AC 2011-1690: REPORTING ON THE USE OF A SOFTWARE DEVELOP-MENT CASE STUDY IN COMPUTING CURRICULAMassood Towhidnejad, Embry-Riddle Aeronautical Univ., Daytona Beach Massood Towhidnejad is a tenure full professor of software engineering in the department of Electrical, Computer, Software and System Engineering at Embry-Riddle Aeronautical University. His teaching interests include artificial intelligence, autonomous systems, and software engineering with emphasis on software quality assurance and testing. He has been involved in research activities in the areas of software engineering, software quality assurance and testing, autonomous systems, and human factors.Thomas B Hilburn, Embry-Riddle Aeronautical Univ., Daytona
because it caused the students to review thework at an earlier time to participate. Figure 3. Domain engineering roadmap emphasizing individual contributions Table 3. Term paper topic influenced by individually- or group-led topic in classStudent Basic Topic Led Advanced Topic Led Term Paper Topic (k) on “Reusability Grace (a) Re-engineering for Reuse Metrics” (k) on “Software Product Dave (b) Measurement and Experimentation
accelerated courseAs Table 1 and 2 show, the overall correlation to regular exam scores for the regular courseremained roughly the same. However, the correlation of the predictive exam to the overallcourse grade increased from 0.33 to 0.39. In addition, the results in Table 3 show that theaccelerated course had an even greater correlation of 0.48. This shows that the questionrefinement technique discussed previously, along with the addition of new and related questions,was effective in increasing the predictive abilities of the exam. A final analysis was done usingthe same ad hoc technique that was used with the Fall 2009 data. The results of this werecombined for both versions of the course and are presented in Figure 2. Appendix B lists
AC 2011-1726: USING VERTICALLY INTEGRATED PROJECT TEAMSTO INSPIRE STUDNET INTEREST IN COMPUTING CAREERSMassood Towhidnejad, Embry-Riddle Aeronautical Univ., Daytona Beach Massood Towhidnejad is a tenure full professor of software engineering in the department of Electrical, Computer, Software and System Engineering at Embry-Riddle Aeronautical University. His teaching interests include artificial intelligence, autonomous systems, and software engineering with emphasis on software quality assurance and testing. He has been involved in research activities in the areas of software engineering, software quality assurance and testing, autonomous systems, and human factors.Thomas B Hilburn, Embry-Riddle Aeronautical Univ
course currency is called Knowledge Gold (KG). The following rules govern the use ofcurrency in the three term sequence: 1. All students start with 0 KG at the beginning of the year. Page 22.1091.10 2. KG is tracked by the instructor for each individual in the course. It is the student responsibility to make sure KG credit is properly recorded. 3. KG will be retained across quarters. 4. KG may be obtained by: a. Completing tasks as stipulated by the instructor. b. Asking good questions. c. Chapter write-ups. d. Research into a technical area related the course topics or topics directly related to
of developing the outcomes and course materials for this project, wehave encountered a number of challenges that pose potential risks for institutions that intendto adopt our work. In this section we identify those risks, while in the next section weprovide a number of strategies that serve to mitigate the risks. The challenges we haveencountered in implementing a more communication-intensive curriculum can be groupedinto four non-exclusive categories: a) Curricular issues, b) Instructional issues, c) Logistical issues, and d) Motivational issues.Curricular issues are primarily concerned with identifying how to best incorporatecommunication skills into a larger degree program. The biggest issue is the add/subtractproblem
algorithm visualizations. ACM SIGCSE Bulletin 32 (2000), 109-113.[11] R. Baecker. Sorting Out SORTING: A Case Study for Teaching Software Visualization in Computer Science, in: J. T. Stasko, M. H. Brown, and B. A. Price, editors. Software Visualization, MIT Press, Cambridge, MA, 1997[12] L. Stern, L. Naish, H. Sondergaard. Algorithms in Action. http://www.csse.monash.edu.au/˜dwa/Animations/index.html, 2000. Page 22.1621.14[13] B. Thompson, D. J. Pearce, C. Anslow, G. Haggard. Visualizing the computation tree of the Tutte polynomial. In SOFTVIS’08: Proceedings of the ACM Symposium on Software Visualization. Herrsching
. Coelho and G. Murphy. ClassCompass: A software design mentoring system. ACM Journal on Educational Resources in Computing, 7(1):Article 2, Mar. 2007. [3] M. Dahm. Grammar and API for Rational Rose petal files. http://crazybeans.sourceforge.net/CrazyBeans/doc/grammar.pdf, 2001. Retrieved January, 2011. [4] C. R. B. de Souza, H. L. R. Oliveira, C. R. P. da Rocha, K. M. Gonc¸alves, and D. F. Redmiles. Using critiquing systems for inconsistency detection in software engineering models. In SEKE, pages 196–203, 2003. [5] A. Egyed. UML/Analyzer: A tool for the instant consistency checking of UML models. In Proceedings of the 29th International Conference on Software Engineering, pages 793–796. IEEE Computer Society, 2007. [6] M
integrated manner than currentpractice, and (b) to introduce team- and project-based software engineering activities in a lowrisk, high student involvement setting in order to create a smoother learning curve for students.This paper contributes: • A discussion of the learning theory foundations for our approach, based on experiential learning targeted at increasing student motivation; • A minimally disruptive framework for better integrating software engineering education within a computer science curriculum by elaborating our course design plan, and providing a description of areas that required particular care; and, • A presentation of quantitative and qualitative evaluation results, based on student surveys, evaluation based
similarities. To theextent that these factors seem to be correlated with administrative housing, perhaps theinstitutional context has shaped the character of the program more.Table 2 summarizes the data relative to the overall content of the technical curricular componentand the degree to which it reflects required coursework. Table 2(a) gives the relevant data forcomputer engineering programs, while Table 2(b) and Table 2(c) summarize this information forcomputer science and software engineering programs. Some interesting patterns emerge whenthis data is analyzed. First, the relative size of the technical component in the computerengineering and software engineering programs is similar – an average of about 51% of the totalcurriculum is technical in
AC 2011-1786: WORKING TOWARDS THE STUDENT SCRUM - DEVEL-OPING AGILE ANDROID APPLICATIONSThomas Reichlmayr, Rochester Institute of Technology I am an Associate Professor in the Department of Software Engineering at the Rochester Institute of Technology. Prior to transitioning to my academic career, I worked as a software engineer in the process automation industry in a variety of roles over a span of twenty five years. My teaching and research interests include the development of undergraduate software engineering curriculum, especially at the introductory level. Of primary interest is the study of software development process and its application to course curriculum and student team projects