AC 2011-1472: DERIVING ORIGINAL SYSTEMS OF EQUATIONS AS ANASSIGNMENT IN ENGINEERING AND TECHNOLOGY COURSESMurray Teitell, DeVry University, Long Beach, CA Murray Teitell, Ph.D. is a Professor at DeVry University, Long Beach, CA. He teaches courses in math- ematics, science and technology. His research interests are algorithms, solutions of equations and active learning. He is a Director of the Mathematics Division of ASEE.William S. Sullivan, DeVry University, Long Beach Page 22.422.1 c American Society for Engineering Education, 2011 Deriving Original Systems of Equations
THINKING TOOL IN CONTEMPORARY MATHEMATICS AbstractThis study examines the relationship among learning, writing, critical thinking, and knowledgeretention. Having noted students‟ surprise at failing a math placement test when they believethey “know” the material on it, the author hypothesizes that a lack of critical thinking about thematerial in earlier math courses allows students‟ memory of it to fade over time. The author usesBloom‟s Taxonomy, as modified and published in 2001, to show the need for higher-levelthinking to facilitate knowledge retention. Writing is used as a principal strategy for stimulatingcritical thinking among students studying Contemporary Mathematics at
in 1981. He is an assis- tant professor in Fundamental General Education Center, National Chin-Yi University of Technology.P. C. Lin, Fundamental General Education Center of National Chin-Yi University of Technology, TaiwanR.O.C.Ruey-Maw Chen, National Chinyi University of Technology Ruey-Maw Chen, he was born at Tainan, Taiwan, R.O.C. He received the B. S., the M. S. and the PhD degree in engineering science from National Cheng Kung University of Taiwan R.O.C. in 1983, 1985 and 2000, respectively. From 1985 to 1994 he was a senior engineer on avionics system design at Chung Shan Institute of Science and Technology (CSIST). Since 1994, he is a technical staff at Chinyi Institute of Technology. Since 2002, he has been
traditional formative frameworkassociated with K-12 education, but rather, in relation to what one might deem, the positiveoutcome framework associated with students majoring in STEM areas at the university level.The motivation for this approach is based on an argument that, while university students inSTEM disciplines are considered as STEM education achievements, fundamental flaws in basicconceptual mathematical knowledge persist; flaws that if more aggressively addressed at the K-12 level could result in attracting more youth to pursue STEM interests. The argument is basedon personal anecdotal evidence associated with the author‟s experiences. Hence, it does not havea rigorous foundation. Nonetheless, it is an argument that will hopefully resonate
the opportunity to immediately apply the new mathematical “tool” to an engineeringproblem. This “tool” consisted of the core mathematical concept which they learned about in thelectures and tutorials of the AEM course, and the numerical implementation that they learnedthrough the Matlab modules. For example, the first module showed the students how to solve aset of simultaneous equations which was directly applicable to the multi-loop DC circuitproblems which they were solving in their Circuit Analysis course at the same time. While in thelast module the students learned how to determine the inverse Laplace transform of rationalfunctions using the residue command in Matlab. This enabled them to work through s-domaincircuit design problems
method of a differentialequation. This kind of question is better suited to engineering students than simply giving Page 22.1371.7them a differential equation and asking them to solve it numerically. An exampleproblem is given below. A sample problem The following equation describes the velocity of a car. Determine the positions of the car, x in meters, at t = , 2 , 3 , 4 , 5 s using Euler method. Compare the numerical solutions with the exact solution at t = 2 and 5 s. dx 2 9cos t 9, x (t 0) 0 Equation (2
of the module are depicted in Figure 3 and 4. Figure 3. Different views of the scenarios Figure 4. Virtual lecture, parameter adjustment, and interactionScenario 2: A human cannonball is launched with an initial velocity v m/s at an angle θ, find thedistance and height the cannonball can travel. Mathematically, we can solve the problem byfinding the cannonball’s vertical and horizontal initial speeds and calculating the distances basedon two different equations (depicted in Figure 5). vy v θ vx v x = v ⋅ cos θ and v y = v ⋅ sin θ
. Page 22.1046.5Fig. 3 Step by step illustration of how the yupana is used to perform the arithmetic operation of addition, e.g. 409 + 107 (= 516), with the 4th column used as temporary memory.Nazca Lines:9-13 The Nazca lines (and geoglyphs) are giant etchings in the desert, created byremoving rocks from the sand and piling them up to create vast shapes when viewed from thesky. They were “discovered” back in the 1930’s when viewed from an airplane and researched /preserved by Dr. Paul Kosok and his assistant, German mathematician Maria Reiche, who,because of her research over subsequent decades, has become singularly famous as the Nazcaline researcher. Many theories abound as to how and why they were constructed. Some dealwith ancient
Policy (COSEPUP), 2007.3. Bochis, C., Hsia, S., Johnson, P., Boykin, K., Wood, S., Bowen, L, and Whitaker, K. “Integrated EngineeringMath-Based Summer Bridge Program for Student Retention”, Proceedings of the 2007 American Society forEngineering Education Annual Conference & Exposition.4. Fletcher, S. L., Newell, D.C., Newton, L.D., and Anderson-Rowland, M. “The WISE Summer Bridge Program:Assessing Student Attrition, Retention, and Program Effectiveness”, Proceedings of the American Society forEngineering Education Annual Conference & Exposition, 2001.5. Varde, K. S. “Effects of Pre-Freshman Program for Minority Students in Engineering”, Proceedings of the 2004American Society for Engineering Education Annual Conference & Exposition
] Breidenbach, D., Dubinsky, E., Hawks J., & Nichols, D. (1992). Development of the Process Conception ofFunction. Educational Studies in Mathematics, 23(3), (pp. 247-285)[5] Lobato, J. E. (2003). How design experiments can inform a rethinking of transfer and vice versa. EducationalResearcher, 32(1), (pp.17-20)[6] National Research Council, Committee on Developments in the Science of Learning (2000). Learning andtransfer. In J. D. Bransford, A. L. Brown, & R. R. Cocking (eds.), How people learn: Brain, mind, experience, andschool (Exp. Ed., pp. 51-78). Washington, DC: National Academy Press.[7] Reed, S. K. (1993). A schema-based theory of transfer. In D. K. Detterman & R. J. Sternberg (Eds.), Transfer ontrial: Intelligence, cognition and
Visibility of Gratings”, J. Physiol. 197, (1968), 551-566. 6. Demirkaya, O., Asyali, M., H., Sahoo, P.K., Image Processing with MATLAB-Applications in Medicine and Biology, CRC Press, Florida, (2009). 7. Gonzalez, R.C., & Wintz, P., Digital Image Processing, Addison-Wesley Publ. Co., MA. (1987). 8. Jain, A., K., Fundamentals of Digital Image Processing, Prentice Hall, NJ, (1989) 9. Lim, J., S., Two-Dimensional Signal and Image Processing, Prentice Hall, NJ, (1990). 10. Nagy, G., “State of the Art in Pattern Recognition”, Proc. IEEE, 56, (1968), 836-862. 11. Pedrycz, W., “Fuzzy Sets in Pattern Recognition; Methodology and Methods”, Pattern Recognition, 20 No. 1-2, (1990), 121-146. 12. Pratt
Statistics.4. Goodman Research Group (2002). Final report of the women’s experiences in college engineering (WECE) project, Cambridge, MA.5. Davis, C-S. & Finelli, C.J. (2007), Diversity and Retention in Engineering, New Directions for Teaching and Learning, v2007, n111, p63-7.6. Derlin, R.L. & McShannon, J.L. (2000), Faculty and Student Interaction and Learning Styles of Engineering Undergraduates, Retrieved May 10, 2008 from http://www.eric.ed.gov/ERICDocs/data/ericdocs2sql/content_storage_01/0000019b/80/16/89/1d.pdf.7. Goldberg, J. & Sedlacek, W. (1996), Summer Study in Engineering for High School Women, Maryland University, College Park, Maryland.8. Pantano, J. (1994), Comprehensive Minority SEM Programs
effective for your learning. • It was perfectly fine. • They did well; I don’t see any way it could be improved. • Providing more examples that were mentioned through the non-SI sessions. Go over previous tests. Finally, maybe making the session longer. • All math classes should have SI sections. • It’s really good with this class, can’t say I would add anything to it. • I don’t know. • Nothing from my experience, it was the best way to become highly successful in the class. • I thought it was fine. Please indicate the reason(s) you did not attend SI sessions: • I didn’t feel it was
integration of mathematics with physics and engineering throughthe use of projects or curriculum incorporation or moving this integration in the sophomore yearof curriculum with project-based learning15,19,20. Some of the literature is beginning to outlineskills from mathematics, but the focus has been on identifying topics from the course and not onthe impact on engineering if a student does not possess these skills. For example, Gomes, Bolite,and Powell19 looked at assessing the mathematics skills necessary for a final course project. Theskills outlined were still framed using the taxonomy level outlined in Cardella’s work in 200716.Manseur, et al.’s work15 addressed the relationship between mathematics and engineering butfrom a curriculum