culturally heterogeneous process where peopleengage in various repertoires of practices and literacies rooted in different communities [12],[13], [14]. Learning is revealed to be a collective, communal, reciprocal, and agentic activitywhere meaning is created in interaction with others [13], [15], [16], [17]. And because learning issituated and contextual, it does not escape from but is in fact deeply affected by the influence ofpower relationships.Learning happens within and between communities. People grow from being more novice toexperts. In communities of practice, learning is being facilitated through network(s) of cognition[13]. When it comes to learning, the flow of power occurs between people, activities and theenvironment [13], [18]. In
-centered design typepedagogies and the parallels between students’ interdisciplinary learning and faculty learning tonavigate institutional processes to create interdisciplinary courses [20]. Her recent research hasbeen to integrate social, political, and economic contexts into technical engineering courses. Asan actor in engineering education working to integrate broader societal contexts into theengineering curriculum at Tufts University, Ozkan’s positioning as a practitioner and researcherof pedagogical change informs and motivates her to pursue this collaborative research oncontextualization.Human-Centered Design: Contextualization for Better Design(s)Research on engineering design education demonstrates how treatment of design
tofurther define and operationalize our definitions. Table 1 summarizes these themes, which will befurther elaborated in the following sections. (Though an analysis of the role of gender and activitystructure is beyond the scope of the present work, see [16] for a fuller discussion). The focus groupquotes are identified according to their structure and gender composition. US = Unstructured. S =Structured. PM = Predominantly Male. PF = Predominantly Female. B = Balanced.Table 1: Overview of salient themes and associated codes. Theme Operational Definition Associated Codes Challenges Difficulties and areas of stagnation or • Ideation preferences and confusion encountered by
is the relationship brokerand mediator between university, military, and government partners. As an example of howCMI2’s facilitation supports success, this paper’s Appendix includes an example Customer NeedsStatement for the LMTV camouflage deployer project carried out by UF ME. Developing thisdocument required several iterations between UF and 3ID to settle on parameters that met theArmy’s need to reduce vehicle camouflage deployment time while aligning with UF’s budget,resource, and experience constraints.Camo deployer development through UF ME and GT ME Capstone proceeded in three steps acrossmultiple semesters. First, given a Customer Needs Statement created in advance of the courses,undergraduate senior Capstone students developed
fields [26].Ultimately, the STEM workforce should reflect the population it serves. However, research bythe National Science Foundation finds “Hispanic, Black, and American Indian or Alaska Nativepersons collectively account for 37% of the U.S. population ages 18–34 years in 2021, and 26%of S&E bachelor’s, 24% of S&E master’s, and 16% of S&E doctoral degrees earned by U.S.citizens and permanent residents in 2020” [27]. In addition, women earned 51% of S&Ebachelor’s, 51% of S&E master’s, and 47% of S&E doctoral degrees in the U.S. in 2020, butdespite women’s high levels of representation in S&E (which includes the life sciences andsocial sciences), women of color earned only 14.9% of all S&E bachelor’s degrees [27
; Morris, M. W. (2010). Negotiating gender roles: Gender differences inassertive negotiating are mediated by women’s fear of backlash and attenuated when negotiatingon behalf of others. Journal of Social and Personality Psychology, 98, 256-267.Ameri, M., Schur, L., Adya, M., Bentley, S., McKay, P., & Kruse, D. (2015). The disabilityemployment puzzle: A field experiment on employer hiring behavior. The National Bureau ofEconomic Research. doi: 10.3386/w21560.Baker, P., & Copp, M. (1997). Gender matters most: The interaction of Gendered Expectations,Feminist Course Content, and pregnancy in student course evaluation. Teaching Sociology, 25,29-43.Barnum, P., Liden, R. C., & Ditomaso, N. (1995). Double jeopardy for women and minorities:Pay
mentorship program for underrepresented minorities (URM). She was a founding member of a STEAM Innovation Program at an urban vocational technical school servicing URM in STEM, where she taught Biology, Chemistry, and Biotechnology. Hilderbrand-Chae has a Masters’ De- gree in Genetics from Tufts University Medical School and now focuses research on epigenetic regulation influenced by substrate stiffness.Shalain Iqbal SiddiquiDr. Chiara E. Ghezzi Chiara Ghezzi, PhD is assistant professor in the department of biomedical engineering at University of Massachusetts Lowell. She received her undergraduate and masterˆa C™s degrees in biomedical engineer- ing from Politecnico di Milano, in Italy. During her dBryan Black
,” Soc. Psychol. Q., vol. 63, no. 3, pp. 224–237, 2000.[7] D. Collins, A. E. Bayer, and D. A. Hirschfield, “Engineering Education For Women : A Chilly Climate,” Women in Engineering Conference : Capitalizing on Today’s Challenges - 1996 WEPAN National Conference. pp. 323–328, 1996.[8] L. K. Morris and L. G. Daniel, “Perceptions of a chilly climate: Differences in traditional and non-traditional majors for women,” Res. High. Educ., vol. 49, no. 3, pp. 256–273, 2008, doi: 10.1007/s11162-007-9078-z.[9] K. F. Trenshaw, “Half as likely: The underrepresentation of LGBTQ+ students in engineering,” CoNECD 2018 - Collab. Netw. Eng. Comput. Divers. Conf., no. 2011, 2018.[10] J. Jorstad, S. S. Starobin, Y. (April) Chen
. Ofthe undergraduate students, 82% are white, 5.9% are Hispanic, 4.2% are African Americans, and0.3% are American Indian or Alaska Native. At the graduate level, these numbers are 80.6%,3.2%, 3.5%, and 0.4%, respectively. In comparison, the statewide demographics are: 79.2%white, 5.3% Hispanic, and 14.1% African American. Efforts to focus on inclusion and equity atthe university level have a long history. In the 1970’s, the university established the MulticulturalCenter that supported a wide range of cultural activities as well as academic and supportprogramming to the Minority Education Cohorts: Minority Science Education Cohort, MinorityTeacher Education Cohort, and Minority Business Education Cohort. This was the primaryapproach at the
Engineering Statistics (NCSES), “Diversity and STEM: Women, minorities, and persons with disabilities 2023,” National Science Foundation, Special Report NSF 23- 315, Alexandria, VA, 2023.[4] E. A. Cech and T. J. Waidzunas, “Navigating the heteronormativity of engineering: The experiences of lesbian, gay, and bisexual students,” Engineering Studies, vol. 3, no. 1, pp. 1-24, 2011.[5] E. Cech, “The (mis)framing of social justice: Why ideologies and meritocracy hinder engineers’ ability to think about social justice,” in Engineering Education for Social Justice: Critical Explorations and Opportunities, J. Lucena, Ed. Dordrecht: Springer, 2013, pp. 67 – 84.[6] S. Farrell, A. Godwin, and D. M. Riley, “A
experiences of faculty of color pursuing tenure in the academy. Urban Review, 41(4), 312–333. https://doi.org/10.1007/s11256-008-0113-yDowdy, J. K., Givens, G., Murillo, E. G., Jr., Shenoy, D., & Villenas, S. (2000). Noises in the attic: The legacy of expectations in the academy. Qualitative Studies in Education, 13(5), 429–446. https://doi.org/10.1080/09518390050156396Goldberg, C. E., & Baldwin, R. G. (2018). Win-win: Benefits of expanding retirement options and increasing the engagement of retired faculty and staff. New Directions for Higher Education, 182, 69–74. https://doi.org/10.1002/he.20281Guramatunhu-Mudiwa, P., & Angel, R. B. (2017). Women mentoring in the academe: A faculty cross-racial
75th percentiles,respectively, and the whiskers extend to data points not considered to be outliers. Outliers areplotted as red +’s. If there are no boxes, then all responses besides the median response areconsidered to be outliers.Figure 1: Statistics for responses to survey question 1: How would you rate your study habits whilelearning remotely as compared to learning in person? 1=better in person, 7=better remotelyFigure 2: Statistics for responses to survey question 2: How would you rate your access to re-quired technology (e.g., computer and internet) while learning remotely as compared to learningin person? 1=better in person, 7=better remotelyAs shown in Figure 1, students generally reported a significant negative impact of
askedparticipants to describe ways to improve entrepreneurship education programs, with specificattention to women faculty experiences.Table 1. Description of Participants Participant Race and Gender Discipline STEM Entrepreneurship Positionality Education Programming Participation Status (Yes/No) Dr. J Black woman (she/her) Engineering No Dr. Sh Black woman Engineering No (she/they) Dr. C Black woman (she/her) Engineering No Dr. W Black woman (she/her) Engineering Yes Dr. S Black
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
and experiments in fluidmechanics, they generally do not possess the capabilities to perform hydrodynamic testing. Thispaper will present the work by the authors to develop a water flume that would allowhydrodynamic testing at velocities up to 2.0 m/s. The flume was constructed by anundergraduate and at a cost lower than commonly available commercial units. Both thefabrication process and the potential experiments that the flume could house are designed toimprove student learning in the area of fluid mechanics. The design is developed to be relativelycompact, with a 7’x3.5’ footprint and utilizes a commonly available single-stage centrifugalpump. Flow velocities in the test section can be varied passively by changing the insertcontaining the
, skills, and ability to solve complexproblems and to produce excellent solution(s) within the structure of the team. This concept wasfurther developed to include defining team and task, team climate, communication, and reflection(for a detailed description, please see Table 1)23-26.Design competence focused on finding and evaluating variants and recognizing and solvingcomplex design problems. These were further defined as having the ability to discover and designmultiple solutions to a given problem and to effectively evaluate those solutions to determine thebest solution, and having the ability to see the overall picture of a complex design problem, thenbreaking it into smaller, more manageable parts to solve while keeping the overall problem
]. New SCCT models were developed to explain vocational satisfaction and well-being [10,11], and career management [9]. At the core of the original SCCT model, and most of the SCCTmodels that followed, are self-efficacy (i.e., confidence in the ability to successfully perform adomain-specific task, like a specific engineering skill), outcome expectations (i.e., anticipatedoutcomes of a particular behavior), interests (i.e., patterns of likes/dislikes for career activities),and goals (i.e., determination for a particular outcome). Taking this one step further, Lent etal.’s [9] integrative social cognitive model of academic adjustment, derived from both SCCT [1,2] and the social cognitive model of academic satisfaction [10, 11], explains how
appropriate realistic constraints, including consideration of health, safety, etc., to the engineering problem for the capstone design. Measure: Evaluated in final CPEN 3850 report • Competency: Students demonstrate ability to generate effective solution(s) to the capstone design problem formulated in CPEN 3850, including identified constraints. Measure: Evaluated in final CPEN 4850 report [1]Thus, in order to determine whether students can both identify and apply appropriate standardsand constraints, and apply these in an engineering design, it was decided that it was necessary toevaluate students continuously working on a project; therefore, measuring in sequentialsemesters was specified. Other required
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
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
for all.References[1] S. Reges. “Why Women Don’t Code,” Quillette, June 19, 2018 [Online]https://quillette.com/2018/06/19/why-women-dont-code/ [Accessed January 14, 2019].[2] B. Oakley. “Why do Women Shun STEM? It’s Complicated,” Wall Street Journal, July 13,2018 [Online] https://www.wsj.com/articles/why-do-women-shun-stem-its-complicated-1531521789 [Accessed January 14, 2019].[3] J. Steinke. "Adolescent girls’ STEM identity formation and media images of STEMprofessionals: Considering the influence of contextual cues." Frontiers in Psychology 8 (2017):716.[4] K. H. Collins. "Confronting Color-Blind STEM Talent Development: Toward a ContextualModel for Black Student STEM Identity." Journal of Advanced Academics 29.2 (2018): 143-168.[5] S. L
University, San Luis Obispo. He spent the last two years working for an AmeriCorps national service program, CSU STEM VISTA. Here, he implemented programming for an NSF S-STEM grant for an academic learning community of underrep- resented students in mechanical engineering and conducted outreach to K-5 students. Currently, he is one of two CSU STEM VISTA Leaders implementing hands-on learning experiences in STEM throughout the CSU system and supporting a cohort of 15 VISTAs across 11 CSU campuses. c American Society for Engineering Education, 2016 PEEPS: Cultivating a cohort of supportive engineering students and building a support team for institutional changeAbstractA National
opportunities for undergraduate laboratory instructionAbstract:This paper outlines a two-semester senior engineering design project that was carried out tostudy a moderately well-defined chemical reaction involving sodium borohydride in aqueousconditions to generate hydrogen for fuel cell applications. Sodium borohydride hydrolysis hasbeen studied extensively since the early 1940’s as a promising hydrogen storage material, whichprovides a content-rich study area for engineering design coursework and undergraduatelaboratory experiences related to energy, hydrogen, and energy storage potential. Throughout thetwo-semester project design course, a two-student engineering team carried out literature reviewsand bench work that lead them to investigate
globally focused experiences outscored those who did not.Notably, the mean EGPI score of students who reported study abroad was significantly higherthan that of those who did not study abroad. In contrast, participation in second-languagecourses, projects or internships abroad, or having an international roommate did not reveal astatistically significant difference in students’ EGPI or GPI performance.Stepwise regression analysis was used to determine potential relationships among studentexperiences and their global preparedness. The regression results indicated that the combinationof such experiences including engineering focused service learning, study abroad, and non-engineering course(s) with a global focus accounted for approximately 12% of
-depletion is far more than privileges need to be defined over time and space, not traditional systems. just by the user.Figure 3. Traditional vs. IWMDs security (comparison for teaching and research integration).Identifying the modularity of different cryptographic algorithms: These include algorithmssuch as SHA3 and the Advanced Encryption Standard (AES). The sub-step includes applyingfault diagnosis and tolerance techniques specified for IWMDs.Fig. 4 shows the first part of an S-box structure for the Pomaranch cipher. The structure ofPomaranch is based on linear feedback shift registers (LFSRs) which allow fast implementationand produce sequences with large period if the feedback polynomial is chosen
their thinking. As students review each other‟s screencasts, their own thinking and metacognition will be re-evaluated from another learner‟s perspective who is not necessarily a teacher or a textbookauthor. Learning from peers is more authentic and more sustainable than learning from atextbook or from a teacher17. In addition, receiving peers‟ comments on their own screencastadds to these metacognitive items that will eventually help improve their CAD knowledge andskills. In this National Science Foundation (NSF) project, two mechanical engineering faculty andtwo learning scientists have collaborated to implement a student-centered instructional strategy,namely peer-generated screencast strategy in teaching CAD in the undergraduate
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
throughout the search process. In addition, she runs a faculty develop- ment and leadership program to recruit and support diverse PhD students who wish to pursue academic positions in engineering or applied science after graduation. Dr. Sandekian earned B.S. and M.S. degrees in Aerospace Engineering Sciences at CU Boulder in 1992 and 1994, respectively. She went on to earn a Specialist in Education (Ed. S.) degree in Educational Leadership and Policy Studies in 2011 and a Ph.D. in Higher Education and Student Affairs Leadership in December 2017, both from the University of Northern Colorado. She is a Founding Leader of the American Society of Engineering Education (ASEE) Virtual Community of Practice (VCP) for LGBTQ
understanding of our overall data, we performed descriptivestatistical analysis. Shown below in Table 4 are the descriptive statistics for average noveltyscores by brainstorming group. Here, N represents the number of ideas generated in a givenbrainstorming session and mean represents the total novelty score of each design divided by thetotal number of designs generated. The groups are denoted by the gender composition andstructure (i.e., PM-S = Predominantly Male-Structured) We also present skewness and kurtosisto demonstrate the suitability of the dataset for subsequent statistical analysis. Based on thevalues shown in Table 4, we used standard statistical tests without violating assumptions ofnormality.Table 4: Overview of descriptive statistics for
andlearning new methodologies, such as Q methodology, engineering education researchers will beable to answer new questions, elicit new insights, and expand their skillsets.References[1] J. W. Creswell, Research design: Qualitative, quantitative and mixed methods approaches, 4th ed. Thousand Oaks, CA: SAGE Publications, Inc., 2014.[2] S. R. Brown, “A primer on Q methodology,” Operant Subj., vol. 16, no. 3/4, pp. 91–138, 1993.[3] W. Stephenson, The study of behavior: Q-technique and its methodology. Chicago, IL: University of Chicago Press, 1953.[4] I. Newman and S. Ramlo, “Using Q methodology and Q factor analysis in mixed methods research,” in SAGE Handbook of Mixed Methods in Social & Behavioral Research, 2nd