Paper ID #10088Work-in-Progress: The Platform-Independent Remote Monitoring System(PIRMS) for Situating Users in the Field VirtuallyMr. Daniel S. Brogan, Virginia Tech Daniel S. Brogan is a PhD student in Engineering Education with BS and MS degrees in Electrical En- gineering. He has completed several graduate courses in engineering education pertinent to this research. He is the key developer of the PIRMS and leads the LEWAS lab development and implementation work. He has mentored two NSF/REU Site students in the LEWAS lab. He assisted in the development and implementation of curricula for introducing the LEWAS at VWCC
Education, First-Year Programs, and Design in Engineering Education Divisions. Dr. Estell is an ABET Commissioner, Vice President of The Pledge of the Computing Professional, a Senior Member of IEEE, and a member of ACM, ASEE, Tau Beta Pi, Eta Kappa Nu, Phi Kappa Phi, and Upsilon Pi Epsilon.Dr. Khalid S. Al-Olimat P.E., Ohio Northern University Dr. Khalid S. Al-Olimat is professor and chair of the Electrical & Computer Engineering and Computer Science Department at Ohio Northern University. He obtained his BS in Electrical Engineering from Far Eastern University in 1990, the MS in Manufacturing Engineering from Bradley University in 1994 and his PhD in Electrical Engineering from the University of Toledo in 1999. Dr
. The transfer function between and an external torque, , can be expressed in the form given in Equation 3, where is the output of interest (represented by Y(s)) and is the input (represented by U(s)) Y ( s) K n2 2 U ( s ) s 2 n s 2 n (3) From Equation 2, we can see that the pendulum is a 2nd order-system (and we can compare it to the general
collaborative administration and industry mentorship planning used to increase enrollments of woman and minorities with declared majors in the areas of Computer Science (CS), Engineering (E), Mathematics (M), and Science (S). Currently, Dr. Kappers is the fulltime Di- rector of the Rothwell Center for Teaching and Learning Excellence Worldwide Campus (CTLE – W) for Embry-Riddle Aeronautical University. In addition, she holds Adjunct Assistant Professor status in the College of Arts and Sciences, Worldwide Campus, teaching RSCH 202 – Introduction to Research Methods, and in the College of Engineering, Daytona Beach Campus, teaching CS120 – Introduction to Computing in Aviation. Both positions allow her to stay focused upon
: Envisioning a Research Discipline and a Domain of Practice. In Proceedings of the LAK ‘11 (Vancouver, Canada, April 29-May 02, 2012).[9] Haythornthwaite, C. 2011. Learning networks, crowds and communities. In Proceedings LAK ‘11, (Banff, Alberta, Canada, February 27 – March 01, 2011).[10] Suthers, D., Hoppe, H. U., Laat, M. and Simon Buckingham, S. (2012). Connecting levels and methods of analysis in networked learning communities. In Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, (Vancouver, British Columbia, Canada, April 29 – May 02, 2012). LAK '12. ACM, New York, NY, 11-13.[11] Ferguson, R. and Buckingham Shum, S. 2012. Social learning analytics: five approaches. In Proceedings
completeprogram, as shown in Program 1, is written which moves the robot forward.#include CLinkbotI r o b o t ;double d i s t a n c e = 5 , r a d i u s = 1 . 7 5 ;robot . connect ( ) ;r o b o t . moveDistance ( d i s t a n c e , r a d i u s ) ; Program 1: Single robot control code.Only five lines of code are necessary to connect to the robot and move it forward. The firstline is C++ syntax to allow the code to know about all of the functions available to controlthe robot. The second line creates the robot within the code so that the functions can Page 24.1058.10interact with the correct robot. Variables are created to store
the best word(s) to branch on at each point to reduce the overall error. The result tends to be a more accurate tree (as each branching word is explicitly chosen to reduce the classification error), but for a non-‐trivial increase in the amount of time needed to identify the appropriate words. Each item took between 8 and 10 hours for this algorithm to identify the final
similar ones. Where three scored problems in a common areaare assigned, the effect of voluntary un-scored practice is not enough to improve performance ona fourth scored problem, for which no practice is provided, regardless of how practice is 11provided. Given the voluntary nature of the practice problems studied here, and the ease withwhich they can be provided with systems such as PathFinder, their use is recommended,especially related practice problems. Future work can focus on more difficult problems. Studentscan be directly asked why they do or do not use practice problems.References1 Bonham, S. W., Deardorff, D. L., & Beichner, R. J. (2003). Comparison of student performanceusing web and
. Page 24.1181.8One initial clustering effort, based on student self-reports of physical and emotional statedemonstrates a strong relationship in outcomes and emotional state. While this is not necessarilysurprising this result raises questions about what responsibility do instructors have to identifystudents having emotional distress? And, once identified, what are the best strategies for dealingwith the students who score low in self reported wellness?ReferencesAnaya, A. R. and J. G. Boticario (2009). A Data Mining Approach to Reveal Representative Collaboration Indicators in Open Collaboration Frameworks. 2nd International Conference On Educational Data Mining. Cordoba, Spain.Baker, R. S. J. d. (2010). Data Mining. International
needed by a student or a researcher.15, 16There are a few simple steps to implement a remote laboratory (Figure 1): Figure 1: Basic concept of remote laboratories. a) The first and foremost thing is that the equipment should have interfaceability with a computer (or with a networked device) along with the ability to exchange its input(s) and output(s) as needed to perform experiments. b) The next required item is a local computer that will provide the processing requirement for an experiment along with hosting a graphical user interface (GUI). The GUI will allow a remote user to perform experiments using the local computer without any
, 2008).6 Computing Research Association. Cyberinfrastructure for education and learning for the future: A vision and research agenda. (Computing Research Association, 2005).7 Boyer, E. L. The Boyer Commission on Educating Undergraduates in the Research University, Reinventing undergraduate education: A blueprint for America's research universities. (Stony Brook, N.Y., 1998).8 Mitchell, W. J., Inouye, A. S. & Blumenthal, M. S. (National Academies Press, Washington, D.C., 2003).9 Barak, M., Lipson, A. & Lerman, S. Wireless laptops as means for promoting active learning in large lecture halls. Journal of Research on Technology in Education 38, 245-263 (2006).10 Barak, M. & Rafaeli
/IT.NET.USER.P2. Accessed December 12, 2013.2. MIT OpenCourseWare | Free Online Course Materials. Available at: http://ocw.mit.edu/index.htm. Accessed December 12, 2013.3. Online Schools, Classes, Degree Programs - University of Phoenix. Available at: http://www.phoenix.edu/. Accessed December 12, 2013.4. Clow D. MOOCs and the funnel of participation. In: Proceedings of the Third International Conference on Learning Analytics and Knowledge. LAK ’13. New York, NY, USA: ACM; 2013:185–189. doi:10.1145/2460296.2460332.5. Green K. Massive Open Online Courses (MOOCs) and Other Digital Initiatives. J Collect Bargain Acad. 2013;(8). Available at: http://thekeep.eiu.edu/jcba/vol0/iss8/10.6. Yuan L, Powell S. MOOCs and Open Education
usto reallocate staff resources from grading to providing walk-in clinic hours to serving studentswho did have difficulties.A typical year's operation saw over 122,000 problems graded automatically – not including theadditional grading resulting from student retries. We attempted to keep the entire class on asingle schedule of due dates, but this imposed significant swings in the load on the autogradingsystem. Fortunately our system administrators were able to deploy adequate server power tohandle our size class. Nevertheless, system performance requires careful attention in courseswhere significant resources are needed for autograding.Lessons learned from the first version of the course – limitations of the original formatMaple T.A.'s grading
Engineering Education, 34(1), 26-39. 5. Stern, F., Xing, T., Muste, M., Yarbrough, D., Rothmayer, A., Rajagopalan, G., Caughey, D., Bhaskaran, R., Smith, S., and Hutchings, B. (2006). "Integration of simulation technology into undergraduate engineering courses and laboratories." International Journal of Learning Technology, 2(1), 28-48. 6. Busch-Vishniac, I., Kibler, T., Campbell, P. B., Patterson, E., Guillaume, D., Jarosz, J., Chassapis, C., Emery, A., Ellis, G., Whitworth, H., Metz, S., Brainard, S., and Ray, P. (2011). "Deconstructing Engineering Education Programmes: The DEEP Project to reform the mechanical engineering curriculum." European Journal of Engineering Education, 36(3), 269-283. 7. Cheah, C., Chen
ExecutionInitially, the set of functions (begin test, next question, previous question) needed to completethe assessment are listed. Next, the event(s) associated with each function are identified as shownin Table I. The two events that are monitored during this portion of the investigation are thelocation of left/right mouse clicks and keystrokes. If a key or combination of keys is used thatfalls within the list of needed keys to execute a function, the student is classified as being on-task. However, if a key or combination of keys is used that falls outside of the list of needed keysto execute a function, the student is classified as being off-task. Similarly, if the mouse is clickedat a location that falls within the list of needed clicks to execute a
Paper ID #10282Feasibility of interactive eTextbooks with computationally intense contentDr. Jacques C. Richard, Texas A&M University Dr. Richard got his Ph. D. at Rensselaer Polytechnic Institute, 1989 & a B. S. at Boston University, 1984. He was at NASA Glenn, 1989-1995, taught at Northwestern for Fall 1995, worked at Argonne National Lab, 1996-1997, Chicago State, 1997-2002. Dr. Richard is a Sr. Lecturer & Research Associate in Aerospace Engineering @ Texas A&M since 1/03. His research is focused on computational plasma modeling using spectral and lattice Boltzmann methods for studying plasma turbulence
sum of all values𝑐=0 // A variable to store the lost low-order bitsfor 𝑖 = 0 to num −1 do 𝑦 = 𝑎𝑟𝑟𝑎𝑦[𝑖] − 𝑐 𝑡 =𝑆+𝑦 // If S is big and y is small, low-order digits of y are lost 𝑐 = (𝑡 − 𝑆) − 𝑦 // c recovers the low-order digits of y 𝑆=𝑡end for Page 24.627.53. FPAvisual SoftwareFPAvisual was developed to provide engaging visualizations that show the inaccuracies causedby FPA, their significant influence on programs, and the techniques to increase the accuracy. Ithas Windows and Linux versions. FPAvisual consists of four components: Roots, Pentagon
positive vertical direction is 5 points. If you pass one line more than once, no additional points are givenIdentify Ball If your robot can identify one blue ball to pass through 10 points. If your robot can identify 2 consecutive blue balls to pass through 20 points.Navigate Maze If your robot successfully navigates the maze – 20 pointsStop at Edge The style in which you robot stops at the edge is between 0-20 points. If your robot falls over the edge – s=0; if your robot stops “short” or has an appendage over the edge – s=0.5; if your robot stops at the edge – s=1 Style*s is the “stop at the edge” scoreTime You will be assigned a t value, based on the relative speed of
OK, but problems with phase angles on plots in Case 5. D OK OK OK E OK, but natural frequencies Results calculated over a freq. OK listed in rad/s instead of Hz. range that differs from user input. Also, node numbering problem in the printed mode shapes. F Program is actually a separate Program is actually a separate OK script for each test case; user script for each test case; user input input is ignored
Paper ID #9007Collaborative Education: Building a Skilled Software Verification and Vali-dation User CommunityDr. Sushil Acharya, Robert Morris University Acharya joined RMU in Spring 2005 after serving 15 years in the Software Industry. With US Airways, Acharya was responsible for creating a conceptual design for a Data Warehouse which would integrate the different data servers the company used. With i2 Technologies he led the work on i2’s Data Mining product ”Knowledge Discover Framework” and at CEERD (Thailand) he was the product manager of three energy software products (MEDEE-S/ENV, EFOM/ENV and DBA-VOID) which were
. Unpublishedmanuscript in progress, 2010. referenced in http://www.cs.cmu.edu/~CompThink/resources/TheLinkWing.pdf[3] Goadrich, M., Rogers, M., Smart Smartphone Development: IOS Versus Android. Proceedings of the 42nd ACMtechnical Symposium on Computer Science Education, Mar. 2011[4] Kurkovsky, S., Engaging students through mobile game development. Proceedings of the 40th AMC TechnicalSymposium on Computer Science Education March 3-7, 2009, 2009.[5] Papert, S., Mindstorms: children, computers, and powerful ideas, New York, NY: Basic Books, 1980.[6] Reilly, M., Kindergarten coders can program before they can read. New Scientist 2927, 21-22, 2013.[7] Resnick, M. All I Really Need to Know (About Creative Thinking) I Learned (By Studying How Children Learn
to achieve isinstead intended to be achieved, typically, via on-line video lectures which the students are respon-sible for viewing before attending the in-person class meeting. The in-person meeting is devotedto answering questions (that students may have based on their viewing of the corresponding videolecture(s)), joint problem solving activities, as well as other active learning tasks that provide in-dividual and group practice. The expectation is that, given the ability of active learning tasks toengage students in learning, the approach will help students better achieve the intended learningoutcomes of the course; and, as an added bonus, students’ abilities with respect to such importantprofessional skills as team work and
is an Assistant Professor of Computer Graphics Technology and Computer and Information Technology. Dr. Whittinghill’ s research focuses on simulation, gaming and computer pro- gramming and how these technologies can more effectively address outstanding issues in health, educa- tion, and society in general. Dr. Whittinghill leads projects in pediatric physical therapy, sustainable energy simulation, phobia treat- ment, cancer care simulation, and games as a tool for improving educational outcomes. Dr. Whittinghill is the director of GamesTherapy.org. Prior to joining Purdue he was a senior software engineer in the research industry focused upon the fields of visualization, games, agent-based modeling, digital
seems to be one that uses both types of exercises: non-real-time and real-time. Withregard to non-real-time exercises, it’s clear that interactive learning, exercises, and demonstrations to stu-dents using off-line methods are very useful for helping them to build an initial mental model.2–6 However,taking the next step by requiring students to make the transition to real-time DSP implementations has beenshown to cement a more complete understanding of DSP topics.7Since the late 1990’s, the authors of this paper have reported on proven DSP teaching methodologies,hardware and software solutions, and various DSP tools that have helped motivate both students and facultyto implement real-time DSP-based systems, and thereby improve education in
education to the new century. The National Academies Press: Washington, DC, 2005. 2. Elby, A., Another reason that physics students learn by rote. American Journal of Physics 1999, S52. 3. Felder, R. M.; Brent, R., Understanding Student Differences. Journal of Engineering Education 2005, 57- Page 24.1387.9 72.4. Crouch, C.; Watkins, J.; Fagen, A.; Mazur, E., Peer Instruction: Engaging Students One-on-One, All At Once. Research-Based Reform of University Physics 2007.5. Bakrania, S., “Getting Students Involved in a Classroom with an iPhone App,” Proceedings of the 2012 ASEE Conference and
increase the level of design complexity without risking overwhelming some otherstudents. The final recommendation is to use the newly designed 3.3V compatible trainersthroughout the course of the labs, which means replacing the traditional TTL 74LS family withthe newer 3.3V compatible 74HC family.References:1. J. Hill, Y. Yu, “The CPLD Provides a Third Option in Introductory Logic Circuits Course,” AC2012-5302, ASEE National Convention, 2012, session W5162. K. Hill, “Schematic Capture – ISE 13.x”, http://uhaweb.hartford.edu/kmhill/suppnotes/isetut/ise13x1/schem.htm3. K. Hill, Y. Yu, “Use of a CPLD in an Introductory Logic Circuits Course,” AC2013-7987, ASEE National Convention, 2013, session M4164. M. Radu, C. Cole, M. Dabacan, and S
normally experienced inthe classroom. Quality control is also needed to assure that the content of the online course issimilar to what is taught in the classroom.References 1. Haugen, Susan; LaBarre, James; Melrose, John, “Online Course Delivery: Issues and Challenges” International Association Computer Information System (2001). 2. Song, Liyan; Singleton, Ernise S.; Hill, Janette R.; Hwa Koh, Myung, “Improving Online Learning: Student Perceptions of Useful and Challenging Characteristics” Internet and Higher Education 7 (2004): 59–70. 3. Kearsley, Greg, "A Guide to Online Education" (1998) Web 1 Jan. 2013. 4. Kearsley, Greg, “Online Education: Learning and Teaching in Cyberspace”, Belmont, CA, Wadsworth
Paper ID #10955Improving the Affective Element in Introductory Programming Courseworkfor the ”Non Programmer” StudentDr. David M Whittinghill, Purdue University, West Lafayette Dr. David Whittinghill is an Assistant Professor of Computer Graphics Technology and Computer and Information Technology. Dr. Whittinghill’ s research focuses on simulation, gaming and computer pro- gramming and how these technologies can more effectively address outstanding issues in health, educa- tion, and society in general. Dr. Whittinghill leads projects in pediatric physical therapy, sustainable energy simulation, phobia treat- ment
Closed-book Exams on Student Achievement in an Introductory Statistics Course. PRIMUS. 2. Dickson, K. L., & Miller, M. D. (2005). Authorized crib cards do not improve exam performance. Teaching of Psychology, 32, 230-233. 3. Erbe, B. (2007). Reducing test anxiety while increasing learning: The cheat sheet. College teaching, 55(3), 96–98. doi:10.3200/CTCH.55.3.96-98 4. Funk, S. C., & Dickson, K. L. (2011). Crib card use during tests: Helpful or a crutch? Teaching of Psychology, 38, 114-117. 5. Gharib, A., Phillips, W., & Mathew, N. (2012). Cheat Sheet or Open-Book? A Comparison of the Effects
Paper ID #9265Technology in classrooms: How familiar are new college students with thepedagogy?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, and international issues in higher education.Mr. S. Cory Brozina, Virginia TechMr. Steven Culver, Virginia Tech