Computing Machinery: Report of the ITiCSE’98 Working Group on Problem Based Learning.9. Cirstea M (2003). Problem-based Learning (PBL) in microelectronics. International Journal of Engineering Education, 19 (5): 738-741.11. Zywno, M.S. Kennedy, D.C.I (2000). Integrating the Internet, multimedia components, and hands-on experimentation into problem-based control education. Proceedings - Frontiers in Education Conference. 1, IEEE, Piscataway, NJ, USA,00CB37135. T2D-5-T2D-10.12. Stonier, H; Marshall, L. (2002). Moving to problem-based learning in the NZ engineering workplace. Journal of Workplace Learning. 14 (5) 190-197.13. Albanese, M. A., & Mitchell, S. (1993). Problem-based learning: A review of
in the awareness of programoutcomes and their importance in the curriculum. Many students see them as overly generalizedstatements that have no bearing on the concepts they need to pass a given course. Thus,dissemination of the notion and value of program outcomes is a major hurdle for the faculty.This paper suggests that engaging students at the freshman level in the departmental programoutcomes is one strategy to foster a climate of their acceptance in later courses. Examples offreshman class assignments and projects that address specific program outcomes in a MechanicalEngineering department are presented.IntroductionIn the mid-1990’s, the Accreditation Board for Engineering and Technology (ABET) developeda new set of criteria for
Page 10.925.2‡ In order to describe the procedures discussed in this paper, commercial products are identified. In no case does such identification imply recommendation orendorsement by the National Institute of Standards and Technology or that the materials or equipment specified are necessarily the best available for the purpose. S S V1 W A1 W Z I I 1 T T D1 C C Balance H A2 H indicator Z V2 I I 2
controls, handheld tools, PDA’s, motorcontrols, computer peripherals, and educational and entertainment devices. While theirimportance is well established, selection of the device(s) to be taught in introductoryuniversity courses is problematic because of the plethora of available choices. Forinstance, the most used embedded controllers are 8-bit devices; however, these oftencontrol peripherals or are connected to higher capacity processors in networks. As thecapability of an embedded processor increases, the amount of available memory increasesand higher level languages are used more often for programming. Thus, the selection of aprocessor is linked to selection of the programming language used in teaching thefundamentals of embedded computing
the final investigation.References1. Frechtling, J., The 2002 User Friendly Handbook for Project Evaluation. Washington, DC: National ScienceFoundation (NSF 02-057), Division of Research, Evaluation and Communication, 2002.2. Moskal, B., Leydens, J. & Pavelich, M. (2002). "Validity, reliability and the assessment of engineeringeducation". Journal of Engineering Education, 91(3), 351-354. (Journal)3. Cooper, S., Dann, W., & Moskal, B. Java-Based Animation in Building viRtual Worlds for Object-orientedprogramming in Community colleges. NSF-DUE-0302542.4. Alice v2.ob Learn to Program Interactive 3D Graphics, http://www.alice.org (accessed December 2004)5. Cooper, S., Dann, W., & Pausch, R. (2005) Learning to Program with Alice Beta
aspects in learning and teachingenvironments. To explore the effects of time on the change in test scores, ANOVA withrepeated measures will be performed. The “within” variable will be time with two levelsrepresenting posttest and the follow-up test, respectively.References[1] Franklin, S., Peat, M., Lewis, A., & Sims, R., “ Technology at the cutting edge: A large scale evaluation ofthe effectiveness of educational resources”, In C. Montgomeries & J. Viteli (Eds.), Proceedings of Ed-Media2001. Tampere, Finland, June 25-30, 2001; Association for the Advancement of Computing in Education(AACE).[2] Pike, R. W., “Creative training techniques handbook”, Minneapolis, MN: Lakewood Books, 1994.[3] Anderson, T., “An Updated and Theoretical
Economy, Sixth Edition, Leland Blank and Anthony Tarquin, 2005 3 • Contemporary Engineering Economics, Third Edition, Chan S. Park, 2002 4 • Engineering Economy, Applying Theory to Practice, Second Edition, Ted G. Eschenbach, 20035 • Engineering Economy, Twelfth Edition, William G. Sullivan, Elin M. Wicks, and James T. Luxhoj, 2003 6 • Capital Investment Analysis For Engineering And Management, Third Edition, John R. Canada, William G. Sullivan, John H. White, and Dennis Kulonda, 2005 7There was one exception found to the use of tables - Modern Engineering Economy by the lateDonovan Young. This text 1 from 1993 uses nomograms in lieu of the tables.The Fundamentals of Engineering (FE) Supplied-Reference Handbook, 6th
key to industrial practice and will draw upon an engineer’stheoretical knowledge and practical experience to be effective. Still, the effect of monthsspent talking about “s” seems to be a lack of motivation for students to grasp thefundamentals of process control.The goal of the changes made to this course’s structure has been to restore the student’sperception of the linkage between the course and engineering practice. Additionally, the Page 10.170.1changes are tied to improved pedagogical methods for student learning, inductive Proceedings of the 2005 American Society for Engineering Education Annual Conference & Exposition
-kindequipment that now must be shared in large groups. This is especially true in upper term courseswhere advanced test equipment is most used.Bibliography1. Eppes, T. and Schuyler, P., “A Robust and Scalable Distance Laboratory Platform” Proceedings of the 2004 ASEE Conference & Exposition, Session 2426.2. Eppes, T. and Schuyler, P. “A Distance Laboratory System Using Agilent Test Equipment” 2004 Frontiers in Education (FIE) Conference, Session T3C.3. Esche, S.K. & Chassapis, C. “An Internet-Based Remote Access Approach to Undergraduate Laboratory Education”, Proceedings of the 1998 Fall Regional Conference of the Middle Atlantic Section of ASEE.4. Esche, S. K. & Prasad, M. G. & Chassapis, C. “A Remotely
Page 10.801.3objectives and contents so that the curriculum can keep its integrity. The draft project is usually “Proceedings of the 2005 American Society for Engineering Education Annual Conference & Exposition Copyright © 2005, American Society for Engineering Education”designed before the semester starts. However, it is tailored to the exact needs of the studentsduring the first half of the semester.Interaction with Students: The interaction occurs at different levels: 1. The industry partner(s) and students meet face-to-face at least four (4) times during a semester. The industry partner teams visit the classroom in the second week of the semester to introduce themselves, present the business
so they learn the business aspect of communications. The use of audience-appropriate vocabulary, content, and style are very important elements in communication, which the co-op students can share with other students.Furthermore, the co-op students at IPFW submit a standard survey form regarding the learningoutcomes of the co-op work experience. The statements are divided into three categories: • Personal development learning outcomes • Professional development learning outcomes • Academic development learning conceptsTable 1. Learner outcome statements at IPFW Academic Development Learning Concepts S I N U Ability to compile information. Ability to analyze
convergences or divergences of opinion may be considered reasonably representative of the Proceedings of the 2005 American Society for Engineering Education Annual Conference & Exposition Copyright ASEE 2005, American Society for Engineering Education.current state of affairs in relations between academe and industry in general, and ourobservations and opinions are offered in this context. Despite any differences in opinion, theauthors remain friends and share a mutual passion for enhancing engineering education.Industry PerspectiveConcerns about the future of engineering education were identified by many in the late 1980’sand early 1990’s. Many of the more pointed concerns expressed at that time related toundergraduate rather
GUI Command ACK H&S Data Console Text Nav Data Inputs Pictures Nav Sensors Computer Config (GPS, IMU) Computer CPU
math classes, such as calculusand engineering concepts courses.Additional Education and TrainingIn addition to their college degree(s), all of the study participants had obtained additionaleducation and training to further their knowledge. The five subject areas most frequently pursuedfor additional knowledge included: leadership/executive development, 18 (72%); technical skills(e.g., computer programming, systems engineering, artificial intelligence, emergingtechnologies), 17 (68%); management development, 13 (52%); project management, 8 (32%);and finance, 8 (32%). The findings reveal that the additional education and training obtained bythe participants related mostly to leadership, business, technical skills, and interpersonal skills.The
described above and increase theinterests of Track B and C faculty members in the first-year engineering courses. In a completeimplementation, students in different sections of the first-year engineering courses may be doingdifferent projects, all of which meet the above specifications. Hopefully, a stream of projects cancontinue to be generated.AcknowledgementThis material is based upon work supported by the National Science Foundation under Grant No.0336591. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.Bibliographic Information1. Caso, R., Clark, C., Froyd, J.E., Inam, A., Kenimer, A.L., Morgan, J.R., and
that moves between provider and the user. Jacobs (2003) presents a formula to calculatethe number of Kanban card sets: Each container represents the minimum production lot size to be manufactured. Hence, the number of containers controls the amount of work-in-process inventory in the system. The number of kanban card sets is determined by the formula: k = expected demand during lead time + safety stock size of the container k = DL (1+S) . C Page 10.730.7 ( p. 432).Proceedings of the 2005 American Society
Functional Representations in Conceptual Design: A First Study in Experimental Design and Evaluation Julie S. Linseya, Matthew G. Greena, Michael Van Wieb, Kristin L. Wooda, and Robert Stoneb a The University of Texas at Austin/ bUniversity of Missouri-RollaAbstractFunctional modeling is an abstraction technique intended to help engineering designers performconceptual design. Functions are constructs that describe a transformation between an input flowand an output flow. A primary characteristic of functions is their independence from thephysical aspects of a device or artifact. In this sense, functions are form independent
. Mahwah, NJ: Lawrence Erlbaum Associates.6. LAVE, J. (1991). “Situating learning in communities of practice.” In L. Resnick & S. Teasley (Eds.), Perspectives on socially shared cognition (pp. 63-82). Washington, DC: APA.7. ECKERT, P. (1989). Jocks and burnouts: Social categories and identity in high school. New York: Teachers College Press.8. ECKERT, P., MC-CONNELL -GINET, S. (1992). “Think practically and look locally: language and gender as community-based practice.” Annual Review of Anthropology, 21, 461-490.9. LAVE, J., WENGER, E. (1991). Situated learning : legitimate peripheral participation. Cambridge England; New York: Cambridge University Press.10. STAR, S
Paper 2005-1462 Session 3266 Using the Design Process for Curriculum Improvement Laura L. Pauley, John S. Lamancusa, Thomas A. Litzinger Department of Mechanical and Nuclear Engineering Penn State UniversityAbstract This paper describes the process that was used to review and improve the MechanicalEngineering curriculum at Penn State University. The improvement process applied designmethodology to review the present curriculum, develop alternate curriculum models, andevaluate those
rate wasrecorded during the sessions. Non-engaged behaviors were marked using four different codes: S(Socializing), U (Uninvolved), W (Waiting), and C (Computer). S was used to describe asituation when two or more students were talking or engaging in some other form ofcommunication. U was used when a student was not paying attention, such as sleeping, staringoff into space, or working on something that was not related to the current class. W was markedwhen a student was waiting for something from the teacher, such as a handout or a topic change.C was used to describe when a student with a laptop was using applications other than SiliconChalk, such as email or instant messaging. The engagement rate was calculated from this data.An examination
Theme-Based Redesign of the Duke University ECE Curriculum: The First Steps a) Leslie M. Collins, a)Lisa G. Huettel, a)April S. Brown, a)Gary A. Ybarra, b)Joseph S. Holmes, a)John A. Board, a)Steven A. Cummer, a) Michael R. Gustafson, a)Jungsang Kim, and a)Hisham Z. Massoud a) Department of Electrical and Computer Engineering, Duke University, Durham, NC, 27708-0291/b)AcuityEdge, 437 Petty Road, Suite 201, Sanford, NC 27330Abstract. Historically, undergraduates in Electrical and Computer Engineering (ECE) atDuke University have had ample exposure to theoretical foundations and
Copyright © 2005, American Society for Engineering Education”mortar bank in two years since all your transactions are done by phone, ATM, or the World-Wide-Web. Even though you manage to avoid intense feelings of paranoia most of the time,there are moments when you just have to stop and wonder how much this technology has madeyou vulnerable to the evil that man can do. As you spend time worrying, scientists and engineers,like those that made all this exciting technology possible, are hard at work creating mechanismsthat may not make you safe in an absolute sense, but perhaps as safe as it can be managed. Someof these people have terminal degrees in their fields, Ph.D.’s and D.Sc.’s, though not all. Manymore of them, in fact, never went beyond a
chosen the self-directed learning version of the course obtain a finalmark higher than that obtained by the students who were taught in a conventional manner . Multi-variable analysis taking into account the GPA of the students, their level at their entry in theengineering program, the mark obtained in the common final exam and that obtained in quizzeswere performed in order to point out the most influencing factor(s). It appears that the differencein student’s success is mostly due to a better performance of the self-directed learning students inthe continuous evaluation by computerised quizzes, the other variables having a negligible effect.We conclude that the main cause of the higher success of the self-directed learning students in
retrieve”3. The Journal of Chemical Engineering Progress’ surveyof chemical engineers reveals that more than half of survey respondents are not able to find anduse appropriate information3.In engineering and other sciences, students may depend on textbooks for most of theirundergraduate learning, and many do not develop retrieval skills until their senior year orgraduate school3. Very little research has shown the attitudes of engineering faculty regardingbibliographic instruction (BI), but general guidelines have emerged in the last decadedemonstrating that context-sensitive IL instruction is critical.Since the 1950's, academic librarians have been integrating library or bibliographic instruction(now known as Information Literacy) into the
selected six coursesas venues, as described in Table 1. Separate problem-based learning (PBL) courses arepositioned in the first and second years. PBL experiences are incorporated into instructionallaboratories associated with third-year systems physiology and biomedical sensors courses. Thecurriculum culminates with a two-semester senior design course sequence, which is a naturalextension of the PBL experience. Course Experience(s) Location within Curriculum BMED 1300 Problems in BME I PBL problems 1st year BMED 2300 Problems in BME II PBL problems
technologies mustintegrate a diversity of disciplinary concepts, multiple skills, communications across disciplinarylanguages, and a receptiveness to new schools of thought. When the Engineering Scienceprogram was conceived and founded in the 1950’s and the Department of Engineering Scienceand Mechanics Department was created in the mid-1970’s, the university unwittingly discoveredthe correct disciplinary mix for the 21st century. Somehow, in the last twenty years, this visionbecame obscured, only to be discovered again with the almost concurrent emergence of the bio-,info- and nano-techological revolutions. Now is the time to re-emphasize the value of
Frontiers in Education Conference, Atlanta, Georgia, 1995. 4. Aorshas, S, Verner, I. M., and Berman, A., “Calculus for Engineers: An Applications Approach,” Proceedings of the 2003 International Conference on Engineering Education, ICEE-2003, Paper No. 4607, Valencia, Spain, 2003. 5. McKenna, A., McMartin, F. and Agogino, A., “What Students Say About Learning Physics, Math and Engineering,” Proceedings of the 2000 Frontiers in Education Conference, Kansas City, Missouri, 2000, p T1F-9. 6. Anderson, C. W., Bryan, K. M., Froyd, J. E., Hatten, D. L., Kiaer, C. L., Moore, N. E., Mueller, M. R., Mottel, E. A. and Wagner, J. F., “Competency Matrix Assessment in an Integrated, First Year Curriculum in
Business School Press: Boston, MA. 8. Brelin-Fornari, J. Homsher, B., Sullivan, L. (2004). Kettering University’s Bioengineering Summer Program for High School Women. American Society for Engineering Education Annual Conference & Exposition. Session 1505. 9. Baxter, L.A., & Babbie, E. (2004). The basics of communication research. Belmont, CA: Wadsworth/Thomson Learning. 10. Atkinson, P., & Hammersley, M. (1994). Ethnography and participant observation. In N.D. Denzin, & Y.S. Lincoln (1994). Handbook of qualitative research. Thousand Oaks, CA: Sage Publications. 11. Titscher, S., Meyer, M., Wodak, R. & Vetter, E. (2000). Methods of text and discourse analysis. London: Sage Publications
]. Bandura, A., “Self-Efficacy”, in Encyclopedia of Human Behavior, 4: 71-81, V. S. Ramachudran ed., New York, Academic Press, 1994. [2]. Bransford, J. D., Brown, A. L., Cocking, R. R. eds., How People Learn: Brain, Mind, Experience and School, Expanded Edition, National Academy Press, Washington DC, 2000. [3]. Chi, M. T. H., Bassok, M. Lewis, M., Reimann, P. Glaser, R., “Self-Explanations: How Students Study and Use Examples in Learning to Solve Problems,” Cognitive Science 13, 145-182, 1989. [4]. Harding, T. S., Carpenter, D. D., Finelli, C. J., Passow, H. J., “The Influence of Academic Dishonesty on Ethical Decision-Making in the Workplace: A study of engineering students,” Proceedings of the 2004 ASEE Annual Conference