Conference Session

Curricular Issues in Computing

Collection

2017 ASEE Annual Conference & Exposition

Authors

Sreyoshi Bhaduri, Virginia Tech; Tamoghna Roy, Virginia Tech

Tagged Divisions

Computing & Information Technology

byorganizations and often reflect the college’s unique vision which sets it apart from peerinstitutions. Analytical techniques which rely on word usage, semantic information, andmetadata information can be used to generate powerful descriptive models with allow us toobtain relevant information from text-based data. This study presents a Natural LanguageProcessing (NLP) based textual data analytical approach using Term Frequency-InverseDocument Frequency (tf-idf) to study the mission statements of engineering colleges/schools. Atotal of 59 engineering colleges/schools: 29 public, and 30 private, across the United States wereanalyzed in this study. Results of this study indicate that there is indeed a difference in tf-idfscores for public versus private

Conference Session

Curricular Issues in Computing and Information Technology Programs II

Collection

2017 ASEE Annual Conference & Exposition

Authors

Chaomin Luo, University of Detroit Mercy; Jiawen Wang, University of Detroit Mercy; Wenbing Zhao, Cleveland State University; Lei Wang, Anhui Polytechnic University

Tagged Divisions

Computing & Information Technology

) in close relation to the content/robot programming (the C). The multi-lab-driven method(MLDM) was employed to construct the TCK of ROS of students in the context of designing anautonomous mobile robot system. A sequence of multiple labs were assigned to students to covervarious topics in the ROS. A variety of labs that reflect the ROS experiments and assist studentsin better understanding robotics programming were elaborately managed. Based on students’performance on various lab assignments, lab reports, presentations, the final robot project,students’ input to the official course evaluation administered by the university, and a comparisonto the instructor’s previous years of teaching experience, we propose that the MLDM is effectivein

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)

Tagged Topics

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

Tagged Topics

Diversity

Tagged Divisions

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

Tagged Topics

Diversity

Tagged Divisions

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

Emerging Computing and Information Technologies I

Collection

2017 ASEE Annual Conference & Exposition

Authors

Brian Patrick, Brigham Young University; Richard G. Helps, Brigham Young University

Tagged Divisions

Computing & Information Technology

audience time only masked the significance of the usability data with an activity thatdid not reflect usability, but merely represented passive reception. All tasks were re-analyzed and certainprocedures were modified to focus on activities that indicated differences in usability. The testing timeoverall has been reduced from the initial design of several hours per user (four platforms, nine tests) toabout 20 minutes per platform or about 45 minutes for a complete single user experience (two platforms,three tests). It would have been difficult and expensive to recruit a statistically significant number ofusers to complete a set of tasks lasting several hours per user.One of the difficulties of measuring cross-platform occurs when the app

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

Conference Session

Emerging Computing and Information Technologies I

Collection

2017 ASEE Annual Conference & Exposition

Authors

Tamer Omar, East Carolina University; Philip J. Lunsford II, East Carolina University

Tagged Divisions

Computing & Information Technology

resources, lab materials (questions templatesand manual), operating systems, software applications and programs are required at least everytwo years. Due to the continuous advancement of technology, the different resources, systems andtools used to implement the network security lab environment must be regularly reviewed to ensurethat the lab environment reflects the current technology used in industry.The rest of the paper is organized as follows. In section two a background about the lab modelincluding lab structure, components, lab support system and the tools used are presented. Sectionthree demonstrates the evaluation methodology. Analysis of the student survey, and feed-backregarding their lab experience during the course and the lessons

Conference Session

Potpourri

Collection

2017 ASEE Annual Conference & Exposition

Authors

Abdulwaheed Johnson, Pace University; Anthony Joseph, Pace University

Tagged Divisions

Computing & Information Technology

andStarbucks applications. Most of the interviewees touted the efficiency of these mobile paymentapplications, as well as the targeting of deals and customer rewards as attractive features, butwhen asked why they do not use these applications their answers ranged from inconvenience,uncertainty regarding the benefits of the payment platform, and mistrust of the platformregarding privacy of their personal information. It is noteworthy, that the privacy of personalinformation is a factor that encourages adoption in the NFC platform, but discourages adoptionof online mobile payment platforms. This is reflected in Figure 5 which shows that adopters ofNFC payment and cash payments are more sensitive towards disclosure of PII with a scoresignificantly above