development 4. Understanding complete solutions and develop the ability to effectively disseminate the entire value not just the value developed within individual domains of expertiseThe project was also meant to measure interdisciplinary learning and student collaboration, to develop atemplate for formalizing such learning opportunities centered around research led by multiple professors. 3.2. Project TeamThe envisioned outputs of the project and the corresponding resource requirements were: 1. A viable, production ready solution requiring the involvement of students interested in research and with prior experience in of three domains of expertise: Design/Manufacturing, Computer5 Hardware and Computer Software. One
informal and formal settings.Dr. Monica E Cardella, Purdue University, West Lafayette (College of Engineering) Monica E. Cardella is the Director of the INSPIRE Institute for Pre-College Engineering Education and is an Associate Professor of Engineering Education at Purdue University. c American Society for Engineering Education, 2017 Computational Thinking in Kindergarten: Evidence from Student Artifacts (Fundamental)AbstractIntegrated learning is fundamental in the current era of STEM education. However,articulating evidence of learning in such complex learning environments can be achallenge. This is especially true in elementary grades where developmentally-appropriatepractices
, which were fundamentally different thantraditional first courses on electric circuits. The new courses focused on ‘what’ to teach instead of‘how’ to teach. In the following paragraphs, we provide examples from these new courses withbrief descriptions of their objectives and contents.A sophomore level course was developed in the Electrical and Computer Engineering Departmentof the Rice University1. Guided by the breadth-first principle, the new introductory course wasdesigned to provide information on virtually all topics that the students would learn throughouttheir undergraduate education. The course was also intended to help the students understandwhat to expect from future advanced courses and eliminate the surprise factor. The course
can utilize their alreadyacquired knowledge of shearing force and bending moment to determine a beam’s slope anddeflection.An approach to teaching this important method of structural analysis that complements thetraditional lecturing through inclusion of a powerful, versatile and user-friendly computationaltool, is discussed in this paper. Students will learn how to utilize Mathcad to perform a varietyof calculations in a sequence and to verify the accuracy of their manual solutions. A Mathcadprogram is developed for this purpose and examples to illustrate the computer program are alsoincluded in this paper. The integration of Mathcad will enhance students’ problem-solvingskills, as it will allow them to focus on analysis while the software
Computer-Architecture ClassesThere are opportunities to use peer review in almost any course. One of the best opportunities isin evaluating student writing. Prospective employers and thesis advisors widely believe thattechnical students need frequent opportunities to hone their writing skills. But students needample feedback in order to improve. Peer review can give more copious feedback than instructoror teaching-assistant review, for the simple reason that each student has only a few submissionsto review, rather than several dozen. Moreover, students will be writing for an audience of theirpeers later in their careers, so it is important for them to learn how to do this.In computer-architecture courses, I have assigned students to write reviews
objectives associated with the completion of eachtask.Table 1. Student Tasks and Learning Objectives Task Learning Objective1 Complete introductory tutorials for three After completing this task the student will be dimensional computer-aided design able to execute drawing commands such as: (CAD) line, trim, rotate, mirror, and length. Also, the student will be able to assign elements to layers and snap to objects2 Interpret plan, elevation and section After completing this task the student will be drawings for the George
implementing computer-based assessments is rapidly evolving. Astechnological shortcomings are identified, they are quickly eliminated. Thus, difficulties withhuman factors are more important for long-term implementation than technologicalshortcomings.Students are very comfortable with the technology and adapt to its usage very rapidly. However,the technology is not perfectly reliable and this leads to insecurity for both the student and theinstructor. Instructors seek technology that enhances learning. This enhancement is most usefulif it comes with modest increases in time and effort and with technology that is user-friendly.The benefits of active learning in various forms (active learning, collaborative learning,cooperative learning, and problem
Paper ID #26116An Approach to Integrating Learning and Engagement Strategies (LESs) intoCS Class ActivitiesDr. Peter J. Clarke, Florida International University Peter J. Clarke received his B.Sc. degree in Computer Science and Mathematics from the University of the West Indies (Cave Hill) in 1987, M.S. degree from SUNY Binghamton University in 1996 and Ph.D. in Computer Science from Clemson University in 2003. His research interests are in the areas of software testing, software metrics, model-driven software development, domain-specific modeling languages, and computer science education. He is currently an associate
Paper ID #27715Assessment of the Educational Benefits Produced by Peer Learning Activitiesin CybersecurityDr. Jeremy Straub, North Dakota State University Jeremy Straub is the Associate Director of the NDSU Institute for Cyber Security Education and Research and an Assistant Professor in the Department of Computer Science at the North Dakota State University. He holds a Ph.D. in Scientific Computing, an M.S. and an M.B.A. and has published over 40 journal articles and over 120 full conference papers, in addition to making numerous other conference presenta- tions. Straub’s research spans the gauntlet between technology
instructionaltechnology tools enabled learning. The tools were selected to engage students in multiple formats:1) those that attended class in person, 2) those who participated in the live stream class, and 3) thosewho would watch the recorded class later in the day. The Matlab Grader feature was instrumentalin providing students practice with computational solutions to vibrations problems. With this tool,instructors create assignments that students solve with a Matlab script. When the student submitshis or her own code, it is automatically graded against the specified output of the instructor solution.Though it would be useful regardless of delivery mode, the Grader was particularly valuable ingetting real-time feedback to students in keeping with the fast pace
rectangles are desks on which computers are placed. (b) is a design ofa panopticon conceptualized by Jeremy Bentham [20].Liberative [1], [16] or engaged [21] pedagogies seek shifting of power in and outside theclassroom. The student is trusted as an equal partner in the process of learning and teaching. Thestudent experiences are valued. The responsibility of education is shared between the studentsand the instructor. The instructor facilitates learning of (individual) and among (peer) students.The shared goal is that of liberation in the sense of equity and social justice. Liberation is soughtthrough “praxis” [1] (reflective action that affects constructive changes in the world). In thisway, education becomes “practice of freedom” [21]. Practicing
Mathematics (STEM) and Computer Science(CS) education. He is also interested in improving STEM+CS education for minorities. He has been volunteering in many education outreach programs including Science Fair and Robotics programs such as First Robotics competitions. Areas of research interest include engineering education, STEM+CS, and robotics in K-12 education. Kaya advocates his view that research, teaching and learning are best practiced as a unified enterprise that benefits students and society. He has received numerous teaching awards as well as grants for his research from several foundations. Kaya is an active member of AERA, ASEE, ASTE, NARST, NSTA, and CSTA, has presented at over 15 conferences, published in
better lab reports. He is currently working on projects related to teaching science in elementary schools.Gerald C. Gannod, Miami University GERALD C. GANNOD is an associate professor in the Department of Computer Science and Software Engineering and Director of the Mobile Learning Center at Miami University in Oxford, Ohio. He re- ceived the MS(’94) and PhD(’98) degrees in Computer Science from Michigan State University. His research interests include service-oriented computing, software product lines, mobile learning, software reverse engineering, formal methods for software development, software architecture, and software for embedded systems. He is a recipient of a 2002 NSF CAREER Award.Mladen A Vouk, North
in aset of skills whose teaching at the K-12 level poses many challenges because of the relianceon the use of electronic computers and programming concepts that are often found tooabstract and difficult by young students. This article attempts to link cognition to basiccomputational processes, particularly modeling and simulation, that are known to facilitatedeductive and inductive inquiries by scientists for decades. Empirical data from a quasi-experimental study in 15 secondary schools suggests a similar impact on student learning.This is consistent with learning theories that students learn science in the way that scientiststhink and work. In this article, we offer a viewpoint on the essence of CT and suggest that weteach students
understand the impact of engineering solutions in a global, economic, environmental, and societal context i. A recognition of the need for, and an ability to engage in life-long learning j. A knowledge of contemporary issuesComputing Accreditation Commission (CAC) E. An understanding of professional, ethical, legal, security and social issues and responsibilities F. An ability to communicate effectively with a range of audiences G. An ability to analyze the local and global impact of computing on individuals, organizations, and society H. Recognition of the need for and an ability to engage in continuing professional developmentAssessment results from fall 2008 and spring 2009 indicated
Paper ID #12196Towards a Framework for Assessing Computational Competencies for Engi-neering Undergraduate StudentsDr. Claudia Elena Vergara, Michigan State University Claudia Elena Vergara is a Research Scientist in The Center for Engineering Education Research (CEER). She received her Ph.D. in Plant Biology from Purdue University. Her scholarly interests include: improve- ment of STEM teaching and learning processes in higher education, and institutional change strategies to address the problems and solutions of educational reforms considering the situational context of the par- ticipants involved in the reforms. She is
Digital bandwidth/throughput Encryption Electric motorsAgain, these topics were chosen because of their importance in Air Force Systems. To becomeelectrical/computer engineers or pilots in the US Air Force, the students need to have a basicfamiliarity with these systems. Also, the extensive hands-on experiences and early introductionto test equipment will allow students to focus more on new material in their future courses andspend less time learning new pieces of equipment or new application software.To gauge the longer-term effects of the course on students in the EE/CpE programs, hardcopysurveys were administered a full academic year after taking the course to 75% of our EE/CpEjuniors. The
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 #24012Designing Undergraduate Data Science Curricula: A Computer Science Per-spectiveDr. Predrag T. Tosic, University of Idaho Predrag Tosic is an early mid-career researcher with a unique mix of academic research, industrial and DOE lab R&D experiences. His research interests include AI, data science, machine learning, intelli- gent agents and multi-agent systems, cyber-physical/cyber-secure systems, distributed coordination and control, large-scale complex networks, internet-of-things/agents, and mathematical and computational models and algorithms for ”smart” transportation, energy and other grids. He is
commercialization and launch of the industry’s first 90-second rechargeable flashlight. In addition he is co-inventor on four U.S. patents and has presented numerous times at advanced energy technology conferences in the areas of business and technology development. c American Society for Engineering Education, 2017 Computer Simulations Developed to Improve Understanding of Thermodynamic PrinciplesThis paper describes the design, development and pilot implementation of computer simulationscreated to support student learning in a first semester course on thermodynamics. This projectwas sponsored by the Course Redesign with Technology program through the California StateUniversity
experiments using computer simulation software and thencompare their results to real lab measurements. The educational merit of this approach isdiscussed with focus on the successes and lessons learned from the implementation process.Preliminary assessment results including direct and indirect measurements satisfying ABET1requirements are addressed. Special emphasis on the evaluation system used to test effectivenessin terms of stated objectives and learning outcomes are presented and discussed in this study.Many studies have been performed to evaluate the merits of using computer simulations asopposed to traditional laboratory2,3,4. Researchers found that the “virtual lab” was as effective asthe “real lab” in term of student achievement, that is, no
students perceive bias within machine learning and search algorithms.Over 700 computer science and computer engineering students from three different institutionsparticipated in the survey from Fall 2018 to Spring 2019. Based on survey results, Google wasoverwhelmingly the preferred search engine. The participants also predicted that artificialintelligence algorithms will improve over time. The majority of respondents believe that privatecompanies, not government organizations, need to regulate their own artificial intelligencealgorithms. On average, computer science and computer engineering students acknowledge thatalgorithm bias could occur when people create algorithms. The results suggest that students arefamiliar with search engines and in
just illustrating the mechanics of the solution for a specificoperating point, a number of operating points can be calculated and results displayed in anorganized fashion. Tools such as this can make the instructional process investigative in nature,by addressing what-if scenarios. Visual Basic was chosen as the software to do this developmentwork.Visual learning“Visual learning is an important method for exploiting students’ visual senses to enhancelearning and engage their interest.” 1 Though this reference focuses on underrepresented studentsin the technical fields, the concepts are applicable across the range of the student population.Ref. 1 was part of a special issue of the IEEE Computer Graphics and Applications society on“innovative
into their discipline specific courses. To successfully accomplishthis, faculty must consider which classical solutions most benefit student learning and how theyshould be utilized. This paper considers some classical methods geotechnical educators shouldconsider as benefiting student learning when combined with computer methods commonly usedin industry. Geotechnical cross-sections sketched by hand, elastic stress distribution using chartsand equations, elastic settlement calculations, seepage analysis using flow nets, and slopestability charts and hand solutions all emphasize the engineering solution process and encouragestudent understanding of soil behavior. Yet the approach to such problems in practice commonlyinvolves computer software
AC 2012-3307: COMPUTATIONAL METHOD FOR IDENTIFYING INAC-CESSIBLE VOCABULARY IN ENGINEERING EDUCATIONAL MATE-RIALSMr. Chirag Variawa, University of Toronto Chirag Variawa is a Ph.D. candidate in the Department of Mechanical and Industrial Engineering at the University of Toronto. He earned his B.A.Sc. in materials science engineering in 2009 from the same insti- tution. His multi-disciplinary research uses principles from artificial intelligence, computational linguis- tics, higher-education, and aspects of neuroscience to investigate inclusive design of engineering learning environments.Dr. Susan McCahan, University of Toronto Susan McCahan is a professor in the Department of Mechanical and Industrial Engineering at
to demonstrate andconsolidate what they had learned in the program. In 1998, this requirement was extended to Page 4.585.1include Computer Science as well.Devising a suitable project course for CS was a challenge. Clearly the course needed to bedifferent from the typical undergraduate course in that it would center on student initiatives. Iuse the term student-centric to describe this, as opposed to a Freshman-level programmingcourse, which I would consider to be teacher-centric.Student-Centric vs. Teacher-Centric Courses:The table below clarifies some differences between student-centric and teacher-centricapproaches
, including the growth of hydrodynamic instabilities and the resulting turbulent mixing. Scott teaches courses across many dis- ciplines, including engineering mechanics, introductory programming, probability and statistics, control systems, and professional development. Scott’s research interests in engineering education are committed to the advancement of innovative teaching methodologies and pedagogies to improve student learning in inclusive learning environments.Dr. Shanon Marie Reckinger, University of Illinois at Chicago Shanon Reckinger is a Clinical Assistant Professor in the department of Computer Science at the Univer- sity of Illinois at Chicago. She received her PhD in Mechanical Engineering at the
Paper ID #42989Assessing Sophomore Cornerstone Courses in Electrical and Computer EngineeringProf. Branimir Pejcinovic, Portland State University Branimir Pejcinovic received his Ph.D. degree from University of Massachusetts, Amherst. He is a Professor and former Associate Chair for Undergraduate Education at Portland State University, Electrical and Computer Engineering department. He has led department-wide changes in curriculum with emphasis on project- and lab-based instruction and learning. He was awarded the best paper award by the ECE division of ASEE in 2017 for his work on freshman engineering course
Accreditation Commission and a FAA licensed sUAS Remote Pilot.Dr. Zhen Wu, Dr. Zhen Wu is a research associate at National Center for Women & Information Technology (NCWIT). Her research interests emphasize the meaningful participation of women in computing. ©American Society for Engineering Education, 2023 Community College Computing Programs’ Unique Contexts for Promoting Gender EquityAbstractThis paper documents issues that community college programs encounter and their needs as theywork to improve gender equity in computing. It also describes how the National Center forWomen & Information Technology (NCWIT) Extension Services Learning Circles (LC) havesupported these
& ethnicity. These differences were found when looking at stu-dents’ senses of their science identity and learning environment. We also found that women hada significantly greater chance of having strong interpersonal relationships within computing. Thesurvey results are augmented by a survey of first-quarter freshmen in Fall 2019 (n = 44) andstudent interviews conducted in Spring 2021 (n = 15). We hope that the addition of these resultsexplain and expand upon our main results and add insight as to how the student experience canevolve from a student’s first quarter onward. These differences shine an important light on somepositive trends as well as several concerning differences to be examined in our quest to create adiverse and equitable