A: Ability to determine the scope of a software project by taking into account various constraints. B: Ability to develop a software project plan. C: Ability to enact a software project plan. D: Ability to estimate various software project parameters. E: Ability to measure and control software products and processes. F: Ability to manage software project risk. G: Ability to lead a diverse team of software developers.Figure 1: Self-assessed contribution of course
many GEs used in previous works,this focuses on the list of GEs that have been used in in the areas of CS and SE education. Basedon our literature review, we identified eleven commonly used GEs in the educational contexts.We have provided brief descriptions of each GE below.Points (Pt): These are the rewards that are assigned to the students for the completion ofa particular task. The point system is used as measure of success or an achievement.Badges (B): These are represented as a token of achievement. These are also rewards thatare assigned to students when they complete a particular task or when they reach a goal.Leaderboards (Lb): These create a competitive environment among the students. Aleaderboard is the board that displays the
): “Engineering design case studies: effective and sustainable development methods”, proc. ASEE Annual Conference, Louisville, Kentucky.17. Acharya, S., Manohar, P., and Wu, P. (2016): “Using Case Study Videos to Effectively Teach Software Development Best Practices”, Proceedings of 2016 World Multi-Conference on Systemics, Cybernetics, and Informatics, Orlando, FL18. Pressman, R. and Maxim, B. (2015): Software Engineering; A Practitioner’s Approach, McGraw-Hill, 2015.19. Robert Morris University Software V&V Fundamentals, https://sites.google.com/a/rmu.edu/rmu-nsf/v-v-fundamentals, retrieved February 3, 2017.
Paper ID #24279A Re-look at the Introduction to Software Engineering CourseDr. James R Vallino, Rochester Institute of Technology (COE) Jim Vallino has academic and industrial experience across a broad range of engineering disciplines. His academic training includes a B.E. in mechanical engineering, a M.S. in electrical and computer engineer- ing, and after more than 16 years in industry, received a M.S. and Ph.D. in computer science. While in industry, he worked in small and large companies doing product development and industrial research. His responsibilities included both hardware and software development at AT&T
Utility of the course content and methodologyStudents answered six open questions related to the perceived difficulty in developing aproject before and after the course, the contributions and the strengths that user-centeredmethodologies add to the software product, as well as the self-confidence to tackle a softwaredesign project before and after the course.Table 1Student profiles. ProfileProfiles A B C D Engineering Advanced Knowledge Basic knowledge of Advanced knowledge of SE oriented to programming knowledge of SE
University of Michigan-DearbornAdvancement of Teaching and Learning Fund.Bibliography1. Maxim, B. R.; Decker, A.; and Yackley, J. J. (2019) “Student Engagement in Active Learning Software Engineering Courses”, Proceedings of 49th IEEE Annual Frontiers in Education Conference, Cincinnati, OH, October 2019 (F3G1-F3G5).2. Branch R. (2010) Instructional Design: The ADDIE Approach, Springer, 2010.3. Samavedham, L. and Ragupathi, K. (2012) “Facilitating 21st century skills in engineering students,” The Journal of Engineering Education, Vol. XXVI No. 1, 2012, pp.38-49.4. Promoting Active Learning (2016) https://utah.instructure.com/courses/148446/pages/active-learning, retrieved February 25, 2016.5. Prince, M., (2004
. (2017b). Preliminary Findings on Software Engineering Practices in Civic Hackathons. 2017 IEEE/ACM 4th International Workshop on CrowdSourcing in Software Engineering (CSI-SE), 14–20. https://doi.org/10.1109/CSI-SE.2017.5Gama, K., Alencar Gonçalves, B., & Alessio, P. (2018). Hackathons in the formal learning process. Proceedings of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education - ITiCSE 2018, 248–253. https://doi.org/10.1145/3197091.3197138Gary, K. (2015). Project-Based Learning. Computer, 48(9), 98–100. https://doi.org/10.1109/MC.2015.268Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research
Paper ID #17765Applying Scrum to Manage a Senior Capstone ProjectDr. Zesheng Chen, Indiana University Purdue University, Fort Wayne Dr. Chen is an assistant professor in the Department of Computer Science at Indiana University - Pur- due University Fort Wayne. He received his M.S. and Ph.D. degrees from the School of Electrical and Computer Engineering at the Georgia Institute of Technology in 2005 and 2007. He also holds B.E. and M.E. degrees from the Department of Electronic Engineering at Shanghai Jiao Tong University, Shang- hai, China in 1998 and 2001, respectively. He worked as an assistant professor in the Department of
Paper ID #23952Work in Progress: One Approach to Software Engineering Project Selectionfor Small Student PopulationsDr. Paul A Bender, Ohio Dominican University Paul Bender is an Assistant Professor of Software Engineering at Ohio Dominican University in Colum- bus,OH. He previously taught Computer Science at McNeese State University in Lake Charles, LA. He holds a B.S. in Computer Science from Missouri State University, Springfield, MO, an M.S. in Computa- tional Mathematics from Ohio University, Athens, OH, and a Ph.D. in Computer Science and Engineering from Wright State University, Dayton, OH. These degrees were
Paper ID #33764Reverse Software Engineering as a Project-Based Learning ToolMs. Cynthia C. Fry, Baylor University CYNTHIA C. FRY is currently a Senior Lecturer of Computer Science at Baylor University. She worked at NASA’s Marshall Space Flight Center as a Senior Project Engineer, a Crew Training Manager, and the Science Operations Director for STS-46. She was an Engineering Duty Officer in the U.S. Navy (IRR), and worked with the Naval Maritime Intelligence Center as a Scientific/Technical Intelligence Analyst. She was the owner and chief systems engineer for Systems Engineering Services (SES), a computer systems design
Paper ID #23289Crafting the Future of Computing Education in CC2020: A WorkshopDr. Stephen T Frezza, Gannon University Deacon Steve Frezza, PSEM is a professor of Software Engineering and chair of the Computer and In- formation Science department at Gannon University in Erie, PA. His research interests include Global Software Engineering, Affective Domain Learning, Engineering Education Research, as well as Philos- ophy of Engineering and Engineering Education. He is regularly involved in supporting the regional entrepreneurial ecosystem, as well as projects that serve the regional community. He is an active member
Paper ID #18882A Case Study in Teaching Agile Software Product Line DevelopmentDr. Derek David Riley, Milwaukee School of Engineering Dr. Riley completed his PhD work in modeling and simulation at Vanderbilt University in 2009 and has expanded his scholarly and professional activity to include mobile computing and software engineering. He is currently a faculty member at the Milwaukee School of Engineering. c American Society for Engineering Education, 2017A Case Study in Teaching Agile Software Product Line Development Derek Riley Milwaukee School of
Paper ID #30235A Course as Ecosystem: Melding Teaching, Research, and PracticeDr. Edward F. Gehringer, North Carolina State University Dr. Gehringer is an associate professor in the Departments of Computer Science, and Electrical & Computer Engineering. His research interests include computerized assessment systems, and the use of natural-language processing to improve the quality of reviewing. He teaches courses in the area of programming, computer architecture, object-oriented design, and ethics in computing. c American Society for Engineering Education, 2020 A Course as Ecosystem: Melding
Paper ID #29451WIP: Lessons Learned from Applying Standards Based Grading to a Soft-wareVerification CourseDr. Walter W Schilling Jr., Milwaukee School of Engineering Walter Schilling is a Professor in the Software Engineering program at the Milwaukee School of Engi- neering in Milwaukee, Wisconsin. He received his B.S.E.E. from Ohio Northern University and M.S. and Ph.D. from the University of Toledo. He worked for Ford Motor Company and Visteon as an Embedded Software Engineer for several years prior to returning for doctoral work. He has spent time at NASA Glenn Research Center in Cleveland, Ohio, and consulted for
Paper ID #21837Measuring Broader Impact of NSF-funded Project on Software EngineeringEducationDr. Sushil Acharya, Robert Morris University Sushil Acharya, D.Eng. (Asian Institute of Technology) is the Assistant Provost for Research and Gradu- ate Studies. A Professor of Software Engineering, Dr. Acharya joined Robert Morris University in Spring 2005 after serving 15 years in the Software Industry. His teaching involvement and research interest are in the area of Software Engineering education, Software Verification & Validation, Software Security, Data Mining, Neural Networks, and Enterprise Resource Planning. He also
results examine several factors influencing the success of a partnership, including differencein cumulative grade point average (GPA), gender balance, and work habits like starting projectsearly. After controlling for GPA, we observed an association between starting projects early andincreased performance on both exams and projects. The impact was greatest among those in thelowest GPA quartile, where an early start made the difference between an average final lettergrade of C+ (lowest early-start quartile) and B- (highest early-start quartile).1 Introduction and Related WorkAn important goal of group work in education is to increase student learning of course material.In computer science courses, group work often takes the form of pair
theirprofessional toolset, refactoring is taught only late in the traditional computing curriculum.A valuable outcome of our study was an educational intervention that really pushes the bound-aries of what is possible to teach to novice programmers, those who have never had any priorprogramming experience. The unique aspect of our study was teaching the very fundamentalsof programming simultaneously with the principles and mechanics of refactoring and automatedrefactoring support required to remove code duplication. In particular, the study participants wentthrough a learning experience, guided by an online interactive tutorial that taught them E XTRACTC USTOM B LOCK1 , the refactoring transformation that replaces duplicate code snippets with calls toa
Paper ID #25343Teaching and Assessing Sustainability Based on the Karlskrona ManifestoDr. Ing. Ivan Cabezas, Universidad de San Buenaventura Ivan Cabezas was born in Colombia in 1973. He received the B. Eng. in Computer Science and the Engineering Ph. D. degrees from Universidad del Valle, in 2004 and 2013, respectively. He is a member of IEEE and ASEE. Engineering education and sustainability concerns during the software engineering design process are among his research interests. He has been working as a full-time professor in the Soft- ware Systems Engineering program at the Engineering School of the Universidad de San
Paper ID #22449Why Educators Need to Team with Industry Professionals in Software Devel-opment EducationDr. Gregory Kulczycki, Virginia Tech Dr. Kulczycki has extensive experience in research and development both in academia and industry. He received his doctorate from Clemson University in 2004 and began working as a professor at Virginia Tech shortly thereafter. In 2011 he went to work for Battelle Memorial Institute as a cyber research scientist, while continuing to be involved in teaching. He is currently back in the computer science department at Virginia Tech as a professor of practice, where he teaches, designs
experience when doing the reading reflection assignments. We alsohope to follow these students and see how successful they are in their Senior Design courses overthe next year.AcknowledgmentsThis project was partially supported by a grant from the University of Michigan-DearbornAdvancement of Teaching and Learning Fund.Bibliography1. Maxim, B. R.; Decker, A.; and Yackley, J. J. (2019) “Student Engagement in Active Learning Software Engineering Courses”, Proceedings of 49th IEEE Annual Frontiers in Education Conference, Cincinnati, OH, October 2019 (F3G1-F3G5).2. Branch R. (2010) Instructional Design: The ADDIE Approach, Springer, 2010.3. Samavedham, L. and Ragupathi, K. (2012) “Facilitating 21st century skills in engineering
the student course evaluations are reported in Table 4. Students answered eachquestion on a five-point Likert scale where 5 is “Strongly Agree” and 1 is “Strongly Disagree”.Table 4. Engineering Student Course Evaluations Fall 2015 Fall 2016 Section A Section B Section A Section B Evaluation Question (Response Rate: (Response Rate: (Response Rate: (Response Rate: Average 14 of 16 enrolled 14 of 18 enrolled 16 of 17 enrolled 11 of 12 enrolled students, 87.5%) students, 77.8%) students, 94.1%) students, 91.7
of the QA strategy,engineering choices, and conclusions. Learning outcomes pertaining to analysis (see above) are hence assessed by assignment sheets,and learning outcomes pertaining to design and development are assessed by the project. Amidterm and a final exam assess a selection of all learning outcome categories. In the face-to-facecourse, all exams were completed on paper, while projects and assignments sheets were preparedand submitted digitally. In-class examples were facilitated using a combination of digital slidesand physical dry erase board, as appropriate. B. HyFlex Implementation Approach The SQA course taught during fall 2020 enrolled 17 students. Course meetings took placeTuesdays and Thursdays for 1 hour and 20
outcomes assessment after everyoffering. Applicable ABET Criterion 3 Learning Outcomes is listed in Table 5.Table 5: Applicable ABET Criterion 3 Learning Outcomes for Software V&V course at author’s institution b. An ability to design and conduct experiments, and analyze and interpret data c. an ability to design a system, component or a process to meet desired needs e. An ability to identify, formulate, and solve engineering problems f. An understanding of professional and ethical responsibilities g. An ability to communicate effectively h. Broad education necessary to understand the impact of engineering solutions in a global and societal context i. Recognition of the need for and an ability to engage in life-long learning. j. A knowledge
for effective software engineering includeknowledge of the: software process – requirements, design, validation and evolution; and toolsand techniques (a) to model various artifacts in the requirements and design phases, (b) supportverification and validation, and (c) maintenance activities post software deployment. The non-technical (soft) skills include effective: communication, team management and participation, andtime management, among others.In this paper we present our experiences of integrating learning and engagement strategies (LESs)into face-to-face (F2F) learning environments with the expectation of improving student learningand engagement for both software engineering and software testing undergraduate classes. Theexperiences
reflections written by four students working on the same web application. Three themeswith four subthemes emerged from the data 1) how students perceived learning a) technical and b) professional skills, 2) how students perceived they were accomplishing project goals, and 3) the perceived relationship they had with the community partner a) the impact of their project and b) the impact of the community on themselves.This section will focus on unpacking each theme with supported quoted evidence from thereflections.Theme 1: Learning The first theme that emerged involved the perceived knowledge the students were acquiring.The knowledge ranged from technical software skills they learned in order to contribute
navigationrequirements resembled the following, starting from the project objective and growing morespecific as you go down in hierarchy: 1. The team shall design and demonstrate capabilities of an autonomous vehicle. (a) The cart shall accelerate when given the appropriate software command (i) On human intervention (i.e. a keypress), all autonomous acceleration instructions Figure 7: Connection Hub software architecture concept shall cease. (ii) The commanded acceleration shall not exceed appropriate speed limits for the areas traversed (iii) ... (b) The cart shall slow when given the appropriate software command (c) The cart shall turn when given the
adedicated private channel. The workspace for each CS course has similar message report. Tosave space, they are not included in this paper.It can be seen in Figure 6(a) that daily active members fluctuate through time, and moremembers are active viewing messages than posting messages. Figure 6(b) shows the portions ofmessages sent through public channels, private channels, and direct messages. Please note thatthe value in private channels reflect the aggregated number of messages sent in all coursechannels. Over all time, messages sent in private channels compose 78% of all messages.However, there are certain periods of time when direct messages dominate the workspacecommunication. (a) Data analytics of the number of active
study will consist of the followingcomponents: a. Case Study Description: This document provides complete information of this active learning tool. It has four categories of information. The first part provides general information about the case study and includes details like the software security focus topic area, module name, prerequisite knowledge, learning outcomes, keywords, expected delivery duration, description of the scenes, and student exercise. The second part describes the instruction and assessment procedure. The third part has a list of possible discussion questions by scene. The final part of this document depicts the survey instrument. b. Student Handout: Student Handout includes
engagedin the discussion board. They learned new approaches and techniques they had not previouslyconsidered, they helped one another, encouraged each other and shared their code.References[1] A. Rosenstein, A. Raghu, and L. Porter. “Identifying the Prevalence of the ImpostorPhenomenon Among Computer Science Students.” In Proceedings of the 51st ACM TechnicalSymposium on Computer Science Education. 2020. Portland, Oregon.[2] R. Ball, L. Duhadway, K. Feuz, K., J. Jensen, B. Rague, and D. Weidman. “ApplyingMachine Learning to Improve Curriculum Design”. In In SigCSE '19 (ACM TechnicalSymposium on Computer Science Education 2019). Minneapolis, Minnesota.[3] L Barker, K. Garvin-Doxas, and E. Roberts E. “What can computer science learn from a
Figure 2. Emulator view of Mapbox’s “route navigation” and “making phone calls” featuresFigure 1 illustrates iTrust artifacts’ processing. Three Eclipse plug-ins are shown: Figure 1-Alists a set of to-be-indexed requirements, Figure 1-B outputs the indices of the input requirement,and Figure 1-D outputs the indices of a Java method that is selected as the to-be-indexed sourcecode artifact (cf. Figure 1-C). The development of Eclipse plug-ins was allocated to the first twolabs in the spring 2015 semester, as shown in Table 1. Similar development tasks were assignedin the spring 2016 semester, though the students worked on direct feature extensions of Mapbox(cf. Figure 2). In both semesters, the last two labs put more emphasis on