. Furthermore, the notebook and postercompetition scores demonstrated superior subject comprehension by student teams. Table 4. The GEMS Camp STEM Outreach Effectiveness Engineering 17 Q: Because of my participation in GEMS, I would like Chemistry 6 to pursue a degree in: Mathematics 3 Strongly Agree 10 Agree 12 Q: My participation
Behavior at Least Once Who Engaged in the during their Past Year Behavior at Least in College (15,664 Once in High School sophomores, juniors (2,537 first year and seniors from 18 students from 5 Specific Behavior institutions) institutions) Cheating on a Test or ExamGetting Q/A from someone who has taken test 30 59Copying from another student during test WITH her
culture of science education at research universities; Science 331:152-153. Available at http://www.physics.emory.edu/Faculty/weeks/journal/anderson-sci11.pdf.2. Angelo. T. (1999). Doing academic development as though we valued learning most: transformative guidelines from research and practice; HERDSA Annual International Conference, Melbourne, p 1-11. Available at http://www.herdsa.org.au/wp-content/uploads/conference/1999/pdf/Angelo.PDF.3. Barab, S. and M. Thomas. (2001). Online learning: from information dissemination to fostering collaboration; J. Interactive Learning Res.12: 105-143. Available at http://scholar.googleusercontent.com/scholar?q=cache:z38SW2yk6aEJ:scholar.google.com/+barab+online+lear
s ua Q s ch
Grant No.DUE-0837409. Portions of this paper are based on a previous presentation12.References[1] Van Gerven, T., and A. Stankiewicz, “Structure, energy, synergy, time – The fundamentals of process intensification,” Ind. Eng. Chem. Res., 48, 2465-2474, 2009.[2] Tsouris, C., and J. V. Porcelli, “Process intensification – Has its time finally come?,” Chem. Eng. Prog., 99(10), 50-55, 2003.[3] Olujić, Ž., B. Kaibel, H. Jansen, T. Rietfort, E. Zich, and G. Frey, “Distillation Column Internals/Configurations for Process Intensification,” Chem. Biochem. Eng. Q., 17(4), 301–309, 2003.[4] Dejanović, I., Lj. Matijašević, and Ž. Olujić, “Dividing wall column—A breakthrough towards sustainable distilling, Chemical
: Eliminating the Gap in Incoming Academic Preparation”, Journal of STEM Education: Innovations & Research, May/June 2012, Vol. 13 Issue 3, p74-86.5. Adulaal R., Al-Bahi, A., Soliman, A., Iskanderani, F., “Design and Implementation of a Project-Based Active/Cooperative Engineering Design Course for Freshmen”, European Journal of Engineering Education, Aug 2011, Vol. 36 Issue 4, p391-402.6. Malik, Q., Koehler, M., Mishra, P., Buch, N., Shanblatt, M., Pierce, S., “Understanding Student Attitudes in a Freshman Design Sequence”, International Journal of Engineering Education, 2010, Vol. 26 Issue 5, p119-1191. Page 23.11.8
assemble their carand then brainstorm and sketch a work flow diagram for automated assembly of the car. Theinstructor concluded the class with Q & A and a 10-minute freewrite. Phase two consumed oneclass period. The students were directed to complete a rough draft of their reports in-progress bythe start of week three.phase three = (rewrite) + (creative/iterate): This phase involved one class period and twospecial 2-hr office-hour sessions outside of class. The students exchanged report drafts andcritiqued each other’s work. Several emergent issues presented (see next section) and wereresolved in-class during lively Q & A sessions with the instructor and in general class-leveldialogue.phase four = (edit) + (perfect): During the final phase
Paper ID #7518A Modular Approach of Integrating Biofuels Education into Chemical Engi-neering CurriculumDr. Qinghua He, Tuskegee University Dr. Q. Peter He is an associate professor in the Department of Chemical Engineering at Tuskegee Univer- sity. He obtained his B.S. in Chemical Engineering from Tsinghua University at Beijing, China in 1996 and his M.S. and Ph.D. degrees in Chemical Engineering in 2002 and 2005 from the University of Texas, Austin. His current research interests are in the general areas of process modeling, monitoring, optimiza- tion and control, with special interest in the application of data
and can easily become boring.The method presented in this paper offers a game-based approach to enhance students’ learning.Students are divided into teams, competing with each other regularly based on an organizedmatch-up schedule. At each match-up, points are awarded based on the performance on solvingan assigned problem and explaining that to the rest of the students. A “Q and A” session followseach presentation for additional points. Certain measures are discussed to improve the process ofassigning members for teams and contribution of every member to the overall results.The rules are thoroughly explained and the motivations behind them are discussed. In addition,the faced challenges during the implementation are discussed and the adopted
ment ning.and learnADM1 iss a system off first-order, linear, diffeerential equaations and algebraic equaations. Amoongthe phenoomena thesee equations describe d are the t chemicall reactions thhat occur duuring biogasproductioon, mass balances of cheemicals with hin the systemm, flow of mmaterials intoo and out of thesystem, and a levels off inhibitory quantities q (pHH, nitrogen, hydrogen suulfide, etc.). Some majoorquestionss of interest for the studeents would be: b what variiables and otther factors aare importannt tothe proceess of biogass
with MANOVASince similar questions were grouped together (Section 4.2), student ratings to questions of thesame group may be correlated, and MANOVA (Multivariate ANOVA) rather than ANOVA wasused to perform significance tests. For each group of questions, we investigated the significanceof mean difference between EECS and ME, between UG and Grad, and between MEundergraduate students (MEUG) and ME graduate students (MEG) by applying MANOVAusing the Wilk’s Lambda test. Although MANOVA requires that the samples are normallydistributed and with similar variances and covariances, violating these conditions does not causemuch harm [13,14].The null hypothesis for question group Q = {q0, q1, …, qn}, where the qi’s are questions, betweentwo student
Page 23.759.8 earlier. o Students get to follow a process with set objectives; the instructor can demonstrate a sustainability game model to help this process o Student teams present and play their games in front of the class – with Q&A at the end of the presentation; this becomes a real world situation and they have also to explain the “engine” and other sustainability elements.MethodologyIn National University’s graduate courses with the intensive and compressed class schedules, aslightly different approach and yet meeting the overall objectives of the GDM was implemented.This approach leads with the instructor first learning to design and play a course relevant game,demonstrate the game to the students, let the
-Pass with variouscutoff frequencies (Experiments 6-2 and 6-3), Band-Pass and Band-Reject with various Q-factors(measurements of these two filters are not included in this Lab); it also allows students toobserve the buildup and decay of the resonant response in Experiment 6-4.The lab manual for Experiment 6-1 includes a brief introduction to soldering, which covers theunderlying physical principles, a safety review, and links to videos demonstrating propersoldering techniques. In the Pre-Lab assignment, students are asked to draft a layout ofcomponents on a diagram of the prototyping board and answer questions reviewing the solderingprocess. In the lab, they are given step-by-step instructions (accompanied with numerousphotographs) to solder
Visualization Test. After completing the mental rotations test, students usedthe 3D Estimator to estimate the volume of six shapes, as in Study 1. In this study, each estimatethat a student entered was recorded and stored in the database.Analysis and Results The first research question was: Do measurement estimations of one-dimensional aspectsand computational estimations of three-dimensional volume represent distinct, separableknowledge components (KCs)? Determining distinct KCs for the 3D Estimator task requires theuse of a learning factors analysis (LFA) and the iterative process of determining q-matricesdescribed by 4. The analysis shows whether a smooth learning curve exists for a given KC.Smooth curves mean that the entire set of
change - A preparation for Calculus (3rd ed.). Wiley.12. Freudenthal, E., Roy, M. K., Ogrey, A. N., and Gates, A. Q. (2009). A creatively engaging introductory course in Computer Science that gently motivates exploration of mathematical concepts. (AC 2009-2188). Proceedings of ASEE Annual Conference.13. Freudenthal, E., Roy, M. K., Ogrey, A., Magoc, T., & Siegel, A. (2010). Media Propelled Computational Thinking. Proceedings of the 41st ACM technical symposium on Computer Science (pp. 37-42). New York: ACM.14. Freudenthal, E., Ogrey, A., & Gonzalez, R. (2010). Work in progress – Eliciting integrated understandings of high school STEM curricula through programming. Frontiers in Education Conference (FIE
between theflow rate and pressure drop. Finally, the students plot the data and the function on log-log axes.They see that there is good correlation between the data and the function, the function plots as astraight line, and the data approximates a straight line. This reinforces the students'understanding that a power function plots as a straight line on log-log axes.The following data was obtained from the experiment: Flow Rate Q (gpm) Pressure Difference P (mm H2O) 1.25 11 1.8 26 2.1 31 2.5 40 2.9
. Sociology of Education, 82(2), 101–125.13. Ishitani, T. T. (2006). Studying attrition and degree completion behavior among first-generation college students in the United States. Journal of Higher Education, 77(5), 861–885.14. National Center for Education Statistics (2012). Integrated Postsecondary Education Data System. Washington, DC.15. Patton, M. Q. (2002). Qualitative research and evaluation methods. Thousand Oaks, CA: Sage Publications.16. Geiger, R. L., & Heller, D. E. (2011). Financial Trends in Higher Education: The United States. Working Paper.17. Alexitch, L. R. (2006). Help seeking and the role of academic advising in higher education. Help seeking in academic settings: Goals, groups, and contexts, 175
over the chip. The camera plugs into the USB portof a PC and produces videos (30 frames/s) of fluid flow. The magnification ranges from 10X to500X. Other camera types and set-ups are of course workable as well, including higher-endconsumer CCD cameras. The quantification of flow rate can be made adding a graduated scale inthe image, such as with a thin plastic ruler placed along the flow channel which shows theposition of the flow front in each frame along with the time for that frame. From this analysis,the flow velocity can be accurately determined as a function of time. A common analysisobjective is to determine the pressure drop ∆𝑃 between two points as a function of flow rate Q orfluid velocity v. ∆𝑃 = 𝑓
Opportunities to Excel (PROPEL) center atColorado State University - Pueblo. The authors gratefully acknowledge the assistance of theentire Faculty at the Department of Engineering in developing the sustainability module.Bibliography1. Allen, D., et al. (2008). “Benchmarking sustainable engineering education: Final report.” Grant X3-83235101- 0, U.S. Environmental Protection Agency, Washington, DC. Page 23.726.92. Zhang, Q., Zimmerman, J., Mihelcic, J., and Vanasupa, L. (2008). “Civil and environmental engineering education (CEEE) transformational change: Tools and strategies for sustainability integration and assessment in
students naturally use three-dimensionalreasoning as a technique for problem solving. When dyslexic students encounter a problemsolving situation, they naturally change their three-dimensional perspective and examine theproblem from various angles without shifting their observation point. Many dyslexic studentsspin an object mentally without needing to alter how they are viewing that object. This skill ofshifting perspectives is useful and effective in physical science; however, in two-dimensionallanguage, changing a three dimensional perspective can result in a “b” looking like a “d”, “p” or“q”, depending on the angle at which the object is viewed. It is possible that the reasoning skillthat results in language challenges for the dyslexic student
last day of the class. On the last day of the class, studentsdress up to present their work as a team. Each presentation lasts 8-10 minutes, and is followed by2-minutes Q&A time. Peer evaluation and team evaluation rubrics were given to the students toevaluate their peers work, and team. At the end of the presentation, the instructor summarizes thestudent projects. A survey was implemented to collect students’ feedback regarding theirsatisfaction with the final project, and their comments on how to improve the delivery of thefinal project.During the four semesters, there were a total of 58 projects designed by 199 students. Someproject topics are listed in Table 1. Figure 3-6 show the exploded view and 3-D view of studentteam projects
Accelerator, Page 23.810.6 ability to create a four-bar linkage that serves as a steering system, ability to take into consideration many factors related to design and use them for overall planning, and ability to organize and work in teams.Formative assessment such as interactive class discussion, exit survey, and oral presentationwere used. The following table showed some of the survey results. RC Car Design Project – Q & A Worksheet Instructions: The answers to the questions below are intended as starting point for discussion and will not be graded
. Page 23.386.12Appendix 1. Course in actionDuring the class meeting time, students actively work within their product teams and regularlypitch ideas and lessons learned to their classmates. Page 23.386.13Interesting product concepts emerged in the inaugural course offering. Page 23.386.14Appendix 2. Final presentation team score sheetEvaluator: _______________________Student Team: _______________________ Date: _______________________Time: 20 minutes plus 3-5 for Q&A (1) The Evaluator should include a ‘0’ or ‘1’ in each shaded cell
Reference Curriculum for Systems Engineering, http://www.stevens.edu/bkcase/?q=content/grcse-graduate-reference-curriculum-systems- engineering, retrieved March 2013 Page 23.124.12
hydrogel was removed from the microscope slides. 10. The hydrogel was placed in DI water for 24 hours to rinse off any possible residual monomer solution that did not polymerize.Tensile TestingMaterials • Synthesized hydrogels • Phosphate buffered saline (PBS) solution, pH 2.2, 6.8. • 2N Shimpo Force Guage, Model:FGV-0.5XY • 1000N Shimpo Force Guage, Model: FGV-200 HX • Shimpo Tensometer • Vaseline ® • Q-tips • 3M Fine grain sand paper with fabric base • Clamp Base • Tensile Clamps • PC with Estand ® Software Page 23.167.5 • Superglue gel Procedure 1. Hydrogels with various formulations
Annual Conference Proceedings (ERM Division), June 2010.[9] Jin, Q., P.K. Imbrie, J.J. Lin, & X. Chen, 2011. “A multi-outcome hybrid model for predicting student success in engineering”, American Society for Engineering Education Annual Conference Proceedings (ERM Division), June 2011.[10] American Society for Engineering Education (ASEE), 2009. Creating a culture for scholarly and systematic innovation in engineering education: Phase 1 report, National Science Foundation. Page 23.238.9[11] Bandura, A. 1997. Self-efficacy: The exercise of control. New York, NY: W.H. Freeman.[12] Hackett, G., N.E. Betz, J.M. Casas
.[25] J. L. White, et al., "Persistence of Interest in Science, Technology, Engineering, and Mathematics: A Minority Retention Study," Journal of Women and Minorities in Science and Engineering, vol. 12, pp. 47-64, 2006.[26] Q. Li, et al., "Development of a Classification System for Engineering Student Characteristics Affecting College Enrollment and Retention," Journal of Engineering Education, vol. 95, pp. 361- 376, 2009.[27] E. Seymour and N. Hewitt, Talking about Leaving: Why Undergraduates Leave the Sciences. Boulder, CO: Westview Press, 1997.[28] L. E. Bernold, et al., "Understanding Our Students: A Longitudinal- Study of Success and Failure in Engineering With Implications for Increased
sections of engineering economics were structured.Methodology- Course and Section StructureEvery effort was made to keep the two sections consistent in as many areas as possible with theobvious exception of the delivery mode. The face to face section held class sessions on Tuesdayand Thursday from 2:00PM-3:15PM and had 37 students. The online section had 27 studentsand held Centra (online chat/ white board system) Q&A sessions at 6:00PM on Tuesday andWednesday with half the class targeted to each time period to assure manageable numbers.Blackboard was the course management system for both sections and all assignments weresubmitted online through the assignment feature. Other consistent factors include the sameinstructor, identical PowerPoint
and graduate students through interactions withresearchers from CAEFF researchers (a graduated NSF Engineering Research Center) workingcollaboratively with industrial researchers from Hoowaki LLC, a small-business involved ininnovative research. AcknowledgmentsThis work was primarily supported by National Science Foundation under Award EEC‐1128481and made use of ERC Shared Facilities supported by the National Science Foundation underAward Number EEC-9731680. References1. Zhang, Z-Z.; Xue, Q-J.; Liu, W-M.; Shen, W-C; Friction and Wear Behaviors of Several Polymers Under Oil-Lubricated Conditions. J. Appl. Polym. Sci., 1998, 68, 2175–2182.2. Samyn, P