worked for 16 years as a software engineer and developed systems for such industries as banking, telecom- munications, publishing, healthcare, athletic recruiting, retail, and pharmaceutical sales.Teresa A. Shanklin, Purdue University Teresa A. Shanklin has a Bachelors degree in Computer Science and graduated from Iowa State University with a Masters Degree in Information Assurance. She is currently a Ph.D. candidate at Purdue University in the College of Technology, where she is a research assistant in the Machine-to-machine (M2M) lab. Her research interests lie in the areas of indoor positioning and path planning, mobile devices and multi-agent systems
. Function Structure Diagrams 6. Concept Generation 7. Estimation and Feasibility 8. Concept Selection 9. Project Planning 10. Math Modeling 11. Prototyping Strategy 12. Tolerance Analysis 13. Intellectual Property and PatentsMethodologyFor this study the CATME survey was administered in the middle of the semester and again atthe end of the semester. After the students received feedback from first survey, they were askedto compare their scoring of themselves to the scores they received from their teammates andformulate a plan to improve. Finally the students were surveyed at the end of the semester aboutthe
traditional lecturing with assigned homework andquizzes, with the lab section of the course being the time for modeling projects and the seniordesign project.Learning DesignThe final learning design was developed based on modeling-based learning. The development ofa four-phase process from these frameworks has previously been reported on [citation blindedfor peer review]. The four phases of the modeling process that students used during theirmodeling activities were: (1) planning the model, (2) building the model, (3) evaluating themodel, and (4) reflecting on the model. Table 1 below overviews the tasks that students didduring each phase of the modeling process.Table 1. Overview of learning design for the modeling projects during the course. Phase
during class, Page 15.1249.3satisfaction with learning, favorite and least favorite DyKnow tools, and open comments.The surveys were placed in each class’s course management system page. Students logged onduring class during the first, fifth, and final weeks of the quarter to complete the surveys. Alldata collection was coordinated by the Office of Institutional Research, Planning, andAssessment. The student responses from the surveys were analyzed then presented in severalways. First, frequency of student responses was calculated overall. Second, an ANOVA wasconducted to compare survey ratings across courses within the year. Third, a paired t
environment that is not integrated into a learningmanagement system. Some comments indicate that students would like the testing environmentto function similarly to the testing environment they are used to. For example, several studentsremarked that they would like the ability to return to previously answered questions and makechanges before submitting the exam. One student noted that right clicking was disabled,disallowing him to use the browsers spell-checking feature. We plan to address these issues inthe next software revision.Participants did not find inherent drawbacks with the bartering concept. Bartering is available,but not compulsory. An interesting comment brought up by several students is that the quality ofthe hints plays a major role in
, object recognition, computer vision, intelligent robot, and human–robot interaction. He has published 70+ SCI and EI papers and holds 10+ national patents. He is the PC member of several top international conferences, i.e. IJCAI. He is also the invited reviewer of several reputed international journals, i.e. IEEE Transactions on Fuzzy SystemsIEEE Transactions on Human-Machine Systems, IEEE Transactions on Systems, Man and Cybernetics: Systems, etc. He is also the associate editor of International Journal of Robotics and Automation Technology. He was granted a ”Talent of Qing Lan Project” award of Jiangsu province and a ”Six Major Top-talent Plan” award of Jiangsu province, China. He is a Standing member, the Specialty
Figure 2. Application ProcessBased on the final selection of the students, the CS department team at the university (UTRGV)along with the team from Upward Bound program identified the technical and non-technical skillsthat were then targeted in the summer camp. Table 1. Summer Enrollment Total 31 Forensics& Cybersecurity Track 16 Mobile Applications Track 15Gender GapAs we were planning for the summer camp, one goal of the team, which consisted of two femalesand two males, was to make sure that the selected applicants are more diverse in terms of thegender, since the schools are already
in leadership positions for numerous professional organizations. Page 26.1585.1 c American Society for Engineering Education, 2015 Time Management Skills and Student Performance in Online CoursesAs educators, we have the almost daily task of turning students’ goals into the reality ofcompleted degrees. In part, we accomplish this by requiring students to spend time with coursecontent. Students, in turn, must plan and use their time effectively in order to accomplish coursegoals and objectives. Online courses present special challenges for student engagement andeffective time management
through the software by aggregating formative assessments at the course level in order toimprove activities and processes that ensure attainment of program goals. Data collected eachyear are used for annual reports and to guide long term planning. Summative evaluations also aidin the achievement of program goals and objectives.SearchLight™ also offers the means to perform program assessments through both direct andindirect means. Direct assessments are appropriate for determining the effectiveness of in-classteaching practices and course outcomes. Indirect assessments through various surveyinstruments are appropriate for determining best-practices for STEM pedagogy and courseoutcomes. Both direct and indirect methods can be mapped to program
engineering) 2. Developing and using models 3. Planning and carrying out investigations 4. Analyzing and interpreting data 5. Using mathematics and computational thinking 6. Constructing explanations (for science) and designing solutions (for engineering) 7. Engaging in argument from evidence 8. Obtaining, evaluating, and communicating informationThere are many similarities between the practices of scientists and engineers – e.g., both includeusing computational tools to test scientific theories and predict outcomes of engineering designs.While new technologies and pedagogies now afford us many opportunities to cultivate students’S&E habits of mind,4,5,18 developing novel approaches to integrate
knowledge or not if students’ability to communicate their knowledge is uncertain[18]. This may also explain why aninstructor may ask, “What is one plus one?” and the students reply, “Green!” Somewhere alongthe line, there is a failure to communicate.Pólya’s methodGeorge Pólya first published How To Solve It in 1957, then updated it in 1973. The currentedition was published post humorously in 1988[20]. This little book was aimed primarily atteachers and promoted the idea that students could learn problem-solving by developing theirown proofs in geometry classes. Briefly, the problem-solving method consists of four steps: 1. Understanding the problem 2. Devising a plan 3. Carrying out the plan, and 4. Looking back
mobile robot programming for ER1 Mobile Robot49Universidad Catolica autonomous navigationde ChileAugsburg College CS course on robot history and theory Robix Manipulator, instructor- created vehicle50Course FormatThe first offering of the IMR course was in spring 2007 and it quickly became apparent that theproposed topics were too ambitious. The topics included simulation, actuators, effectors,locomotion, kinematics, sensors, control, navigation, localization, path planning, computervision, image processing, human-robot interaction and GUI design. The problem was that someof these topics were entire courses in themselves (i.e. computer vision, human-robot
c Society for Engineering Education, 2021Online COVERAGE (Competition Of VEX Educational Robotics to Advance Girls Education) (Research-to-Practice, Strand: Other)IntroductionThe major objective of the COVERAGE (Competition Of VEX Educational Robotics toAdvance Girls Education) project is to increase female West Virginia middle school students’interest in Computer Science and STEM. As the original plan of the COVERAGE project, GirlsRobotics Clubs would be organized in three counties of West Virginia, including Kanawha,Fayette, and Lincoln Counties, to prepare female middle school students for a regional roboticscompetition at the end of 2020. The Covid-19 pandemic started soon
theclassroom. Discussion forums and sharing of computational artifacts (lesson plans anddemonstrations) were central to the structure of this class to address Practice 1 (Fostering anInclusive Computing Culture in an exploration of cyber citizenship), Practice 2 (CollaboratingAround Computing in the creation and sharing of computer artifacts), and Practice 7(Communicating About Computing). Application Development reinforces computationalthinking and traditional programming skills (Practices 5 & 6) in the development of artifacts thathave immediate classroom applications. To summarize, with the directive issues by former Governor Mead, and the Practicesoutlined in the Wyoming Computer Science Standards, it became clear that COSC 1010
forward until obstacle is detected Lab #5: Avoid obstacle using lidar (introduce path planning) Lab #6: Turtlebot mapping and localization (team projects exploring obstacle avoidance using vector field histograms and other advanced algorithms)An example of MATLAB code to move the Turtlebot forward for 10 seconds is shown in figure2. This is considerable less code and less steep learning curve than would be necessary inPython or C++ in a Linux environment. ipaddress = '192.168.1.1‘ % IP of Turtlebot (will depend on your setup) rosinit(ipaddress) % start ROS robot = rospublisher('/mobile_base/commands/velocity'); % publish velocity topic velmsg = rosmessage(robot); % get message format for velocity tic
PowerPoint slides. Our roleshould be to get students working on the tutorial exercises and assignment problems anddesign projects.Professional practice The engineering method is the use of heuristics to cause the best change in a poorly understood situation within the available resources 13.As we grapple with more complex problems, it is even more obvious that we must teach theprofessional practice of engineering (which should include the practice of engineeringresearch). Students will then understand:• The lifecycle of engineering artefacts and the roles of engineers from strategic planning through design and construction and operation to decommissioning and recycling• The engineering method that guides their work• The
students in operations research to focus their learning on the power of dynamicprogramming, as opposed to the nuances of computer implementations.IntroductionSince the formulation of Dynamic programming (DP) by Bellman,1 it has been successfullyapplied to a variety of problems, including capacity planning, equipment replacement,production planning, production control, assembly line balancing and capital budgeting(hundreds of articles referring to the use of dynamic programming are given in Sniedovichand Cole7 ). Despite seemingly successful, dynamic programming has not been adaptednearly as readily, and thus successfully, as its mathematical programming counterpartssuch as linear and integer programming. Some of the reasons for this are the lack
AC 2007-1122: TRANSFORMING TEACHING AND LEARNING USING TABLETPCS ? A PANEL DISCUSSION USING TABLET PCSFrank Kowalski, Colorado School of Mines Frank Kowalski is Professor of Physics at Colorado School of Mines. Interested in improving classroom communication, he spearheaded efforts to introduce the use of clickers in CSM's introductory level physics classes. He currently uses InkSurvey to enhance his teaching of a junior/senior level electricity and magnetism course.Julia Williams, Rose-Hulman Institute of Technology Julia Williams is executive director of the Office of Institutional Research, Planning and Assessment and a professor of English at Rose-Hulman Institute of Technology. She has
AC 2010-2283: DEVELOPING NETWORK INFRASTRUCTURE FORCLASSROOM TECHNOLOGIESJoseph Tront, Virginia TechDavid Bailey, Virginia Polytechnic and State UniversityThomas Walker, Virginia TechSteven Lee, Virginia Tech Page 15.387.1© American Society for Engineering Education, 2010 DEVELOPING NETWORK INFRASTRUCTURE FOR CLASSROOM TECHNOLOGIESAbstractIn order for classroom technologies to be useful in engineering education, appropriateinfrastructures must be planned, implemented and tested so that they are sufficiently robust toserve the needs of the target usage. Usage will vary depending on size of the class, complexityof the teaching technology being used, and
might be to replace a statement like “capture cue ball” with “capture theclosest ball.” By simplifying their original script, participants typically earned a sub-optimalscore. A better solution is to reorganize the script so that the maximum number of points, basedon remaining balls, can be earned.Strategy games such as Robo-Billiards can help to engage students in activities that are fun andsupport STEM concepts. As observed in the student behaviors, the most successful results occurwhen a clear and defined plan (algorithm) is used to form the necessary script. Even in the faceof a fault, it is the ability to adapt to the new circumstances that allowed further success. Therobot’s design likewise impacts the potential STEM learning
Education, 2008 Integration of Computer-Based Problem Solving into Engineering CurriculaAbstractThe primary objectives of this engineering project are (1) to examine how to develop students’problem solving and computational skills early in their program of study and (2) to furtherenhance these skills by building upon critical computing concepts semester after semester. Theproject is a component of NC State University’s quality enhancement plan, which focuses on theuse of technology in enhancing student learning. The project stems from new introductorycomputer-based modeling courses that were created in two engineering departments, and hasexpanded to include other departments. We give an overview of the
competition requires the team to design and build a medium-sized robot to autonomously traverse an outdoor obstacle course. Obstacles normally consist of colored barrels, construction netting, white lines and trees. The team uses stereovision cameras as the primary obstacle detection sensor. The team is currently exploring several algorithms for path planning. Paul recently become a member of the UMR Applied Computational Intelligence Lab. He recently spent the summer developing adaptive user-interfaces as part of a research partnership with Boeing.Donald Wunsch, Missouri University of Science and Technology Donald C. Wunsch II (S’87–M’92–SM’94–F’05) received the B.S. degree
takes onfamiliar plots/themes), and pedagogical objectives (e.g., exposing or re-framing via adocumentary) are completely different. Hollywood Movie TED Talk Veritasium Khan Academy Production Massive, Well-organized, Low-budget single- Tablet-style, low- professional, well- rehearsed, and camera shoots and budget procedural funded endeavor planned interviews videos presentations Purpose Entertainment Engaging product Pose intriguing Detailed product guaranteeing
planned for Spring 2011: a. The formal class times will be changed from MWF (55 minutes each time) to a MW schedule with 2 back-to-back class periods on Monday and a single class period on Wednesday to allow more continuous discussions and hands-on opportunities on Monday. b. With the use of EMMA, when students work on their assignments outside of formal class times, for example they would be able to just use their cell phones to Page 22.1702.5 record video clips of the problems encountered and post them via EMMA. The instructor in turn
related to hierarchy, outline our students first hands-onexperience with logic circuit design and propagation delay using a CPLD. Our new CPLDstructure and timing document is outlined. Next, our issues regarding the CPLD module andthe CAD software are presented. We present our concerns with having our student's use of theCAD software outside of the class laboratory environment. We close with an outline of ourfuture plans. We will make use of lab sessions in the first two weeks of class for so-called labstartup activities, where our students will have a first hands-on activity with logic circuits andlearn how to use a breadboard. They will also perform the CAD tutorial and learn about ourexpectations for project reports. We will also provide in a
]. Spohrer [3] analyzed programming errors using a cognitive sciencemodel. Spohrer used a Goal And Plan tree to trace the root causes of errors, which defined plans(steps/procedures) as the techniques to solve the problem, and the goals as the desired result toachieve or accomplish. Spohrer found that once there is a mismatch between a plan and a goal,an error occurs. Yarmish used a similar approach but added more components to a plan [4].Other work suggests that errors occur due to inaccurate mental models about program state[3][4][7][13][14]. Horstmann [5] presents a list of common errors when introducing C++programming concepts and constructs. Horstmann presents common errors in each chapter,which may help students avoid such errors. Oualline [6
and technology and that try to foster the interest of the younger generation in STEM fields.Ms. Jennifer Arreola, University of Texas, El Paso Jennifer Arreola is pursuing a Bachelors in Engineering Leadership with a concentration in Environmental Engineering. She plans on working for the protection of human health and ecosystem. She believes that as an engineer the ability to understand not only the problem but other issues such as political, business and social are necessary to approach this new generation.Ms. Andrea Annette Duenez Andrea A. Duenez is a senior at the University of Texas at El Paso majoring in Engineering Leadership with a focus in Electrical Engineering. Andrea plans to graduate in December of
learning 4.Our plan was to introduce STARS Computer Clubs into all Auburn City Schools. In the first fiveyears of the project, we focused our activities on Auburn Elementary and Middle Schools and inthe upcoming year plan to incorporate Auburn Junior High and High School to provideenrichment activities to get students excited about education. Auburn University’s department ofComputer Science and Software Engineering started computer clubs in the elementary schools atthe 3rd, 4th and 5th grade levels. We studied students in their usage of computing technologyand found that these experiences have a positive effect of getting students excited about learningto utilize new technology, and excited about demonstrating their understanding of
been developed to implement agility within manufacturingenterprises, including Flexible Manufacturing Systems (FMS) and Computer IntegratedManufacturing (CIM) systems. Such systems consist of flexible, programmable manufacturinghardware and information system components. They allow for centralized control ofmanufacturing-related activities and help to improve the overall integration of design withmanufacturing. In addition, they may support production planning and scheduling, enhanceproduct service activities such as maintenance and repair, and furthermore provide a vehicle formanufacturing training and research [2]. Page 15.111.2However
develop a series of practical, handson laboratory exercises to educate students on the fundamentals of PLC application design andimplementation. In conjunction with development of laboratory courseware, an IndustrialControl Laboratory was developed and equipped with state-of-the-art PLC and controlinstrumentation and test equipment. This paper discusses the development and content of the laboratory exercises andphysical laboratory. We have now taught this course twice and have gathered studentperceptions on the quality and utility of the Industrial Control course. Students have requestedadditional emphasis in this area. We conclude the paper with plans for future courseenhancements.Overview The Electrical and Computer Engineering