. Reputation systemsA reputation system is a way of measuring the reliability of ratings. Scores assigned byreviewers and metareviewers can be factored into a student's reputation. Several algorithms[4, 5, 6] have also been published for determining reviewer reliability, based only on thescores assigned by reviewers. These algorithms consider (i) consistency of scores assignedby this reviewer with scores assigned by others to the same work, and (ii) spread, how muchthe highest score the reviewer assigned differs from the lowest score (s)he assigned. Somealgorithms also consider (iii) leniency, the tendency of a reviewer to give scores that arehigher than other reviewers. Research [6] demonstrates that these algorithms provideeffective quality control
about and can effectively use this system,researchers at Missouri University of Science and Technology, supported by the NationalScience Foundation, have set out to explore creative and effective means of teaching this systemto students. There are many segments of GIS, but for the purpose of this study we will beevaluating the transportation module created by Missouri S&T scientists and engineers tocomplement the Geographic Information System learning tool.The transportation module itself is a web-based help system that contains categories to explainhow to use many of the transportation-related capabilities of Geographic Information Systems.This module is to act as an aid to learning the application of GIS. The purpose of this study isto
computing (Wu& Hisa, 2004). These principal ICT directly enabling modern E-commerce include Web-basedcomputing, mobile computing, and ubiquitous computing (Banavar & Bernstenin, 2002; Kannanet al., 2001; Samaras, 2002).The Web-based computing was implemented based on a wirednetwork using the Internet until the ability to connect started approaching physical limit-mobility.The mobile computing based on wireless infrastructure gave rise to a new S curve, with the newphysical limits being a higher level of ubiquity and embeddedness (Lyytinen & Yoo, 2002).Over the past decade, we have witnessed the rapid developments in ICT which have substantiallychanged the landscape of E-commerce. The Internet has introduced a significant wave of
Page 15.1020.121. A Companion to Science and Engineering Indicators 2004, National Science Foundation Report. http://www.nsf.gov/statistics/seind04/c0/c0s1.htm#c0s1l4, Retrieved on March 2005.2. National Science Foundation Statistics on Women, Minorities and Persons with Disabilities in Science & Engineering, http://www.nsf.gov/statstics/wmpd/sex.htm, accessed on Jan 2010.3. Freeman, C. E., Trends in Educational Equity of Girl s and Women: 2004. Retrieved from http://nces.ed.gov/pubs2005/equity/Section9.asp.4. Bentz, N. E., & Hackett, G. (1986). Applications of Self-Efficacy Theory to Understanding Career Choice Behavior. Journal of Social and Clinical Psychology, 4, 279-289, 1986.5. Beyer, S., Rynes, K., Perrault, J., Hay, K
skills which are practical and valuable.We believe that this paper will help others to reuse, redesign and redevelop hands-on modulesfor mobile and wireless networking courses in both electrical engineering and computer scienceprograms. Some these hands-on labs could be used as either introducing laboratory modules inexisting computer network courses or to aid in the creation of new stand-alone mobile andwireless networking course.Bibliography[1] Abbott-McCune. S., Newtson, A. J., Girard , J., Goda, B. S., (2008). Developing a Reconfigurable Network Lab, Proceedings of the 9th ACM SIGITE conference on Information technology education, pp255-258[2] Cannon, K., Lab Manual for CWNA Guide to Wireless LANs, Second Edition, Thomson Course
://www.compete.org/.6. Council on Competitiveness, Spin Fiber Faster to Gain a Competitive Edge for U.S. Textile Manufacturing. 2005; Available from: http://www.compete.org/.7. Council on Competitiveness, Customized Catalysts to Improve Crude Oil Yields: Getting More Bang from Each Barrel. 2005; Available from: http://www.compete.org/.8. Council on Competitiveness, Full Vehicle Design Optimization for Global Market Dominance. 2005; Available from: http://www.compete.org/pdf/.9. Baker, M. and R. Buyya, Cluster computing: the commodity supercomputer. Software-Practice and Experience, 1999. 29(6): p. 551-76.10. Graham, S., M. Snir, and C. Patterson, Getting up to speed: The future of supercomputing. 2005: Natl Academy Pr
the student model the system provides intelligent,personalized tutoring and support to the student. In particular, based on information concerningthe knowledge level of the student in each concept of the domain knowledge, the system providesindividualized support when s/he navigates through the course material.The system uses the direct guidance technique to inform the learner whether s/he is ready to visitthe corresponding topic or if the studying of a page is unnecessary due to the fact that the studenthas already mastered the concept that is associated with this test frame. With the direct guidancetechnique, the system suggests and leads the student to the particular learning level the systemconsiders as the most appropriate for the
; Guidelines for the Future. (2004). theAmerican Society for Engineering Education. Washington, D.C.4. Z.P.Ye and P.Hua Jin. (2007). A Review of Studies on Practice Teaching of Engineering Education in China.Apr, 2007. Research in Higher Education of Engineering, China.5. Paul Kirschner and Peter Gerjets. (2006). Instructional Design for Effective and Enjoyable Computer-SupportedLearning. Jan, 2006. Computers in Human Behavior.6. John E. Brough, Maxim Schwartz, Satyandra K. Gupta , Davinder K. Anand, Robert Kavetsky and RalphPettersen. (2007).Towards the development of a virtual environment-based training system for mechanical assemblyoperations. Mar, 2007. Springer.7. P. Long, S. Liu, Y. Wu and the FDS Team. (2007). Design and Testing of the Fusion
airline database as well as the handheld device built around a 16-bit Motorolamicrocontroller (MC68HC12). RFID is a growing technology that could be used to reducenumber of mishandling luggage which was reported by the Department of Transportation to beover 1.1 million between January to June 20092 .Introduction:There are many Automatic Identification and Data Collection (AIDC) technologies that havebeen used throughout the years 1930s and 1940s. The most pervasive ones are barcode, magneticstripe, and Radio-Frequency Identification (RFID). Many experiments have been conductedwhen the barcode was first introduced in the 1940’s. The first patent of the barcode was in 1949by Bernard Silver and Norman Joseph Woodland 8. The first major application
from it. There is no doubt that it is a great idea toteach a data mining course in computer science curriculum. As you can tell, students taking adata mining course need to have background in quite a few areas to be successful. Not everystudent taking this course may have the background required in all these areas. The question ishow can an instructor remedy the challenge of teaching a group of students with widely-rangingbackgrounds, and at what level should this course be taught. Furthermore, the issue of groupwork arises, specifically as to whether data mining course projects should be accomplishedindividually or as teams.Studies show that many universities are teaching data mining course(s) within their computersscience curriculum. Each
forinstructors to imagine all the variations of how a word or phrase can be written. In the code,the list of alternatives becomes long, hindering readability. And still some correct answersare marked wrong. Either the instructor needs to examine each answer individually, or (s)heneeds to wait until students complain. There is no easy way out.When answers are longer than a single word, the difficulties compound. Many of myclasses involve programming. My students had problems with Moodle, which treatsembedded blanks as significant. For example, a blank after a parenthesis in an expressioncan cause the system to give zero credit for the answer. Moreover, several specialcharacters, including “” are discarded by the system1 before answers are graded.Worse
isolated. This paper begins with programming language comparison anddelves into network centric computing, issues in enterprise development, and leveraging the Page 15.842.2power of java in enterprise.Programming Language ComparisonThere is a plethora of programming languages and new ones are being created on a constantbasis for a number of applications. In order to provide some general guidelines for someone whowishes to decide which popular object oriented language(s) to learn and make a judiciousselection for a certain application the following table is presented to help make evaluation andcomparison depending upon the application
peer reviews. The reviewers will then upload their reviews to the system.The paper review process will remind reviewers about their tasks, and use the notificationsystem to notify all of them about any other related issues. When all reviews are collectedtrack chair(s) and conference chair will make a decision about papers being accepted orrejected for conference. Respective authors will receive a formal notification email aboutthe final decision. The authors of the accepted papers need to submit the final cameraready copy of the paper.Use Case DiagramThe use case model in general helps identifying the system in terms of functionality andrequirements. It defines the proposed functionality, helps in achieving the goals of thesystem and contains
Mile Connecting Smartphones to the Service Cloud." 2009 IEEE International Conference on Cloud Computing. Bangalore, India., 2009. 80-87.9. Zualkernan, I, S Nikkhah and M Al-Sabah. "A Lightweight Distributed Implementation of IMS LD on Google's Andriod." The 9th IEEE International Conference on Advanced Learning Technologies (ICALT2009). Riga, Latvia, 2009. 59-63. Page 15.180.13
Encyclopedia of Social Measurement, K. Kempf-Leonard, Editor. 2005, Elsevier: New York. p. 927-938.9. Stake, R.E., The Art Of Case Study Research. 1995: Sage Publications Inc.10. Guba, E.G. and Y.S. Lincoln, Fourth Generation Evaluation. 1989, Newbury Park, London, New Delhi: Sage.11. Brand, S., How Buildings Learn: What Happens After They're Built. 1994, London: Viking Penguin.12. Gibbons, A.S. and P.C. Rogers, The Architecture of Instructional Theory, in Instructional Design Theories and Models: Building a Common Knowledge Base (Vol III). 2009, Routledge. p. 305-326. Page 15.1109.12