interested who transferred to Virginia Techfrom regional community colleges. To date we have interviewed 28 individuals, including fivefocus group participants. The pool includes 11 women, one (male) underrepresented student,seven first-generation college students, and 14 students who transferred from communitycolleges.AcknowledgementsThis material is based upon work supported by the National Science Foundation under GrantNumber 1734834. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation. We also wish to thank Ms. Claudia Desimone for help with data collection.References[1] M. Boynton, C. A. Carrico, H. M
the operationalization of LMMI in thecontext of EML which will inform future curriculum development, particularly for large first-year engineering design and project-based learning courses.References[1] A. J. Dutson, R. H. Todd, S. P. Magleby, and C. D. Sorensen, “A review of literature on teaching engineering design through project-oriented capstone courses,” J. Eng. Educ., vol. 86, no. 1, pp. 17–28, 1997.[2] D. Clive et al., “Engineering design thinking, teaching, and learning,” J. Eng. Educ., no. January, pp. 103–120, 2005.[3] C. Charyton and J. A. Merrill, “Assessing general creativity and creative engineering design in first year engineering students,” J. Eng. Educ., vol. 98, no. 2, pp. 145–156, 2009.[4
-1711533. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.References[1] Paulson, D. R., & Faust, J. L. (1988). Active and Cooperative Learning. Los Angeles: California State University, Los Angeles. Retrieved from http://www.calstatela.edu/dept/chem/chem2/Active/index.htm[2] Prince, M. (2004). Does active learning work? A review of the research. Journal of Engineering Education, 93(3), 223-231.[3] Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics
– think of trying to gather more new contacts than your roommate. In projects,we will continue to emphasize how all students have unique talents to bring to their teams.References[1] T. Rath, StrengthsFinder 2.0, New York: Gallup Press, 2007.[2] M. L. Loughry, M. W. Ohland and D. J. Woehr, "Assessing teamwork skills for assurance of learning using CATME team tools," Journal of Marketing Education, vol. 36, pp. 5-19, 2013.[3] S. Zemke and D. Elger, "Curricular elements that promote professional behavior in a design class," in ASEE Annual Conference Proceedings, Chicago, 2006.[4] J. Asplund, S. Agrawal, T. Hodges, J. Harter and S. J. Lopez, "The Clifton StrengthsFinder 2.0 Technical Report," Gallup Inc., Washington DC, 2014.[5] S. J
purpose of this paper is to recommend adapting new pedagogical methods to theaccepted topics in an introductory probability and statistics course for engineeringundergraduates—methods that better match the learning characteristics of Millennial students inour courses. In a nutshell, those characteristics may be summarized as: (1) They want relevanceto their major, and future engineering career; (2) They want rationale (for the textbook selected,and for specific course policies and assignments); (3) They revel in technology (to collect data,compute, communicate, and multi-task); (4) They want a relaxed, hands-on environment; (5)They prefer instructors who rotate among several classroom delivery methods.Considering the “Five R‟s” learning
duein class the following week. Two midterm exams and one final exam were given, and studentscompleted two Matlab projects in groups of three.ParticipantsThe course was taught by the same instructor in both terms considered in this study. Theinstructor was a full-time faculty member at the university with over 10 years of teachingexperience. S/he had taught the DTSS course discussed here several times prior to the two termsin question. Student participants in the study were predominantly male, junior or senior students,majoring in electrical engineering. The majority of students were also domestic and in-state.However, they varied greatly in GPA. The students were also diverse in race/ethnicity with overhalf being either White or Asian. The
definition of mission engineering is the deliberate planning, analyzing,organizing, and integrating of current and emerging operational and system capabilities toachieve desired mission effects.Mission engineering applies the mission context to complicated and complex system(s) ofsystems [2]. Most current systems engineering practices do not fully address the uniquecharacteristics of mission engineering, addressing the end-to-end mission as the ‘system’ andextending further beyond data exchange between the individual systems for cross-cuttingfunctions, controls, and trades across the systems.Mission engineering differs from the established term of mission analysis in that the latter onlyaddresses examination of current operational and system
: “[t]here has not been any official training or demonstration of laboratory protocols atthis point.” However, as time progressed, BEST Fellows increasingly agreed that their learning wasbeing adequately supported by their lab experience. For example, the same individual with thenegative experience in the second week reported that there was nothing that hindered his/herlearning in the sixth week. BEST Fellows also rated their experience in the Friday workshop positively. Moreover,Fellows were in agreement that working together during these workshops was helpful. Whenasked what aspects of the workshop promoted their learning, Fellows responded: “[s]haring outexperiences and open group discussions”, “[t]he readings and paired
Pendulum System,” IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Vol. 3, pp. 1804–1809, 2009. 2018 ASEE Mid-Atlantic Spring Conference, April 6-7, 2018 – University of the District of Columbia2 K. Lai, Jin Xiao, Xiaoguang Hu, Jianxin Fan, Bing Wu, “Modeling and Control for Stability and Rotation Velocity of a Rotary Inverted Pendulum,” 2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA), 2015, pp. 955–960.3 Y. Kim, S. H. Kim, and Y. K. Kwak, “Dynamic analysis of a nonholonomic two-wheeled inverted pendulum robot,” Journal of Intelligent and Robotic Systems: Theory and Applications, Vol. 44, No. 1, 2005, pp. 25– 46.4 S. Awtar, C. Bernard, N
. 28 References[i]Bennett,J.&Hogarth,S.(2009).Wouldyouwanttotalktoascientistataparty?Highschool students'attitudestoschoolscienceandtoscience.InternationalJournalofScience Education,31(14),1975–1998.[ii]Britner,S.L.(2008).Motivationinhighschoolsciencestudents:acomparisonofgender differencesinlife,physical,andearthscienceclasses.JournalofResearchinScience Teaching,45(8),955–970.[iii]Brotman,J.S.&Moore,F.M.(2008).Girlsandscience:areviewoffourthemesinthe scienceeducationliterature.JournalofResearchinScienceTeaching,45(9),971–1002.[iv]Miller,P.H.,Blessing,J.S.,&Schwarz,S.(2006).Genderdifferencesinhigh-school
- ing Education and the Algae Biomass Organization. Dr. Shuman served as Chair for the ASEE Energy Conversion and Conservation Division last year. She received a Dipl.Ing. degree in mechanical engineering from Belgrade University in 1992, an M.S.M.E. from the University of Washington in 1994 and a Ph.D. from the University of Washington in 2000.Dr. Gregory Mason, Seattle University Gregory S. Mason was born and raised in Spokane Washington. He received the B.S.M.E. degree from Gonzaga University in 1983, the M.S.M.E. degree in manufacturing automation from Georgia Institute of Technology in 1984 and the Ph.D. degree in mechanical engineering, specializing in multi-rate digital controls, from the University of
?" Paper presented at the 2016 IEEE Frontiers in Education Conference (FIE). Erie, PA.Dick, T. P., & Rallis, S. F. (1991). Factors and influences on high school students’ career choices. Journal of Research in Mathematics Education, 22(4), 281 - 292.Garriott, P. O., Raque-Bogdan, T. L., Zoma, L., Mackie-Hernandez, D., & Lavin, K. (2016). Social cognitive predictors of Mexican American high school students’ math/science career goals. Journal of Career Development, 44, 77-90. doi:10.1177/0894845316633860Gillen, A. L., Kinoshita, T., Knight, D., Grohs, J., Carrico, C., Matusovich, H. M., … Bradburn, I. (2017). WIP: Gatekeepers to broadening participation in engineering: Investigating variation across high
. Sweeney, S. Nolen, M. Koretsky, M. Bothwell, D. Montfort, S. Nolen and S. Davis. “Re-situating community and learning in an engineering school.” Proceedings of the ASEE Annual Conference and Exposition, Columbus, OH, 2017, https://peer.asee.org/27753.[3] S. Lord, D. Rover, N. Kellam, N. Salzman, E. Berger, E. Ingram and J. Sweeney. “Work-In-Progress: Talking about a revolution - overview of NSF RED projects”. Proceedings of the ASEE Annual Conference and Exposition, Columbus, OH, 2017, https://peer.asee.org/28903.[4] S. Lord, J. London, N. Salzman, B. Sukumaran, T. Martin, A. Maciejewski, J. LeDoux and J. Sweeney. “Work-In-Progress: Progress of the NSF RED Revolution”. Paper and panel
. W., & Pizzico, M. C., & Levy, B., & Nagel, R. L., & Linsey, J. S., & Talley, K. G., & Forest, C. R., & Newstetter, W. C. (2015, June), A Review of University Maker Spaces, Proceedings from 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.234422. Tomko, M., & Nagel, R. L., & Aleman, M. W., & Newstetter, W. C., & Linsey, J. S. (2017, June), Toward Understanding the Design Self-Efficacy Impact of Makerspaces and Access Limitations, Proceedings from 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. https://peer.asee.org/277613. Penney, M. F., & Watkins, J. D., & Levy, B., & Linsey, J. S., & Nagel, R. L., & Newstetter, W. C
Course for First-year Engineering Students in Microsystems and Nanomaterials. Proceedings of the 2013 ASEE Annual Conference and Exposition, Atlanta, Georgia.Lambeth, M. C., McCullough, M. B., & Aschenbrenner, M. H. R. (2015). Creating a Pipeline into Biomedical Engineering. Proceedings of the 2015 ASEE Annual Conference and Exposition, Seattle, Washington.Madihally, S., & Maase, E. (2006). Introducing Biomedical And Biochemical Engineering For K 12 Students. Proceedings of the 2006 ASEE Annual Conference & Exposition, Chicago, Illinois.Martinez, A. W., Phillips, S. T., Whitesides, G. M., & Carrilho, E. (2010). Diagnostics for the developing world: microfluidic paper-based analytical devices
disengagement.ReferencesBardi, A., & Schwartz, S. H. (2003). “Values and behavior: Strength and structure of relations,” Personality and Social Psychology Bulletin, vol. 29, no. 10, pp. 1207-1220, 2003.Boucher, K. L., Fuesting, M. A., Diekman, A. B. & Murphy, M. C. (2017). “Can I Work with and Help Others in This Field? How Communal Goals Influence Interest and Participation in STEM Fields,” Frontiers in Psychology, vol. 31, May 2017.Brown, E. R., Smith, J. L., Thoman, D. B., Allen, J. & Muragishi, G. (2015b). “From bench to bedside: A communal utility value intervention to enhance students’ science motivation,” Journal of Educational Psychology, vol. 107, no. 4, pp. 1116-1135, Nov. 1, 2015.Cheryan, S., Plaut, V. C
which isgoing to observe in frequency domain with the interval Sv = [−fv , fv ] from1-2. Given a timeseries that can regard as a realization of a discrete sequence x(1), x(2), x(3), … , x(N)describedby (2), the periodogram with this sequence in2,9 is defined in the frequency domain as: Δt 2 S(f) = [∑N t=1 x(t)e −j2πftΔt ] (4) NTherefore, the total S(f) is extended as
fundamental S&E research. ” PROCESS IDEAS Mid-scale Research NSF 2026Infrastructure Growing NSF INCLUDES: Convergence Enhancing STEM Research at NSF through Diversity and Inclusion FY 2018 Budget NSF FY18 Budget Proposals (% change from FY17 Enacted) Under the new budget caps, on February 12th
thatacademic preparation is typically not one of the main reasons for attrition 4,5. In other words, moststudents who leave academia choose to leave because of their own personal decision, not becausethey failed qualifying exams or are doing poorly in their courses 5–7. Indeed, Barnes et al.’s 8,9studies of graduate attrition showed that the attributions that professors give for their students thatleave are different than the rationale that the corresponding non-completing students give forleaving. The misalignment, misunderstanding, or attribution bias that may exist (from both parties)is worthy of study and is likely due to the issues that have arisen with sampling a sensitivepopulation.Further, most attrition literature takes a sociological view of
otheractivities. By practicing what you teach, you can efficiently accomplish the teaching,scholarship, and service goals necessary for promotion and tenure and have a fruitful andenjoyable career. Reference List[1] R. Brent, R. Felder, S. Rajala, J. Gilligan and G. Lee, "New faculty 101: an orientation to theprofession [engineering teacher training]," 31st Annual Frontiers in Education Conference.Impact on Engineering and Science Education. Conference Proceedings (Cat. No.01CH37193),Reno, NV, 2001, pp. S3B-1-3 vol.3. doi: 10.1109/FIE.2001.964046 [Accessed Jan. 11, 2018].[2] C. Lucas, J. Murry, “Teaching: Lectures and Discussion,” in New Faculty. New York:Palgrave Macmillan, 2011, pp. 39-63.[3] J. Pedersen, G
models, statewide pre-college math initiatives, teacher and faculty professional development programs, and S-STEM pro- grams.Ms. Olivia W. Murch, Purdue University Senior at Purdue University pursuing a Bachelor of Science degree in Biological, Food Process, Engi- neering. Currently conducting research under Dr. Ferguson through Engineering Education.Dr. Daniel M. Ferguson, Purdue University, West Lafayette (College of Engineering) Daniel M. Ferguson is CATME Managing Director and a research associate at Purdue University. Prior to coming to Purdue he was Assistant Professor of Entrepreneurship at Ohio Northern University. Before assuming that position he was Associate Director of the Inter-Professional Studies
code for creation and analysis of a cam profile.%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%Program Name: CamAnalysis%%Program Description: Analyzes and Creates Cam Profile%%Inputs: Number of Zones and the Parametersassociated with% each%%Outputs: S,V,A,J Curves, Force, Power, Torque,Pressure Angle,% and Cam Profile Plots. Tabular Data Sets.Max Values.%%Date Created: 11-5-2016%%Revisions:%%0) 11-5-2016 Creation%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%clearclc%Parameters%s_harmonic = @(h,theta,Beta,Beta_time) h/2*(1-cos(pi*theta/Beta));v_harmonic = @(h,theta,Beta,Beta_time)pi*h/2/Beta_time
stereotypes regarding AfricanAmericans academic capabilities, their numerical majority status within the HBCU context actsas a buffer enabling them to perceive their racial and professional identity as compatible andintegrated. On the contrary, the numerical minority status of African American engineeringstudents in PWI exacerbates their vulnerability to feel threatened by the negative stereotypesabout their group. Even as they struggle to maintain a positive ethnic identity, they question thecompatibility between their ethnic and professional identities. As Du Bois states, it is the tensionthat impedes “fluid participation in Black world(s) and white world(s)”. It is for this reason thatAfrican American engineering students in PWIs may struggle more
Career Guidance Short- & Long-Term Goals Parent & Family STUDENT-SPECIFIC BELIEFS Encouragement of activities Activity Choice & Expectations for Student s Opportunities to learn various Engagement Achievement skills Performance Specific Socialization Goals Reinforcement Patterns Perceptions of: Other Communications of Beliefs -- Student s Abilities -- Value of Various Skills -- Student s interest
), white board(s),projector(s), and printer(s). The author was the professor of record and independently designedthe course based on Purdue University CLOOs. In course planning and preparation, theinstructor adopted a learning-centered paradigm, while using a Learning Management System(LMS) (i.e., Blackboard) for course organization, file sharing, assignment posting/submission,grading, and testing. The instructor’s goal was to create a learning environment in which studentscould learn to restructure the new information and their prior knowledge into new knowledgeabout the content, and practice using it. Course design included a combination of mini/bridginglectures (as needed), readings, group discussions, exams, assignments, and a team project
Group 2 identified by applying the separation criteria RV249 and RV242). Note that while eachof these separation criteria identifies distinct groups, the group characteristics are very different. (a) (b) (c) Figure 3: For course 1’s top two separation criteria (RV249 and RV242 shown in (a) and (c), respectively), the response pattern statistics for the applied science course result in distinct response groups (labeled Group 1 and Group 2, matching the labels from Figure 2). The dimensions that are unaffected by the criteria (i.e., personal interest and university application for RV249; fit with lifestyle for RV242) remain consistent (within
and Their Pedagogical AssessmentAbstractImparting real world experiences in the classroom for a software verification and validation(S/W V&V) course is typically a challenge due to lack of effective Active Learning Tools(ALTs). At Robert Morris University (RMU, the author’s institution), this educational resourcegap has been addressed by developing several ALTs in the form of class exercises, case studies,and case study videos that were created by collaborating with the academia and industrialprofessionals. Through this three-year work 20 delivery hours of case studies, 18 delivery hoursof exercises and 6 delivery hours of role play videos totaling 44 delivery hours of Software V&Vcourse materials have been developed. The developed
engineering. 10References[1] E. Godfrey and L. Parker, “Mapping the Cultural Landscape in Engineering Education,” J. Eng. Educ., vol. 99, pp. 5–22, 2010.[2] T. McCarty and T. S. Lee, “Critical culturally sustaining/revitalizing pedagogy and Indigenous educational sovereignty,” Harvard Educ. Rev., vol. 84, no. 1, pp. 101–124, 2014.[3] H. S. Alim, “Critical Hip-Hop Language Pedagogies: Combat, Consciousness, and the Cultural Politics of Communication,” J. Lang. Identity Educ., vol. 6, no. 2, pp. 161–176, 2007.[4] J. Irizarry, The Latinization of U.S. Schools: Successful Teaching and Learning in Shifting Cultural Contexts. Routledge, 2015.[5] V. Kinloch, Harlem on Our Minds
teacher professionaldevelopment experience may trickle down to impact student self-efficacy and interest.Fortunately, our research is ongoing with the results of these implementation changes remainingto be seen.AcknowledgmentThis material was supported by the National Science Foundation under Grant DRL-1513175.References[1] National Science Board, "Science and engineering indicators digest 2012," Author, Arlington, VA,2012.[2] K. D. Welde, S. Laursen, and H. Thiry, "Women in science, technology, engineering and math (STEM)," Sociologists for Women in Society, University of Kansas, Lawrence, KS,2007.[3] P. M. Sadler, G. Sonnert, Z. Hazari, and R. Tai, "Stability and volatility of STEM career interest in high school
experiencescontributed to understanding how we might think to make the teaching of engineering, andspecifically problem definition, in K-12 settings more inclusive. Overall, these findings add tothe growing conversation inclusive classroom environments, that make more explicit connectionbetween youths’ out of school knowledge and practices in school settings.Works Cited[1] S. Sismondo, An Introduction to Science and Technology Studies, 2 edition. Chichester, West Sussex, U.K. ; Malden, MA: Wiley-Blackwell, 2009.[2] G. Goggin, Cell Phone Culture: Mobile Technology in Everyday Life. Routledge, 2012.[3] B. Latour and S. Woolgar, Laboratory Life: The Social Construction of Scientific Facts. Sage, 1986.[4] C. L. Dym, A. M. Agogino, O. Eris, D. D. Frey, and L