factors relating to student attrition in engineering &applied science are debated within the literature [23,24] studies which suggest that ‘ActiveLearning’ has a positive impact on the student experience within the engineering field areperhaps the most optimistic; with evidence suggesting that hands-on, relevant active learningexperiences can do much to promote a positive student experience [25,26].2.1 The Case Study OrganisationGosta University is located in the central region of the United Kingdom. A university since the1960’s, Gosta is one of the UK’s most diverse universities, with over 60% of its studentpopulation originating from Black and Minority Ethnic (BME) backgrounds. In terms of ‘addedvalue’ and the promotion of social mobility
accepted for publication in Science Scope.4. Daugherty, J., Custer, R. L., Brockway, D., & Spake, D. A. (2012). Engineering Concept Assessment: Design and development (AC 2012-2987). American Society for Engineering Education.5. Greene, B. A. (2015). Measuring cognitive engagement with self-report scales: Reflections from over 20 years of research. Educational Psychologist, 50, 14-30. doi:10.1080/00461520.2014.9892306. Unfried, A., Faber, M., Stanhope, D. S., & Wiebe, E. (2015). The development and validation of a measure of Student Attitudes Toward Science, Technology, Engineering, and Math (S-STEM). Journal of Psychoeducational Assessment, 1-18.7. American Association for the Advancement of Science (2017). Science
the measured/calculated data alongwith the above mentioned plots (Q2) to report if any differences are observed in the results forthe two different balls that are tested along with a scientific explanation for it. In addition thefollowing discussion questions are asked as well.(Q3) If the ball is projected with a velocity = 2000 ft/s in air how would its flight characteristicsbe affected?(Q4) A ball projected with velocity v at an angle θ breaks apart into two pieces at the highestpoint of its trajectory such that each piece acquires an additional horizontal velocity v opposite indirection to the other piece and perpendicular to the initial horizontal direction. Find the locationof each piece with respect to the launch point when it falls to
new formative assessment probes. Arlington, VA: National Science Teachers Association, 2016.[6] P. Keeley, Uncovering student ideas in science, Volume 1, Second edition. Arlington, Va.: NSTA press, National Science Teachers Association, 2018.[7] S. Foroushani, “Misconceptions in engineering thermodynamics: A review,” International Journal of Mechanical Engineering Education, p. 030641901875439, Feb. 2018.[8] D. Hammer, “More than misconceptions: Multiple perspectives on student knowledge and reasoning, and an appropriate role for education research,” Am J Phys, vol. 64, no. 10, pp. 1316–1325, Oct. 1996.[9] J. P. Smith, A. A. diSessa, and J. Roschelle, “Misconceptions Reconceived: A Constructivist Analysis
with assessment from self on the first line and peerassessment on the subsequent lines. The normalized scores are on the right and listed as with andwithout self-assessment to check if the student’s self-perception matches the group’s. Softwarewas formatted to color cells when assessment data was +/- 0.05 or greater (< 0.95 = orange, >1.05 = green), making it easy to find low and high performers. Table 3: Student X Assessment at Project Initiation Student X L E A D E R S w/self w/o self 5 5 5 5 5 5 5 4 4 4 4 4 4 4 0.901 0.911
a, e, i Customer Discovery b, d, e, f, i, k Evaluating Solutions b, c, d Ideation b, c, d, l Rapid Prototyping g, h, q Design Iteration c, h, l Potential Value Evaluation e, i, j, k, m, n, o Market Forces e, i, j, k, n, o*Topic Area “p”, not categorized above, focuses on teamwork, which is extensive in the first-year design course and is therefore covered throughout.Based on coverage of each Topic Area, we rated each (a-q) EM outcome as to the mode(s) bywhich it was covered: Introduced, Developed Skills, and/or
factors constituting initial mental representations of a design problem and thenrecoded with the four characteristics of an entrepreneurial mindset. Through the two-dimensionalcoding procedure and reflecting on student’s initial mental representations of design problems, aquality description of how their thinking and actions are guided by entrepreneurial mindset willbe provided to better understand the potential promise of integrating the entrepreneurial mindsetin P-12 engineering coursework.ReferencesAdams, R. S., Beltz, N., Mann, L., & Wilson, D. (2010). Exploring student differences in formulating cross-disciplinary sustainability problems. International Journal of Engineering Education, 26(2), 324-338.Atman, C. J., Chimka, J
, racial and ethnic identity, and gender. Participants then indicatedtheir current year in school, whether they were currently a major in the College of Engineeringand Computing, intended to declare a major in engineering/computing, or were/intended to majorin another university division. They indicated their SAT/ACT score, high school GPA, theirhighest level of high school physics and mathematics, and whether they had taken an AP and/oran IB exam in Physics or Mathematics and their score(s) if so.Participants then completed additional measures unrelated to the present research questions.2) Post-exam survey. Participants who had completed the intake survey received an emailinvitation to take the follow-up survey using a link provided in the email
Processing Workshop, 2004 and the 3rd IEEE Signal Processing Education Workshop. 2004 IEEE 11th, pages 58–62, Aug 2004. doi: 10.1109/DSPWS.2004.1437911. [2] Xuemin Chen, Gangbing Song, and Yongpeng Zhang. Virtual and remote laboratory development: A review. In Proceedings of Earth and Space 2010: Engineering, Science, Construction and Operations in Challenging Environments, pages 3843–3852, Honolulu, HI, 2010. [3] Lyle D. Feisel and Albert J. Rosa. The role of the laboratory in undergraduate engineering education. Journal of Engineering Education, 94(1):121–130, 2005. [4] S. Dormido Bencomo. Control learning: Present and future. In Annual Reviews in Control, pages 115–136, 2004. [5] Nancy Roberts. Teaching dynamic feedback
@stevens.eduAcknowledgmentsThis work was supported by NSF Grant No. 0326309. This support is gratefully acknowledged.The collaborative efforts and discussions with Mr. Chenghung Chang are very much appreciated.References[1] Gustavsson, I. (2002). A remote laboratory for electrical experiments. Proceedings of the 2002 ASEE Annual Conference & Exposition, Montreal, Canada, June 16-19, 2002.[2] Esche, S. K. (2005). On the integration of remote experimentation into undergraduate laboratories - pedagogical approach. International Journal of Instructional Media, Vol. 32, No. 4, 2005.[3] Esche, S. K. et al. (2003). An architecture for multi-user remote laboratories, World Transactions on Engineering and Technology Education. Vol. 2, No. 1, pp. 7
AC 2007-2785: START: A FORMAL MENTORING PROGRAM FOR MINORITYENGINEERING FRESHMENTony Mitchell, North Carolina State University Dr. Tony L. Mitchell, Lieutenant Colonel United States Air Force, Retired, received his B.S. degree in Mathematics from North Carolina A&T State University, the M. S. in Information and Computer Science from Georgia Tech, and Ph.D. in Electrical and Computer Engineering from North Carolina State University. Currently he is Assistant Dean, Engineering Student Services, Director, Minority Engineering Programs, and Associate Professor of Electrical and Computer Engineering at North Carolina State University in Raleigh. Previous educational assignments include
limits. At that point, the triallimits are adopted for future control.V. ESTIMATING PROCESS CAPABILITYThe X and R charts provide information about the performance or capability of the process inreal time frame. These charts work like a window into the process and provide a quantitativemeasure of the product quality. One must at least go through the following steps to determine theprocess capability.1) After all the assignable causes have been eliminated from the process as far as it is practical,check to see that the process is stable and under tight control, collect at least 25 to 50 samples, 3to 6 reading per sample.2) Record the data set in a time ordered sequence. After calculating X ’s, R’s, X ’s, and R ’s.estimate the values of Upper
t A A s B X B y C X C n D X X D n E X E X n F X X F s G X X G s H X X H s I X I g J X X J t K X K Page 12.1450.7 Figure 5. Design Structure Matrix 62.4 Needs-Functional RelationshipThe
AC 2007-756: MOBIUS MICROSYSTEMS: A CASE STUDY IN THECOMMERCIALIZATION OF GRADUATE RESEARCH IN ELECTRICALENGINEERINGMichael McCorquodale, Mobius Microsystems, Inc. Michael S. McCorquodale was born in Richardson, TX, on November 12, 1974. He received the B.S.E. degree with honors in electrical engineering from the University of Illinois at Urbana-Champaign in 1997. For the next year, he was with Hughes Space and Communications Co., El Segundo, CA, where he developed GHz InP and SiGe digital integrated circuits. In 1998, he began graduate work at the University of Michigan where he completed the M.S.E and Ph.D. degrees in electrical engineering in 2000 and 2004, respectively, in the National
that integrating many differentmathematics ideas in one concrete context is challenging. Further supports, such as using thedesign context as a capstone activity or incorporating structured transfer activities, may berequired to effectively enable students’ mastery of the more general mathematical ideas. In ourfuture work, we intend to consider more case studies of the curriculum in-action withimprovements to the implementation based on these findings, in addition to conductingcomparative analyses of the curriculum relative to alternative approaches. This will help us tofurther elaborate on the conditions necessary for designing effective K-12 engineering curricula.Bibliography1. W. H. Schmidt, C. C. McKnight, and S. A. Raizen, A Splintered
.) The Nature of Expertise (pp. 261-285). Hillsdale, NJ: Lawrence Erlbaum Associates 2. Bransford, J.D. (1993). Who Ya Gonna Call? Thoughts About Teaching Problem- Solving. In P. Hallinger, K. Leithwood, J. Murphy (Eds.), Cognitive Perspectives on Educational Leadership (pp. 171-191). New York: Teachers College Press. 3. French, S., Simpson, L., Athertona, E., Belton, V., Dawes, R., Edwards, W.,O P. Hamalainen, R.P., Larichev, O., Lootsma, F., Pearmani, A., Vlek, C. (1998)Problem Formulation for Multi-Criteria Decision Analysis: Report of a Workshop. J. Multi- Criteria Decision. Analysis, Vol. 7, pp. 242–262. 4. Jonassen, D.H. (1997). Instructional Design Models for Well-Structured and Ill
AC 2008-1705: ENHANCING THE SOFTWARE VERIFICATION ANDVALIDATION COURSE THROUGH LABORATORY SESSIONSSushil Acharya, Robert Morris University Sushil Acharya, D.Eng. Assistant Professor of Software Engineering Acharya joined RMU in Spring 2005 after serving 15 years in the Software Industry. With US Airways Acharya was responsible for creating a Data Warehouse and using advance Data Mining Tools for performance improvement. With i2 Technologies he led the work on i2’s Data Mining product “Knowledge Discover Framework” and at CEERD (Thailand) he was the product manager of three energy software products (MEDEE-S/ENV, EFOM/ENV and DBA-VOID) which are currently in use in 26 Asian and 7
WPI many entering students have recently expressed an interest in robotics. During theacademic year 2006/07, for example, over 130 visiting prospective students listed robotics eitheras a principal interest area or as their planned major on WPI Admissions Information forms. InFall 2005 and 2006, 96 and 101 freshmen, respectively, joined the WPI Robotics Team. One-third of them stated an interest in pursuing robotics for their senior project or academic major.43% had known of the WPI/FIRST/robotics connection before enrolling at WPI and 62% ofthese indicated that this knowledge was a strong positive reason for selecting WPI.3.0 Education in RoboticsOne may date the earliest robotics-related undergraduate curricula to the 1980’s where
outside of class; note that other types of communication were notreported. Page 13.1109.4Table 1: Student Responses to Background Items(n = 322) Item No. Read Skim No NR 1 Have you read the UH academic honesty policy? 44.1% 39.8% 14.3% 1.9% Often Some Never NR 2 I communicate with other students in most of my 14.9% 63.7% 21.4% 0.0% course(s) outside of class time via electronic means. Strly
create anyproblem. Page 13.535.5Design and Delivery Consideration IssuesThe following were identified/recommended for the design and delivery process.• Hybrid-based course(s) should be clearly designated and advertised as such to prevent student confusion at the time of enrollment.• Students should be informed regarding course delivery methodology and the requirements for student participation. This is particularly important from the point of view of student satisfaction, as student expectations must be molded to fit the constraints of the online-based course delivery.• Support for online delivery classes needs to be expanded
probabilistically-flawed,potentially dangerous criteria [1]. These criteria have been in-use since at least the 1960’s [2],but their limitations were only formally recognized recently. While prior work has thoroughlyarticulated the technical issues in these flawed design criteria [1], [3], the present work aims tosupport formal study of how engineers recognize and treat variability, with an eye towardsunderstanding how the aforementioned flaws evaded notice for over a half-century.In this work, we present a novel theoretical framework and initial empirical results. We use theproposed cause-source framework to analyze aircraft design flaws and to design an interviewprotocol. Through interviews with engineering students, we find initial evidence of an
) Kinematic Equations Since the crate doesn’t slip relative to the truck, we have (aA )x = (aB )x and (aA )y = (aB )y = 0. Now, using the constant acceleration eqns, we can find the acceleration of the truck, that is, (vB )2x = (vB0 )2x + 2(aB )x (xB − xB0 ) Profs. Gray & Costanzo (Penn State) Lecture 12: N-E Eqns: Examples February 12, 2007 7 / 20 Example: Problem 3.3 (continued) Plugging in numbers: 0 = (88)2 + 2(aB )x (350) ⇒ (aB )x = −11.06 ft/s2 . where I have used the fact that (vB0 )x = 60 mph = 88 ft/s. Computation
this type is not a working prototype product but a package of deliverables includingconcepts, descriptions of user needs, and specifications for products or systems, with thoughtfuldesign of the interface and the basic structure of the product(s) or system to be built. Comingfrom a technology background the design team should show a depth of understanding of thetechnical issues facing the product design.In order to achieve high quality results, such as those described above the designers (students)need to follow a reliable design and development process that requires discipline, technical skill,and creative design work. All the attributes for successful capstone courses will be required bythe students, some to an enhanced degree.4. The case
validated “best” set hadbeen stored on behalf of all.Background and Literature ReviewThe University of California (UC) is comprised of ten universities located in Berkeley (N), Davis(N), Irvine (S), Los Angeles (S), Merced (N), Riverside (S), San Diego (S), San Francisco (N),Santa Barbara (S) and Santa Cruz (N), nicely divided into five Northern (N) and Southern (S)campuses. Two Regional Storage Facilities (RLFs), north and south, located near Berkeley andin Los Angeles, have provided storage space for older and lesser-used materials for about threedecades. For a conceptual description of the roles of the RLFs, see Schottlaender1. Recentpolicy changes have led to them being managed as persistent shared collections. This changeguarantees that
, T(r | p) T(p | p) for all r p andT(r* | p) T(p | p) when r* = p. [1-4] Many strictly proper scoring rules have been developed.Three of the most popular are given below.Quadratic (Q): Qi (r ) 2 ri r r [1,1] (2)Spherical (S): Si (r) ri / (r r)1/2 [0,1] (3)Logarithmic (L): L i (r ) ln( ri ) ( ,0] (4)The range of possible scores differs considerably. For example, logarithmic scoring holds thepossibility of an infinitely negative score. While this may seem like a defect, we will argue thatthis feature is a benefit of log scoring. Any linear
projects; rather it directs you to these resources and how onecan initiate working on projects. Although the goal of this paper is to address educators on how to promoteengineering education through NXT, but not to focus too much on the building andprogramming instructions or procedural steps involved in a robot design, as the NXT kitcomes with very clear and user friendly instructions[2][5][6]. However, the author(s)would like to cite one specific “Multi –NXT robot design” that students at University ofNorth Dakota built and programmed, because it is definitely worth mentioning. The author (s) would like to address this project in particular in two differentPhases:Phase I – To get to know the NXT kit and its programming blocks by
and Techniques for et al. Residential Buildings 4. Consequence of Climate R. H. Chaudhary Texas Section ASCE 2008 Change on the Infrastructure 5. Green Buildings – Y. R. Kanapuram ASEE Gulf 2008 Sustainable Construction Southwest 6. Sustainable Building Design S. R. Yardimalla ASEE Gulf 2008 Southwest 7. Overview of Adaptive A. P. Pakalpati Texas Section ASCE 2007 Techniques and Materials used in Sustainable Buildings 8. Effective Municipal Solid D. Siringi
Promote Growth. Journal of Engineering Education, Vol. 93, No. 4, 279, 2004.8. D. Tolfree. Commercializing Nanotechnology. Concepts–products–markets. Int. J. Nanomanufacturing, Vol. 1, No. 1, pp. 117-133, 2006.9. S. Fonash et al. Nanotechnology Education: The Pennsylvania Approach. MRS Symposia, Vol. 931, Section E, 2006.10. A. K. Lyton-Jean, H. S. Han, and C. A. Mirkin. Microarray Detection of Duplex and Triplex DNA Binders with DNA-Midified Gold Nanoparticles. Analytical Chem., Vol. 79, pp. 6037-6041, 2007.11. J. S. Lee, S. I. Stoeva, C. A. Mirkin. DNA-Induced Size-Selective Separation of Mixtures of Gold Nanoparticles. J. Am. Chem. Soc., Vol. 128, pp. 8899-8903, 2006.12. J.R. von Ehr, “Zyvex Corporation: Providing Nanotechnology
AC 2009-233: TEACHING SHIP STRUCTURES WITH SHEET METALWilliam Simpson, United States Coast Guard Academy Dr. William M. Simpson, Jr. is a faculty member in the Engineering Department at the U.S. Coast Guard Academy. He has a Ph.D. in Aerospace Engineering from the University of Maryland, a Masters in Naval Architecture and Marine Engineering from Massachusetts Institute of Technology, and a Bachelor of Science from the U. S. Coast Guard Academy. He is a registered Professional Engineer in the State of Connecticut. He served on active duty in the U.S. Coast Guard from 1965 to 1992 and had assignments in Marine Safety, Naval Engineering, Acquisition, and Research and Development
: dI (t ) 1 R 1 = ea (t ) − I (t ) − eb (t ) dt L L L Tm (t ) = K i I (t ) eb (t ) = Kω (t ) d ω (t ) 1 1 = Tm (t ) − TL (t ) Page 14.321.7 dt J Jwhere • Ki is the torque constant (Nm/A); • K is the back emf constant (V/(rad/s)); • I(t) is the armature current (A); • R is the