the Motion of Pendulums,” Cambridge Philosophical Transactions, IX, 8, 1851. 2. Fox, Robert W., McDonald, Alan T., and Pritchard, Philip J., Introduction to Fluid Mechanics, sixth edition, John Wiley & Sons, Inc, 2004. 433- 447. 3. Zhang S. and Jin, J. Computation of Special Functions, John Wiley & Sons, New York, 1996. 4. Carlson, B. C. Special Functions of Applied Mathematics, Academic Press, New York, 1977. 5. Temme, N. M. Special Functions, John Wiley, New York, 1996 6. Knacke, T. W. Parachute Recovery Systems and Design Manual 7. Richard Nakka’s Experimental rocketry website, http://members.aol.com/ricnakk/paracon.html 8. http://en.wikipedia.org/wiki/Apollo_15,_Return_to_Earth 9. http
this course I received more frequent feedback 3.52 1.06on my progress towards course objectives.Compared to my experiences in other courses, in this course I received more opportunities to 3.88 0.99assess my own understanding and learning.Compared to other courses, the technology allowed more interaction with the instructor(s). 3.33 1.05Compared to my experiences in other courses, in this course I experienced more interaction 4.33 0.85with my fellow students.FeedbackStudents’ reaction was very diverse. Many of our students never took a flipped class, and did notexpect to be in one of them, probably because our school never had flipped class. Below wereport some of the comments after the first
and organize and facilitate ongoing research on retention. Ms. Bego is a registered professional mechanical engineer in New York State.Mr. Il Young Barrow, University of Louisville IL Young Barrow is the QEP specialist for assessment at the University of Louisville. He specializes in knowledge around national assessment instruments (e.g. NSSE, CIRP, CAAP), assessment of student learning outcomes, retention studies, and various data analyses related to student success. IL also has wide-ranging experiences in undergraduate teaching, academic advising, and graduate admissions and student services.Dr. Patricia A. Ralston, University of Louisville Dr. Patricia A. S. Ralston is Professor and Chair of the
Paper ID #23801Infusion of Big Data Concepts Across the Undergraduate Computer ScienceMathematics and Statistics CurriculumDr. Carl Pettis, Alabama State University Dr. Carl S. Pettis is a Professor of Mathematics at Alabama State University. He received his BS degree in 2001 and his MS degree in 2003 both from Alabama State University in Mathematics. Dr. Pettis received his PhD in Mathematics from Auburn University in 2006. He currently serves as the Interim Associate Provost for the Office of Academic Affairs.Dr. Rajendran Swamidurai, Alabama State University Dr. Rajendran Swamidurai is an Associate Professor of Computer
-mathematics-education. [Accessed 2016].[3] N. Klingbeil, R. Mercer, K. Rattan, M. Raymer and D. Reynolds, "The WSU Model for Engineering Mathematics Education," in 2005 Annual ASEE Conference, Portland, OR, 2005.[4] L. Albers, "Implementing the Wright State Model First-Year Engineering Mathematics Course in a Startup School of Engineering," in 2018 ASEE Annual Conference & Exposition, Salt Lake City, Utah, 2018.[5] S. Das, "Implementing the Wright State Model for Engineering Mathematics at University of Detroit Mercy," in 2019 ASEE Zone I Conference & Workshop, Niagara Falls, NY, 2019.[6] N. Klingbeil, B. Newberry, A. Donaldson and J. Ozdogan, "The Wright State Model For Engineering Mathematics Education: Highlights From A Ccli
Qualitative and Quantitative Analysis of University Students’ Ability to Relate Calculus Knowledge to Function Graphs 1 Emre Tokgöz, 1Berrak S. Tekalp, 1Elif. N. Tekalp, and 2Hasan A. Tekalp 1 Emre.Tokgoz@qu.edu, 1Elif.Tekalp@qu.edu, 1Berrak.Tekalp@qu.edu, 2Hasan.Tekalp@qu.edu 1 Industrial Engineering, School of Engineering, Quinnipiac University, Hamden, CT, 06518 2 Mechanical Engineering, School of Engineering, Quinnipiac University, Hamden, CT, 06518In this work, 19 undergraduate engineering students’ responses to a set of power series questions are collectedat a university located on the
40problems. Because of the nature and speed of the course, and problems, students areencouraged to work together on the homework assignments, both during class time and inthe evening.Each day the previous day’s assignment is turned in by 8:05 AM, the start of class. Thecounselors grade the assignment during the morning, and return the assignments to thestudents at 1:30 PM each afternoon, at the problem session. The assignments are gradedas E for excellent above 90% correct; S for satisfactory, above 80% correct; and U forunsatisfactory for below 80% correct. Any student who receives a U on an assignmentmust redo all the problems the student missed and resubmit the assignment. Theassignment is not considered passed until all missed problems are done
understanding. By including reflective writing, teachers can promotehigher order critical thinking and return responsibility for learning back to the students. While itis true that rote practice is still essential in mathematics, the developers stress that evenimplementing parts of an EFFECT are an excellent way to engage students and start thedevelopment process of creating entire units of study designed around the EFFECT framework.References[1] EFFECTs Web page: http://sdii.ce.sc.edu/effects/?q=node/14[2] Mason, Gregory S.; Shuman, Teodora Rutar; Cook, Kathleen E. “Comparing the Effectiveness of an InvertedClassroom to a Traditional Classroom in an Upper-Division Engineering Course” IEEE TRANSACTIONS ONEDUCATION 56 (4), 430-435, 2013.[3] Latterell
”, Page 25.489.10 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. Kalanad, A. and Rao, B., N., Detection of Crack location and size in structures using improved damaged finite elements, IOP Conf. Series: Materials Science and Engineering, IOP Publishing, 10, (2010), 1-10. 10. Lim, J., S., Two-Dimensional Signal and Image Processing, Prentice Hall, NJ, (1990). 11. Mannan, M.,A
the effort to develop the post-test for the lesson. Awell-defined template is used by the Fellow to create the lesson, which can be disseminated onthe project’s website soon after its implementation. This template consists of the followingblocks: 1) Summary – goal to be achieved by students; 2) Objectives – skills to be acquired bystudents; 3) Standards to be addressed; and 4) Lesson Information – Grade Level, Subject Area,Duration, Setting, Materials Needed, Background Knowledge, Lesson Plan(s) details, andAdditional Resources (learning objects, timelines, assessment rubrics, surveys, etc.). Item 4includes detailed information provided via hotlinks. The Fellow submits the final lesson to theGrant Coordinator for checking and approval before
. pp. S.16-24.8. Dunn, J. W., and J. Barbanel. “One model for an integrated math physics course focusing on electricity and magnetism and related calculus topics.” American Journal of Physics, August 2000: 68.8.9. Froyd, J.E., and M. W. Ohland. “First-year Integrated Curriculum Projects - Supplemental Information for the Paper: Integrated Engineering Curricula.” Journal of Engineering Education, 2005: 94.1.10. Froyd, J. E., and G. J. Rogers. "Evolution and evaluation of an integrated, first-year curriculum." Proceedings of the 27th Annual Frontiers in Education Conference, Teaching and Learning in an Era of Change, 1997, vol. 2. pp.1107-1113.11. Jeffrey E. Froyd, and Matthew W. Ohland. “Integrated Engineering
). Page 23.1330.102. MyMathLab by Pearson Publishing. http://www.mymathlab.com/ (accessed January 4, 2013).3. Budny, D.; LeBold, W.; Bjedov, G. Assessment of the Impact of the Freshman Engineering Courses. Journal of Engineering Education 1998, No. October, 405-411.4. Moore, R.; Jensen, M.; Hatch, J.; Duranczyk, I.; Staats, S.; Koch, L. Showing Up: The Importance of Class Attendance for Academic Success in Introductory Science Courses. The American Biology Teacher 2003, 65 (5), 325-329.5. Hatfield, J.; Hieb, J. Using Retrieved Panels from DyKnow in Large Classes. In The Impact of Tablet PCs and Pen-Based Technology on Education; Reed, R., Berque, D., Prey, J., Eds.; Purdue University Press: West Lafayette, Indiana, 2009.6. Hatfield, J
same students. The discussions were extensive in the discourse of the non-mentored professor; however, these were not part of a classroom experience design based on the critical reflection of the instructor, as it was the case for the mentored professor. TG students had access to computers to use GeoGebra to work individually and collectively. In contrast, in the CG, students had no access to computers, and although some accessed through their smartphones, most of the times was the instructor the only one using GeoGebra to make explanations to the students, while they listened passively.It is evident the positive impact that the redesign of the learning activities had on the learningenvironment from the perspective of the student´s particular
. during300,000 BC-250 BC. Section 3, on the other hand, is an exposition of mathematical ingenuityto perform computation during pre-computer era, i.e., during 200 BC till the birth of anelectronic digital computer during early twentieth century. Section 4, on the other hand,presents the impact of ever increasing power of computing on the computing scenario since theappearance of the first digital computer during 1940’s. Section 5 comprises conclusions.2. Computing Scenario During Pre-historic Era (300,000 BC – 250 BC)Universe is a gigantic errorless never-stoppable parallel computer with infinite precisionBefore 15 trillion BC, the universal errorfree computer boots up with a Big Bang. Since thenthe computing in nature/universe is going on continuously
Learning Environment. Journal of Research on Technology in Education, 39(3), 229–2436. NSF (2000). National Science Foundation: The Interplay between Mathematics and Robotics. Arlington: National Science Foundation. Page 23.1050.167. Rogers, C., & Portsmore, M. (2004). Bringing engineering to elementary school. Journal of STEM Education, 5(3&4), 17–28.8. Papert, S. (1980). Mindstorms. New York. Basic Books.9. Brand, B., Collver, M., & Kasarda, M. (2008). Motivating Students with Robotics. The Science Teacher, 75(4), 44-9.10. Silk, E., Higashi, R., Shoop, R., & Schunn, C. (2010). Designing
Paper ID #7658Using projects in mathematics and engineering mathematics courses designedto stimulate learningDr. Hassan Moore, University of Alabama, Birmingham Years with the University of Alabama at Birmingham (UAB): 5 Current Position(s): • Assistant Professor, Mechanical Engineering • Director of Outreach, School of Engineering Current Job Responsibilities: Dr. Moore’s primary interest is in the area of engineering education, par- ticularly in developing project-based learning tools in Differential Equations and Multivariable Calculus. Dr. Moore has created and developed a new course in the School of Engineering
Active Learning Work? A Review of the Research, Journal of Engineering Education, July 2004. 8. Silberman, M., Active Learning: 101 Strategies to Teach Any Subject, Allyn & Bacon, 1996. 9. Polio, H.R., What Students Think About and Do in College Lecture Classes. Teaching-Learning Issues No. 53. Knoxville: Learning Research Center, University of Tennessee, 1984. 10. Srinivasan, M., Wilkes, M., Stevenson, F., Nguyen, T., and Slavin, S., Comparing Problem-Based Learning with Case-Based Learning: Effects of a Major Curricular Shift at Two Institutions, Academic Medicine, Vol. 82, No. 1, January 2007. Page
teaching and learning methods: Definitions, comparisons, and research bases. Journal of engineering education, 95(2), 123-138.[11] Ryan, A. M., Gheen, M. H., & Midgley, C. (1998). Why do some students avoid asking for help? An examination of the interplay among students' academic efficacy, teachers' social– emotional role, and the classroom goal structure. Journal of educational psychology, 90(3), 528.[12] Smith, K. A., Sheppard, S. D., Johnson, D. W., & Johnson, R. T. (2005). Pedagogies of engagement: Classroom-based practices. Journal of engineering education, 94(1), 87-101.
), 370 - 392.4. Dubinsky, E. and McDonald M. A. (2002). APOS: A Constructivist Theory of Learning in Undergraduate Mathematics Education Research, The Teaching and Learning of Mathematics at University Level, 7 (3), 275-282.5. Piaget, J., and Garcia, R. (1989). Psychogenesis and the history of science (H. Feider, Trans.). New York: Columbia University Press. (Original work published in 1983).6. Piaget, J., J.-B. Grize, A., Szeminska, and V. Bang (1977). Epistemology and psychology of functions (J. Castellano`s and V. Anderson: Trans.)7. Thompson, P. W. (1994). Students, functions, and the undergraduate curriculum, Conference Board of the Mathematical Sciences Issues in Mathematics Education, 4, 21-44.8. Tokgöz
is supported through National Science Foundation Grant Number 1317651.References[1] National Science Board. The Science and Engineering Workforce: Realizing America’s Potential, Publication NSB 03-69, 2003.[2] Augustine, N. “Rising Above the Gathering Storm: Energizing and Employing America for a Brighter Economic Future”, Committee on Science, Engineering, and Public Policy (COSEPUP), 2007.[3] Herzog, S. “Measuring Determinants of Student Return vs. Dropout/Stopout vs. Transfer: A First-to-Second Year Analysis of New Freshmen”, Research in Higher Education, pp. 883-928, December 2005.[4] Krauss, R., Fries, R., Karacal, C. “Evaluating the Impact of a Revised Introductory Engineering Course: Student
. Figure 5: Example Problem Involving Electric Circuits Page 24.1391.8After an introduction to Nodal Analysis and Mesh Analysis to give the students an idea wherethe equations are coming from, the focus is shifted to competency in solving the resultingequation(s). Particularly with Nodal, the student needs to be comfortable in dealing withfractions and finding a common denominator. After simplifying, the remaining equation is linear.Solving for , the result is 12 V. This can be validated using PSPICE, which can serve as agood technology application if the class is able to access this program (Figure 6). Figure
) fromdirectors of graduate studies at several well-known R1 engineering graduate schools, especiallyones offering Ph.D.’s in both electrical and mechanical engineering, since those are theundergraduate programs that St. Thomas offers (3 requests in total). Unfortunately, none ofthem responded! That said, based on the author’s academic experience over many years alongwith discussions with other faculty members (including several from the MathematicsDepartment), the following core topics were selected: (1) vector integral Calculus, (2) anintroduction to Fourier series, (3) an introduction to partial differential equations, (4) anintroduction to complex analysis, and (5) conformal mapping and applications. Note that a highpercentage of the material builds
, S. (1992). The function concept as a prototype for problems in mathematical learning. In E. Dubinsky & G. Harel (Eds.), The concept of function: Aspects of epistemology and pedagogy (195-213). Washington, DC: Mathematical Association of America.
, N.Y.), vol. 359, no. 6383, 2018, pp. 1468–1470. [Online]. Available: ProQuest, http://dx.doi.org.ezproxy1.lib.asu.edu/10.1126/science.aap8892. [Accessed Mar. 31, 2020][3] M. Prince, “Does Active Learning Work? A Review of the Research.” Journal of Engineering Education, v ol. 93, no. 3, 2004, pp. 223–231. [Online]. Available: Scopus, https://search.lib.asu.edu/permalink/f/53hn25/TN_scopus2-s2.0-3342952938. [Accessed Feb. 3, 2020][4] S. Freeman et al. “Active learning boosts performance in STEM courses.” Proceedings of the National Academy of Sciences, vol. 111, no. 23, 2014, pp. 8410–8415. [ Online] Available: PNAS, https://doi-org.ezproxy1.lib.asu.edu/10.1073/pnas.1319030111
, http://www.reuters.com/article/pressRelease/idUS192979+28‐Jan‐2009+PRN20090128.2. Ewo Y., All W., Mahmud R., and Baki, R. (2009). Computer games development and appreciative learning approach in enhancing students’ creative perception, Computers & Education, Elsevier.3. Kelly, H., Howell, K., Glinert, E., Holding, E., Swain, C. Burrowbridge, A., Roper, M. (2007). How to build serious games, Communications of the ACM, 50(7).4. Denner, J., Bean, S., & Martinez, J. (2009). Girl game company: Engaging Latina girls in information technology. Afterschool Matters, 8, 26-35.5. Game Maker Site: http://www.yoyogames.com/gamemaker/windows.6. Project Site: http://www.isi.edu/pedtek.7. Project Annual Report 2011
thiseducational effort can be expanded outside the classroom to involve the entire student body, inthe hopes of motivating students to enroll in elective courses in the future. The classroomstudents can then analyze the data obtained from this school wide challenge to determine ifmathematical models can be used to help understand human intuition. Ultimately, this week longexperience helps students realize the practical applications of mathematics, and demonstrates thata systematic analysis in lieu of intuition can give your bracket the statistical edge.References 1. Jacobson, S. H., Nikolaev, A. G., King, D.M., Lee, A. J., 2011, “Seed distributions for the NCAA Men’s Basketball Tournament”, OMEGA, 39(6):719-724. 2. Lunardi, J
Recreational Mathematics.Mineola, N.Y.: Dover Publications, 2000.[9] K. Azad, Math, Better Explained, 2014.[10] O. E. Fernandez, Everyday Calculus: Discovering the Hidden Math All around Us.Princeton: Princeton UP, 2014.[11] T. Apostol, A Visual Approach to Calculus Problems, Engineering & Science, no. 3, 2000www.mamikon.com/VisualCalc.pdf[12] www.mamikon.com[13] D. Raviv, “Have you seen an integral? Visual, intuitive and relevant explanations of basicengineering-related mathematical concepts,” ASEE National Conference, Salt Lake City, UT,June 2018.[14] L. Edelstein-Keshet, Differential Calculus for the Life Sciences, 2018In: http://www.math.ubc.ca/~keshet/OpenBook.pdf[15] H. Kojima and S. Togami, The Manga Guide to Calculus, No Starch Press, 2009
perform significantly better than random learners in computerapplication courses12 and other Science and Math-related courses, while random learners excel inFine Arts courses.13Table 1. Four Learning Style Types Identified by Gregorc Style Delineator. Sequential (S) Random (R) Concrete (C) Abstract (A) Concrete (C) Abstract (A)Concrete-Sequential Abstract-Sequential Concrete-Random Abstract-Random (CS) (AS) (CR) (AR)Motivational Orientations and Learning StrategiesIn addition to learning styles, students’ motivational orientations and learning strategies that theyuse also