabilitiesrelated to data security; (f) define best practices related to HTTPS implementation; and (g)delineate optimal encryption method. Figure 1 presents the MEA.Once the learning objectives were identified, the next step in the process was to apply the

Conference Session

Emerging Computing and Information Technologies II

Collection

2017 ASEE Annual Conference & Exposition

Authors

Joseph William Beckman, Purdue University; Melissa Jane Dark, Purdue University; Pratik Kashyap, Purdue University; Sumra Bari, Purdue University, School of Electrical and Computer Engineering; Samuel S. Wagstaff Jr, Purdue University; Yingjie Chen, Purdue Polytechnic Institute; Baijian Yang, Purdue Polytechnic Institute

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different representations can easily translate between them, and can assess theusefulness of a particular representation in different situations. Similarly, Spiro (1992) found thatwhen learners develop multiple representations they are better able to transfer knowledge to newdomains with increased cognitive flexibility (Spiro, 1992). Representational fluency in theSTEM fields can include: a) visualizing and conceptualizing transformation processes abstractly;b) understanding systems that do not exhibit any physical manifestations of their functions; c)transforming physical sensory data to symbolic representations and vice versa; d) quantifyingqualitative data, e) qualifying quantitative data; f) working with patterns; g) working withcontinuously