Paper ID #33251Understanding Non-Traditional Students in Engineering and Computing(Work in Progress)Dr. Stephen Secules, Florida International University Stephen is an Assistant Professor of Engineering and Computing Education at Florida International Uni- versity. He has a prior academic and professional background in engineering, having worked profession- ally as an acoustical engineer. He has taught a number of courses on engineering and education, including courses on engineering design, systems in society, and learning theories. Stephen’s research interests include equity, culture, and the sociocultural dimensions of
variables varied slightly. However, the effectiveness of assessments in spring2007 was tenuous. The paper concludes by discussing the implications of the results aswell as outlining next steps in the assessment process for the course. IntroductionThe intent of the Computer Engineering Technology capstone course (ELET 4308) is toprovide students with a dynamic learning environment that simulates industryexpectations (e.g. deadlines and production of deliverables). The assessment andevaluation structure of the course encourages active participation and exposes students toall phases of the project development life cycle. Technical depth of the subject, teamwork, planning, scope, student commitment and successful
Paper ID #18633Partnership Characteristics and Student Performance in an Introductory Com-puter Science CourseCharles Kowalec, University of Michigan Charles Kowalec is an undergraduate student at the University of Michigan interested in the science of how students learn.Dr. Andrew DeOrio, University of Michigan Andrew DeOrio is a lecturer at the University of Michigan and a consultant for web, machine learning and hardware projects. His research interests are in ensuring the correctness of computer systems, including medical devices, internet of things (IOT) devices, and digital hardware. In addition to teaching software
. Studying these interactions and mediations is complicated by being within those samesystems [7]. We worked to operationalize intersectionality both within the workshop content andin our design and delivery of the workshop.An Intersectional Design IntentionAs our end goal is to enact a systems change, we are keenly aware that power dynamics andother issues of intersectionality must be addressed. As members of this community, we have hadthe opportunity to learn from leaders in the field about racial marginalization in computing andengineering spaces, the influence of disability on participation in computing and engineering,and the long history of gender-focused initiatives that have centered women in the past and arebeginning to include TNB people
|10⟩ state in a 2-qubit space. At the top is thequantum circuit, and below is the histogram of measurement outcomes for 1024 runs of thismeasurement.CONCLUSIONS AND FUTURE WORKThis paper summarizes the creation of a new quantum computer engineering course using anopen access quantum computer to facilitate learning. Based on the results from teaching the firstsemester of this course, I plan to refine and improve the overall course. One key goal is toincorporate more hands-on exercises with quantum computers. The graduate-level students wererequired to complete more computing exercises compared to the senior-level students, and thefeedback from the graduate students was that they understood the concepts better afterperforming the exercises. My
Paper ID #22611High-Achievers Scholarship Program in Computer Science and MathematicsDr. Rahman Tashakkori, Appalachian State University Rahman Tashakkori received his PhD in Computer Science from Louisiana State University in 2001. He is currently serving as the Chair and Lowe’s Distinguished Professor of Computer Science at Appalachian State University. He has led several NSF projects that include CSEMS, S-STEM, STEP, and RET.Dr. Cindy Norris, Appalachian State University Dr. Cindy Norris is a Professor in the Department of Computer Science at Appalachian State University. She received her PhD in Computer Science from the
Paper ID #25290Human vs. Automated Coding Style Grading in Computing EducationJames Perretta, University of Michigan James Perretta is currently pursuing a master’s degree in Computer Science at the University of Michigan, where he also develops automated grading systems. His research interests and prior work focus on using automated grading systems and feedback policies to enhance student learning.Dr. Westley Weimer, University of MichiganDr. Andrew DeOrio, University of Michigan Andrew DeOrio is a teaching faculty member at the University of Michigan and a consultant for web and machine learning projects. His research
. Girls met three female professors in engineering including NDSU distinguished professor Dr. Kalpana Katti in Civil and Environmental Engineering, Women-In- Research Chair Dr. Yechun Wang in Mechanical Engineering and Vice President of IEEE Red River Valley Section Dr. Na Gong in Electrical and Computer Engineering. Touring research laboratories in ECE. The girls also toured research laboratories in ECE. During the tour, they were introduced to different research equipment and various research projects. Learning outstanding senior design projects: The outstanding senior design groups introduced and demonstrated their senior design projects to the girls. Meeting ECE female undergraduate and graduate Students
2793principles to freshmen who had not had any programming experience. These freshmen weretypically not the students who were heading for an Electrical and Computer Engineering majorand had some anxiety over the prospect of having to learn how to program. Looking back totheir own experiences and those of their “non-EE” friends, the instruction team concluded thatthe best way to learn how to program is to “just do it.” They developed a totally hands-onProgramming Preparation Course.The Programming Preparation CourseThe curriculum for this program was guided by the “pre-test” that is given by the ComputerScience Department to all students who are beginning their programming course. This testaddresses the topics that the students are expected to be
Technologists) project. Since September 2016, she co-leads the NSF STEM+C project, Curriculum and Assessment Design to Study the Development of Motivation and Computational Thinking for Middle School Students across Three Learning Contexts, that builds on TECHFIT. Professor Harriger’s current interests include outreach to K-12 to interest more students to pursue computing careers, applying IT skills to innovating fitness tools, and wearable computing.Suyash Agrawal, Purdue University Suyash Agrawal is currently pursuing M.S.(2019) in Computer Information Technology from Purdue University. He received his B.S.(2014) in Information Technology from JSSATE, Noida, India and then worked at Nokia as a software developer. His
China has experienced three major periods:knowledge oriented period, cognitive tools oriented period and universal value oriented[7]period.In the first period (1960s-1995), the majority of computing education was educatingcomputing knowledge and skills. Lecturers aimed to promote students' competence byimproving students' programming skills and using computer language. Time to the newcentury (1995-2003), computing education gradually evolved from "knowledge learning" to"tool utilization" that concentrated on improving students’ ability to use informationtechnology to solve problems. For the third period (2003-present), the widespread use of bigdata, cloud computing and mobile communication technologies have created a completelynew digital
, streaming algorithms, and graph visualization. She also devotes research time to the study of computer science education in underrepresented and low income pop- ulations. One of Theresa’s current projects involves teaching programming and computational thinking at jails in SLO county; a project in which she has involved several Cal Poly Computer Science students.Dr. Lizabeth T Schlemer, California Polytechnic State University, San Luis Obispo Lizabeth is a Associate Dean at Cal Poly, SLO. She has been teaching for 22 years and has continued to develop innovative pedagogy such as project based, flipped classroom and competency grading. Through the SUSTAIN SLO learning initiative she and her colleagues have been active
Paper ID #14470Encouraging Student Innovation in a Freshman-Level Computer Science CourseMs. Cynthia C. Fry, Baylor University Cynthia C. Fry is a Senior Lecturer of Computer Science and the Director of the Computer Science Fel- lows program at Baylor University. She teaches a wide variety of engineering and computer science courses, deploys a series of faculty development seminars focused on Curiosity, Connections, and Cre- ating Value, and works collaboratively and remotely with a series of colleagues on the development of EML-based courses. She is a KEEN Fellow.Dr. Kenneth W. Van Treuren, Baylor University Ken Van
Paper ID #14616WIECE: Women Undergraduates in Electrical and Computer EngineeringSummer Research ProgramDr. Jinhui Wang, North Dakota State University Dr. Jinhui Wang has been an Assistant Professor in the Department of Electrical and Computer Engineer- ing at North Dakota State University (NDSU), since Aug. 2014. His research interests include low-power, high-performance, and variation-tolerant integrated circuit design, 3D IC and EDA methodologies, and thermal issue solution in VLSI. He has more than 80 publications and 6 patents in the emerging semicon- ductor technologies. Dr. Wang has been with the editorial board of
using the learning management system. While the current approach allows forstudents to track their development it separates the documentation of professional skillsperformance from the technical content. Using electronic portfolios will allow students to alsointegrate artifacts showing their technical skill performance next to their professional skillsdevelopment.AcknowledgementThis work was supported by the National Science Foundation, IUSE/Professional Formation ofEngineers: Revolutionizing Engineering and Computer Science Departments (RED) under GrantEEC-1519438.References[1] M. Hoffmann and J. Borenstein, “Understanding Ill-Structured Engineering Ethics Problems,’’Science and Engineering, vol. 20, no. 1, pp. 261-276, 2014.[2] E. Alpay
AC 2007-1072: INTRODUCING ZIGBEE THEORY AND PRACTICE INTOINFORMATION AND COMPUTER TECHNOLOGY DISCIPLINESCrystal Bateman, Brigham Young University Crystal Bateman is an Undergraduate Student at BYU studying Information Technology. Her academic interests include ubiquitous technologies and usability. She is currently finishing an honors thesis on using mobile ZigBee motes in a home environment, and enjoying life with her husband and two daughtersJanell Armstrong, Brigham Young University Janell Armstrong is a Graduate Student in Information Technology at BYU. Her interests are in ZigBee and public key infrastructure. She has three years experience as a Teacher's Assistant. Student
corresponding increase in administrationoverhead. In addition, it was determined that requiring the students to learn the proper Xencommand usage and syntax could detract from the overall learning objectives, so a simplerinterface was required; one that would require a minimal learning curve. Finally, it wasdetermined that providing students command line access on the Xen Worlds server could be asecurity risk without a dedicated system administrator maintaining a proper configuration.The solution for addressing the scalability issue was to use a small cluster of diskless computersthat would use a single 1U computer for network booting and system services. The current XenWorlds configuration consists of 8 diskless computers, each with a Celeron 2.0GHz
lab exercises, they musttherefore be well prepared prior to conducting the hands-on activities. In this regards, this paperproposes that the computer simulation tools offer a wonderful opportunity to enhance the Page 24.524.3teaching – learning process. The paper describes a couple of process simulation and visualizationtools developed by the students at the authors’ institution as part of their project work.Over the past three decades a number of computer based expert systems have been developedaround the world for a more efficient solution of manufacturing problems in several areas suchas diagnostic, design, planning, scheduling, process
Paper ID #10694C-STEM Curriculum for Integrated Computing and STEM Education (Cur-riculum Exchange)Prof. Harry H. Cheng, University of California, Davis Harry H. Cheng is a Professor in the Department of Mechanical and Aerospace Engineering, Graduate Group in Computer Science, and Graduate Group in Education at the University of California, Davis, where he is also the Director of the UC Davis Center for Integrated Computing and STEM Education (http://c-stem.ucdavis.edu) and Director of the Integration Engineering Laboratory. His current research includes developing computing and robotics technologies and integrate them into
, and lessons learned that are described here may be helpful to others contemplating a similar course, or those anticipating a revision to an existing computer engineering design course.1 IntroductionTypically, computer engineering design courses are forced to use outdated and/or simpler technolo-gies in order to facilitate student fabrication and testing, since modern devices in ’student friendly’packages are not readily available. We made a radical shift in methodology when redesigning ourembedded systems design course. This was done to expose our students to a realistic design en-vironment. In particular, we wanted to ensure that our students worked with more modern toolsand concepts while ensuring that they still did actual
, but their overarching role is to build higher-levelfunctionality from those components.The curriculum is designed to first teach the students the design and functionality ofvarious computer vision tools. As each tool is learned, an experiment is performed todemonstrate the tool’s capabilities and limitations. The topics are presented in an orderthat allows several tools to be grouped together to form a higher-level experiment on realworld images. An example of this would be to group edge detection, automaticthresholding, and Hough transforms to build a road detection system that could be usedfor vehicle navigation.A broad range of topics are covered within the course. The image processing portioncovers the following topics: Image formats
support is needed. With regard to Dia3 I learned thatwhile such software is new to some students, other students have very specific tastes. I believethat the need for such software must be emphasized and that at least one free technical drawingpackage be made available to students. In closing, both KiCad and Dia are exceptionally goodexamples of free software1 and both are valuable to computer engineering students.Bibliography1. Free Software Foundation: http://www.fsf.org/2. KiCad web site: http://www.lis.inpg.fr/realise_au_lis/kicad/3. Dia web site: http://live.gnome.org/Dia/4. Adel Sedra, Kenneth Smith, Microelectronic Circuits, 1998, Oxford University Press5. Peter Spasov, Microcontroller Technology, The 68HC11 and 68HC12, fifth
Computer-based Adaptive Testing for Assessing Problem-Solving Skills N. Khandan Civil & Geological Engineering Department New Mexico State University, Las Cruces, NM 88003IntroductionProblem-solving is one of the skills that engineering programs strive to instill in their graduates.In typical engineering programs, students are expected to gain this skill by observing instructorssolving example problems and by practicing with homework assignments that are similar toexample problems. These problems can be elementary problems, complex problems, or open-ended problems. Since complex problems and open-ended problems can be solved by breakingthem down
1 A Novel Hands-On Project in Computer-Aided Manufacturing Lorin P. Maletsky, Charles E. Gabel Department of Mechanical Engineering The University of Kansas Lawrence, KS 66045AbstractThis paper describes a project that involved designing and fabricating puzzle-type parts to formletters that were machined using a three-axis computerized numerically controlled (CNC) millingstation. The project was part of the Design for Manufacturability course at the University ofKansas. The letters were
Proceedings of 2014 Zone 1 Conference of the American Society for Engineering Education (ASEE Zone 1) Educational Computer Program for Simulating Behavior of Structures under Dynamic Loads Mohammed-Noor N. Al-Maghrabi and Ahmed A. Abdou El- Abbasy Engineering. In 1934 Professor Lydik Jacobsen and his Abstract— Saudi Arabia has constructed many universities in student, John Blume, developed the first field instrument forthe last decade. Civil, mechanical, and mining engineering strong shaking of structures and investigated the performancedepartments have courses deal
ASEE 2014 Zone I Conference, April 3-5, 2014, University of Bridgeport, Bridgpeort, CT, USA. Method for Computational Intelligence Based on Behavior of Grasshoppers Tiago Martins Ribeiro Raimundo Pereira da Cunha Neto Coordination of Computer Science Coordination of Computer Science Centro de Ensino Unificado de Teresina - CEUT Centro de Ensino Unificado de Teresina - CEUT Teresina, Brasil Teresina, Brasil tiagomartinz@hotmail.com netocunhathe@gmail.com
likelihood of completion.In this paper, we seek to better understand these compounded challenges by investigating howdoctoral computing students from URGs understand what is expected of them and how to do it.3 Research QuestionsRQ1: How do students from URGs form expectations of their CS PhD programs?RQ2: What sources do students from URGs rely on to form expectations of their CS PhD pro- grams?RQ3: How do students from URGs in CS PhD programs learn how to meet these expectations in order to complete their degree?4 MethodsIn order to answer the above research questions, our research team conducted a survey and follow-up interviews with Computer Science doctoral students at a large, Research 1 institution. Partici-pants for the
reinforce their motivation ensuresthat everyone’s efforts remain in place after mentors leave.Physical Resources The faculty is arguably the most critical resource to explore, but it is certainly not theonly factor in helping a mentor gain the proper perspective of the environment. More traditionalresource limitations will play a large role in determining how certain subjects may be taught or ifthey may be taught at all. Developing a CS curriculum requires consideration of available Page 13.158.4computing resources to include labs, faculty machines, and student computers. Most CS topicsare best learned when reinforced with hands-on
Paper ID #28931Student Sense of Community Through an Introductory Computer Program-mingCourse SequenceDr. Laura K Alford, University of Michigan Laura K. Alford is a Lecturer and Research Investigator at the University of Michigan. She researches ways to use data-informed analysis of students’ performance and perceptions of classroom environment to support DEI-based curricula improvements.Dr. Amir Kamil, University of MichiganDr. Andrew DeOrio, University of Michigan awdeorio@umich.edu contact Andrew DeOrio is a teaching faculty member at the University of Michigan and a consultant for web and machine learning projects
future computer engineering curricula. Such curricula should meet the standards oftoday yet look forward to adapting to the guidelines of tomorrow, which are embodied by theIEEE/ACM Computing Curricula 2020 Paradigms for Global Computing Education.IntroductionAt our institution, like many others worldwide, it has been over a decade since we havereimagined and redesigned our engineering curricula. Since then, we have ensured andconfirmed compliance with accreditation agencies [1], perfected the delivery of courses, andassessed learning outcomes to ensure that our graduates can be successful in all the differentstages of their careers. The problem is that in the last ten years, the careers that await ourgraduates have changed fundamentally such