: Summative instructional events are now presented. Knowledge and learner centered. Go public: This is a high stakes motivating component introduced to motivate the student to do well. Learner and community centered.Challenge 2…NThe following progressively more ambitious challenges enable the student to increasinglydeepen their knowledge of the topic being explored. Repeat the complete legacy cycle for eachchallenge.Reflect BackThis gives student the opportunity for self-assessment. Learner centered.Leaving LegaciesThe student is asked to provide solutions and insights for learning to the next cohort of students,as well as to the instructor(s). Community centered. The legacy cycle contains steps or activities that appeal to
Response Reports (Miami Fall 2009)module 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16number of students 69 70 68 69 64 71 64 59 54 66 58 50 62 49 49 55who submittedFor modules 6 and 7 (which provide data now to the DDL) we could determine the participationin individual LBD and DIGT exercises, as shown in Table 3. Page 15.1313.10 10Table 3. Initiation and Completion of Individual Exercises in Module 7 (Miami Fall 2009)page in module 7 1 2 3 4 5 6 7# of students s f s f s
Students Earning Bachelor’s Degrees. Dedicated Engineers Communications Critical Issues Series. 2006 [cited Retrieved 7/6/06.].5. The Engineer of 2020: Visions of Engineering in the New Century. 2004, Washington, D.C.: The National Academies Press.6. Sheppard, S.D. and B.H. Tongue, Statics: Analysis and Design of Systems in Equilibrium. 2005, Danvers MA: John Wiley.7. Ashmore, C., Upton, D., Lee, B. Y., Thomas, G., Harrell, S., Valle, C., Murray, J., Newstetter, W., Jacobs, L. J., Rosser, S., “INTEL: Interactive Toolkit for Engineering Education,” ASEE Annual Conference and Exposition, Pittsburgh, June 2008.8. C. Ashmore, D. Upton, B. Y. Lee, G. Thomas, S. Harrell, C. Valle, J
. Thesetags are: - bold font, - italic font, - subscript, - superscript, - paragraphbreak, and - symbol font. Up to two random variables named var1 and var2 may beinserted anywhere in the question statement. The random variable minimum value, maximumvalue, and step size dictate the range and division of the random variables and are entered in theappropriate fields of Figure 4. The axis system (2- or 3-dimensional) is determined by entering 2or 3, respectively, in the Axis field. The minimum number of the various graphical objects isthen entered into appropriate fields. Acceptable units, separated by #’s, are entered in the Unitsfield. Point deductions for major and minor errors are entered into their respective fields. Thetitle for the graphic
Dynamics course − is themost useful model because it can be used even before a semester begins and thus the instructorhas sufficient time to consider what proactive measures s/he will use in the new semester.However, if an instructor wants to generate a large number of good predictions, so s/he can focuson individual students, particularly those “academically at risk” students, Model #1 should not beused because of its lowest percentage of good predictions. Either Model #2 or Model #3 can beused after the first or second mid-term exams because both models have moderate predictabilityto generate good predictions. For example, if Model #2 or Model #3 predicts that a student willreceive a final exam score below 50 (out of 100), the student will be
improvement in undergraduate instruction. SACS is the recognized regionalaccrediting body in Alabama, Florida, Georgia, Kentucky, Louisiana, Mississippi, NorthCarolina, South Carolina, Tennessee, Texas and Virginia for those institutions of highereducation that award associate, baccalaureate, master's or doctoral degrees. “An effective QEPshould be carefully designed and present a focused course of action that addresses a well-definedtopic or issue(s) related to enhancing student learning.”[1]In January 2005, a QEP Team of faculty, staff and students were charged with developing such aplan for the University of Louisville. A university-wide survey was conducted to identify areasof instruction that needed improvement, and solicit suggestions on ways
appear tobe unduly affecting the process. Page 15.1342.7 45 40 35 30 S tudents E nrolled 25 20 15 10 5 0 Fall 05 SP 06 Fall 06 Sp 07 Fall 07 Sp 08 Fall 08 SP 09 Fall 09 SemesterFigure 2: Dynamics Class Enrollment Over Nine Semesters Average course grades are shown in Figure 3 with the grade distributions
40 0.747 to 0.824 0.801 2 40 0.792 to 0.830 0.811 3 40 0.796 to 0.821 0.810 All three 120 0.747 to 0.830 0.8074 Page 15.1331.13Tabl e 3 Ranges an d average va ues tIor the coe ffiICIents . 0 f restItutIOn 0 f new ba 11 s. Used Ball no Number of data samples Range of values Average value 1 40 0.780 to 0.834 0.813 2 40
instrumentation - accelerometers Page 15.599.4and FFT analyzers – typically used for vibration analysis of vehicles and machines in industry orresearch. However, much more time is required if one designs and builds custom apparatuses,such as a rig for 2 DOF torsional system developed by Souza et al. 3 Also, with a customapparatus, custom instrumentation and transducers are required – which may or may not beresearch caliber instruments. One unique apparatus that the author experienced as a graduatestudent at The Pennsylvania State University in the 1990’s used an air-hockey like track toconnect mass elements with springs. It worked well, but a leaf
a plate in plane stress. The geometry is created in ANSYS (ANSYS 12 (2009)). Aneight node quadrilateral element is used to model the bar quadrant. Isotropic material propertiesfor steel, namely the Young‟s modulus (207 GPa) and the Poisson‟s ratio (0.3) were introducedas inputs. Figure 7: Application of Loads and Boundary Conditions on the Quadrant Model Page 15.1137.7 Figure 8: Stress Profile for the X-StressFigure 7 shows the load applied and the applicable boundary conditions. Tensile load is appliedas a uniform pressure of 100 psi applied on the vertical edge to the right. The bottom edge ofthe quadrant is input
the traditional methods.2-12 This method enriches students’ study and setof skills in their determining reactions and deflections of beams, and it provides engineers with ameans to quickly check their solutions obtained using traditional methods.References1. I. C. Jong, “An Alternative Approach to Finding Beam Reactions and Deflections: Method of Model Formulas,” International Journal of Engineering Education, Vol. 25, No. 1, pp. 65-74, 2009.2. S. Timoshenko and G. H. MacCullough, Elements of Strength of Materials (3rd Edition), Van Nostrand Compa- ny, Inc., New York, NY, 1949.3. S. H. Crandall, C. D. Norman, and T. J. Lardner, An Introduction to the Mechanics of Solids (2nd Edition), McGraw-Hill, New York, NY, 1972.4. R
Phys., 66 (1), 64-74.3. Johnson, D., Johnson, R., & Smith, K. (1998). “Cooperative Learning returns to college: What evidence is there that it works?” Change, July/August, 27 - 35.4. MacGregor, Jean, Cooper, J., Smith, K., and Robinson, P. (2000). Strategies for Energizing Large Classes: From Small Groups to Learning Communities, Jossey Bass Publisher, San Francisco, CA.5. Mazur, Eric (1997). Peer Instruction. Prentice Hall, NJ.6. Smith, K. A., Sheppard, S. D., Johnson, D. W. and, Johnson, R. T. (2005). Pedagogies of Engagement: Classroom-Based Practices. Journal of Engineering Education, Volume 94, Issue 1, pp 87 – 1017. Mechanics Readiness test. (http://comp.uark.edu/~jjrencis/aseemechanics/education/Mechanics
‘depth-averaged’ model.However major subsequent contributions to the subject matter took place during the 1960’s,wherein ‘variable-depth’ models were introduced. Let us consider for example, the potential flow over a horizontal bed. Let us consider a three-dimensional space with co-ordinates, x, y, z. However, for this example let us consider only the two dimensional plane x and z. If h is the mean water depth, and z is the vertical coordinate, then z = – h. One can arrive at a Taylor Expansion of the velocity potential η∀(x,z,t) around the bed level, z = – h. Page 15.214.3 Assume that u is the
careful inthe bar random analysis to compute symbolically for the two statistical randomdisplacement values of bar for 4 cases. Even so, please do each analysisidentified to verify the random displacement results before using it for teaching oras such for any professional value of interest.Bibliography1. Ang, A.H-S. and Tang, W. H., “Probability Concepts in Engineering”, John Wiley, 20072. National Research Council, “Science and Judgment in Risk Assessment”, National Academy Press, 19943. US DOE, “Characterization of Uncertainties in Risk Assessment with special reference to Probabilistic Uncertainty Analysis”, 19964. NASA, “Probabilistic Risk Assessment Procedures Guide for NASA Managers and Practioners”, 20025. National
comprehensive review of this literature here, wecite and discuss selected works that have influenced our thinking.A large body of research evidence suggests that active learning techniques – broadlytaken here to mean any form of instruction that engages students beyond passivelyreceiving information – promote learning10,11. A particularly convincing study conductedby Hake in the 1990’s demonstrated that physics students exposed to some form of“interactive engagement” developed higher levels of conceptual understanding than thosein “traditional” instructional settings12. Active learning grounds the SCALE-UP projectat North Carolina State University13, many of the integrated engineering curricula thatemerged in the 1990’s14, and some of the emerging