(thinking vs. feeling), and outside world orientation (judging vs. perceiving) resulting in 16 personality types. Kolb Learning Based on quadrants of 2 dimensions of perception (sensing/feeling vs. Cycle thinking) and 2 dimensions of processing (doing vs. watching). Felder and Based on 5 dimensions of learning: perception (sensory vs. intuitive), Silverman’s input (visual vs. auditory), organization (inductive vs. deductive), Index of processing (active vs. reflective), and understanding (sequential vs. Learning Styles global). Herrmann Brain Based on 4 quadrants of thinking preferences generally characterized Dominance
automated systems for use as a learning tool and reference.AcknowledgementsThis material was supported by a National Science Foundation grant no. 0238269. Anyopinions, findings, and conclusions or recommendations expressed in this material are those ofthe author and do not necessarily reflect the views of the National Science Foundation.Bibliography1. Hsieh, S. "Automated Manufacturing System Integration Education: Current Status and Future Directions," Proceedings of 2005 ASEE Annual Conference, June 12-15, 2005, Portland, OR.2. Schank, R.C. and Abelson, RP. (1977). Scripts, Plans, Goal and Understanding: An Inquiry into Human Knowledge Structures. Hillsdale, NJ: Erlbaum.3. Abelson, R.P. (1981). Psychological status of the script
in the body of the report they submit. A meeting with course stafffollows to provide teams with feedback on their plans.Typical errors seen in team Gantt charts include failing to divide the work between members, or,at the opposite extreme, assigning tasks so atomistically that a coherent overall vision is lost.These typically are symptomatic of deeper problems—wanting to work together on all aspects ofthe project, for example, often comes from a lack of trust and confidence in one another, whereastotally compartmentalizing the project between team members may reflect a generalunwillingness to lead on the part of individual team members. In these cases, the project plan canserve as a diagnostic for team problems and a reason to
active learningGetting Experience Reflective Dialogueinformation &ideas‚ lectures ‚ take apart of common household ‚ students and faculty‚ textbooks products to identify and sort material collectively make decisions on‚ seminars from types course structure and rules guest speakers ‚ convert energy ‚ end of class discussions on the‚ collaborative ‚ use softwares (e.g., SimaPro, EIO- course materials and learning websites LCA) to perform life cycle analysis problems ‚ case-studies ‚ 1-minute tests ‚ role play
State University and a B.A. in Mathematics from Kenyon College.William Clement, Boise State University William P. Clement is Associate Research Professor at the Center for Geophysical Investigation of the Shallow Subsurface at Boise State University. His research interests include using near-surface geophysical methods such as Ground Penetrating Radar reflection data and cross-hole GPR tomography to better understand processes in the shallow subsurface.Joe Guarino, Boise State University Joe Guarino is a Professor in the Mechanical and Biomedical Engineering Department at Boise State University. His research interests include simulation modeling for engineering education, vibrations
PrimaryAs shown in figure 1, any given transformer can be reflected to the primary side or to thesecondary side. Also, the student has the choice of analyzing a given transformer based on theexact model as well as the approximate model. If the approximate model is selected, the studentneeds to specify one model from the list of the approximate models. The list consists of thefollowing approximate models: 1. Shunt branch moved to primary side. 2. Shunt branch moved to secondary side. 3. Shunt branch neglected 4. Both Shunt branch and resistance neglected.The parameters of the given transformer in this module must be inserted as an input values. Inaddition, the load voltage, the turn ratio of the transformer, the rated load in KVA and
, especially projects 1 and 2.Table 8. EXTREMESQuestion 4. From what material or method did you learn least?1. Project 2.2. The lectures.3. Again, difficulty with third presentation.4. Algorithms for image processing.5. The book itself. We had little motivation to open it. *6. N/A.7. --- Page 13.747.118. The book. ** Responses 5, 8 reflect the instructor’s implementation of the course, not the merits of the text.Table 9. OTHER. What other comments do you have on other aspects of the course?1. ---2. All in all, it was a
have been developed to-date. Thisdiversity reflects the complexity and breadth of modern engineering. At the same time, it poseschallenges to educators and policy makers seeking to understand how—or whether—engineeringcan become a more regular part of U.S. pre-college education. The noticeably thin presence ofmathematics, as well as of some key engineering concepts, such as modeling and analysis, raisesadditional questions about the difficulty of developing curricula that authentically represent thepractice of engineering.Another important question, not addressed in this paper but to be considered in the largerproject’s final report, is what impact K-12 engineering education has had on such things asstudent engagement and retention
fields. The Engineering in Health Care andEngineering Energy Solutions INSPIRES modules reflect real-world problems that chemicalengineers face today, and the students are given the theory and background information neededto consider possible solutions. The curriculum guides students through the engineering designprocess, which includes hands-on activities and mini design challenges coupled with the web-based tutorials and interactive simulations, to lead them to the final design challenge. TheEngineering in Health Care module has been tested with a wide range of students, and theEngineering Energy Solutions module is slated to begin testing in 2008.Engineering in Health Care: A Hemodialysis Case StudyThe Engineering in Health Care module has
complicated hardware and software based modules could be built withLabVIEW. In this section, we explain which modules we have built using LabVIEW 8.2 and itstool DSP Module 2. Specifically, we have developed 13 NI-Speedy-33 modules, 2 NXT modules,and 4 software-based modules. We elaborate more on the hardware-based ones utilizing the NI-Speedy-33 to reflect the real-time examples as much as possible. However, most aspects ofsignal processing and DSP classes could be implemented with software-based modules, but theywould be based on non-real-time data.When building hardware-based modules, some of the signal processing concepts such as signalgeneration, FFT, convolution, and filtering can be implemented directly by the students with thefunctions and
precursor to EGR 101 for initially underprepared students, WSU has made the coreengineering curriculum immediately accessible to roughly 80% of its first-year students. This isexpected to have an even stronger impact on student retention and success than the initialimplementation of EGR 101.7.0 Acknowledgments This work has been supported by the NSF Division of Engineering Education andCenters under grant number EEC-0343214, by the NSF Division of Undergraduate Educationunder grant numbers DUE-0618571 and DUE-0622466, and by a Teaching Enhancement Fundgrant at Wright State University. Any opinions, findings, conclusions or recommendationsexpressed in this material are those of the authors and do not necessarily reflect the views of
) ‡ Average agreement with the statement “The session helped me perform my role as a TA,” with 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, and 5 = strongly agree We are gratified by how positive these ratings are—particularly the post-semester ratings,which reflect the students’ evaluations of the value of the workshops in light of their actualexperience as TAs. At the same time, we recognize the limits of self-assessment for evaluation ofthe effectiveness of training programs, and one might wish for student ratings of the TAs’performance with which to triangulate the self-assessments. Unfortunately, the engineeringdepartments at this university do not collect such data except in the very rare cases whenteaching
. There are sixteen four-letter MBTI types. Example descriptionsof two of the sixteen types follow:ISTJISTJ is the most common type among practicing engineers. They are usually quiet andcan appear withdraw because of the I, but most of them make good use of their quiet timeby thinking of ideas and how facts go together. As S’s, they concentrate on executing thejob at hand, using logic (a T trait) to figure out the solution. Their J preference enablesthem to schedule and plan ahead, and they don’t like to have to adapt and change oncethey start down a path. ISTJs are dependable, organized, goal-oriented, and focused onthe facts.INTJINTJs combine their love of personal reflection with a structured and logical assembly ofendless possibilities. They
TestBefore discussing environmental concerns and to assess learning, students were given a pretestbefore beginning the topic and posttest after discussing the case studies. The questions asked onboth test were the same and reflect a sample of the various creative thinking and environmentalissues covered in the case study discussions. Table 4 lists the results from last semester’senvironmental pretest and posttest, and Table 5 lists selected questions asked on the pretest andposttest. Incidentally, the results from last semester’s pretest and posttest were consistent withthose of previous semesters.Table 4: Results from the environmental pretest and posttest for OLS 350 (Fall 2007)Pretest: Posttest:Number of
unlimited time) from the pure brainstormingactivity. Perhaps to gather statistically significant data, a class could be subdivided and only half Page 13.723.11given the bisociation half of the talk with the others simply given three more minutes to logideas. Then the numbers of ideas could be compared between the groups. The authors haveconjectured about doing this but have stopped short due to small class sizes and a concern thatthe variability person to person would most likely statistically mask the general trend without avery large sample size.Bisociation: Teaching PointsThe authors like to ask the students to reflect on how their thinking
practices, and more. The vast amount ofapplications developed for the Internet, like the Web, make computer networking an integral partof our daily life. These new trends and applications, including concepts and disciplinesencompassed, have introduced new research and educational requirements demanded by industryand/or society that are reflected in work force demands, employment figures, research grantopportunities, and enrollment in educational programs related to computer networking.Tying in concepts and techniques from networking and distributed processing (NDP) into thecurricula will better prepare students for future work force, and is therefore a major componentof this application. The goal of the lab was to incorporate elements of NDP into
assigned to schools in the area in which they live, the school demographics ofcourse reflect those of the surrounding community. In urban areas, this often results in studentpopulations with high needs. This is the case with Rachel Freeman. The unintended consequencesof such an assignment policy are numerous and daunting. The simultaneous implementation of anengineering curriculum with a predominantly new staff takes a strong administrator and hugesupport. The principal of Freeman is a very experienced administrator who is well regarded by herstaff, colleagues and central office personnel.The biggest challenge was in acclimatizing the students to a disciplined environment with highexpectations for behavior and academics. As stated, the children
Engineering (PLE), supported by PLM and Simulation Lifecycle Management(SLM). An initial implementation step is centered on the GIT Integrated Product Life-Engineering (IPLE) Laboratory, School of Aerospace Engineering (AE), to develop thenecessary digital support environment and to introduce PLM into its graduate andundergraduate aerospace systems design courses. Figure 1. The new educational research program architecture for lifelong learningAs illustrated in Figure 1 the new educational research program includes both educationand research. Its major focus is on introducing PLM seamlessly along the studentlifecycle. The yellow oval labeled GT Design Courses reflects graduate courses in theGIT School of AE graduate program in Aerospace Systems
consistency of ballistic gel is very similar to tissue, but the gel is homogeneouswhich does not provide a good image on an ultrasound. Tissue is inconsistent which results in auseful image because the sound waves are reflected adequately. To make the gel less consistent,particulate was added while the gel was setting. As a result, the image of the model neckappeared similar to the image of a human neck (Figure 2). Figure 1: Gel model of a neck without vessels Figure 2: Ultrasound of gel neck modelFor the tracking system, stationary fluid was used in the vessels; however, when the Dopplerfunction is implemented, the use of a pump system will need to be added to circulate the fluidthrough the vessels in opposite directions in a controlled
residing overseas at FerdowsiUniversity. The course structure format was designed to reflect the level and maturity of thestudents. Class met online twice a week. Hybrid e-learning methodology was used in the designand delivery of this course.Summer2006A programming course for engineers (CMPSC 201), a 3-week course meeting everyday for 3.5hours, was delivered according to the flexible delivery model. None of the students took Page 13.535.8advantage of connecting from home, but many of them downloaded the recorded lectures.Fall 2006Two courses were delivered using the described model: CSE 121 (new number for CSE 103),with an enrollment of 7 students
participants four months after thesession to determine the value and usage of the model to students. The post-test and sessionevaluation results (Table 2) reflected the attendees’ initial perceptions of the workshop and theAIR model. The usefulness of the workshop was directly related to the perceived relevance ofethical thinking in the student work. Not only are the statistics for Questions 1 (usefulness) and2 (relevance) exactly the same, but looking at individual responses, the majority of ratings forQuestions 1 and 2 were usually the same. While the results are positive, it still indicates thatsome students do not see any relevance in having a concrete ethical problem solving schema fortheir work in nanotechnology. The students also appreciated
2007 team-baseddiscussions and, occasionally, concept sketching31-34 was used to supplement lectures. In the2007 course concept sketching was used for the topic of metal deformation but not for the topicof annealing of work hardened material. On the MCI there was one question that reflected eachof the two topics. The questions and results for each of the two topics are presented belowThere are many types of macroscale-property/atomic-scale-structure material misconceptionsthat exist. One is the inappropriate attribution of a macroscale property to an atomic-scalefeature. For example if a softer, lower strength, annealed metal is cold worked by die drawing,extrusion or cold rolling, dislocation multiplication and pinning occurs which will
. The knowledge oftechnology for the purpose of this study consisted of practical, technical skills and knowledge oftechnical products. Undoubtedly the one major change in technology since the PATT study in1986 is the ubiquitous presence of computers at all levels of our society and the educationsystem. Therefore the knowledge and the comfort level of working with computers becomes amajor aspect of defining technology. In today’s society the two are often found to besynonymous however we have used a broader definition to reflect the interdisciplinary nature oftechnology that applies to more careers than that of computer science.This research investigated the reasons behind a student’s perception as well as their intent to notonly attend college
, consideration ofhow other professions, such as law and medicine, utilize practicing professionals in theireducational processes is warranted. The American Bar Association12 (ABA) establishes aset of standards for programs of legal education. Their curriculum requirements given inStandard 302.(b) state: “A law school shall offer substantial opportunities for: (1) live-client or other real-life practice experiences, appropriately supervised and designed to encourage reflection by students on their experiences and on the values and responsibilities of the legal profession, and the development of one’s ability to assess his or her performance level of competence; …”12In describing the instructional role of faculty, Standard 403(c) states: “A
the remaining tworesponses.From the survey question analysis it was ascertained that questions 1 and 3 indicated significantchanges from pre- to post-test, and questions 1, 2, and 3 showed 50% of the students respondingpositively to the module. Upon comparison of the quiz results to the pre- and post-test surveydata analysis, it was found that their performance on the first three questions of the quizconformed to their responses in the surveys. Questions pertaining to precision and accuracy andcontrolling a system, that were answered correctly by 10 out of 14 students in the quiz showedpositive response in the survey analysis. While the quiz reflected that only 7 out of 14 studentsanswered the question on sensitivity correctly, it was
. Fontecchio is the recipient of a NASA New Investigator award, the International Liquid Crystal Society Multimedia Prize, and the Drexel ECE Outstanding Research Award. He has authored over 35 peer-review publications on Electro-Optics and Condensed Matter Physics. His current research projects include developing liquid crystal polymer technology for optical film applications including electro-optic virtual focusing optics, reflective displays, flexible displays, power generating MEMS arrays, and photonic crystal structures with tunable defects. Page 13.798.1Eli Fromm, Drexel University Eli Fromm is
issues.Limitations and Future Work As this was an initial attempt to provide a taxonomic view of crowdsourced and openinnovation organizational perspectives on privacy, recruitment and engineering ethics, a limitednumber of these organizations were selected for evaluation. The goal of this research was toselect organizations for evaluation that reflected an overview of various types and from differingregions. With the crowdsourcing and open innovation market continuing to expand in size,complexity of project and area of reach, there is significant opportunity for further research intothis segment and the investigation of selected crowdsourcing industry silos or specific ethicalconcern.Conclusion Crowdsourcing and open innovation initiatives
experimentation mode, video feedback information in addition to theinformation should be given to the remote computer through the graphical user interface. Fastsystem responsiveness is a key goal of remote experimentation, so adopting fast Internetconnections like DSL, Cable or LAN should minimize response times. Different kinds ofinformation streams are exchanged between the server and the clients as follows: The data stream representing the measurements made on the physical system. The video stream acquired by the camera. The parameter stream that reflects the user actions on the client side. The administrative stream which deals with login/logout issues.National Instruments provides a fully featured built-in web server written in G language
representatives, employers, or surveys of alumni, as is theusual case for continuous program improvement assessment, cannot provide the depth of detail that potentially couldcome from an analysis of the labor markets’ supply and demand indicators. By using the data resources of theFederal-State Cooperative Labor Market Statistical System, known collectively for this paper as the labor marketinformation system (LMIS), to inform their continuous program improvement efforts, STEM programs couldinclude a relevant layer of information sources to aid in the identification, design, and alignment of programoutcomes and objectives with economic demands and needs of the state and region.This paper reflects one STEM program’s use of the LMIS to inform its program
scores for each student during the semester. (independent variable) • WPRSUM – The sum total of weekly progress report scores for each student during the semester. These totals reflect group work. (independent variable) • Proposal – Proposal presentation score. (independent variable) • Midterm – Midterm exam score. (independent variable) • Final Exam – Final exam score. (dependent variable) • Project – Final project total score. (dependent variable)Analysis for Fall 2006It was hypothesized that of the four independent variables, the weekly progress reports(WPRSUM) and proposal scores had the highest likelihood of having a relationship withthe final project since these items most closely