my protégé. And she started getting a masters in nursing. So we were like going, who's gonna finish first?”Nathan’s wife encouraged him to pursue an advanced degree as she said, “…hey look, you should go forward to great opportunities. So I decided to do it and never looked back since then. It was a great experience. Great professors and yeah, that's pretty much it.”Alex reflected on who had a role in directing him toward the engineering field and mentioned hismother: “It was maybe, her, pushing me to do something else [other than her profession], you know, turned me more toward engineering.”Another participant said it like this “... they [my family] don't truly understand what I go through as a PhD
activitiespromoted ‘connectedness’ among SCOAM students and motivated students to work hard andcomplete their coursework.Small Group Activities and Monthly MeetingsStudents were asked to participate in 3 small group activities each semester. In cross-generational groups (i.e., freshman, upper classman, graduate student), students were asked toseek out and attend activities on campus or create their own social event. The purpose ofattendance at these activities was to encourage relationships between members of the cohort andto foster a sense of ‘belonging.’ After attending an activity, students were required to postpictures and a reflection on SCOAM’s online learning management platform. At least one ofthese activities had to focus on a social issue
80 63 14 13 2015 206 154 24 63 2016* 94 86 20 19*In 2016, we recruited one math teacher who was suitably matched to a research project, but he failed to completethe program.Table 2 shows the diversity of the applicant pool demographics reflecting the diversity of theteachers in the Houston region.Table 2. Demographics of the RET applicant pool (2014-2016).Ethnicity % Gender %Asian 13% Female 64
BPHS. 2. Have higher program retention rates for S-STEM Scholars than they would have had without the S-STEM program. Specifically, to have a 95% second-year retention rate and an 80% five-year graduation rate. 3. Improve the career-related knowledge of S-STEM Scholars through participation in career-development activities, including career counseling and formal reflection on internship experiences in relation to their assessed interests and values. 4. Have at least half of the S-STEM Scholars intern in the electric power industry and work in the industry upon graduation.Student Selection Process and Criteria The S-STEM program worked with the three partner high schools to recruit students fromeach high
, theCALSTEP team will have as one of its priorities connecting with organizations (e.g., theCalifornia Online Education Initiative, or OEI) to find resources to support the effort todisseminate the CALSTEP resources and prepare additional faculty to use the resources in theirclassrooms.AcknowledgementsThis project is supported by the National Science Foundation through the ImprovingUndergraduate STEM Education (IUSE) program, Award No. DUE 1430789. Any opinions,findings, and recommendations expressed in this paper are those of the authors and do notnecessarily reflect the views of the National Science Foundation.References[1] President’s Council of Advisors on Science and Technology (PCAST) (2012). Engage to excel: Producing one million additional
backgroundIn 2006, Jeannette Wing, at that time, head of the computer science department at Carnegie Mellon,promoted the term computation thinking (CT). She defined computational thinking as "a range ofmental tools that reflect the breadth of the field of computer science."[1] (p.33). In this same article,Wing invited the community to see CT not only as a set of skills concerning computer scientistsbut every professional.After 2006 a significant movement of supporters of CT started to look for a formal definition andcomposition of CT. In the last 14 years, over 20 definitions and frameworks for CT have beenproposed [2], [3]. Nevertheless, although there have been increasing efforts to compile a singledefinition, those were unsatisfactory[4]. It is the
career following the REU experience.Acknowledgement: This research was supported by a REU Site grant from the National ScienceFoundation (# EEC 1757882). Any opinions, findings, conclusions, or recommendationspresented are those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References 1. Aggies Invent : Solving Problems in 48 Hours, Engineering Entrepreneurship program, College of Engineering, Texas A&M University, https://engineering.tamu.edu/student- life/aggies-invent/index.html (accessed, May1, 2020). 2. Nepal, B., Pagilla, P. R., Srinivasa, A., Bukkapatnam, S., Moturu, P., 2019, “Preparing Next Generation of Manufacturing Leaders: A case of REU site in Cybermanufacturing
, the shared Redshirt model consists of seven mainprogrammatic elements that are designed to improve the engagement and rates of retention andgraduation of students underrepresented in engineering and computer science. These elementsare “intrusive” academic advising and support services; an intensive first-year academiccurriculum; community-building; programming to develop career awareness and identification;mentoring by an engineering or computer science faculty member; financial support, includingthe NSF S-STEM scholarships; and second-year academic support. There is flexibility acrossinstitutions in how these core components are implemented, reflecting distinctions in theadministrative structure, resources, and student populations at each
laboratory environments.Acknowledgement This research is funded by the National Science Foundation NSF NRI #1527148. Anyopinions, findings, or conclusions found in this paper are those of the authors and do notnecessarily reflect the views of the sponsors.References1. National Robotics Initiative 2.0: Ubiquitous Collaborative Robots (NRI-2.0) (nsf17518) | NSF - National Science Foundation.2. Tucker C, Kumara S. An Automated Object-Task Mining Model for Providing Students with Real Time Performance Feedback. In: ; 2015:26.178.1-26.178.13.3. Hu Q, Bezawada S, Gray A, Tucker C, Brick T. Exploring the Link Between Task Complexity and Students’ Affective States During Engineering Laboratory Activities. In: ASME 2016
; Faust 1994) by examiningimportant relationships reflected in the strength, direction, and complexity (or number) of tiesembedded in a network. The strength of such an approach is that it enables an analysis of socialphenomena beyond the abstract social structures (e.g. social, economic, political) traditionallystudied by researchers in the social and behavioral sciences (Wellman 1999).Ego-centered (or personal) networks make the individual the focus of attention where egodescribes people (alters) close to him or her (Boissevain 1974; Wellman & Berkowitz 1988).According to Wellman (1999), such investigations “enable researchers to study community ties,whoever with, wherever located, and however structured…and avoid the trap of looking
demand STEM careers.AcknowledgementThis material is supported by the National Science Foundation under DUE Grant Numbers 1501952and 1501938. Any opinions, findings, conclusions, or recommendations presented are those of theauthors and do not necessarily reflect the views of the National Science Foundation.References1. Coleman, N., and Ford, M., 2014, "North Dakota and Texas now provide half of U.S. crude oil production," Today in Energy, July 1, http://www.eia.gov/todayinenergy/detail.cfm?id=16931 (Retrieved on July 25, 2014)2. Texas Wide Open for Business, 2013, "Manufacturing in Texas," TexasWideOpenforBusiness.Com, http://www.governor.state.tx.us/files/ecodev/Manufacturing_in_Texas.pdf (Retrieved on July 25, 2014)3. Modine, J
or recommendations expressed in this material are those of theauthors and do not necessarily reflect the views of the National Science Foundation.References [1] Rakesh Agrawal, Anastasia Ailamaki, Philip A. Bernstein, Eric A. Brewer, Michael J. Carey, Sura- jit Chaudhuri, AnHai Doan, Daniela Florescu, Michael J. Franklin, Hector Garcia-Molina, Johannes Gehrke, Le Gruenwald, Laura M. Haas, Alon Y. Halevy, Joseph M. Hellerstein, Yannis E. Ioan- nidis, Hank F. Korth, Donald Kossmann, Samuel Madden, Roger Magoulas, Beng Chin Ooi, Tim O’Reilly, Raghu Ramakrishnan, Sunita Sarawagi, Michael Stonebraker, Alexander S. Szalay, and Ger- hard Weikum. The claremont report on database research. SIGMOD Record, 37(3):9–19, 2008. [2
metropolitan public university, designatedas High Doctoral Research by the Carnegie Foundation are also be participating. Studies at thissecond location are focusing on impact of teaching function on capstone design quality. Resultsof these studies are forthcoming.AcknowledgementsThis work is supported by the National Science Foundation through grants 1525449, 1525170,and 1525284. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of National Science Foundation.References1. Pahl G, Beitz W, Feldhusen J, Grote KH. Engineering Design: A Systematic Approach. 3rd ed: Springer Verlag; 2007. 2
ofIllinois or to the topic of state machines in digital logic. Interviews with instructors of digitallogic courses are ongoing. Comparisons between the reasoning and problem solving approachesof students and instructors will be compared in future studies to enable comparisons betweenexperts and novices.6. AcknowledgmentsThanks to Lance Pittman for his help with collecting data and supporting analysis. This projectwas supported by the National Science Foundation under grant EEC 1429348. The opinions,findings, and conclusions presented in this paper do not necessarily reflect the views of theNational Science Foundation or the authors’ institution.References1 Juhl, J. & Lindegaard, H. Representations and visual synthesis in engineering design
). Using the focus group method in software engineering: obtaining practitioner and user experiences. In Empirical Software Engineering, 2004. ISESE'04. Proceedings. 2004 International Symposium on (pp. 271-280). IEEE.38. Martınez, A., Dimitriadis, Y., Rubia, B., Gómez, E., & De La Fuente, P. (2003). Combining qualitative evaluation and social network analysis for the study of classroom social interactions. Computers & Education, 41(4), 353-368.39. Mawdesley, M., Long, G., Al-Jibouri, S., & Scott, D. (2011). The enhancement of simulation based learning exercises through formalized reflection, focus groups and group presentation. Computers & Education, 56(1), 44-52.40. Natishan, M. E
. Age Group: {22 or under, over 22} 2. Gender: {male, female} 3. Under-Represented Minority: {yes, no} 4. Transfer Status: {admitted to engineering as a freshmen, transferred to engineering from a community college with an associate’s degree, other transfer status} 5. Pell Grant Recipient: {yes, no} 6. Combined Work and Credit Hours/Effort: {under 40, 40-65, over 65}The age categories reflect our interest in traditional vs. non-traditional engineering students, withthe traditional student starting college at age 18. The students in this course were juniors andseniors. The under-represented minority students consisted of Hispanic, American Indian,Black/African American, or Hawaiian/Pacific Islander students. The work and credit
researchexperience so that the students can learn how to conduct their own research projects.While other benefits may be experienced by particular students, they should not beconsidered an expectation for a successful URE for most engineering students.AcknowledgementsPartial support for this work was provided by the National Science Foundation's ResearchInitiation Grants in Engineering Education program under Award No. 1340324. Anyopinions, findings, and conclusions or recommendations expressed in this material arethose of the authors and do not necessarily reflect the views of the National ScienceFoundation. The authors would also like to thank Al Ghorbanpoor and Wendy Pero atUWM for their assistance with this project.Bibliography1. National Science Board
consider how we might provide resources and education to parents to help them support their children’s engineeringrelated interests. Acknowledgement Page 26.962.10 This material is based upon work supported by the National Science Foundation, Division of Engineering Education and Centers, Grant Number 1129342. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the National Science Foundation. References 1 Bureau of Labor Statistics, US Department of Labor. (2014). Occupational outlook handbook, 2014 edition . Washington DC: U.S
team to use existing codebooks to analyzethese responses. Although the number of pilot responses limits our ability to fully test thesecodebooks on the responses, our preliminary review suggests meaningful overlap.Remaining pilot data is planned for collection and analysis in early 2015 along with any changesdeemed necessary. Deployment of the final survey to the larger participant population is plannedfor the spring of 2015.AcknowledgementsThis paper is based on research supported by the National Science Foundation under Grant No.EEC-1232629. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the National ScienceFoundation.Bibliography1
guest lecturer issue.(3) Design the lightweight and more detailed version for each course module so that itwill take less lecture time and leave some work for student to do after class.AcknowledgementsThis material is based upon work supported by the National Science Foundation underAwards DUE-1140567, DUE-1141112, and DUE-1141200. Any opinions, findings, andconclusions or recommendations expressed in this material are those of the authors anddo not necessarily reflect the views of the National Science Foundation. The authors alsothank the anonymous reviewers for their feedback.Reference:1. G. Bieber, L. Architect, and I. Ci. Introduction to service-oriented programming. In Openwings, 2001.http://www.openwings.org.2. P. Brusilovsky. Webex
a comprehensive list of Case Studies, Class Exercises, and Video CaseStudies.3.1.1.1 Development MethodologyAn iterative development methodology depicted in Focus groups Decide on Active LearningFigure 1 was used to ensure the modules reflected both Contents and Formats (case study, class exercise, or case studyacademic research and industry best practices. The video)content development process began with a meeting of PI & Co-PI refine Contents Listthe focus groups at the author’s institution. The
in this material are those ofthe authors and do not necessarily reflect the views of the National Science Foundation. Thework was initiated through a STEM Collaborative grant awarded by the Leona M. and Harry B.Helmsley Charitable Trust. Development of the freshman engineering course was also supportedby the Boeing Company and by a STEM grant from the Office of Naval Research (ContractNumber N00014-15-1-2434). The authors are also grateful for support from the Provost’s Officefor the FYrE program, and to Professor Monika Kress of the Department of Physics andAstronomy at San José State University, who provided insight on her pre-physics coursedevelopment. Finally, the contributions of the entire FYrE faculty and staff team, notably DebbieWon
”. Journal of Counseling Psychology, 57(1), 2010, p. 23.[17] S. Porter & P. Umbach, “College major choice: An analysis of person–environment fit”. Research in higher education, 47(4), 2006, pp. 429-449.[18] J. Holland, Making vocational choices: A theory of vocational personalities and work environments. Psychological Assessment Resources, 1997.[19] K. Rask & J. Tiefenthaler, “The role of grade sensitivity in explaining the gender imbalance in undergraduate economics”. Economics of Education Review, 27(6), 2008, pp. 676-687.[20] M. Anderson & J. Swazey, “Reflections on the graduate student experience: An overview”. New directions for higher education, 1998(101), 3-13.[21] G. Malaney, “Why
Center 5. Continue the engineering specific tutoring and provide the engineering cohort leadership opportunities and a community in which they feel they can belong. 6. Create a programmatic pre-engineering track. This material is based upon work supported by the National Science Foundation under Grant No. DUE-1832553. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Approved by the City Colleges of Chicago IRB (IRB2018007). 11[1] T. D. Holmlund, K. Lesseig, and D. Slavit
of the students at ASU, though some students there were also challenged by them.It may be desirable to introduce more features to customize the level of the exercises to differentstudent populations and to give instructors more flexibility on which levels they can choose toassign. Such adaptations will be explored in future work.The biggest differences between institutions appeared to be on the preference between CircuitTutor and other options, which may reflect the use of different electronic homework systems atdifferent institutions. For example, WileyPLUS is used at ASU and Pearson’s Fig. 5. Results of an end-of-semester survey at three different institutions in Fall 2019 covering the entire Circuit Tutor system (not just the topics
projects course on student retention,” in Proceedings ASEE Conference and Exhibition, 2003.[19] C. B. Zoltowski and W. C. Oakes, “Learning by doing: Reflections of the epics program.” International Journal for Service Learning in Engineering, vol. 9, 2014.[20] National Academy of Engineering, Educating the engineer of 2020: Adapting engineering education to the new century. National Academies Press, 2005.[21] J. A. Mejia, D. Drake, and A. Wilson-Lopez, “Changes in latino/a adolescents engineering self- efficacy and perceptions of engineering after addressing authentic engineering design challenges,” in Proceedings of American Society for Engineering Education Annual Conference, 2015, pp. 1–14.[22] C. B. Zoltowski, W. C. Oakes, and
reflectivity, mechanical robustness, and environmental sustainability, such as carbides, sol-gel coatings, high temperature oxides, and sev- eral polymers. Her research is interdisciplinary in nature and fosters collaborations with Chemical and Biomedical, Mechanical, and Environmental Engineering, Physics, Chemistry, Public Health, Medicine, and the Nanotechnology Research and Education Center (NREC).Prof. Rhonda R. Franklin, University of Minnesota Rhonda Franklin (S’84-M’96) received the B.S. degree in electrical engineering from Texas A&M Uni- versity, College Station, TX and M.S. and Ph.D. degree in electrical engineering from The University of
Monthly Email Advisor. 2008;6(8):2–3.22. Nickerson RS. The teaching and thinking of problem solving. In: Sternberg RJ, editor. Thinking and Problem Solving. 2nd ed. San Diego, CA: Academic Press; 1994. page 409– 49.23. Wankat P. Reflective Analysis of Student Learning in a Sophomore Engineering Course. Journal of Engineering Education. 1999;88(2):195–203.24. Jonassen DH. Toward a Design Theory of Problem Solving.pdf. Educational Technology Research & Development. 2000;48(4):63–85.25. Bowman D, Benson L. MuseInk : Seeing and Hearing a Freshman Engineering Student Ink and Think. ASEE Annual Conference Proceedings. Louisville, KY: American Society
and do not necessarily reflect the viewsof the National Science Foundation. The authors would also like to thank Shuwen Tang,Cindy Walker, Todd Johnson, Tina Current, Sharon Kaempfer, and Jennie Klumpp (all atUWM) for their assistance with this project.Bibliography1.National Science Board. 2003. The Science and Engineering Workforce: Realizing America’s Potential.Publication NSB 03-69. (www.nsf.gov/nsb/documents/2003/nsb0369/nsb0369.pdf)2. Augustine, N. “Rising Above the Gathering Storm: Energizing and Employing America for a BrighterEconomic Future”, Committee on Science, Engineering, and Public Policy (COSEPUP), 2007.3. Good, J., Halpin, G., and Halpin, G. “A Promising Prospect for Minority Retention: StudentsBecoming Peer Mentors”, J