. Application of the universal soil lossequation in estimating relative sediment yields associated with urbanization. Seewww.tubs.com/abstract/usle_abs.htm. Abstract with program, Annual meeting of theGeological Society of America, Seattle WA.Fangmier, D.D., W.J. Elliot, S.R. Workman, R.L. Huffman and G.O. Schwab. 2006. Soiland water conservation engineering. Thompson Delmar Learning, New York, NY.Foster, G.R. 2005. Revised Universal Soil Loss Equation version 2 (RUSLE2): Sciencedocumentation. See http://www.ars.usda.gov/Research/docs.htm?docid=6010.Agricultural Research Service, US Dept. Agr., Washington, DC.Haan, C.T., B.J. Barfield and J.C. Hayes. 1994. Design hydrology and sedimentology forsmall catchments. Academic Press, New York, NY.McCuen, R.H
semester, the program was opened to all faculty at the EEdepartment (total of 25 faculty). No faculty opted out, which allowed more course options forstudents to choose from.4-Pedagogy Training of Student Observers: Volunteering students were enrolled in a learningmodule on teaching and learning best practices on the Canvas learning management system,covering topics such as backward design and assessment, observation practices, and givingconstructive feedback. All handouts and training materials were provided within that Canvasmodule. The students were required to attend a one-hour training session on how to observe andevaluate teaching effectiveness and how to provide constructive feedback to faculty members.The training session was offered
Computer Science from University of Maryland, College Park in 1986. He is currently Professor of Computer Science at Virginia Tech, where he has been since 1987. He directs the AlgoViz and OpenDSA projects, whose goals resp ©American Society for Engineering Education, 2024 WIP: Exploring Office Hour Interactions in a Data Structures and Algorithms CourseAbstractLarge universities often have introductory computing courses with hundreds of students, dozensof TAs, and multiple TAs on duty at the same time. We investigate what occurs during office hourinteractions between students and TAs, focusing on a large intermediate data structures coursewith major programming assignments
abetter job teaching the course while spending less time. Beyond the third or fourth timeyou may start to become bored with the course, and it may be time to move on.Designing a course is basically an engineering design problem. First, gatherinformation. What is the purpose of the course? The purpose of a requiredundergraduate course is obviously very different than the purpose of an elective. Obtainseveral old outlines and syllabi. Talk to those professors who have taught the courseand those who teach prerequisite courses to see what you can expect the students toknow (but cut rosy comments based on "coverage" in half). Talk to professors whoteach follow-up courses to determine what students must learn in your course.Then develop your tentative
Paper ID #41195Board 359: Reaching DEI targets in STEM: Lessons from a National ScienceFoundation Research Traineeship (NRT) with Outstanding DemographicsDr. Eduardo Santillan-Jimenez, University of Kentucky Dr. Eduardo Santillan-Jimenez is PI and project coordinator of a National Science Foundation Research Traineeship (NRT) program designed to enhance graduate education by fully integrating research and professional skill development within a diverse, inclusive and supportive academy. Originally from Mexico, Dr. Santillan-Jimenez joined the University of Kentucky (UK) first as an undergraduate research intern and then as
Paper ID #8854Poll Everywhere! Even in the Classroom: An investigation into the impact ofusing PollEverywhere in a large-lecture classroomDr. Wendi M. Kappers, Embry-Riddle Aeronautical University Wendi M. Kappers has a Ph.D. in Instructional Technology from the University of Central Florida (UCF). Her thesis work explored how educational video game effects upon mathematics achievement and mo- tivation scores differed between the sexes. During her tenure at Seminole Community College working as a Tenured Professor and Program Manager of the Network Engineering Program, she was Co-PI for the CSEMS NSF grant that explored
Industrial/Organizational Psychology and a leading expert in the areas of team dynamics, virtual teams, conflict management, personality, and assessment. He is director of the Individ- ual and Team Performance Lab and the Virtual Team Performance, Innovation, and Collaboration Lab at the University of Calgary, which was built through a $500K Canada Foundation for Innovation Infrastruc- ture Grant. He also holds operating grants of over $300K to conduct leading-edge research on virtual team effectiveness. Over the past 10 years, Tom has worked with organizations in numerous industries, includ- ing oil and gas, healthcare, technology, and venture capitals. He is currently engaged with the Schulich School of Engineering at
approach students get aprogramming project assigned. They acquire the knowledge to do the project by self-study.During a lab class they present their project to the other students, discussing their programdesign, the difficulties they ran into and finally demonstrate the product, i.e. the compiledprogram.Assessment and retentionOn the surface, assessment doesn't seem to be all that different from a traditional class. There arebasically three parts that can be assessed: presentations, exams/quizzes and programming “Proceedings of the 2007 American Society for Engineering Education Pacific Southwest Annual Conference Copyright © 2007, American Society for Engineering
final exam scores forthe two cohorts, using prerequisite GPA as a control variable (Norusis, 2005). This GPA wasbased on the grades obtained in the prerequisite coursework (i.e., calculus 2, calculus 3, ordinarydifferential equations, statics, dynamics, and thermodynamics), which were gathered via ademographics survey. The demographics survey was also used to gather gender, ethnicity, PellGrant status, and transfer information (i.e., transfer into the engineering program) to enablestratified analyses.Given the small sample sizes associated with some of the demographic strata, the nonparametricversion of ANCOVA - Quade’s test - was also run (Quade, 1967; Lawson, 1983). The p-valuesbased on the parametric and nonparametric versions of ANCOVA were
studentlearning inside and outside of the classroom. But first, however, the team had to determine howbest to develop and implement a manageable, multi-level self-study that could offer meaningfulinsights into the complexity of barriers to STEM student success—and then begin to proposemeaningful solutions. This paper describes how a diverse campus team designed andimplemented such a self-study, and how a similar approach can be adapted for use at otherinstitutions of higher learning seeking to improve STEM student success, including studentsenrolled in computer science and engineering. The work described here is part of a larger studythat is ongoing. Subsequent stages of the study involve deeper analysis of the data, especiallywithin each of the
Paper ID #33523Experience in Moving Information and Computer Technology Courses On-lineDr. Peng Li, East Carolina University American c Society for Engineering Education, 2021Experience in Moving Information and Computer Technology Courses Online1. INTRODUCTIONThe COVID-19 pandemic brought tremendous challenges to higher education institutions. Manycolleges moved most or all courses online, at least temporarily. New technologies, such as highspeed internet and cloud computing, make it easier to deliver courses remotely. It is expectedthat the share of hybrid and online courses will grow [1] with
Robotics Process Automation: The Virtual Assistant Kanwaljeet Singh, Prof. Christian BachAbstract – The Robots have long time presence in the manufacturing industry. In today’s Worldthey are helping small to big companies to reduce their operational cost. And they are not limitedto manufacturing industry only. These days, Robots are part of every organization from banking,finance, communication, electronics, engineering, healthcare, and technology. Companies candeploy them based on their needs or requirements and they can do very simple to complex tasks.Especially, in the finance industry, Robots are helping to perform simple tasks of bookingjournal entries to reconciling bank accounts
Instruction, 29:153–170, February 2014. [8] L. C. Kaczmarczyk, E. R. Petrick, J. P. East, and G. L. Herman. Identifying student miscon- ceptions of programming. page 107. ACM Press, 2010. [9] K. C. Midkiff, T. A. Litzinger, and D. L. Evans. Development of Engineering Thermody- namics Concept Inventory instruments. pages F2A–F23. IEEE, 2001.[10] D. Hestenes, M. Wells, and G. Swackhamer. Force concept inventory. The Physics Teacher, 30(3):141–158, March 1992.[11] K. Rollag. Teaching business cases online through discussion boards: Strategies and best practices. Journal of Management Education, 34(4):499–526, 2010.[12] G. Salomon and T. Globerson. When teams do not function the way they ought to. Interna- tional Journal of
Session 2355 How to Grow Your Graduate Students: Mentoring Tips for New Professors Julie L. P. Jessop University of IowaAbstractIn the College of Engineering at the University of Iowa, tenure-track assistant professors areevaluated on their “effectiveness in directing undergraduate, M.S., and Ph.D. research tocompletion.” This statement assumes that, along the students’ paths to degree completion, thefaculty adviser has engaged them in effective mentoring relationships. Unfortunately, goodmentoring skills are not innate
engineer who retired from IBM after serving for 30 years. He is a development engineering and manufacturing content expert. He develops and teaches all related engineering courses. His responsibility as a director of Center on Access Technology Innovation Laboratory include the plan- ning, implementation and dissemination of research projects that are related to the need of accessibility. He received his BS from RIT and his MS from Lehigh University. His last assignment with IBM was an Advanced Process Control project manager. He managed team members in delivering the next generation Advanced Process Control solution which replaced the legacy APC system in the 300 mm semiconductor fabricator. Behm has fifteen patents
Paper ID #35571Fostering a Supportive Mentoring Space During a Global PandemicDr. Matthew Voigt, Clemson University Matthew (he,him,his) is an Assistant Professor of Engineering and Science Education at Clemson Uni- versity. His research interests center around issues of equity, access, and power structures occurring in undergraduate STEM programs with a focus on introductory mathematics courses.Dr. Eliza Gallagher, Clemson University Eliza is an Assistant Professor of Engineering and Science Education at Clemson University, with joint appointments to Mathematical Sciences and Education and Human Development. Her research
Biomedical Informatics Lab is to design cost effective computational medical decision aids that will help physicians better diagnose, treat, and manage cancer. Her primary interest in improving engineering education is the identification of effective strategies for coordinating instructional technologies to reinforce learning. Page 11.233.1© American Society for Engineering Education, 2006 Assessing an Instructional Technology Scaffold for Reinforcing Learning of Probability and StatisticsAbstractIn order to facilitate active learning (i.e., student interactions) and emphasize real
held fellowships in Ethics of AI and Technology & Society organizations.James N. Magarian, Massachusetts Institute of Technology James Magarian, PhD, is a Sr. Lecturer and Associate Academic Director with the Gordon-MIT En- gineering Leadership (GEL) Program. He joined MIT and GEL after nearly a decade in industry as a mechanical engineer and engineering manager in aerospace/defense. His research focuses on engineering workforce formation and the education-careers transition.Dr. Alison Olechowski, University of Toronto Alison Olechowski is an Assistant Professor in the Department of Mechanical & Industrial Engineer- ing and the Institute for Studies in Transdisciplinary Engineering Education and Practice (ISTEP
of fourdrop down lists (i.e., Mode, Linear Interpolator, Circular Interpolator, and Test) for Simulinkmodel component settings and two pushbuttons for Simulink Model Build and View. The Modelist offers three options: Linear Interpolator Test, Circular Interpolator Test, and Linear&CircularInterpolator Test. The Linear Interpolator category contains two options: Default and UserDefined. A default constant velocity linear interpolator is provided in the program, and the usercan use the User Defined option to designate the linear interpolator. The Circular Interpolatorcategory offers two options: Default and User Defined. The Test category determines the type oftest used in the Simulink model to be built. Linear single segment, Linear
universities in the UK. A similar study is currently being undertaken in Sweden.The first university has well-established degree programs and is fully BCS accredited. Thesecond university recently redesigned their IT awards, some of which are now BCSaccredited. The degree programs at the first university offer students the opportunity toexamine a PC in the first year as part of a module in Computer Organization. However theynever take a PC apart. Students are taught network modeling, design and management but Page 5.111.2they do not physically construct networks. The results clearly demonstrate that studentslacked knowledge about PC technology and the basic
AC 2012-3166: INNOVATIVE APPLICATIONS OF CLASSROOM RESPONSEDEVICES IN MANUFACTURING EDUCATIONDr. George M. Graham P.E., Chattanooga State Community College George M. Graham Graham is the Director of the Wacker Institute and Department Head of Chemi- cal, Manufacturing, and Industrial & Systems Engineering Technology at Chattanooga State Community College. He was previously an Assistant Professor in the Department of Manufacturing and Industrial Technology at Tennessee Technological University. Prior to his academic appointment, he held Director, Manager, engineering, and research positions in automotive manufacturing and construction industries. He is a member of the American Society of Mechanical Engineers
Paper ID #44153Integrating Theory and Practice: A CFD Education ApproachDr. MEHMET Nasir SARIMURAT, Syracuse University Mehmet Nasir Sarimurat earned his Ph.D. from Syracuse University in Syracuse, NY, USA, in 2008. He held positions as a Senior and Staff Engineer at United Technologies Carrier Corporation in East Syracuse, NY, USA, from 2007 to 2018. In 2018, he made the transition to the Department of Mechanical and Aerospace Engineering at Syracuse University. Currently, he serves as an Associate Teaching Professor and also holds the role of Undergraduate Program Director for Mechanical Engineering. His research is
of instructors as possible. These experimental modulesshould be designed primarily for faculty who do not have resources for high-end experiments norwant to spend a lot of time developing, building or maintaining experiments. Furthermore, thehands-on demos and experiments must be easy for students to use without the need for a lengthylearning period.A cohesive program to develop distributed laboratories with the above features exists that wasfunded by an NSF CCLI Phase 2 Grant, which supported the development of the TESSALCenter3. TESSAL (Teaching Enhancement via Small-Scale Affordable Labs) includes labs forsignal processing4, digital logic5, power systems, electromagnetics, and control systems. Thecontrol systems modules are discussed in
Paper ID #8400NCAA Basketball Tournament Analysis for High School MathematicsDr. Adrian J Lee, Central Illinois Technology and Education Research Institute Dr. Adrian Lee received his Ph.D. in mechanical engineering from the University of Illinois at Urbana- Champaign in 2009, specializing in probability and risk analysis of aviation security systems. Dr. Lee served as a post-doctoral research engineer at Vishwamitra Research Institute, Center for Uncertain Sys- tems: Tools for Optimization and Management, and is currently President of Central Illinois Technology and Education Research Institute. Dr. Lee also holds an
Paper ID #37427Comparing labs before, during, and after COVID in aMeasurements and Analysis CourseBridget M. Smyser (Teaching Professor) Bridget Smyser is a Teaching Professor in the Mechanical & Industrial Engineering department at Northeastern University. She holds a BS in Chemistry from the Massachusetts Institute of Technology and a Ph.D. in Materials Science and Engineering from Worcester Polytechnic Institute. Her research interests include capstone design and lab pedagogy, , effective methods to teach technical communication, and integrating diversity, equity, and inclusion concepts into engineering
graduate student, a program of supervised practical training is an excellent way for futureprofessors to gain skills and confidence in classroom instruction. In this manuscript, we present themotivations, observations, and lessons learned during a recent instructor-in-training mentoring experience,described from both the mentor’s and the trainee’s perspective. Where appropriate, the students’ perspectivehas been included also.Motivation Trainee’s Perspective When I made the decision to pursue my Ph.D. in Chemical Engineering, it wasa choice motivated in large part by a desire to teach. Past experience with tutoring had shown me that I trulyenjoyed helping people learn. It felt great when I knew I had made a connection and that the student
express the program pthat runs in M and produces s as an output. The smallest possible L(p) for a given s over allprograms and all machines that outputs s is the Kolmogorov measure of information in Xrelative in complexity to M represented as: KM(s) = min(L(p))+CM where CM is the number of bitsthat it takes to describe the machine M, a quantity that is independent of s. Since a Turingmachine may simulate any other machine, it may be used to estimate CM except that we cannot Proceedings of the 2013 ASEE Gulf-Southwest Annual Conference, The University of Texas at Arlington, March 21 – 23, 2013. Copyright 2013, American Society for Engineering Educationbe sure of a
, andgraphical communication in broadly-defined technical and non-technical environments; and anability to identify and use appropriate technical literature” [ETAC SO #3] by critically evaluatingthe requests for proposals submitted by potential clients, researching and formulating plausibletechnical solutions, and then writing persuasive and credible proposals to satisfy the presentedproblem. In addition, students must also demonstrate “an ability to design systems, components,or processes meeting specified needs for broadly defined engineering problems appropriate to thediscipline” [ETAC SO #2] by articulating in their proposals technical solutions that arereasonably designed and supported by the data and rationale used by the student in theirproposals
, asynchronousinstructional delivery and administration system (CyberProf;) in the introductory physics course over the past fewyears has led to dramatically increased student comprehension of fundamental principles. Course examinations arenow so difficult that many professors in the department find it difficult or impossible to solve some of theexamination problems. (For additional information on CyberProf;, see note 5 below.)4. The Sloan Foundation's program in Learning Outside the Classroom has a central theme of exploring newoutcomes in science and engineering higher education which are made possible by asynchronous access to remotelearning resources through current, affordable technology. For details, seehttp://www.sloan.org/education/ALN.new.html Sloan sorts
Paper ID #38729Comparative analysis of remote, hands-on, and human-remote laboratoriesin manufacturing educationMr. Joshua Grodotzki, Technical University Dortmund, Institute of Forming Technology and LeightweightComponents Joshua Grodotzki manages the group of Profile and Sheet Metal Forming at the Institute of Forming Technology and Lightweight Components, Department of Mechanical Engineering, at the Technical Uni- versity of Dortmund. Since six years, his research activities center on engineering education topics with a particular focus on the use of digital technologies, such as apps, augmented and virtual reality, and