percent of the participants statedtheir sibling(s) did not have an influence on their decision to major in an engineering program.Fifty-four percent of the African American respondents and 40% of the Caucasian respondentsindicated their mother/female guardian had a strong positive influence on their choice of major.Thirty-one percent of the Caucasian respondents and 16.6% of the African Americanrespondents stated their mother/female guardian had a somewhat positive influence on theirdecision to enroll in an engineering major. Twenty-one percent of the Caucasian respondentsand 12.3% of the African American respondents felt that their mother/female guardian did nothave any influence on their choice of major.Fifty percent of the Caucasian
offering are moregregarious while students in the Spring 2019 offering are friendly yet reserved).AcknowledgementsThis work was supported in part by the National Science Foundation EPSCoR Program underNSF Award # OIA-1655740. Any Opinions, findings and conclusions or recommendationsexpressed in this material are those of the author(s) and do not necessarily reflect those of theNational Science Foundation. (http://scepscoridea.org/MADEinSC/acknowledgements.html).References[1] N. Thomas and R. Erdei, "Stemming stereotype threat: recruitment, retention, and degree attainment in STEM fields for undergraduates from underrepresented backgrounds," in 2018 CoNECD - The Collaborative Network for Engineering and Computing Diversity
reviewers for constructive comments.ReferencesAnderson, M. S., Horn, A. S., Risbey, K. R., Ronning, E. A., De Vries, R., & Martinson, B. C. (2007). What Do Mentoring and Training in the Responsible Conduct of Research Have To Do with Scientists’ Misbehavior? Findings from a National Survey of NIH-Funded Scientists. Academic Medicine, 82(9), 853–860.ASCE. (2017). Code of Ethics. Retrieved from https://www.asce.org/code-of-ethics/.Bachmann, B. (2017). Ethical Leadership in Organizations. New York, NY. Springer.Bedi, A., Alpaslan, C. M., & Green, S. (2016). A Meta-analytic Review of Ethical Leadership Outcomes and Moderators. Journal of Business Ethics, 139(3), 517–536.Brown, M. E., Treviño, L. K., & Harrison, D. A. (2005
theAPVAWT capstone team has passed will be introduced to show how the engineering students ofthe team design and build the APVAWT system with the Liberty art students. 2.1 Decision Gate 1 – Stakeholder RequirementsThe 1st decision gate is to identify and confirm stakeholder requirements that guide the capstoneteam in understanding what is needed to be accomplished for the project and the class. Here,stakeholders represent all entities who are involved in this project: the capstone team, theclient(s), and the class instructor. Table 1 shows stakeholder requirements the team presentedand is required to fulfill. Table 1 – Stakeholder Requirements for Design and Construction of the APVAWT Task ID Name Description
complicated virtual environments. It is uncertain that the grant program will continue to offerfree credits in the future. Third, students create their own accounts and therefore usermanagement is a problem.In the future, we plan to develop more labs on commercial, public cloud systems and use VirtualPrivate Network (VPN) to connect students’ virtual machines with a central server to providebetter support and monitoring when needed. We are also considering integrating automaticassessment scripts through the central server on the public cloud to provide immediate feedback,which has been done successfully in some labs on our in-house, cloud-based systems.REFERENCES[1] D. Puthal, B. P. S. Sahoo, S. Mishra and S. Swain, "Cloud Computing Features, Issues
Annual Conference and Exposition, Pittsburgh, Pennsylvania. 3. Sheppard, S., Gilmartin, S., Chen, H. L., Donaldson, K., Lichtenstein, G., Eris, O., . . . Toye, G. (2010). Exploring the Engineering Student Experience: Findings from the Academic Pathways of People Learning Engineering Survey (APPLES). TR-10-01. 4. Buse, K. R. (2009). Why they stay: The ideal selves of persistent women engineers. (Doctoral Dissertation), Case Western University, Cleveland, OH. 5. Byars-Winston, A., Estrada, Y., Howard, C., Davis, D., & Zalapa, J. (2010). Influence of social cognitive and ethnic variables on academic goals of underrepresented students in science and engineering: a multiple-groups analysis. Journal of
Technology.References1. E. Barnes, Lecture Notes on Computational Methods, Georgia Institute of Technol- ogy.2. A. Caprara, M. Fischetti and P. Toth, A heuristic method for the set covering problem, Operations Research 47 (1999) 730–743.3. A. Caprara, M. Fischetti and P. Toth, Algorithms for the set covering problem, Annals of Operations Research 98 (2000) 353–371.4. S. Chopra, E. Erdem, E. Kim and S. Shim, Column generation approach to the convex recoloring problem on a tree, Modeling and Optimization: Theory and Ap- plications (MOPTA, Bethlehem, PA, USA, August 2016), Volume 213 of the series Springer Proceedings in Mathematics & Statistics, pp 39-53, 2017.5. S. Chopra, B. Filipecki, K. Lee, M. Ryu, S. Shim and M. Van Vyve, The convex
(PCAST). “Transformation and opportunity: The future of the U. S. research enterprise,” Washington, DC: PCAST, 2012.[2] M. W. Ohland, and E. R. Crockett. “Creating a catalog and meta-analysis of freshman programs for engineering students: Part 1: Summer bridge programs,” in Proceedings of the 2002 American Society for Engineering Education Annual Conference & Exposition. Montreal, Canada: ASEE, June 16-19, 2002.[3] B. P. An. “The Impact of Dual Enrollment on College Degree Attainment Do Low-SES Students Benefit?” Educational Evaluation and Policy Analysis, 0162373712461933, 2012.[4] A. Gamoran, A. C. Porter, J. Smithson, and P. A. White. “Upgrading high school mathematics instruction
in the field studies reported here. Any opinions,findings, and conclusions or recommendations expressed in this material are those of theauthor(s) and do not necessarily reflect the views of the National Science Foundation.References1. Arnold, A. (1999). Retention and persistence in postsecondary education: A summation of research studies. Texas Guaranteed Student Loan Corporation, 5.2. Chang, M. J., Sharkness, J., Hurtado, S., & Newman, C. B. (2014). What matters in college for retaining aspiring scientists and engineers from underrepresented racial groups. Journal of Research in Science Teaching, 51(5), 555-580.3. Hayes, R. Q., Whalen, S. K., & Cannon, B. (2009). Csrde stem retention report, 2008–2009. Center for
the National Science Foundation under Grant No.1148806. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the author(s) and do not necessarily reflect the views of the National ScienceFoundation.References[1] C. A. Wolters, “Self-regulated learning and college students’ regulation of motivation.,” J. Educ. Psychol., vol. 90, no. 2, pp. 224–235, 1998.[2] J. H. Flavell, “Metacognition and cognitive monitoring: A new area of cognitive– developmental inquiry,” Am. Psychol., vol. 34, no. 10, pp. 906–911, 1979.[3] P. Pintrich, “The role of metacognitive knowledge in learning, teaching, and assessing,” Theory Pract., vol. 41, no. 4, pp. 231–236, 2002.[4] O. Lawanto, “Students
affords us thechance to change our curriculum, making improvements based on teacher and student feedback;we will continue to do so, analyzing forthcoming results to gauge the success of the curriculumin changing student perceptions. The continuation of the project presents further opportunities toimmerse ourselves in student design experiences and uncover features that are influential forchanging student perceptions about engineering.AcknowledgementsThis materials is based upon work supported by the National Science Foundation under GrantNo. 1513175-DRL.References1. McGrath, E., Sayres, J., Lowes, S., & Lin, P. (2008, October). Underwater lego robotics as the vehicle to engage students in STEM: The build it project's first year of
in relation toengineering-specific domains of thinking, such as Testing and Design Requirements (criteria andconstraints). Future studies can expand this assessment instrument by testing it in other middleschool classrooms, and they can validate later iterations of this instrument. References[1] Manz, E. (2015). Representing student argumentation as functionally emergent from scientific activity. Reviewof Educational Research, 85(4), 553-590.[2] Sampson, V., & Blanchard, M. R. (2012). Science teachers and scientific argumentation: Trends in views andpractice. Journal of Research in Science Teaching, 49(9), 1122-1148.[3] Ryu, S., & Sandoval, W. A. (2012). Improvement to elementary
. Kinetics principle(s) and/or kinematics you Kinetics principle(s) and/or kinematics you would use: would use: 3. During a hammer thrower’s practice swings, the 4. Knowing that crank AB rotates about Point A 7.1-kg head A of the hammer revolves at a constant with a constant angular velocity of 900 rpm speed v in a horizontal circle as shown. If = 0.93 clockwise, determine the acceleration of the piston m and = 60, determine the tension in wire BC. P when = 30. Kinetics principle(s) and/or kinematics you would use: Kinetics principle(s) and/or kinematics you
supportwas provided by the Role of Reflection in SoTL Faculty Learning Community program throughthe Indiana University-Purdue University Indianapolis Center for Teaching and Learning.References[1] A. R. Carberry, M. Siniawski, S. A. Atwood, and H. A. Diefes-Dux, “Best Practices for Using Standards-based Grading in Engineering Courses,” presented at the 2016 ASEE Annual Conference & Exposition, New Orleans, LA, USA, Jun. 26-29, 2016.[2] S. L. Post, “Standards-Based Grading in a Thermodynamics Course,” Int. J. Eng. Pedagogy, vol. 7, no. 1, pp. 173–181, Jan. 2017.[3] L. Nilson, Specifications Grading: Restoring Rigor, Motivating Students, and Saving Faculty Time. Sterling, VA: Stylus, 2014.[4] J. J. Polczynski and L. E. Shirland
completed using challenge activities. For spreadsheets, challengeactivities allow students to enter formulas, functions, and calculated values to test their strengthsusing spreadsheets. With hundreds of numeric combinations on many problems, students canrepeat a new version of any question until they compute correct answer(s). With over 100 differentquestions, the most difficult spreadsheet skills can be identified from students’ success. Thenumber of attempts before correct and total attempts will complement the percent correct to givemultiple metrics. Over 9,000 questions were attempted by the 2018 cohort and will be analyzedhere. Responses from the 2019 cohort will be compared in the conference presentation.Challenge activity scores varied
program, 40% of the population is comprised of women, a stark contrast to thesmall percentage of women represented in more traditional engineering programs. We felt thatinterviewing a proportionally larger number of women in a context different than traditionalengineering programs might provide insight into their construction, understanding, and valuingof knowledge(s). We acknowledge that this might risk having the male student having tokenrepresentation, and a follow-up study and analysis plans to address this gender imbalance.Data Collection: Participants were recruited from the AME capstone course and were chosenbecause the course is only taken by students approaching graduation; we felt that these studentshad ample experience with the program
projects were well balanced. On average, the studentsshared that the biological concepts were a bit more difficult than the mechanical engineeringconcepts (65% v/s 62.5%). Standardized pre-/post-summer experience surveys were also usedto assess the impact of the course modifications on the participants’ scientific self-efficacy andimpression of research (Survey of Undergraduate Research Experiences, SURE) [18]. Theresults from the SURE survey at the end of the Summer 2018 show that out of the 21comparative learning gains, the EGGN 122 freshmen and sophomore were higher than thenational average in 11 and lower than the average in 5 gains. In response to the survey results,the last semester of the program involved improving the students’ preparation
. The minimumparking space length can be obtained from the solution of θ, which is Lmin = 104 cm. Lpmin thenhas to be 94cm. From the result that S+ Lp = 138 cm, and choosing Lp =100 cm > 94 cm, one canobtain S = 38 cm. The rear sensor should read a distance around dr = 30 cm at the turning point P.To avoid accident, the parking space length is set as L = 110 cm > 104 cm and is then used in thecriteria for parking space finding in Eq. (1). 9 Figure 7. The picture of the modified RC toy car.The toy car does stops after finding a proper parking space and start backing up to park.However the parked positions are not at the theoretical location and are also not identical
). at 4. Morozov, E. Making it. The New Yorker (2014). at 5. Foster, T. Welcome to the maker-industrial revolution. Popular Science (2015). at 6. Chachra, D. Why I am not a maker. The Atlantic (2015). at 7. Moldofsky, K. The maker mom. (2015). at 8. Hatch, M. The maker manifesto. McGraw Hill Education (2014). at 9. Martinez, S. & Stager, G. Invent to learn: Making, tinkering, and engineering in the classroom. (Constructing modern knowledge press, 2013).10. Make. Maker Pro. (2014).11. Makerspace North. Makerspace north. (2014). at 12. The British Council. Maker library network. at 13. Chaihuo Maker Space. Shenzhen Maker Faire. (2015). at 14. Seeed. First open hardware gathering in
ontological framework. Lastly, upon examination of the cognitive processes K-12 students’ employ duringdesigning, few coding schemes actually are informed by educational philosophies, learningtheory, and STEM educational reform. Nor, do they indicate how students can be better equippedto learn and develop their cognition while designing. As researchers and educators moveforward, examining decision making strategies as well as normative models may provideadditional relevance to Design Cognition in terms of how students are performing in relation toeducational philosophies, learning theory, and STEM Educational reform. ReferencesAdams, R. S., Turn, J., & Atman, C. Y. (2003). Educating effective
rubrics and exemplars, and an assessment tool is being developed to provide tuningfeedback in order to refine the laboratories in future years.References:1. Bartolo, L. et.al (2008), The Future of Materials Science and Materials EngineeringEducation, Workshop on Materials Science and Materials Engineering Education, NSF,September 2008.2. Olson, G. B. (2000). Designing a new material world. Science, 288(5468), 993-998.3. Feisel, L. D., & Rosa, A. J. (2005). The role of the laboratory in undergraduate engineeringeducation. Journal of Engineering Education, 94(1), 121-130.4. Feisel, L.D., and Peterson, G.D.,(2002). The Challenge of the Laboratory in EngineeringEducation,” Journal of Engineering Education, 91(4), 2002, pp. 367–3685. Edward, N. S
forengineering students. Not only would this improve the normality of the data and decrease theneed for additional analytical processes that will reduce the statistical power, but it would alsoallow for improved understanding of student learning and improved assessment of curriculumimpact on student abilities.Funding and AcknowledgementsBenjamin Call is funded by Utah State University’s Presidential Doctoral Research Fellowship.We would like to thank all of the students who participated in the study.References1. Halpern, D. F., & Collaer, M. L. (2005). The Cambridge Handbook of Visuospatial Thinking. Cambridge: Cambridge University Press.2. Sorby, S., Casey, B., Veurink, N., & Dulaney, A. (2013). The role of spatial training in
expressed herein are solely the authors’.REFERENCES CITED 1 Lighthall, A. (2012). Ten things you should know about today’s student veteran. Thought & Action: The NEA Higher Education Journal, 80-89. Available at http://www.nea.org/home/53407.htm2 Lord, S., Kramer, K., Olson, R., Karsada, M., Hayhurst, D., Rajala, S., … & Soldan, D. (2011). Special Session – Attracting and supporting military veterans to engineering programs. Proceedings of the 2011 Frontiers in Education Conference, Rapid City, SD, October.3 U.S. Department of Veterans Affairs. (2012). Annual benefits report fiscal year 2012. Available at
-scientificchallenge: Energy production. It is hoped that students learning about bioenergy willhave a deeper understanding of energy issues facing the planet and be prepared to be apart of solving these issues in the future.ReferencesBittle, S., Rochkind, J., & Ott, A. (2009). The Energy Learning Curve. Retrieved 8/15/14 from: http://www.publicagenda.org/files/energy_learning_curve.pdfBolte, C. (2009). Enhancing pupils’ abilities to properly judge and make informed decisions in the field of renewable energy sources. In Proceedings of the Australasian Science Education Research Association (pp. 149–154).Chen, K. L., Huang, S. H., & Liu, S. Y. (2013). Devising a framework for energy education in Taiwan
. Page 26.556.1 c American Society for Engineering Education, 2015 DNA Extraction Using Engineering Design: A STEM Integration Unit (Curriculum Exchange) Target Grade Level: 6-8 En gr TEA MSE n gin eerin g t o Tran sform t h e E d ucat ion of An aly sis, Measuremen t , & Scien ce Authors and Contact: Corey A. Mathis Tamara J. Moore S. Selcen Guzey Purdue University Purdue University Purdue University mathisc@purdue.edu
Engineering Initiative I. An Education Outreach Manual in TissueEngineering. In: Pittsburg Uo, editor. 2010.9. Birol G, Liu S, Smith D, Hirsch P Educational Modules in Tissue Engineering Based onthe “How People Learn” Framework. Bioscience Education E-journal. 2006;7.10. Bhatia S. A disease-centered approach to biomaterials education and medical devicedesign. 33rd Annual International Conference of the IEEE EMBS; Boston, Massachusetts2011.p. 3617-9.11. Reichert W, Harris TR, Lemmons J, Mikos AG, Puleo DA, Schoen FJ, Temenoff JS.2011 Panel on developing a biomaterials curriculum. Journal of Biomedical Materials ResearchPart A. 2011;100A:802-16.12. Feldman D, Gombotz WR. Biomaterials Education: An academic and industrialviewpoint
; Geophysical Division, Science and Technology Directorate.[2] Stephen G. Katsinas, "America's Rural Community Colleges: Demographics, Challenges, and Opportunities", (a Briefing on Rural Community Colleges for the U.S. Department of Education), Washington, D.C. (invited talk). February 24, 2010.[3] K. Koscher, A. Czeskis, F. Roesner, S. Patel, T. Kohno, S. Checkoway, D. McCoy, B. Kantor, D. Anderson,H. Shacham, and S. Savage. “Experimental security analysis of a modern automobile”, In Proceedings of the 31st IEEE Symposium on Security and Privacy, May 2010.[4] Elinor Mills, “Hackers broke into FAA air traffic control system”, The Wall Street Journal, page A6, 2009.[5] Vanessa Fuhrmans, “Virus Attacks Siemens Plant-Control Systems
of Applied Psychology, 97(4), 890–900.5 Côté, S. (2014). Emotional Intelligence in Organizations. Annual Review of Organizational Psychology andOrganization Behavior, 1, 459–488.6 Frye, C. M., Bennett, R., & Caldwell, S. (2006). Team Emotional Intelligence and Team Interpersonal ProcessEffectiveness. American Journal of Business, 21(1), 49–58.7 Gibbs, N. (1995, October 2). EMOTIONAL INTELLIGENCE: THE EQ FACTOR. Time, Cover story.8 IRR113-3. (2009, January 1). Alignment During Pre-Project Planning: A Key to Project Success, Version 2.1.Retrieved January 1, 2013, from https://www.construction-institute.org/scriptcontent/more/ir113_3_v2_more.cfm9 Jordan, P. J., Ashkanasy, N. M., Härtel, C. E. J., & Hooper, G. S. (2002). Workgroup
questionnaire.Self-Rating of Engineering Leadership Skills. The second part of the survey included a skillsquestionnaire that was developed based on the survey instrument created by Ahn et al.3. Ahnet al.’s survey contained 45 items specifically designed to measure outcomes in engineeringundergraduate students related to leadership, adaptability to change, and synthesis abilities3.Twenty of these items, principally the ones directly related to leadership, were chosen for theskills questionnaire (e.g. I independently initiate new individual or team projects and Imanage and organize my time efficiently). The participants were asked to rank the extent towhich they embodied each statement on a scale of one to four (1=rarely, 2=sometimes,3=frequently and 4
). Page 26.1430.4 Table 1 – Coding scheme description and examples.Domain Category Description Example Refers to writing or presentation of the design “There are grammatical error[s] Communication work. throughout the paper.” Explicitly refers to one of the design concepts Design Concepts taught in class by using terminology taught in “The goal could [be] more specific.” class.Substance Refers