Conference Session

Emerging Computing and Information Technologies II

Collection

2017 ASEE Annual Conference & Exposition

Authors

Hassan Rajaei, Bowling Green State University; Ramin Khakzad

Tagged Topics

Diversity

Tagged Divisions

Computing & Information Technology

to develop models to reflect the reality. Clear examples can teachstudents how to collect data, develop base model, improve it to advanced models, analyze theobtained results, and think about usability of their simulation results. These learning outcomes canclearly demonstrate valuable educational objectives.This paper, presents an example where a group of students were assigned to develop a simulationmodel for the BGSU Students Union (BTSU) Cafeteria. Managing a university cafeteria oftenexhibits challenges for the food services located in the cafeteria. One challenge regards waitingtimes. This study was focused on reducing the average waiting time of the diners in the queues,while increasing overall efficiency of the food services.The

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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Diversity

Tagged Divisions

Computing & Information Technology

-coding Learning Prior coursework and grades in Math, Physics, Chemistry, as well as specialized topics like Statistics, Drafting, Manufacturing…Team experiences Whether the student has been asked to work in a team, of what size and nature and how they perceive that experience. Student outcomes include robust data set in the form of exams, in-class assignments andhomework. This study is focusing on Computational Thinking aspects of this class, thus allreported grades are filtered to assignments that reflect CT and/or CS topics, unless otherwisestated. An example of topics omitted include questions about the general engineering designprocess

Conference Session

Emerging Computing and Information Technologies I

Collection

2017 ASEE Annual Conference & Exposition

Authors

Damla Turgut, University of Central Florida; Lisa Massi, University of Central Florida; Salih Safa Bacanli, University of Central Florida; Neda Hajiakhoond Bidoki, University of Central Florida

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Diversity

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Computing & Information Technology

mentor (11variables) on the post-survey is 4.35 (out of 5) with std = 0.97. An inspection of the Q-Qplots and histogram graphs for the remaining five variables (v2, v4, v5, v8, and v12) forwhich the confidence interval were not computed (variables not normally distributed) showone or two outliers. These outliers could be a reflection of the type of research project andthe student’s academic level.Table 2 (Evaluation 1): CISE REU Survey Constructs Differences df Std. Error 95% confidence interval Mean SmdConstructs

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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Diversity

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Computing & Information Technology

form. Thequestions are also re-designed in order to attempt to maximize activation related to cryptographyconcepts by maximizing the effort subjects exert to answer the question. We expect that thesechanges to the fMRI methods will add to our understanding of where cryptography concepts areprocessed in the brain.AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grant No.1500046. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.ReferencesAlvarez, J. A., & Emory, E. (2006). Executive function and the frontal lobes: a meta-analyticreview. Neuropsychology

Conference Session

Curricular Issues in Computing

Collection

2017 ASEE Annual Conference & Exposition

Authors

Secil Caskurlu, Purdue University; Iryna Ashby, Purdue University; Marisa Exter, Purdue University

Tagged Topics

Diversity

Tagged Divisions

Computing & Information Technology

Proceedings of the 45th ACM Technical Symposium on Computer Science Education (pp. 355-360). ACM.15 Exter, M., & Turnage, N. (2012). Exploring experienced professionals’ reflections on computing education. ACM Transactions on Computing Education (TOCE), 12(3), 12.16 Lethbridge, T. C. (2000). What knowledge is important to a software professional? Computer, 33(5), 44-50.17 Andriole, S. J. and Roberts, E. (2008). Technology curriculum for the early 21st century. Retrieved from http://cacm.acm.org/magazines/2008/7/5359-point-counterpoint- technology-curriculum-for-the-early-21st-century/fulltext 21Formal