conceptual gains and usingthose gains to motivate development of the math skills needed for application.Bibliography1.Olds, Moskal, and Miller, “Assessment in Engineering Education:Evolution, Approaches, and FutureCollaborations”, Journal of Engineering Education, January 20052. David Hestenes, Malcolm Wells, and Gregg Swackhamer, “Force Concept Inventory”, The Physics Teacher, Vol. Page 14.15.630, March 1992.3. Evans, D.L. Gray, G.L. Krause, S. Martin, J. Midkiff, C. Notaros, B.M. Pavelich, M. Rancour, D. Reed-Rhoads, T. Steif, P. Streveler, R. Wage, K. “Progress on concept inventory assessment tools”, Proceedings ofthe 2003 Frontiers in
the overall pedagogy involved. 4) Publishing all of the exercises on the website http://eet.cecs.pdx.edu.AcknowledgementsThis work is supported by the National Science Foundation under Grant No. DUE 0633754. Anyopinions, findings, and conclusions or recommendations expressed in this material are those ofthe author(s) and do not necessarily reflect the views of the National Science Foundation. Page 14.37.11 References:1. G. Recktenwald, R.C. Edwards, “Using Simple Experiments to Teach Core Concepts in the Thermal and Fluid Sciences,” Proceedings of the 2007 American Society for Engineering Education Annual Conference
institutions in the U.S., Universityof Oklahoma, Norman, Oklahoma and University of Cincinnati, Cincinnati, Ohio. The goal ofeach REU Site was to provide eight week summer full-time in-residence research training andprofessional development program on the use of modern technology in conducting anddisseminating research in “Structural Engineering,” with special focus on techniques to studythe "Development of Enhanced Materials and Structural Assemblages for Seismic PerformanceEvaluation Studies." Each year six to nine students were selected, based on a nationalapplication process, who were divided in three teams, and each team worked on a well-definedresearch project under the guidance of faculty mentors(s) and a graduate research assistant(GRA
, ROM, and I/O. The initial experiment has the students use theHC11’s Buffalo Bug software to manipulate port outputs. The traffic light LEDs are connectedto the output ports of the microprocessors. Thus, the students directly control the lights bymodifying the contents of the memory locations associated with the output ports. This helps thestudents see the connection between software and what happens in hardware. Then the lectureexplains how programs can be written for the microprocessor and stored in on-chip RAM. Theidea of a simple flow chart is introduced to alternate green and red lights between N/S and E/W.The second experiment has the students implement the flowchart in C code, compile the code,and download it to the microprocessor. The
., Rosser, S.,Shalala, D. & Sheridan, J. (2005 August). More women in science. Science Magazine 309. 1190-1191.Trower, C. & Chait, R. (2002 April). Faculty diversity: Too little for too long. Harvard Magazine.Stewart, A. Malley, J. & LaVaque-Manty, D. (2007). Transforming Science and Engineering: Advancing AcademicWomen. Ann Arbor, MI: University of Michigan Press.7 Etzkowitz, et. al. (1994)Gibson, S. (2004). Being mentored: The experience of women faculty. Journal of Career Development 30(3). 173-188.Stewart, A. Malley, J. & LaVaque-Manty, D. (2007). Transforming Science and Engineering: Advancing AcademicWomen. Ann Arbor, MI: University of Michigan Press.Yedida, M. & Bickel, J. (2001). Why aren’t there more women leaders in
meanthat students are better equipped to solve statistical problems later in their careers.The benefits of NPCI are being investigated and results are presented elsewhere.This paper focuses on the concepts, methods, and applications of NPCI statistics.NPCI Concepts Page 14.912.2The theory behind many NPCI methods is not new. Many of the basic conceptshave been in the statistics literature since the 1940’s. However, NPCI methodsdid not see widespread application until the early 1980’s because the necessarycomputing power was not available. With the advent of cheap and easy-to-usecomputers, computer intensive methods for realistic data sets became possible.The
, individualize studentmodel, tutor module, and post-test module.Pretest and question module. The system offers a dynamic pre-test that can classify learnersaccording to their level of knowledge, such as beginner, intermediate, or advanced.Student model. The system includes an Error Patterns database that records patterns of errors inrung programming. If a learner attempts to run a program that contains an error, the system willuse built-in heuristic functions to identify the error pattern in the database that most closelymatches the learner’s error. Once the most similar error pattern has been identified, themisunderstood concept(s) will be displayed for the learner to see
Distribution & Logistics Manufacturing Systems Mechanical Technology Architectural Technology College of Technology and Computer Science 1st P Technology programs to match a student’s skills and ambition r o f Doctor of Technology Systems (DTS) e (Proposed Fall ‘08) s s Operational Systems Information & o Computer Technology n a l M.S. D
research using Multi-Institution Database for InvestigatingEngineering Longitudinal Development (MIDFIELD). MIDFIELD is a rich longitudinaldatabase with student-level records for all undergraduate students at nine southeastern publicuniversities from 1987-2005. The MIDFIELD database contains records for 857,001 uniquestudents of whom 462,443 received at least one bachelor’s degree, 135,860 who were at somepoint enrolled in engineering with 71,277 receiving a bachelor’s degree in engineering. First-time-in-college students who are U. S. citizens or permanent residents make up approximatelyhalf of this population and are the focus of this study.While many types of institution are not represented in the dataset, MIDFIELD includes datafrom multiple
protect an account with a strong password if the answersneeded to reset the password are just a few clicks away. That was the case with Yahoo accounts[23, 24]. A user trying to recover a forgotten password is asked to enter his/her e-mail address. Page 14.954.4Then (s)he is given the option of e-mailing a new password to an alternate e-mail address, orimmediately resetting the password through a form on the current Web page. If the user choosesProceedings of the 2009 American Society for Engineering Education Annual Conference & Exposition 3Copyright 1 2009, American Society for Engineering Educationan immediate reset, the site prompts
a librarian is asked a question, s/he may nothave to answer the same or similar question in the future. Imagine that students can askquestions online and are able to receive their professor’s answers even while that professor is offdoing his or her research, on sabbatical, or just on down time. A natural language knowledgemanagement system could be the solution. An integral component of knowledge managementsystems, a knowledge base, is used to optimize information collection, organization, and retrievalfor an organization, or for the general public [1]. Functions of a natural language knowledge basemake it possible to answer specific questions that are likely to be asked repeatedly by other usersbut perhaps in a slightly different manner
. Hwan, Y. S., Echols, C, Wood, R. Vrongistinos, K. (2001, April). African American college student’s motivation in education. Paper presented at the meeting of the American Educational Research Assoication. Seattle, Washington.9. Deci, E.L. & Ryan, R.M. (1985). Intrinsic motivation and self- determination in human behavior. New York:Plenum.10. Dweck, C.S. (2006). Is math a gift? Beliefs that put females at risk. In S. J. Ceci & W. Williams (Eds.), Are sex differences in cognition responsible for the underrepresentation of women in scientific careers? (pp. 47-55). Washington, DC: American Psychological Association.11. Vansteenkiste, M., Lens, W., & Deci, e. (2006). Intrinsic verus extrinsic goal
engineering curricula to meet the needs of a modern industrial society. Also, arecurring theme from American business and industry is that leadership must emerge at all levelsif we are to maintain our competitive edge. Because of the changing nature of modernengineering, young technical or staff engineers must grow into leadership roles faster than theirpredecessors.”2 In general the current engineering education system has been primarilyconcerned with the development of technical expertise and has not taught or promoted leadershipeducation and development in a systematic way. Since the 1990’s industry has, beenencouraging educational institutions to spend more effort on the development of communication
Cohoon and William Aspray. 2006. p. 205-238.3. DEEP: Developing Effective Engineering Pathways. NSF grant DUE-0336517.4. Eggleston, L. E. and Laanan, F. S., Making the Transition to the Senior Institution. In Transfer students: Trends and issues. New Directions for Community Colleges, edited by F. S. Laanan. 2001. p, 87-97. San Francisco: Jossey-Bass.5. Glass, J. C. and Harrington, A. R. Academic performance of community college transfer student and "native" students at a large state university. 2002. Journal of Research and Practice, 26, p. 415-430.6. Hills, J. Transfer shock: The academic performance of the transfer student. The Journal of Experimental Education , 33(3), (Spring, 1965). (ERIC Document Reproduction Service No. ED
AC 2009-1473: LEARNING MECHATRONICS THROUGH GRADUATEDEXPERIMENTATIONJohn Rogers, United States Military Academy John Rogers received the B. S. degree in aerospace and ocean engineering from Virginia Tech in 1986, and the M.S. degree in mechanical engineering from Montana State University in 1993, and his Ph.D. degree in mechanical engineering at Rensselaer Polytechnic Institute in 2003. Dr. Rogers is an Assistant Professor at the United States Military Academy. His research interests are design of mechatronic and robotic systems, and modeling of dynamic systems. Dr. Rogers is a registered professional engineer.Robert Rabb, United States Military AcademyChristopher Korpela, United States Military
theirgraduate student or post-doctoral mentor than with their faculty mentors, although satisfactionwith both was generally high (Table 2). Participants felt like a welcome member of the universityand the department, the program left them with a positive impression of research, and they allwould recommend the program to a friend (Table 2). Participant Survey Results Ave ± SD My grad student and/or post-doc mentor(s)... was available to assist me 4.7 ± 0.7 had a positive impact on my experience 4.7 ± 0.7 My faculty mentor... Was available to assist me 4.0 ± 1.4
the choice of assignment(s) with the assessment chair by the second week of the semester to ensure that the proper student work is being assessed. The instructor will be provided with the required rubric from the assessment chair. The rubric will be applied to all of the collected student work for the identified assignment. For archival purposes, the instructor places examples of each of the categories in the outcome binder. Note that an instructor may not have any examples for a given category if they did not rate any of the student work as being of that quality. Complete a summary sheet (a template is provided by the assessment chair) describing the assignments evaluated with the rubrics
TEPEER. The team effectiveness from the one general team effectiveness in the peerevaluation instrument is designated as TECT. The detailed list of the items is shown in Table 2.Constructs are labeled I, G and P, representing interdependency, goal setting and potency, shownas the last letter of “Item ID” in Table 2.Table 2: Peer evaluation items for measuring how a student evaluating their peers.9-items within TEPEER: Item ID Item Description CI021I Collaborates well with my team on all in-class and out of the class assignments. CI022I Contributes to my team's effectiveness by having a clearly defined role(s). CI023I Is a reliable team member. CI024G Often helps my team think of what we were/were not achieving
1 30 School S c Middle School Life Science (7th) 1 1 1 36 School D Computer High School Programming (12th) 1 1 1 20 School M d Elementary School General Science (3rd) 4 4 4 92 School P Science Elementary School (Kindergarten) 1 1 1 20 School L High School Physics
students.IntroductionAccording to the National Science Board (NSB)’s Science and Engineering Indicators 2004,enrollment in undergraduate engineering and science programs in the United States has been indecline since the 1980s1. Clearly, there is a continued need for increased enrollment andretention in science and engineering. Science, Technology, Engineering, and Mathematics(STEM) have become increasingly central to our economic competitiveness and growth. Long–term strategies to maintain and increase living standards and promote opportunity will requireunprecedented coordinated efforts among public, private, and non-profit entities to promoteinnovation and to prepare an adequate supply of qualified STEM workers2.The MSETI - AREA project utilizes an undergraduate
outcomes.Bibliography1. Commission on the Advancement of Women and Minorities in Science, Engineering, and Technology Development. (2000). Land of plenty: Diversity as America’s competitive edge in science, engineering, and technology. Arlington, VA: National Science Foundation.2. U.S. Office of Science and Technology Policy National Science and Technology Council. (2000). Ensuring a strong U.S. scientific, technical, and engineering workforce in the 21 st century. Washington, DC.3. Chubin, D. E., & Malcom, S. M. (2008, October 6). Making a case for diversity in STEM fields [Electronic Version]. Inside Higher Ed, from http://insidehighered.com/views/2008/10/06/chubin4. Antonio, A. L., Chang, M. J., Hakuta, K., Kenny, D. A., Levin, S
for Technology Innovation: The Framework of Education for Technology Innovation,” Proceedings of the 2008 National Meeting of ASEE, Pittsburgh, PA, June, 20083. Stanford, T. G., D. A. Keating, D. D. Dunlap, and R. N. Olsen, “Enabling the U. S. Engineering Workforce for Technological Innovation: The Role of Competency-Based Learning for Professionals,” Proceedings of the 2007 National Meeting of ASEE, Honolulu, HI, June, 20074. Schuver, M., T. G. Stanford, et. al., “Enabling the U. S. Engineering Workforce for Technological Innovation: The Role of Interactive Learning Among Working Professionals,” Proceedings of the 2007 National Meeting of ASEE, Honolulu, HI, June, 20075. Dunlap, D. D., D. A. Keating, T. G. Stanford, A. L. McHenry
-25. 2000.8 Astin, Alexander W, Executive Summary: How Service Learning Affects Students, Jan. 2000. Higher Education Research Institute. 19 Mar. 2009 .9 Astin, Alexander W, Executive Summary: How Service Learning Affects Students, Jan. 2000. Higher Education Research Institute. 19 Mar. 2009 . Page 14.1276.910 Duffy, John. “Village Empowerment: Service Learning with Continuity”. International Journal for Service Learning in Engineering. 3(2). pp. 1-12. Fall 2008.11 Driscoll, A., Holland, B., Gelmon, S., & Kerrigan, S. An Assessment Model for Service-Learning
Wheatland, J., “Research experience program for undergraduates in a Historically Black College and University.” Proceedings of the 2004 American Society for engineering Education Annual Conference & Exposition, 2004.3. Mervis, J., “Wanted: A better Way to boost number of minority Ph.D.s”, Science, 281, 1998, 1268-1270. Page 14.1308.94. Smith, S., Working recruitment miracles. Black Issues in Higher Education, 16 (170), 1999, 40-41.5. Jiang, X., Sarin, S., and Williams, M., “Assessment of NC-LSAMP project: A longitudinal Study”, Proceedings of the 2005 American Society for engineering Education Annual Conference
this topic will support my overall degreeobjectivesExample of Lab Partner Rubric, suitable for groups of twoPlease complete the following table to evaluate your own work and that of your lab partner.Me: ____________________ Did you/she/he . . . . Lab Partner: ____________________Did not Met my Exceeded Did not Met my Exceeded mymeet my expectation my meet my expectati expectationsexpectations s expectations expectation ons s
Proceedings of the Section on Statistical Education, Alexandria, VA: American Statistical Association, 143- 147, 1997. 3. ASA Section on Statistical Education Committee on Training of Statisticians for Industry, "Preparing Statisticians for Careers in Industry," The American Statistician, 34, 65-75, 1980. 4. Barton,R.R., Nowack, C.A., Bisgaard, S., Czitrom, V., Spurrier, J.D., Vardeman, S., “A One-Semester, Laboratory-Based Quality-Oriented Statistics Curriculum for Engineering Students,” The American Statistician, Vol. 52, 1998. 5. Bryce, G. R., “Data Driven Experiences in an Introductory Statistics Course for Engineers Using Student Collected Data,” Proceedings of the Section on Statistical Education, American
) #DIV/0! Thermal Expansion 1/K #DIV/0! Thermal Conductivity W/(m∧K) #DIV/0! 2 Thermal Diffusivity m /s #DIV/0! 2 Dynamic Viscosity N∧s/m #DIV/0! 2 Kinematic Viscosity m /s #DIV/0! Prandtl Number NONE #DIV/0!Dark shaded cells will be user input. Values for light shaded cells will be inputtedduring testing by the course instructor.Once the spreadsheet is
were willing to continue applying concept mapping approach into other subjects even though the beginning works were sort of hard for them. ACKNOWLEDGMENTS The work reported here was supported by grants from NSC-95-2516-S-276-008-MY3, the National Science Council in the Republic of China (Taiwan) and the principle investigator was Dr. Kuo-Hung Tseng. The authors also greatly appreciate the kind assistance of Dr. Page 14.1091.6 Wang-Long Li, Wen-Ping, Vicky and all those who made this paper possible
AC 2009-939: A SYSTEMIC SOLUTION: ELEMENTARY TEACHERPREPARATION IN STEM EXPERTISE AND ENGINEERING AWARENESSLouis Nadelson, College of Education Louis S. Nadelson is an Assistant Professor in the College of Education at Boise State University. His research agenda is motive by science education and includes aspects of conceptual change, inquiry, and pre-service and in-service teacher education. He has investigated learning for conceptual change and the impact of inquiry on modifying misconceptions. Dr. Nadelson earned a B.S. degree in Biological Science from Colorado State University, a B.A. with concentrations in computing, mathematics and physics from The Evergreen State University, a
, their workersare forced to adopt complex understanding and problem solving skills in technical areas.However, research pertaining to worker preparedness indicates that colleges and universities arenot adequately preparing graduates for this new work environment (Wieman, 2008)24.Manufacturing has become a field where global view and technical savvy are desirous qualitiesfor all persons involved. Since the 1980’s, manufacturing has undergone significant changes inoperational costs and product quality. The lean mangers of the 20th century are now retiring andthere are not enough new lean experts to lead US manufacturing into the next 20 years (Linford,2007)13.BackgroundResearch surrounding instructional design models has found that effective