. A Report to the Nuffield Foundation. London1966 LeBold, W. K., Perrucci, R. and Howland, Reported that in the 1930’s in the US three W. E., 'The Engineer in Industry and fifths of engineers under 40 were occupied Government," Journal of Engineering with administrative rather than technical Education, vol. 56, no. 7, March 1966, pp. work
University of Michigan’s Rackham Merit Fellows program, theNational Science Foundation’s Graduate Research Fellowship program, the National ScienceFoundation’s Research Initiation Grants in Engineering Education, and the University ofMichigan Center for Research on Learning and Teaching’s Investigating Student Learning Grant.The study team thanks the students who volunteered as study participants.Bibliography1. Simon, H. A. The Sciences of the Artificial. (MIT Press, 1996).2. Dym, C., Agogino, A., Eris, O., Frey, D. & Leifer, L. Engineering design thinking, teaching, and learning. J. Eng. Educ. 94, 103–120 (2005).3. Kujala, S. User involvement: a review of the benefits and challenges. Behav. Inf. Technol. 22, 1 – 16 (2003).4
0.999 0.999 FunctionB Page 26.178.9 Weighted Avg. 0.999 0.001 0.999 0.999 0.999 0.999 === Confusion Matrix === a b 16. Lockerd, A. & Breazeal, C. Tutelage and socially guided robot learning. in 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2004. (IROS 2004). Proceedings 4, 3475–3480 vol.4 (2004).17. Konidaris, G., Kuindersma, S., Grupen, R. & Barto, A. Robot learning from demonstration by constructing skill trees. Int. J. Robot. Res. 31, 360–375 (2012).18. Ammar, B., Rokbani, N. & Alimi, A. M. Learning system for standing human detection. in Computer Science and Automation
The AIMS2(HSI-STEM Grant)CSU Northridge, Glendale CC, College of the Canyons JD 1568 2 PM – 4PM Nov 14, 2013 S. K. Ramesh, Dean, College of Engineering and Computer Science, and PI of the HSI-STEM Grant EDI Panel on Diversity and 03/31/16 1 Inclusion •AIMS2 Cohort: Photo Courtesy Armando Cohort 3 Cohort
, thinking, and interdisciplinary capabilities. Attitude proficiencies included themotivation required to be successful in the course, the student’s belief about their capability to besuccessful and achieve the course goal, and their ability to work with ideas that challenge theircurrent mental models of the world. After developing the learning proficiencies, course developerssorted them into early, middle, and late proficiencies. The timing did not necessarily correspondwith the timeline students would learn the material, but focused primarily on the sequence. Table1 summarizes the learning proficiencies. (K=knowledge, S=skill, A=attitude) Stage Category Proficiency K …know and apply sustainability principles
. 12, 2018.[2] L. Wimsatt, A. Trice, and D. Langley, “Faculty Perspectives on Academic Work and Administrative Burden: Implications for the Design of Effective Support Services.,” Journal of Research Administration, vol 30, no. 1, pp. 77–89, 2009.[3] K. M. Hannum, S. M. Muhly, P. S. Shockley-Zalabak, and J. S. White, “Women leaders within higher education in the United States: Supports, barriers, and experiences of being a senior leader,” Advancing Women in Leadership, vol. 35, pp. 65–75, 2015.[4] E. Judson, L. Ross, and K. Glassmeyer, “How Research, Teaching, and Leadership Roles are Recommended to Male and Female Engineering Faculty Differently,” Research in Higher Education, vol. 60, no. 7, pp. 1025–1047
activities. The DET survey is a five-point Likert-scale that consists of 40 items.The instrument focused on measuring the participants’ perceptions and familiarity with the DETconcepts. A S-STEM survey was also administrated to the teachers’ students at the beginning andthe end of the school year. The S_STEM survey is a five-point Likert-scale with 37 items. TheS_STEM survey captured the students’ attitudes towards the STEM fields and the 21st-centuryskills. In the paper we will describe the research conducted and discuss the implications forcultivating STEM literacy and integrated STEM education. Both pre- and post-comparison resultsand correlation results are presented.IntroductionSTEM fields play a crucial role in generating technological
/Nov). Ausubell‟s learning theory: An approach to teaching higher order thinking skills,The High School Journal, 82(1). Research Library[13] Ausubel, D.P. & Robinson, F. G. (1969). School learning: an introduction to educational psychology. (p.46). New York: Holt, Rinehart & Winston.[14] Oxford, R.L. (1990). Looking at language learning strategies. In Language learning strategies: what everyteacher should know, (pp. 1-37). New York: Heinle & Heinle Publishers.[15] Bransford, J.D., Brown, A.L., Cocking, R.R. (2000). How people learn: brain, mind, experience andschool. (p.20). Washington, D.C.: National Academy Press
, manyengineering programs have incorporated international service projects4,5,6,7,8,9,10,11.. In his Ph.D.dissertation regarding humanitarian aspects engineering in the engineering curriculum, Page 15.896.2Vandersteen provides and eloquent history of the evolution of engineering education discussinghow the profession has evolved to see the interconnection between technology and humanity.He further states that the “2000s (have seen an) increased interest in social, environmentalimpact of engineering”12. In fact, six years after the advent of ABET‟s EC-2000, thefundamental change in engineering accreditation, the International Journal for Service
E-mail: fnaja@ce.ufl.edu And Alex E. S. Green Graduate Research Professor Emeritus ICAAS, CLEAN COMBUSTION TECHNOLOGY LABORATORY (CCTL) College of Engineering, University of Florida Weill Hall Rm 577 PO Box 116550, Gainesville, Florida 32611-6580 Phone: (352)392-2001 E-mail: aesgreen@ufl.edu Natural gas prices have increased significantly in the past four years. Natural gasaccounts for almost a quarter of the United States’ energy consumption. The increase in naturalgas prices may create an economic problem in the U.S. economy and the university’s budgetdeficits. The
for his academic activities from various sources including NASA, The National Science Foundation, The Texas Higher Education Coordinating Board’s Advanced Research Program, U. S. Department of Commerce, The Texas Manufacturing Assistance Center, The U. S. Department of Education, and The U. S. Department of Labor. One of his current interests is in the area of manufacturing systems for rapid response Manufacturing. An extension of this work is the current effort that established the UTPA Rapid Response Manufacturing Center in a consortium of aca- demic institutions, economic development corporations, industry, local, state, and federal governments. This initiative is an integral component of the North American
favorable/positive andunfavorable/negative categories with respect to each outcome for the SW analysis; i.e.,perceptions were re-grouped into positive (4’s or 5’s), neutral (3’s) and negative (1’s or 2’s). Thisaggregation is necessary in order to obtain the desired confidence level given the relatively smallsample sizes when data were analyzed by program and year. Figure 1 shows an examplehistogram for one particular survey item. Histogram of Responses for a Typical Survey Item 30% 25% Percentage 20% 15% 10
Session 3422 Crossing Professional Boundaries: The Interprofessional Projects Program at IIT Thomas M. Jacobius, Gerard G. S. Voland Illinois Institute of Technology Illinois Institute of Technology is transforming its undergraduate program through theconcept of interprofessional education by requiring project-based team experiential learningacross the span of disciplines within the Undergraduate College and by involving graduateprograms from across the university, including those in engineering, science, law, business,psychology, design and architecture
assimilation of difficult concepts: Classical movies, such asthe ones by G.I. Taylor and S. Corrsin, can be reformatted and placed as computer resources thatcan be accessed through the Internet. A number of efforts, supported by National ScienceFoundation, has recently resulted in the generation of multi-media modules in areas such as fluidmechanics and process technology [2-3].Incorporation of virtual and real experiments that can be performed through the Internet: Virtualexperiments are possible with today’s technology. For instance, consider the illustration of self-diffusion through random walk through IRIM. A computer program to simulate random walk willbe linked to the IRIM. The student can “click” on the appropriate icon to run this program
preferred to P, since it is not good for students to tailor their writing to aparticular reviewer, but strategy P has advantages where one assignment builds on the theprevious one. If a particular student has reviewed the design document for a project, forexample, there are advantages in having him (her) also review the finished project. If groups ofstudents work on a single project, students may be randomly assigned to review other student(s)within the same group [Topp 00]; let us call this Strategy G.One variant of Strategy G was used by Henderson and Buising [HB00]. They had groups of 3-5students select topics from a list of 13. The groups then subdivided the topics, assigning part toeach member of the group. The groups then exchanged their
as scaffolds for tissue engineering, ● Bioresponsive hydrogels for controlled drug delivery and biosensors, ● Hydrolytically degradable biomaterials in treatment of cancers, and ● Fabrication of structurally-specific biomaterials on the molecular level using microfabrication techniques. This review paper will address briefly the past methods used to develop biomaterials and willconcentrate on the advances being made in the areas of controlled drug delivery, tissue engineering,biodegradable biomaterials and environmental y responsive biomaterials. A range of materials will bediscussed, including hydrogels and poly(lactic-co-glycolic acid)s. Novel formulations which
that presents eight steps in developing an assessment plan4. But regardless ofhow the assessment plan is developed, an effective plan must start with the identification ofspecific goals and objectives, definition of performance criteria, followed by the data collection1 Penn State University, University of Washington, and the University of Puerto Rico at Mayagüez in collaboration with SandiaNational Laboratories. Project sponsored by the Technology Reinvestment Project. (TRP Project #3018, NSF Award #DMI- Page 3.501.19413880)2 John S. Lamancusa, Jens E. Jorgensen, and José L. Zayas, The Learning Factory – A New
(S < 29) 31 (~57%) Neglected (29 <= S < 31) 12 (~22%) Reversed (31 <= S) 11 (~20%)The results above suggest that, for practicing engineers making decisions with data presented intabular form, targeting the consequences of variability is relatively difficult: Whereasengineering students readily targeted variability in scenarios with “everyday” variability (>90%of individuals targeted), in this pilot only ~57% of participants targeted variability correctly. It ispossible that the ~20% of participants with “reversed” responses were attempting to targetvariability, and that in a more deliberate setting (i.e., in the workplace), they would have
autism spectrum disorders during the transition to adulthood. J. Autism. Dev. Disord. 41 (5), 566–574. doi:10.1007/s10803-010-1070-312. Kouo, J. L., Hogan, A. E., Morton, S., & Gregorio, J. (2021). Supporting students with an autism spectrum disorder in engineering: K-12 and beyond. Journal of Science Education for Students with Disabilities. 24(11).13. Ehsan, H., & Cardella, M. E. (2019). Investigating Children with Autism’s Engagement in Engineering Practices: Problem Scoping (Fundamental). Proceedings of the ASEE Annual Conference & Exposition, 15027–15043.14. Steinbrenner, J. R., Hume, K., Odom, S. L., Morin, K. L., Nowell, S. W., Tomaszewski, B., Szendrey, S., McIntyre, N. S., Yücesoy-Özkan, S., & Savage, M
the NationalScience Foundation.References[1] D. F. Lohman, “Spatial Ability and G.” 1993.[2] K. S. McGrew, “CHC theory and the human cognitive abilities project: Standing on the shoulders of the giants of psychometric intelligence research,” Intelligence, vol. 37, no. 1, pp. 1–10, Jan. 2009, doi: 10.1016/j.intell.2008.08.004.[3] H. B. Yilmaz, “On the Development and Measurement of Spatial Ability,” International Electronic Journal of Elementary Education, vol. 1, no. 2, pp. 83–96, Mar. 2009.[4] C. Julià and J. Ò. Antolì, “Enhancing Spatial Ability and Mechanical Reasoning through a STEM Course,” International Journal of Technology and Design Education, vol. 28, no. 4, pp. 957–983, Dec. 2018.[5] M. Stieff and D. Uttal, “How
are based on a201 student sample from Engineering Technology Division at Wayne State University. It would be202 interesting to further validate the effectiveness of BIM education for improving students’203 communication skills in other engineering disciplines, programs, or institutions.204205 References206 [1] S. Bhattacharya and G. Pant, “Digital transformation in AECO industry: impending207 dilemma in the Indian context,” J. Organ. Change Manag., 2023.208 [2] B. Bradley, “Global BIM Survey: U.S. market is maturing as advances wake imaginations.”209 Accessed: Feb. 03, 2024. [Online]. Available: https://agacad.com/blog/global-bim-survey-u-210 s-market-is-maturing-as-advances-wake-imaginations211 [3] J. Du, D
. Calculating the value of the curl.Figure 8. Curl vectors superimposed on a user-created vector field.Divergence ExerciseThe purpose of the Divergence exercise is to demonstrate the concept of divergence of a vectorfield. The users enter the components of a vector field which are then plotted as shown in Figure10. The users are given a “control volume” whose location can be chosen by the users. Thepurpose of this “control volume” is to provide a means to visualize whether the vector field isconverging or diverging at a particular location. Once the users choose a point that they desire,one user is prompted for an exact calculation of the divergence at the control volume‟s location.If the user answers correctly, the program continues to the next round
number of universities beyond Oregon State University to develop evidence of the portability and generalizable use of the virtual laboratory instructional materials. Table 2 lists the institutions that have used the Virtual CVD laboratory remotely.Table 2. Summary of experimental activity of the Virtual CVD Laboratories outside Oregon State University Class Term Students Groups Runs Measurements Virtual Cost U Oregon Su 06 11 3 40 538 $240,350 U Oregon Su 07 10 3 57 610 $330,750 UC Berkeley S 07 25 25 96 8,980 $1,153,500
Session 3264 Case Study: Using a Neural Network to Identify Flaws during Ultrasonic Testing A. Kayabasi, G. S. Kohne and P. J. Coyne, Jr. Loyola College in Maryland Department of Electrical Engineering and Engineering Science Baltimore MD 21210-2699Abstract: A feed forward neural network with a single hidden layer was used to identify a series ofcylindrical samples based on the first ultrasonic echo. The simulated flaws were placed at varyingdistances directly in front of a 1 MHz broadband
UnitedNations Sustainable Development Goals (SDGs) (SDG 4, SDG 5, and SDG 10). Proceedings of the 2024 ASEE Gulf-Southwest Annual Conference West Texas A&M University, Canyon, TX Copyright 2024, American Society for Engineering Education 2Based on lessons from The Goal: A Process of Ongoing Improvement,1 it is important to firstidentify the goal of education and then to identify the best way(s) to reach that goal. Finally, thispaper considers the impacts of improving methods to meet the goal. In their book Investment inLearning, Bowen and Fincher assert that three primary goals of education are 1) practicalcompetence
theassessment of instructors, parents and other professional observers (one of the observers had a doctorate ineducation) during 2006-07. Table 1 Learning level (Basic, Intermediate, Advance), underlying STEMS areas (S, T, E, M), expected impact (Low, Normal,High), learner interest (Low, Normal, High), possible audience types (Families, Children, Adults, College Students, Teachers,Professionals, Underserved, Retired, Boy Scouts, Hobbyists and Explorers), and possible locations (Museum, Science &Technology Center, Community Center, Mall and Shopping Center, Library, Websites, After-School Locations). Gen. Learning STEM Expected Learner Audience Possible Unique Aspect Area
of growth mindsets than their White peers,yet they also reported lower levels of fixed mindsets [13]. Said differently, Ge et al.’s [13] cross-sectional study showed that White engineering students demonstrate a higher predispositiontowards a growth mindset and a higher predisposition towards endorsing a fixed view of theirabilities. An exploratory study aimed at understanding the relationship between students’engineering identity and mindsets longitudinally found that both a fixed and a growth mindsetwere positive predictors of identity [14]. However, the authors did acknowledge that there may bemoderating effects not considered in the model, such as course difficulty, that may also helpexplain the positive relationships [14]. The studies
. The use of accreditation panels thus provides another example of the way in whichknowledge is preserved by those in power and there is a need to involve people with a varietyof perspectives and experiences within accreditation panels [56].LOs are typically enforced by the structures and systems present within HE, for example byorganization of knowledges into distinct modules timetabled in isolation from one another.This can be considered to result in compartmentalized of knowledge. The formation of ‘silos’tends to restrict the use of knowledge to within specific domains and “limit(s) opportunitiesfor them (students) to learn about the strengths and limitations [of disciplines] in real-worldcontexts and multidisciplinary arenas” [62]. This, of
the percentage of thestudents who submitted each of the lab assignments, for one section of the lectures and onesection of the labs, with the same instructor. There was a total of 6 lab assignments during Fall2018 (F’18) and Spring 2019 (SP’19). Starting Fall 2019 (F’19), we introduced additional labassignments. In Table 1, we are providing the mapping of the labs used in F’18 and S’19, to thenew labs used in F’19, Spring 2020 (S’20), and Fall 2020 (F’20) for consistency. The labassignments are mapped based on the complexity of implemented designs, language constructsused, and level of tool skills needed. We will continue to use the names for new labs (1 - 8). Percentage of submitted labs
motivation and positive engagement [11], [28]-[30]. Onthe contrary, controlling teacher behaviors have been shown to lead to negative motivation typesand restricted engagement [31], [32]. Using structural modeling, Fortier et al. (1995) demonstratethe positive influence of perceived competence and self-determination on autonomousmotivations and academic performance [7]. Greene et al. (2004) illustrate linkages betweenautonomy support and self-efficacy, mastery goals, strategy use, and achievement [33]. Walkeret al.’s path model shows that self-efficacy and intrinsic motivation can predict meaningfulcognitive engagement, while extrinsic motivations predict shallow cognitive engagement [8].Although empirical research that directly links different