AC 2011-2060: MODE OF ERROR ANALYSIS OF STUDENT RESPONSESTO PRE-REQUISITE KNOWLEDGE ASSESSMENTSDavid B Benson, Kettering University Page 22.1071.1 c American Society for Engineering Education, 2011 Mode of Error Analysis of Student Responses to Pre-Requisite Knowledge AssessmentsAbstract In engineering education there are a number of central concepts and skills that formthreads which connect one content area to another within a discipline. These threads form thecore of an engineering education and are the scaffold upon which all future knowledge is built.An incomplete understanding in any
the community where he chairs the local Military Affairs Committee, serves on the Chamber of Commerce Advisory Board, and is on the Board of Directors of the Base Community Council which supports the Columbus Air Force Base. He is working on his PhD dissertation in Public Policy and Administration with a focus on organizational change in the engineering and military professions.Rayford B. Vaughn, Mississippi State University Dr. Vaughn received his Ph.D. from Kansas State University in 1988. He is a William L. Giles Dis- tinguished Professor and the Associate Vice President for Research at Mississippi State University. He teaches and conducts research in the area of Information Security. Prior to joining the University
. He has authored or co-authored more than 60 technical journal and conference papers on these topics. He is a senior member of IEEE and member of ASEE.Arthur B. Ritter,Ph.D., FAIMBE, Stevens Institute of Technology Dr. Ritter received his BChE degree from the City College of New York, and his MS and PhD degrees in ChE from the University of Rochester. Before returning for his PhD degree he had over 10 years of indus- trial experience in the aerospace industry for the US Navy and United Aircraft in solid rocket propellant development and as a development engineer for the Mixing Equipment Company and the DuPont Co. His first academic appointment was at Stevens Institute of Technology in the department of Chemistry and
B. Ritter, Ph.D., FAIMBE, Stevens Institute of Technology Dr. Ritter received his BChE degree from the City College of New York, and his MS and PhD degrees in ChE from the University of Rochester. Before returning for his PhD degree he had over 10 years of indus- trial experience in the aerospace industry for the US Navy and United Aircraft in solid rocket propellant development and as a development engineer for the Mixing Equipment Company and the DuPont Co. His first academic appointment was at Stevens Institute of Technology in the department of Chemistry and Chemical Engineering where he did research on solar energy storage and conversion and optimal control of chemical processes. He taught courses in
AC 2011-507: CERTIFICATE/CONCENTRATION IN ENGINEERING FORP-12 EDUCATORSAnnMarie Thomas, University of Saint Thomas AnnMarie Thomas is an assistant professor of Engineering at the University of St. Thomas, and co- director of the UST Center for Pre-Collegiate Engineering Education. Her teaching and research focus on Engineering Design and K-12 Engineering Education. Prior to her appointment at UST, she was a faculty member at Art Center College of Design.Jan B. Hansen, Ph.D., University of Saint Thomas Jan B. Hansen is co-director of the Center for Pre-Collegiate Engineering Education at the University of St. Thomas. Her current interests as an educational psychologist focus on outreach through the nonprofit
multi-faceted, multidisciplinaryengineering issues. They are then asked to determine the most important problem/s and todiscuss stakeholders, impacts, unknowns, and possible solutions. Table 2 presents a summary ofsample scenarios, and Appendix B provides three full scenarios with instructional prompts. TheEPS Rubric, an analytic rubric, was developed to measure the extent to which studentperformance in response to a given scenario achieved the six learning outcomes associated with Page 22.38.2the ABET professional skills. This method is flexible, easy to implement, and can be used at the course level for teaching and measuring engineering
Page 22.683.1 c American Society for Engineering Education, 2011 Experimental Modules Introducing Microfabrication Utilizing A Multidisciplinary Approach S. Wagoner, W. Cui, W. E. Jones, D. Klotzkin, G. Meyers, and B. E. White Jr. Binghamton UniversityAbstract A comprehensive, multidisciplinary approach to introducing the concepts ofmicrofabrication to the undergraduate student body is being developed. The approach relies onmultidisciplinary expertise in electrical engineering, mechanical engineering, chemistry, andphysics and utilizes a pipeline approach to introduce concepts in microfabrication at thefreshman, sophomore
NSF funded programs: the UT System Louis Stokes Alliance for Minority Participation, the Bridge to the Doctorate Program. Through his work on student retention issues, he has gained international recognition as an expert in the effectiveness and impact of strategies for access to higher education. He regularly consults with other institutions, nationally and abroad, on these issues.G. B. Lush, University of Texas, El PasoGabriel Della-Piana, Evaluation Consultant Gabriel Della-Piana is Professor Emeritus in Educational Psychology from the University of Utah. He is currently a consultant on program design, development and evaluation in educational programs and projects. Most recently (Jan 2003 to Jan 2007) he was
AC 2011-2226: TESSAL: PORTABLE DISTRIBUTED LABORATORIESIN THE ECE CURRICULUMBonnie Ferri, Georgia Tech Bonnie Ferri received a BS from Electrical Engineering from Notre Dame in 1981, a MS in Mechanical and Aerospace Engineering from Princeton in 1984, and a PhD in Electrical Engineering from Georgia Tech in 1988. She is currently a Professor and Associate Chair for Graduate Affairs in ECE at Georgia Tech. Her research has been in the areas of embedded control systems, applications of control, control of computing systems, and education. She is the recipient of the 2007 IEEE Education Society Harriet B. Rigas Award.JillL L Auerbach, Georgia Institute of Technology Jill Auerbach is a Senior Academic Professional
mounting a campaign to a) take computer science to the high schools, b)increase the visibility of computing as a career, and c) develop curriculum and studies on how toconvey an appealing message that describes the opportunities and challenges of the field24.Compounding this problem is the fact that once we have prospective majors in the classroom,their prospects for success are not great. Low enrollments and high DFW rates are obviouslyconnected. Although computer science advocates claim computer science is not about mindless Page 22.985.6abstract programming done by lone hackers late at night, that is almost exactly what mostintroductory
been developed and assessed. A collaboration was established between two U.S.universities for this project: California Polytechnic State University (Cal Poly) and AuburnUniversity (Auburn). Cal Poly is a predominantly undergraduate institution, while Auburn is aTier 1 research institution.This paper provides progress on this extensive investigation including a) recent activities thathave been conducted at the universities, b) recent activities that have occurred between theuniversities and other project partners, and c) overview of assessment methods and data. Some ofthe categories of activities reported have been conducted over multiple terms and modificationshave been made to improve effectiveness of these new teaching methods. This paper
, Page 22.142.9assignments, examinations, etc.) in an attempt to identify how differences in instruction affectconceptual learning. Table 3: Selection frequency of all answer choices (correct answers are highlighted) a b c d e f g 1 17% 5% 12% 66% 2 57% 26% 14% 3% 3 5% 25% 56% 14% 4 28% 13% 45% 13% 5 72% 20% 6% 1% 6 4% 9% 12% 12% 56% 7% 7 37% 12% 16% 35% 8 13% 85% 1% 2% 9 36% 12
associate degree program at the urban communitycollege that trains students to be super technicians who are qualified to be hired as robotics,automation, manufacturing, and/or electronics technicians; (b) set up a state of the art roboticslaboratory at the urban community college to offer students an abundance of hands-on, practicalexperience that prepares them for immediate entry into the workforce upon completion of theprogram; (c) increase the success rate of the electronics, computer information system, andcomputer aided drafting & design technician programs at the urban community college byincorporating robotics-related activities and instruction into their curricula; (d) introduce roboticsconcepts to 11th and 12th graders in select high
AC 2011-417: IMPLEMENTATION AND ASSESSMENT OF CASE STUD-IES IN A FRESHMAN ENGINEERING PROGRAMJames E. Lewis, University of Louisville James E. Lewis, Ph.D. is an Assistant Professor in the Department of Engineering Fundamentals in the J. B. Speed School of Engineering at the University of Louisville. His research interests include paral- lel and distributed computer systems, cryptography, engineering education, undergraduate retention and technology (Tablet PCs) used in the classroom.Patricia A Ralston, University of Louisville Dr. Ralston is currently professor and Chair of the Department of Engineering Fundamentals and an As- sociate in the Chemical Engineering Department at the University of Louisville. As
engineer and(b) how epistemic frame development progresses over time. Data are collected during theseinterviews through:1. An epistemic frame inventory, to assess the extent to which players have developed the skills, knowledge, values, sense of identity, and epistemology (the epistemic frame) of the engineering profession6-9; Page 22.1567.52. An engineering intentions instrument, including items from the Test of Science Related Attitudes to assess the extent to which players intend to pursue further study of engineering and/or an engineering career10; and3. A game immersion instrument, to assess students’ qualitative experiences with the
, and (4) links new knowledge with prior knowledge. Asindicated in Table B, the author suggests three generalized types of communication tasks forengineering education (each focused on strategy acquisition for a specific type of higher-orderperformance). These assignments are sequential, and all culminate in – and contribute to thequality of – the final course artifacts for teaching the design process (devices /prototypes andattendant documentation, which are the traditional end-product of most engineering designcourses).Crafting a communication assignment that guides students through a series of higher-ordermental manipulations is not an easy task. However, the authoring functions of CPR andreification of the dynamics of the four structured
of Science, Lab on a Chip, and had an AIChE Journal cover. She is an active men- tor of undergraduate researchers and served as co-PI on an NSF REU site. Research within her Medical micro-Device Engineering Research Laboratory (M.D. ERL) also inspires the development of Desktop Experiment Modules (DEMos) for use in chemical engineering classrooms or as outreach activities in area schools. Adrienne has been an active member of ASEE’s WIED, ChED, and NEE leadership teams since 2003.Keisha B. Walters, Mississippi State University Keisha B. Walters is an Assistant Professor of Chemical Engineering at Mississippi State University (MSU). She received her B.S. degree in Biological Sciences from Clemson University
; • Identify characteristics of: o successful engineering education innovation adopters; o work environments that promote and those that impede successful implementation of engineering education innovations by individual faculty members; and • Develop an implementation model that promotes successful faculty characteristics and work environments.Specific tasks, discussed in further detail in the Plan of Work, must be performed in order toachieve these research objectives, including: • Assess, document, benchmark, and validate: a) characteristics of individuals who adopt (or choose not to adopt) engineering education innovations and b) their respective work environment; • Analyze faculty
0 11 9 7 5 3 1 1 3 5 7 9 11 11 9 7 5 3 1 1 3 5 7 9 11 Learning Preferences Scale Learning Preferences Scale (c) (d)Figure 2. Graphs of the Learning Preferences for Students in Environmental Engineering Courseand the number of students with the learning style preference. (a) Active vs. Reflective, (b)Sensing vs. Intuitive, (c) Visual vs. Verbal, and (d) Sequential vs. GlobalWhat does this mean to improving learning? The class as a whole favors active, sensing
pace3,4,5.Both of these systems are good examples of how technology can be used effectively to teachPLC programming. However, a PLC is just one component of an automated system.Technologies are needed to enable students to learn how to integrate multiple components toform an automated manufacturing system, develop the associated control logic, and run thesystem. In addition, research suggests that realistic practice in authentic learning environmentsleads to better transfer of skills6,7. Figure 1(a). Flow diagram for PSE for design of automated systems (top section) Page 22.435.3 Figure 1(b). Flow diagram for PSE for
View A&M Universityjoined colleagues at Wayne State University to be trained in the process of developing andvalidating test items consistent with the MILL Project goals and objectives. The test items werereviewed in accordance with SME guidelines for CMfgT exam item reviews, which includedteam-based evaluation of: (1) Item Content and Relevancy; (2) Rubric, at the topic learningoutcome, ABET criteria and SME BOK levels; (3) Cognitive level (Knowledge, Application, orJudgment). The test items were subject to editing, modification, and in some cases removal fromthe test bank as needed, to meet requirements. It was determined to create a standardized test,consisting of two forms (Form A and Form B), and allow the test‟s length initially to
paces. We hypothesize that this approach to hands-onelectronics education will improve multiple learning outcomes within the ABET assessmentframework, including outcomes (a) apply math and science, (b) conduct experiments andinterpret data, and (e) solve problems. This paper presents our experiences using a customportable electronics experiment kit (PEEK) in a general engineering program. The PEEK andthe accompanying laboratory experiences were developed with NSF-CCLI support. Twoelectronics courses, ENGR 3014—Circuit Analysis and ENGR 3050—Instrumentation andControls were selected for this research. As a supplement to regular face-to-facelaboratory meetings, each student was given a PEEK to complete the pre-laboratory workand to complete any
instruments and mobile hardware to support sessions that address amyDAQ/RASCL tutorial, second-order filters, instrumentation amplifiers, electrocardiography,and electrooculography. Pre- and post-session surveys and assessments indicate that (a) learningobjectives were effectively met with this technology, (b) students find the toolset to be a sensiblealternative to learning environments that employ desktop instrumentation, and (c) students wouldbe willing to invest in a such a resource, as it would be useful for many analog and digitalcourses offered in standard electrical and computer engineering curricula.I. IntroductionLaptop-based data acquisition (DAQ) toolkits used for secondary electronics education have thepotential to (a) alleviate
getfamiliar with the basic commands and functions of the real FDM3000. When the usermove his/her mouse to a certain button on the 3D virtual machine, thedescription/introduction of the button function will pop up and instruct the user how tooperate that part on the real machine (see Figure 1-b). In (2) the user can practicecalibration of the machine in its virtual calibration environment. It is critical to calibratethe FDM machine frequently. Improper calibration can result in misalignment ordisplacement of its support material from its proper XYZ-axis position. Because there areseveral functional keys and buttons in the front panel of the machine, therefore, it is veryeasy to get confused by the user. Moreover, the user may run the machine before
Case Study (2 students) while 4 students identified “learning about different biometric systems” as the most interesting part of the course. • What was the least interesting part of the course? Students thought that the least interesting part of the course was the mathematical computations (3 students) and review of DSP material (2 students) while 5 students did not identify any part of the course as least interesting. • After graduation, are you considering working/studying in the field of (a) Forensics (b) Applied Signal Processing (c) Biometrics (d) Other 6 students were considering one of the first 3 choices as an option while 3 others had already decided on a different area
programs/courses was targeted for the requisitestudent participants in this study. Student interview participants were selected at random fromthe pool of applicants, with an effort to ensure adequate representation among all target groupswithin engineering programs (gender, ethnicity, disciplines). All universities will use EWB-USAas the target extracurricular program. Control group students (not participating in LTS) will beselected from the broader collection of students in each institution’s School/College ofEngineering. A final control cohort will be selected for each university’s Clusters A and B tomirror the average demographic composition (gender, ethnicity, majors) of the two cohorts(curricular and extracurricular LTS) as closely as
elaborate. The specific objectivesare: (a) development, and implementation of web-based virtual experiments in the chosenlaboratory course and (b) assessment of virtual experiments from a perspective of studentlearning enhancement.Description of Virtual ExperimentsThe methodology for converting a physical experiment into a virtual experiment has beendescribed in Refs [14-15], and readers are referred to those articles for more details. In designingall four virtual experiments described in this study, following criteria were used.(i) The salient features of each physical experiment must be preserved in the physical to virtual domain mapping.(ii) The objectives, experimental procedure, data acquisition and expected outcomes of the experiment are
-Capacitor-Based Step-Up Resonant Converters”, IEEE Trans. Circuits and Systems—I: Regular Papers, vol. 52, no. 5, May 2005[6] H. Patangia, “Amplitude Division Multiplexing Scheme in Analog Signal Processing”, in Proc. IEEE Int. Midwest Symp. Circuits & Systems, August 2005, Cincinnati, Ohio.[7] B. P. Lathi, Modern Digital and Analog Communications Systems, (The Oxford Series in Electrical and Computer Engineering), 3rd edition, Oxford University Press, April 1998.[8] H.C. Patangia and D. Gregory, “High Voltage Signal Processing Using a Small Signal Approach” in Proc. IEEE 2007 ISSPIT, December 2007, Cairo, Egypt.[9] H. Patangia and D. Gregory, “Sectionalized PWM(S-PWM): A New Multilevel Modulation
, Conference Proceedings[7] Desai R, Lord E, (2002) ASEE Annual Conference Proceedings 261-265.[8] Thinger B, Memon A, Shih LF, (2006) ASEE Annual Conference and Exposition, Conference Proceedings[9] Collins EL, (2002) NSF 03-305:[10] Gibbings P, Brodie L, (2008) International Journal of Engineering Education 24:1119.[11] Crossman GR, (1997) ASEE Annual Conference Proceedings[12] Skurla C, Eisenbarth S, Campbell R, (2007) ASEE Annual Conference and Exposition, ConferenceProceedings[13] Krenelka L, Watson J, Salehfar H, Seames W, C. N. N. Caldarola, (2006) US-China Forum on DistanceLearning 1:[14] Rajagopal C, (2008) ASEE Annual Conference and Exposition, Conference Proceedings[15] Feisel LD, Rosa AJ, (2005) Journal of Engineering Education 94:121.[16
Engineering of Washington State University. He received his PhD in mechanical Engineering from Texas A&M Univer- sity, College Station, TX in 2001.David B. Thiessen, Washington State University David B.Thiessen received his PhD in Chemical Engineering from the University of Colorado in 1992 and has been at Washington State University since 1994. His research interests include fluid physics, acoustics, and engineering education.Baba Abdul, Washington State University Baba Abdul received an MSc. in Chemical Engineering from Ahmadu Bello University, Nigeria in 2005. He is currently a doctoral candidate in the Voiland School of Chemical Engineering and Bioengineering at Washington State University. His research