Applied Research), Volume 2004, Issue 7. 3. Kadle A. (2009). “Blended Learning with Social Technology Components”, Upside Learning Page 23.569.8 Blog, December 22, 2009 (www.slideshare.net/UpsideLearning/blended-learning-3374296).4. Driscoll M., “Blended learning: let‟s go beyond the hype”, IBM Global Services (http://www- 07.ibm.com/services/pdf/blended_learning.pdf).5. Milne A.J., “Designing blended learning space to the student experience”, EDUCAUSE (http://www.educause.edu/research-and-publications/books/learning-spaces/chapter-11-designing- blended-learning-space-student-experience).6. Dean B. (2007). “Blended learning
; Burford, B. C. (2008). Portfolio learning for foundation doctors: Early feedback on its use in the clinical workplace. Medical Education, 42, 214-223.22. Jun, M., Anthony, R., Achrazoglou, J., & Coghill-Behrends, W. (2007). TechTrends, 51(4), 45-50.23. Tzeng, J. Y. (2011). Perceived values and prospective users’ acceptance of prospective technology: The case of a career eportfolio system. Computers and Education, 56, 157-165.24. Canar, M. (2010). Students’ views on using portfolio assessment in EFL writing courses. Anadolu University Journal of Social Sciences, 10(1), 223-236.25. Elango, S., Jutti, R. C., & Lee, L. K. (2005). Portfolio as a learning tool: Students’ perspective. Annals Academy of Medicine, 24(8
, K. (2009). Real Outreach Experiences In Engineering: Merging Service-Learning and Design in a First-Year Engineering Course. ASEE Annual Conference Proceedings. Austin, TX.[4] Zarske, M. S., Reamon, D. T., Bielefeldt, A. R., & Knight, D. W. (2012). Service-Based First Year Engineering Projects : Do They Make a Difference? Proceedings in Annual Conference of the American Society for Engineering Education. San Antonio, TX[5] Jacoby, B (1996). Service-learning in Higher Education: Concepts and Practices.[6] Freeman, S. F. (2011). Service-Learning vs. Learning Service in First-Year Engineering: If We Cannot Conduct First-Hand Service Projects, is It Still of Value? ASEE Annual Conference Proceedings. Vancouver, BC
five response options. Therefore, the higher numbers indicate higher expectations of proficiency. The ten major subject areas shown on the Four Pillars model made up the first ten sets of topics in the survey with each having multiple sub-topics ranging from five to twelve. The 11th area was labeled “Miscellaneous topics” and it included five items that were not specifically mentioned in the Four Pillar model. A total of 99 topics were included in the eleven sets. 4. The final survey item asked each responder to indicate their primary fields of manufacturing experiences, with 20 options provided.Appendix A. lists the sorted Overall Rankings by Survey RespondentsAppendix B. provides Number and
. Kjeang, N. Djilali, D.Sinton, Microfluidic fuel cells, Journal of Power Sources 186, 353-369, 20097. N. Damean, P.P.L. Regtien, M. Elwenspoek, Heat transfer in a MEMS for microfluidics, Sensors and Actuators,A 105, 137 – 149, 20038. W. Lee, W. Fon, B. W. Axelrod, M. L. Roukes, High-sensitivity microfluidic calorimeters for biological andchemical applications, Proceedings of National Academy of Sciences, 106 (42) 18040; doi:10.1073 /pnas.0910433106, 20099. L. Wadsö, A. L. Smith, H. Shirazi, S. R. Mulligan, T. Hofelich, The Isothermal Heat Conduction Calorimeter: AVersatile Instrument for Studying Processes in Physics, Chemistry, and Biology, J. of Chemical Education, 78 (8
in problem 1, b) If the bar does not remain at rest, then de- if at all. scribe its subsequent motion as a result of the application of the force. Figure 1: Rigid body dynamics questions given the first day of StaticsStudents’ answers were analyzed to see whether students understood that the body would bothtranslate and rotate in both cases, and coded accordingly. Performance on the rigid body motionquestions were correlated to student performance on the Conceptual Assessment Tool for Statics(CATS)* pre-test and post-test results, both overall and on the specific equilibrium questions, andon performance on the final exam, both overall and on two conceptual questions, one on
for a pattern to be "interesting". 2. Data Preprocessing. Real world data are generally (a) incomplete: lacking attribute values, lacking certain attributes of interest, or containing only aggregate data (b) noisy: containing errors or outliers and (c) inconsistent: containing discrepancies in codes or names. Certain basic preprocessing techniques are discussed here, including: • Data cleaning: fill in missing values, smooth noisy data, identify or remove outliers, and resolve inconsistencies. • Data integration: using multiple databases, data cubes, or files. • Data transformation: normalization and aggregation. • Data reduction: reducing
consumer electronics product. Each student team is toanalyze the current offerings in the market and design a product that will better meet needs of thetargeted environmentally conscious/green population.The external design activities include following steps: Step 1. Analysis of customer needs Step 2. External search (Product Dissection and Benchmarking) a. Component and assembly analysis b. Literature Review c. Patent Search Step 3. Revising the design statement Step 4. Internal work for concept generation Step 5. Concept Generation (Conceptualization and Virtual Representation) Step 6. Concept Selection Step 7. Embodiment of the design and feasibility analysis
Paper ID #6742Mentoring Team Conflicts in Capstone Design: Problems and SolutionsDr. Marie C Paretti, Virginia Tech Marie C. Paretti is an Associate Professor of Engineering Education at Virginia Tech, where she co-directs the Virginia Tech Engineering Communications Center (VTECC). Her research focuses on communica- tion and teamwork in engineering, design education, and engineering identity. She was awarded a CA- REER grant from NSF to study expert teaching practices in capstone design courses nationwide, and is co-PI on NSF . Her work includes studies on the teaching and learning of communication, the effects of
) West West State Tech West West West College State Univ (E) (F) Univ State Comm (A)* (B) (D) (G) (H) College (I)Level 4-year 4-year 4-year 4-year 4-year 4-year 4-year 4-year 2-yearControl Private Public Public Public Public Private Private Public PublicPopulation <5000 <
, Louisville, KY, 12 pages, CD-ROM and www.asee.org 10. Anderson-Rowland, M. R., Rodriguez, A. A., Bailey, J. H., Grierson, A. E., Pangasa, R., Vangilder, C., McBride, R. B., and Hall, R. A. (2011) “STEP Grant Challenges and Results: Motivated Engineering Transfer Students From Non-Metropolitan Community College,” 2011 American Society for Engineering and Education Proceedings, Vancouver, British Columbia, Canada, 13 pages. www.asee.org Page 23.1265.14
] Hiremath, P. S., & Prabhakar, C. J. (2008). Symbolic factorial discriminant analysis for illumination invariant face recognition. International Journal of Pattern Recognition and Artificial Intelligence, vol. 22, no. 3 (2008) pg. 371-387. doi:10.1142/S021800140800634X[3] Chai, X., Gao, W., Fu, X., & Shan, S. (2003). Virtual face image generation for illumination and pose insensitive face recognition. Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on Issue Date: 6-10 April 2003. p. IV - 776-9 vol.4. doi:10.1109/ICME.2003.1221270[4] Beveridge, J. R., Bolme, D., Draper, B. A., & Givens, G. (2003). A statistical assessment of subject factors in thePCA recognition of
-year collaborations betweenadministrators, faculty, and staff in academia with local community partners. Each project isrequired to: (a) integrate the performing arts into the education, service, and scholarly missionsof the academy and engage chief academic officers and executive leadership; (b) provideopportunities to deepen and expand the participation of artist(s) in the academy through longterm residencies, commissions and/or other creative activities; and (c) identify, document, andshare lessons learned that will contribute to an evolving knowledge base and learning communityfor campuses and the wider performing arts and presenting field.17 This paper focuses on howwe accomplished (a) in partnership with the Learning Factory while also
Vocational Behavior. 2005, 67, 87–101.(5) Godwin, A.; Potvin, G. Chemical Engineering Students: A Distinct Group Amongst Engineers. Chemical Engineering Education (In Press).(6) Zhang, G.; Thorndyke, B.; Ohland, M. Demographic Factors and Academic Performance: How Do Chemical Engineering Students Compare with Others? In ASEE 2003 Annual Conference & Exposition; 2003; pp. 1– 12.(7) Witt, P.; Handal, P. Person-environment fit: Is satisfaction predicted by congruency, environment, or personality? Journal of College Student Personnel. 1984, 25, 503–508.(8) Hazari, Z.; Sonnert, G.; Sadler, P. M.; Shanahan, M.-C. Connecting high school physics experiences, outcome expectations, physics identity, and physics career
reflect the views of the National Science Foundation. Page 23.767.9References1. Brandenberger, J. W., Bringle, R.E., Duffy, D.K. (1998). Developmental psychology and service-learning: A theoretical framework. American association for higher education, 68-84.2. Jaboci, B. (1996). Service-Learning in Higher Education: Concepts and Practices. The Jossey-Bass Higher and Adult Education Series, San Franciso, CA.3. Eyler, J., Giles D.E.J., Stenson C.M., Gray C.J. (2001). At a glance: What we know about the effects of service- learning on college students, faculty, institutions and communities, 1993-2000. Corporation for National Service Learn
processing board reads the sensors’ measured values and sends them to an internet server.The user can view the date either as numerical values or as a graph. The data can be alsodownloaded as Microsoft Excel sheet. Figures 4B and 4C show the main processing board andits associated components. Figure 4.B. Main Processing Board and its Associated Hardware.8.1. SensorsThe SHT 75 sensor from Sensirion is selected to measure temperature and relative humidity.This sensor consists of a sensing element and a signal processing unit and provides calibratedtemperature and relative humidity measurements. This sensor uses capacitive and band gapsensing technology to measure the relative humidity and temperature, respectively. In this systemfive of
. Figure 15. A snapshot of the Control screen of the CCM4. Assessment of Student Learning OutcomesStudent learning outcomes were assessed throughout the project duration in each department aspart of its own senior design course. As in senior design courses at most institutions, the studentlearning outcomes in the senior design in the three departments typically were assessed on some ofthe key ‘a thru k’ ABET-defined student learning outcomes such as a) ability to apply knowledgeof mathematics, science, and engineering, b) ability to design and conduct experiments, c) abilityto design a system, component, or process to meet desired needs, d) ability to function onmultidisciplinary teams, f) understanding of professional and ethical responsibility
with one another, teams must engage in both individualactions (member contributions) and shared actions (team processes). The quality and complexityof team processes and level of team member effort directly affect the quality of their projectoutput [12-15]. Project achievement impacts team member motivation to invest effort in the team[16]. Team culture that exhibits respectful social interactions is also important to gainingengagement of team members in the team’s work [17-18].Katzenbach and Smith [2] (p. 113) summarize requirements of a good team as one that has: (a)shared leadership roles, (b) individual and mutual accountability, (c) specific team purpose thatthe team itself delivers, (d) collective work products, (e) active problem
excel in their chosen professions. Each candidate is Page 23.409.8required to build a digital portfolio, demonstrating proficiency in written, spoken, visual, andtechnological communication. Candidates must also show successful use of their communicationskills in leadership roles and community service. Upon successful completion of the program,these students possess the competitive skills and knowledge needed for 21st century leadership.This coveted designation becomes part of official transcripts and gives the certified graduatesignificant leverage in today’s job market. In order to earn certification, students must • Earn a B or higher in
Paper ID #7719Design and Analyze the Frame for the Global Sustainable Urban Transport(SUT) VehicleDr. Mohammad Kamal Hossain, Tuskegee University Mohammad Kamal Hossain is an Assistant Professor in the Department of Mechanical Engineering at Tuskegee University. He received his Ph.D., M.S., and B. Sc. in Mechanical Engineering from the University of Nevada, Las Vegas (USA), Tuskegee University (USA), and Bangladesh University of En- gineering and Technology (Bangladesh), respectively. His specialization is in the areas of materials and design. Before coming to Tuskegee University (TU), he worked as a Visiting Assistant
Page 23.1013.3\ Table 2: ABET Outcomes and Assessment Methods ABET Outcome SES FE CDSA CRSW (a) (apply math, science and P S engineering) (b) (conduct and design S P experiments) (c) (design a system, component S P P or process) (d) (multidisciplinary teamwork) S S P (e) (identify and solve eng
research areas include mist and microstructure characterization during machining using minimum quantity lubrication. He is performing research to develop sustainable machining processes which are environmentally friendly and harmless to the machining operators. Page 23.906.1 c American Society for Engineering Education, 2013 Microlubrication effects in milling AISI 1018 steel: An approach towards Green Manufacturing Vasim Shaikha, Nourredine Boubekria* and Thomas W. Scharfb a Department of Engineering Technology b
2005 through 2015 isestimated at nearly 3,000 students.The data collection will start by studying the course enrollment and success rates for a subset ofgateway courses at UAHuntsville to measure the probabilities of successful completion (earningan A, B, or C), unsuccessful completion (earning a D or F), and withdrawal for students given atheir individual sets of characteristics and factors. The gateway class sizes at UAHuntsville aresizeable enough to provide an extensive set of records over the anticipated 10 year period. Forexample, during the 2011-2012 academic year student enrollment figures for the Calculus A – Csequence were 608, 486, and 483 students, respectively. Similarly, the total 2011-2012enrollment for the Physics 1 and 2
). xy abcdefg a y x y x 00 0111000 f g b 1 DQ DQ DQ 10 1100011 e d c 11 1101010 (0 lights the segments) 0 1 (blank) 1111111 Figure 5: Showing letters on the seven-segment displayThe functions for the seven segments of the display to
, marital status, number of children, parents’ educationalachievement and enrollment information.Table 2 contains the evaluation of the group performance. The enrolled students were dividedinto three groups because gauge R&R studies require at least two operators to be conducted.Student performance was evaluated as Exceptional (A-level), Effective (B-level), Acceptable (C-level) and Unsatisfactory (D-F level). In general, the student performance was unsatisfactory.Only one group performed a gauge R&R study using the steel rule at an acceptable level. Theanalyses of gauge R&R studies using the caliper and micrometer were unsatisfactory for everygroup. All groups made the same mistake when gathering data for the gauge R&R studies
appreciated.Bibliography 1. Beede, D., Julian, T., Langdon, D., McKittrick, G., & Khan, B. (2011). Issue Brief #04-11, Women in STEM: A gender gap to innovation. U.S. Department of Commerce, Economics and Statistics Administration. 2. Ross, T., Kena, G., Rathbun, A., Kewal-Ramani, A., Zhang, J., Kristapovich, P., & Manning, E. (2012). Higher education: Gaps in access and persistence study. U.S. Department of Education, National Center for Education Statistics. 3. Social analysis: Gender analysis. (2011). The World Bank. Retrieved from http://go.worldbank.org/XKLV2D86N0 4. Srinivas, H. (2012). What is gender analysis? Global Development Research Center. Retrieved from
). Exploring engineering day. Proceedings of the 2005 American Society for Engineering Education Annual Conference & Exposition. 6 Klenk, P. A., Ybarra, G.A., &. Dalton, R.D (2004). Techtronics: Hands-‐on exploration of technology in everyday life. Proceedings of the 2004 American Society for Engineering Education Annual Conference & Exposition. 7 Wang, E., LaCombe, J., & Rogers, C. (2004). Using LEGO® bricks to conduct engineering experiments. Proceedings of the 2004 American Society for Engineering Education Annual Conference & Exposition. 8 Barker, B. S., & Ansorge, J. (2001). Robotics as means to increase achievement scores in an
, Engineering Education in the 21st century: Roles, Opportunities and challenges “4th NEA ICETE Conference Proceedings, Taichung, Taiwan, October 2010.23. Moving Forward to Improve Engineering Education, National Science Foundation, November 2007. http://www.nsf.gov/pubs/2007/nsb07122/nsb07122_2.pdf24. Alice M. Agoginohttp, “ The Engineer of 2020: Global Visions of Engineering Practice and Education” //best.berkeley.edu/~aagogino/papers/NSB2005.pdf25. The SoTL Commons – Center for Teaching, Learning & Scholarship, Georgia Southern University http://academics.georgiasouthern.edu/ijsotl/conference/201126. Khalid, A., Nuhfer-Halten, B., “Enhancing Learning at the Polytechnic University: Interactive Classroom
returned both samplesshowed a 4% error. Figures 1 and 2 show the structure of the AA and MA formulas show A,B,C hydrogens are the same. The only difference ison D Hydrogen which has threehydrogens forMA and AA has two hydrogens. This is used as to determine the quotients in equation 2 for MAand AA respectively. Table 2 shows the real composition of the copolymers as determined from1H NMR spectra.Table 2 follows that in all the cases the content of AA units in the copolymer issomewhat lower than the content of AA in the respective reaction mixture, thus indicating thatAA is less reactive than MA. Page 23.168.6
of instruction and stu- dent support. Prior to joining UW-Madison, Wayne directed the Midwest solid waste consulting services of Camp Dresser McKee and led energy conservation research projects for Argonne National Laboratory. He has a BS in engineering from Carnegie-Mellon University, an MS in civil engineering with an emphasis in regional planning from Northwestern University, and is a licensed professional engineer. For more information about UW-Madison’s online graduate engineering degree programs see http://distancedegrees.engr.wisc.edu Page 23.1224.1 c American