-averageperformance for example, in a prerequisite course). In this case, a negative correla-tion between website use and final exam performance would not determine a negativeeffect. For this reason, Cramster website use was first compared with common mea-sures of students’ skills entering the course to determine whether a lack of preparationcaused a predisposition for website use. Scores on both the SAT Math test and thefinal exam of the prerequisite course were normalized; the Z score for a given student’sexam, s, is calculated by normalizing the deviation from the mean by the standarddeviation, or s−µ Zs = . (1
-semester EngineeringStudents and its Implementation in a Large Introduction to Engineering Course,” ASEEConference Proceedings, pp. 10135-10139, 2004.4M. Grimheden, “From Capstone Courses to Cornerstone Projects: Transferring Experience fromDesign Engineering Final Year Students to First Year Students,” ASEE Conference Proceedings,AC 2007-1582, 2007. Page 22.401.85 S. Ekwaro-Osire, J. J. Mendias III, and P. Orono, “Using Design Notebooks to Map Creativityduring Team Activities,” Proc. FIE Conference, 2009.6 H. Hassan, “Creativity and Innovation for Electrical and Computer Engineering Research,”Proc. ASEE Annual Conference, 2004.7 A. J. Wilkinson, R
a 10-Likert scale from Page 22.454.4zero to 100 rather than a 5-point Likert scale, because it is a stronger predictor of performanceand students, the population of interest, have a comfort level in being scored in school on a 100-point scale.5 Finally, the scale was modified in order to identify the impact of their serviceexperience(s) relative to their traditional (i.e., non-service-learning) coursework simultaneously.This was accomplished with a double-sided scale where the extremes represent 100% for oneintervention and 0% for the other intervention Example: 10CL/90SE = 10% from coursework learning/90% from service experienceA
-patterned adhesives," IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, Page(s): 105 - 111, February 2006.9. P. Glass, M. Sitti, and R. Appasamy, "A New Biomimetic Adhesive for Therapeutic Capsule Endoscope Applications in the Gastrointestinal Tract," Gastrointestinal Endoscopy, Vol. 65, No. 5, Page AB 91, April 2007.10. B. Kim, S. Park, C. Jee and S. Yoon, "An Earthworm-Like Locomotive Mechanism for capsule endoscopes," IEEE/RSJ International Conference on Intelligent Robots and Systems, Page(s): 2997 - 3002, August 2005.11. R. Siegwart and I. Nourbakhsh, "Introduction to Autonomous Mobile Robots," The MIT Press, 2004
attitude has been observed in bothgroups of students. However, the change is less in case of model group. The negative change instudent’s attitude can be attributed to difference between students’ perception aboutprogramming before the course and the reality they learned during the course.REFERENCES [1] Shallcross, Lynne, “Piecing It All Together”, ASEE Prism, November 2006, Volume 16, Number 3, http://www.prism-magazine.org/nov06/tt_01.cfm. [2] Canfield, S. L., and M. A. Abdelrahman, “Enhancing the Programming Experience for Engineering Students through Hands-On Integrated Computer Experiences,” Proceedings of 2009 ASEE Southeastern Section Annual Conference, Marietta, GA, Apr. 5-7, 2009. [3] Herniter, M
S. Garcia-OteroAbstractThe Goddard Electro-Magnetic Antenna Anechoic Chamber (GEMAC) is a world-class facility formeasuring radiation patterns of antennas and other microwave devices and instruments.. Anechoicmeans neither having nor producing echoes and is a shielded room whose walls have been covered with amaterial that absorbs so much of the incident energy that it can simulate free space. The anechoicchamber measures the isotropic (all directions) gain pattern of an antenna. These measurements are takenat different angles and frequencies. Goddard Anechoic chamber has been used for decades to test bothprototype and flight antennas affiliated with Goddard missions and outside entities. This paper presentsthe procedure and findings to
in their professional career along withsolid knowledge and skills in pursuing graduate degrees.Foremost, engineers are people of action. Engineering students deserve to be prepared for the challengesof their profession. They should be able to implement their creativity and make their dreams come trueby also relying on the computing power.References[1] Bäcker, A. Computational Physics Education with Python. IEEE Computer Society, Computing in Science and Engineering, May 2007, pp. 30-33.[2] Glotzer, S. C., B. Panoff & S. Lathrop. Challenges and Opportunities in Preparing Students for Petascale Computational Science and Engineering. IEEE Computer Society, Computing in Science and Engineering, September 2009, pp. 22-27.[3
vmpp vmppDifferentiating (1) gives v iRs 1 R di di v isat e t s (10) dv v v dv t t This gives v mpp i mpp Rs i sat vt
”, Polymer Composites 4, pp 40-46 (1983).[3] Z. Ounaies, C. Park, K. Wise, E. Siochi, and J. Harrision, “Electrical properties ofsingle wall carbon nanotube reinforced polyimide composites”, Composite Science andTechnology 63, pp 1637-1646 (2003), available online at sciencedirect.com.[4] Dietrich Stauffer, Taylor and Francis, “Introduction to Percolation Theory”, (1985).ISBN 0-85066-315-6.[5] O. Meincke, D. Kaempfer, H. Weickmann, C. Friedrich, M. Vathauer, and H. Warth,“Mechanical properties and electrical conductivity of carbon-nanotube filled polyamide-6and its blends with acrylonitrile/butadiene/styrene (ABS)”, Polymer 45, pp 739-248(2004), available online at sciencedirect.com.[6] S. Bose, A. Bhattacharraya, A. Kulkarni, P. Poetscheke
. Most 50-minutelecture periods involve a set of PowerPoint lecture slides that run on average about 15 minutes,and then the instructor solves two or three example problems for the remainder of the period.Additionally, many classes use models and physical demonstrations to aid students in visualizingconcepts. These demonstrations are usually five minutes or less in duration. Students areassigned simple homework problems that are similar to the in-class examples, and theseproblems are turned in by the students at the beginning of the next class period for credit.Quizzes are given weekly to gauge learning and reinforce the most important learning outcomes.Upon grading of the quizzes the instructors note and record the specific mistake(s) made by
(if their focus was on businessapplications). With the development of microprocessors in the 1960’s, the character of thelandscape began to change. Technology changed, creating demand for engineers whounderstood the hardware and electronics underlying the chips but also were conversant with andcapable of developing the software components of a system. It was not possible to adequatelytreat the topics needed for education of these engineers in the context of a specialization areawithin an electrical engineering program of study. The first computer engineering program wasaccredited by the EAC of ABET in 1971, and between about 1970 and 1990, computerengineering emerged as a separate discipline. The last decade of the twentieth century
and universities; panel reviewer for US DOE GAANN Fellowships (2009, 2010), NSF EEP (2005-08), and S-STEM (2008). Her assessment findings and evaluative works are reported in IEEE, presented in ASEE and FIE conference proceedings, and acknowledged in Mixed-Nuts on several different projects. Dr. Lee- Thomas also presented her evaluative work as a key component in an award-winning NPR radio broadcast ”Sounds of Progress” on The Women In Science, Technology, Engineering and Mathematics ON THE AIR! as part of a NSF funded project with Norfolk State University’s College of Science, Engineering and Technology.Autar Kaw, University of South Florida Autar K Kaw is a Professor of Mechanical Engineering and Jerome
-existing ideas may very well be an approach that can enthuse studentsto attain the goal of becoming future scientists, technologists, engineers, and mathematicians.i This material is based upon work supported by the Learning through Engineering Design and Practice, NationalScience Foundation Award# 0737616, Division of Research on Learning in Formal and Informal Settings, under Page 22.1238.2Information Technology Experiences for Students and Teachers (ITEST) Youth-based Project. Opinions, findings,conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflectthe views of the
drawings on paper or whiteboard, but also might include screenshots or photos of partially developed sketches/prototypes. There should be several! 4. Choice rationale: Provide a rationale for your choice of the design idea(s) that you converged on for prototyping. That is, given the set of ideas that you considered, why did you choose these ideas for further development? 5. Novelty: Is it novel? If not novel, how does it differ from what currently exists, and how is it better? 6. Appropriate to user needs: Make sure to indicate how this design meets the key goal(s) that you Page 22.1631.3
Stefanou et al.’s framework, student autonomycan be promoted at three different levels: organizational, procedural, and cognitive. These threelevels include varying degree of student choice: organizational autonomy takes into account theenvironment (e.g., due dates), procedural autonomy incorporates form (e.g., deliverable form),and cognitive autonomy involves content (e.g., designing projects). This range of possible SDLexperiences allows for a wide interpretation of the role and value of SDL and student autonomyby both students and faculty. Using methods of grounded theory, three research questions wereaddressed: (a) How do the pedagogical practices in the first-year mathematics, physics, andengineering classes fit into Stefanou et al.’s
director of the undergraduate program in computer engineering at MSU. She also served as interim department chair in the Department of Electrical and Computer Engineering from 2000 to 2001. She was a research staff member in the Scalable Computing Laboratory at the Ames Laboratory under a U.S-D.O.E. Postdoctoral Fellowship from 1989 to 1991. Her teaching and research has focused on the areas of embedded computer systems, reconfigurable hardware, integrated program development and performance environments for parallel and distributed systems, visualization, performance monitoring and evaluation, and engineering education. She currently serves as principal investigator for NSF STEP and S-STEM grants in the college. Dr
class titled “ENGR 1510Intensive Hands-on, Interactive Fluid Flow & Heat Transport” was focused on developingstudents’ intuition using videos, hands-on activities, lectures and discussions. It was made opento all engineering majors because a lot of engineering classes contain elements of FMHT, and thegrading policy adopted was a pass/fail (S/U) with course participation taking 50% of theweighting and the remaining 50% equally distributed between the class exercises and finalexamination.Given the context of this class, the researchers deemed it fit to ask questions in the form: Can thelearning in this class be deemed significant enough to prepare the students’ cognitively andaffectively for more learning? Also, given the pass/fail grading
process, and supporting transfer students at theuniversity.Transfer students at the Ira A. Fulton School of Engineering at Arizona State Universityare supported by a Motivated Engineering Transfer Student (METS) Center wherestudents can network, study, socialize, and receive informal mentoring. In addition,transfer students can enroll in an Academic Success Class for one credit and attendadditional workshops which are held in the Center. Scholarship for over 30 qualifiedtransfer students are provided each year through an NSF S-STEM Scholarship Program.An experimental scholarship program, for transfer students who do not qualify for NSFS-STEM scholarships, was also evaluated. An emphasis in this project was placed oninvolving women and
designer’s usual way of thinking and the type(s) of thinkingrequired to resolve a given Problem A. For example, a designer whose capacity for sketchingis low might learn some basic drawing techniques to help bridge this (level) gap. Or, adesigner who tends to think tangentially may need to apply techniques that help him/her to“stay focused” (a different style) in order to solve a particular problem. Once again, werecognize the need for a systematic way to characterize design techniques, so the appropriatechoices can be made; we turn now to our development of such a classification scheme.3. A Cognition-Based Classification Scheme for Design TechniquesBased on the Cognition-Based Design (CBD) framework described briefly above, we havedeveloped a
, mesh, and solve. Within about an hour, anyone who is familiar withMicrosoft Windows and understands the component description of a force can learn how to dothis for a diverse range of shapes and loadings. And the graphical portrayal of input and outputquantities makes it easy to detect many user errors. But what are educators doing to incorporatethis ubiquitous, increasingly inexpensive tool into basic engineering classes?The practice of embedding or integrating FEA into freshman design courses seems to have madean appearance in the 1990‟s, coincident with the movement to develop integrated freshmancurricula that include or emphasize design. Barr et al. (1998; 2005)1,2 describe their work toinclude FEA as part of a larger focus on solid
a secondary student’s design-based project(s) – an often important aspect of anundergraduate Introduction to Engineering Course.Currently, a student’s transcript is the most widely applied and utilized model for representing astudent’s learning and practice of STEM concepts. The transcript provides a series of one-dimensional, snapshots (grades) aggregated as a Grade Point Average – GPA, and is sometimessupplemented with other data such as SAT® or ACT® scores. The assessment process that ismost often used to generate a transcript grade is the administration of multiple-choice tests,inferences from which have, for the past century, been central to the definition of competency.Given the potential richness and complexity of evidence of
), 339.2. Heller, R. S., Beil, C., Dam, K., & Haerum, B. (2010). Student and Faculty Perceptions of Engagement in Engineering. Journal of Engineering Education, 99(3), 253-261.3. Lin, C., & Tsai, C. (2009). The relationship between students' conceptions of learning engineering and their preferences for classroom and laboratory learning environments. Journal of Engineering Education, 98, 193- 204.4. Prince, M
teaching continues todevelop.AcknowledgmentsSupport for this work was provided by the National Science Foundation through theUTeachEngineering: Training Secondary Teachers to Deliver Design-Based EngineeringInstruction award (DUE-0831811) and the CAREER: Advancing Adaptive Expertise inEngineering Education award (EEC-0748186). The opinions expressed in this paper are those ofthe authors and do not necessarily represent those of the Foundation.References Page 22.1612.161. Martin, T., Petrosino, A., Rivale, S., Diller, K. (2006). The development of adaptive expertise in biotransport. New Directions in Teaching and Learning 108
; Exposition, Annual Conference, 2004.4 Flemming, L., Engerman, K., and Williams, D. ―Why Students Leave Engineering: the Unexpected Bond,‖Proceedings of the 2006 American Society for Engineering Education Conference& Exposition, Annual Conference,2006.5 Fortenberry, N., Sullivan, J., Jordan, P., and Knight, D., ―Engineering Education Research Aids Instruction,‖Science, Vol. 317, 2007.6 Ohland, M., Sheppard, S., Lichtenstein, G., Eris, O., Chachra, D., and Layton, R., ―Persistence, Engagement, andMigration in Engineering Programs,‖ Journal of Engineering Education, July 2008.7 Seymour, E., and Hewitt, N., Talking About Leaving: Why Undergraduates Leave the Sciences, Westview Press,Boulder, CO, 20008 Zhang, G., Min,YK., Ohland, M., and
author(s) and donot necessarily reflect the views of the National Science Foundation (NSF). Page 22.208.2This paper has materials that will appear in: Ganesh, T. G. (in press). Children-produced drawings: aninterpretive and analytic tool for researchers. In E. Margolis & L. Pauwels, (Eds.). The Sage Handbook ofVisual Research Methods. London, UK: Sage. The author thanks Sage for the use of these materials.Review of the LiteratureThe use of children-produced drawings in research is not new. Margaret Mead used subject-produced drawings as contemporary responses by the public to events that represented rapidtechnological change after
at the top. The four dots denote vertically aligned, equally spaced points along the member. other forces Assuming the other forces stay the same, what load(s) could replace the 60 Nm 60 Nm couple and maintain equilibrium? 2m Mark all possible answers. other other other other other other forces forces forces forces forces forces 10 N 30 N
inclass suggest that other dynamics such as culture and family upbringing 24 may mitigate theirobservations of bias. This study begins to address the issues of climate in engineering forwomen of all races and ethnicities. Examination of other dimensions of diversity, particularlyclass and culture, may provide further insight into the mechanisms that enable women of certainracial/ethnic groups to persist despite being in an environment that singles them out for theirunderrepresented status.Bibliography1 Malcolm, S. M. (1976). The double bind: The price of being a minority woman in science. Washington, DC: Page 22.953.10 American
Labor, Bureau of Labor Statistics. Occupational Outlook Quarterly. 2009th ed.Government Printing Office; 2009.3. Kalwarski T, Mosher D, Paskin J, Rosato D. 50 Best Jobs In America. Money. 2006;35(5).4. Best Jobs in America. Money. 2010;39(11).5. Zweben S. Computing Degree and Enrollment Trends. 2010.6. Denning PJ. The field of programmers myth. Commun. ACM. 2004;47(7):15–20.7. Margolis J, Fisher A. Unlocking the Clubhouse: Women in Computing. MIT Press; 2003.8. Felleisen M, Findler RB, Flatt M, Krishnamurthi S. The DrScheme project: an overview.SIGPLAN Not. 1998;33:17–23.9. Allen E, Cartwright R, Stoler B. DrJava: a lightweight pedagogic environment for Java. In:ACM SIGCSE Bulletin. SIGCSE '02. New York, NY, USA: ACM; 2002:137–141.10. Barnes DJ
, findings, conclusions, orrecommendations expressed in this material are those of the author(s) and do notnecessarily reflect the views of the NSF.References1. Feisel, L.D. and A.J. Rosa, The Role of the Laboratory in Undergraduate Engineering Education. Journal of Engineering Education, 2005. 94(1): p. 121-130.2. Richard L. Clark, J., et al., Work in Progress - Transitioning Lab-in-a-Box (LiaB) to the Community College Setting in 39th ASEE/IEEE Frontiers in Education Conference. 2009: San Antonio, T. Page 22.1630.123. Millard, D., Workshop - Improving Student Engagement and Intuition with the Mobile Studio
complexity of this PDLlearning context and the fact that it seeks to develop skills rather than highly specifiedknowledge, we have attempted to collect various kinds of data to determine how well we aredoing in fostering an interdisciplinary perspective and disposition. Assessment of studentlearning takes several forms. • Facilitator observation and evaluation: Each team of eight has a faculty or post-doc facilitator that observes and facilitates the team for three hours each week. In these sessions they can observe and assess each student’s behaviors as s/he interacts with, helps in the problem solving, works to develop knowledge and contributes through individual research to the process team. The assessment scoring