individual department schedule constraints. Ingeneral, a single faculty member from each department is designated to be with the students forthe two week duration. Table 2: EGR 1700 Department Schedule (each for Che, ECE, ME, CEE ) W eek 1 M o nday Tue s day W e dne s day Thurs day Friday Le ctu r e 1 Le ctu re 1 Le ctu re 2 Le ctu r e 2 no thing 1 2 :3 0 -1 :2 0 1 :0 0 -1 :5 0 1 2 :3 0 -1 :2 0 1 :0 0 -1 :5 0 (Se c tio ns 2 ,3 ,4 ) (Se c tio ns 1 ,5 ,6 ) (Se c tio ns 2 ,3 ,4 ) (Se c tio ns 1 ,5 ,6 ) 0
their intelligence andSTEM identity. Maya described that being the only one created heightened awareness and lesscomfort than her white coworkers. Like Walton et al.’s study, lack of diversity in a professionalsetting detracted from a sense of belonging in the workplace [54].Authenticity was also experienced when the interns had a strong commitment to their racialidentity, or internalization of their identity. Similar to Helms and Piper, as people of Colordevelop and grow in their careers, racial identity is internalized and there is “positive racial-group commitment, humanistic orientation, and internally defined racial attributes” [57, p. 127].Stanley and Evie showed strong commitments to their identities and were agents within theirworkplace
risk factors for persistence of American Indian students and retention of non-American Indian teachers in reservation schools,” in 2017 ASEE Annual Conference & Exposition, Columbus, OH, June 2017.[16] C. H. Foster and S. S. Jordan, “A philosophy of learning engineering and a Native American philosophy of learning; An analysis for congruency,” in 2014 ASEE Annual Conference & Exposition, Indianapolis, IN, June 2014.[17] I. Anderson and S. S. Jordan, “Engineering connections in a Native American community and culture,” in 2018 ASEE Annual Conference & Exposition, Salt Lake City, UT, June 2018.[18] D. Luecke et al., “Efforts to improve mathematical preparation for a pre-engineering
work supported by the National Science Foundation under AwardNumbers 2114241 and 2114242. Any opinions, findings, and conclusions, or recommendationsexpressed in this material are those of the author(s) and do not necessarily reflect the views ofthe National Science Foundation.ReferencesBartlett, R. (2013). Playing with meaning: using cartoons to disseminate research findings. Qualitative Research, 13(2), 214-227.Berhane, B., Secules, S., & Onuma, F. (2020). Learning While Black: Identity Formation and Experience for Five Black Men Who Transferred Into Engineering Undergraduate Programs. Journal of Women and Minorities in Science and Engineering, 26(2), 93–124. https://doi.org/10.1615/JWomenMinorScienEng
strategies for creating equitable access to the discipline. Byexamining how Western Tech Scholars and their peers become cybersecurity professionals, thispaper provides information about “what works” in influencing a diverse body of students tostudy cybersecurity in institutions that are minority serving.3 MethodologyThis qualitative case study considers the Western Tech S-STEM program as the bounded system[15] under investigation. This section describes the data sources used in this study as well as thedata analysis strategies used. IRB was obtained before gathering data.3.1 Data CollectionData sources for this study include the following: a) Annual interviews with Western TechScholars, occurring between May and October from 2019 to 2021, b
identities are encouraged and how strongly they are expressed. Separating bygender, the results show the significant difference between men, women, and nonbinaryengineering students and how they consider their gender identity. The average Model for MultipleDimensions of Identity based on school type can help understand students' priorities when decidingto attend a small school.References[1] A. D. Patrick and M. Borrego, “A Review of the Literature Relevant to Engineering Identity,” in ASEE Annual Conference and Exposition, Conference Proceedings, 2016, doi: 10.18260/p.26428.[2] K. L. Meyers, M. W. Ohland, A. L. Pawley, S. E. Silliman, and K. A. Smith, “Factors Relating to Engineering Identity,” Glob. J. Eng. Educ., vol. 14
Science Teaching, 44(8), 1187-1218.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.Collins, D., Bayer, A. E., & Hirschfeld, D. A. (1996). Engineering Education for Women: A Chilly Climate? Women in Engineering ProActive Network.Crenshaw, K. (1990). Mapping the margins: Intersectionality, identity politics, and violence against women of color. Stan. L. Rev., 43, 1241.Cross, K. J., Clancy, K. B., Mendenhall, R., Imoukhuede, P., & Amos, J. R. (2017, June). The double bind of race and gender: A look into the experiences of
in the geotechnical arena. Dennis is a registered professional engineer in the states of Colorado and Arkansas.Debra Larson, Northern Arizona University Debra S. Larson is a Professor and Chair for the Department of Civil and Environmental Engineering at Northern Arizona University in Flagstaff, AZ. Prior to her faculty appointment at NAU, Debra worked as a structural and civil engineer for various companies. She is a registered Page 13.586.1 Professional Engineer in Arizona. Debra received her B.S. and M.S. degrees in Civil Engineering from Michigan Technological University in, respectively
bachelor’s degrees earned by women in the U.S. has remained between 18.1% and20.5% from 2000 to 2015, with women receiving 20.1% of degrees in 2015 [1]. By contrast,women’s representation in the engineering workforce has been steadily increasing since the1990’s, from 8.6% in 1993 to 14.5% in 2015 [1]. However, according to statistics from 2010,within five years of graduation, 36 percent of women who obtained engineering bachelor’sdegrees either left or never entered the field and within fifteen years after graduation, 60 percentof women who earned engineering bachelor’s degrees had left the field [2]. Despite the recentincreases, these numbers indicate that women are still underrepresented in the workforce and thatretention of women engineers in
manufacturing systems; control of large-scale complex systems; robotics/mechatronics; and adaptive and robust control of nonlinear dynamic systems.Prof. Satish Bukkapatnam, Texas A&M University Satish T. S. Bukkapatnam received his Ph.D. and M.S. degrees in industrial and manufacturing engineer- ing from the Pennsylvania State University. He currently serves as Rockwell International Professor with the Department of Industrial and Systems Engineering department at Texas A&M University, College Station, TX, USA. He is also the Director of Texas A&M Engineering Experimentation Station (TEES) Institute for Manufacturing Systems. His research in smart manufacturing addresses the harnessing of high-resolution
students discussed whichfoot type to use for the foot adaptation component of the survival suit design. The first instanceof EBR stated by Sean was also coded functionality because he explicitly referred to hisknowledge that human feet would work in the snowy conditions. The second instance of EBRwas coded technology, since Samuel justified his counterargument by referring to an existingtechnology, shoes. He used his prior knowledge about existing technologies to point out a flaw inhis teammate’s argument that human feet would be the best option for the survival suit.Example related to colors and camouflageIn addition to the choice of the survival suit covering material, students also had to choose whichcolor(s) to make the exterior of their suit
presenting the total externalwork and total strain energy equations beginning first with a single load P applied to a planartruss with one load sequence. Then loads P and Q are applied using two load sequences in whichthe load Q is applied at the location and in the direction of the desired displacement. From thisbasis of understanding, an additional load S is included in both load sequences to discuss itsinfluence on the displacement expression. This leads to a general understanding of the influencethat any number of additional loads would have on the displacement expression, and that theeffect of the load Q remains unchanged as these loads are applied. It then becomes evident thatBarry T. Rossonthe desired displacement due to all the applied loads
' judgment of his or her abilityto perform the task) play a more significant role. These results are novel given that all examsvaried based on content only, and there was no variation in format and difficulty level of theexams.AcknowledgmentWe want to thank Dr. Morgan Hynes for helping us in the data collection process.References[1] S. Y. Chyung, A. J. Moll, and S. A. Berg, "The role of intrinsic goal orientation, self- efficacy, and e-learning practice in engineering education.," J. Eff. Teach., vol. 10, no. 1, pp. 22–37, 2010.[2] J. M. Dennis, J. S. Phinney, and L. I. Chuateco, "The role of motivation, parental support, and peer support in the academic success of ethnic minority first-generation college students," J. Coll. Stud
inEngER, (6) there is low level of connectivity between researchers in this area, (7) Krause, S. is the“most popular” author according to social network analysis, and (8) the field that has done the mostresearch in this area is “Education, Scientific Disciplines”, which indicates that most venues to publishK-12 EngER are educational rather than engineering venues.Keywords— K-12; engineering; education; research; social network analysis Introduction Engineering education (EngE) has strong associations with science, technology and mathematicseducation and it is concerned with the teaching and learning related to engineering practice. Currently,K-12 EngE is emerging as a new discipline, overcoming
’, ‘behavior’ and ‘function’ as wellas similarly named and closely related concepts (such as “form and function”) for describingaspects of design. I have chosen to use the terms Structure (S), Function (F) and Activity (A) anddefine them as follows.Designers apply functional intentions (F) to abstract structures of instruction architecture (S) byexecuting a variety of instructional design activities (A). These structures, functions andactivities are different abstract domains or layers of the design process; each domain capturessome aspect of design decisions. The usage of these terms will be illustrated by an example.Technical content changes rapidly and constantly but the professor has no control of that changeprocess and cannot make design
engineering is a young discipline. Although the term “software engineering” wascoined in 1968, development of the first undergraduate programs in the discipline did not beginin the United States until the mid to late 1990’s. The first software engineering programsdeveloped in the United States were not baccalaureate programs. Early programs were focusedat the graduate level, working with students who already had a base of knowledge in computerscience. Although there were isolated courses in software engineering offered at someinstitutions as early as the mid-1980’s, it was not until the early to mid-1990’s that softwareengineering concepts began filtering into undergraduate programs. Sometimes these conceptswere incorporated into computer engineering
that has little meaning in the real world. Seniors take to and light up whenlearning and implementing their final design projects. There is a sense that all the courses led tothis moment and now it can be applied to building an actual process. And yet control is the subjectarguably most critical to a graduating chemical engineer that most likely will have a first industrialjob as a process engineer. What does a process engineer do? Well, she is responsible formaintaining a process of unit operation(s) to run at specified conditions 7 days a week, 24 hours aday. Yes, she is essentially doing control. Look again at Figure 1. Realize that those of us that arecontrol engineers, the applied mathematicians of the engineering world, do not cover all
globally competent engineer as one who “work[s] effectively with people whodefine problems differently than they do” (p. 110).8 Moreover, we understand navigating acrosscultures to be a salient characteristic of working effectively with those “who define problemsdifferently.” We understand culture to be “dominant images” (p. 5),9 a framework also proposedby Downey and Lucena.10 Lucena nicely articulates this understanding of culture: “[I]ndividualsliving and working in a particular spatial and temporal location are challenged by dominantimages. Dominant images create expectations about how individuals in that location aresupposed to act or behave. In this … concept of culture, the image remains the same over aperiod of time, while individual or
forTeaching and Learning Ordinary Differential Equations: A Systemic Literature Review andBibliometric Analysis,” Mathematics, vol. 9, no. 7, p. 745, Mar. 2021, doi:https://doi.org/10.3390/math9070745.[5] S. Arslan, “Do students really understand what an ordinary differential equationis?,” International Journal of Mathematical Education in Science and Technology, vol. 41, no. 7,pp. 873–888, Oct. 2010, doi: https://doi.org/10.1080/0020739x.2010.486448.[6] C. L. Rasmussen and K. D. King, “Locating starting points in differential equations: arealistic mathematics education approach,” International Journal of Mathematical Education inScience and Technology, vol. 31, no. 2, pp. 161–172, Mar. 2000, doi:https://doi.org/10.1080/002073900287219.[7] C. L
to student success in engineering education,” EuropeanJournal of Engineering Education, vol. 42, no. 4, pp. 368–381, 2017.[5] M. Scheidt, A. Godwin, E. Berger, J. Chen, B. P. Self, J. M. Widmann, and A. Q. Gates,“Engineering students’ noncognitive and affective factors: Group differences from clusteranalysis,” Journal of Engineering Education, vol. 110, no. 2, pp. 343–370, 2021.[6] S.-M. R. Ting and R. Man, “Predicting academic success of first-year engineeringstudents from standardized test scores and psychosocial variables,” International Journal ofEngineering Education, vol. 17, no. 1, pp. 75–80, 2001.[7] B. F. French, J. C. Immekus, and W. C. Oakes, “An examination of indicators ofengineering students’ success and persistence
beneficial involvement. Threshold theories of studentinvolvement predict diminishing or negative returns at higher levels of involvement. These studieshave measured level of involvement as either number of activities or number of hours involved inactivities [58], [63], [64]. These studies fit nonlinear functions of involvement with respect ofacademic outcomes, finding that at high levels of involvement the benefits leveled off or evendeclined slightly. Vetter et al.’s [17] findings about the significance of quality of involvement overquantity of involvement echo these findings, concluding that “co-curricular programs andactivities are of greatest benefit when they encourage students to engage more deeply… only oneor two meaningful co-curricular
metrics. Hinze-Hoare (2008) maintains thatproblems exist with evaluation of VLEs due to lack of clear objectives associated withassessment frameworks. This issue covers the educational ground of the VLE as well as theHuman Computer Interface (HCI) segment. Although some limited work has been done toevaluate the conversational framework between students and teachers (Hinze-Hoare, HCI andEducational Metrics as Tools for VLE Evaluation, 2008), the goal in this paper will be toevaluate the HCI metric and effectiveness of Moodle.The principles used to evaluate Moodle‟s effectiveness from student‟s point of view are based onBruner‟s Principle (Hinze-Hoare, HCI and Educational Metrics as Tools for VLE Evaluation,2008). These principles are based on core
layout of conducive learning environment, foster community the study space engagement, and establish a smooth educational transition between high school and college.Internal budget analyses indicate that [University] will 1 5 $2 is too small to beneed to raise undergraduate tuition by $2 to fund the consideredstudy space maintenance.[University]’s preferred furniture supplier says that 1 5 Limited impact ondesks and chairs for the study space are on 6-month the physical layout ofbackorder. the study spaceStudent organizations, including sororities and 4 3 Student
learn to see individualstructures or features, and to ask what function that structure or feature accomplishes and whythat is important to the organism. When students are practiced in this, they “learn to see theworld through new eyes” – the world around them is no longer part of the background of theirlives, but rather is now filled with potential solutions to challenging design problems [16].Curriculum BID specific ActivitiesSeveral standard lessons and activities were used for teaching engineering, brainstorming forideas, and as empathy building exercises for problem description. For example, we useSCAMPER, a semi-structured approach to ideation and improving ideas. The categories are, (S)Substitute, (C) Combine, (A) Adapt, (M) Modify
, M. Henderson, E. Creely, A. A. Carvalho, M. Cernochova, D. Dash, T. Davisand P. Mishra, "Creativity and risk-taking in teaching and learning settings: Insights from sixinternational narratives," International Journal of Educational Research Open, vol. 2, no. 2, pp.1-11, 2021.[6] N.R. Kuncel, S. Hezlett, and D. Ones, "Academic performance, career potential, creativity,and job performance: Can one construct predict them all?," J. Educ. Psychol., vol. 102, no. 3, pp.599-616, Aug. 2010.[7] P. C. Wankat, R. M. Felder, K. A. Smith and F. S. Oreovicz, "The scholarship of teachingand learning in engineering," in Disciplinary Styles in the Scholarship of Teaching andLearning: Exploring Common Ground, vol. 1, Indiana University Press, 2002, pp. 217
: “In general, the studies did not take a critical stance on how engineering knowledge is constructed, who participates in engineering, and who decides who becomes an engineer. In terms of critical pedagogy, few studies questioned how to empower students of color (e.g., concientização) or considered taking action and working alongside the students (e.g., praxis) to de-colonize and re-inhabit their spaces, including all of these different domains that students of color inhabit” (pp. 157-158).In a similar vein, Patrick et al.’s state-of-the-art review of papers claiming to use critical methodsin STEM education found that many articles mentioned using a critical theory at the beginningbut did not follow through by
Students and Developing Professional Support NetworksIntroduction The Purdue University Rising Scholars program was initially funded in 2016 by NSF S-STEM#1644143 Rising Scholars: Web of Support Used as an Indicator of Success in Engineering. Theterm ‘Rising Scholars’ has come to represent the strata of the population that are of low socio-economic status (SES) striving to complete a collegiate education (Kent State University, 2021;Stanford University, 2020). The current collegiate entrance metrics favored by many well-regarded state institutions for their STEM programs have certain gateway values, and in general,do not select equitably across many notable factors, including gender; race; ethnicity; first-time,full-time status; and low-SES
engineering, many of the URM studentsstruggle to complete their degree due to various factors: inadequate academic preparation,insufficient awareness career options, lack of necessary financial, academic, social, and culturalsupport for success, and low levels of self-efficacy.To address these barriers and build capacity for student success, SFSU has partnered with twolocal HSI community colleges, Skyline College and Cañada College. This collaboration involvesdeveloping and implementing several strategies through the Strengthening Student Motivationand Resilience through Research and Advising (S-SMART) project, which is funded by theNational Science Foundation's HSI Improving Undergraduate STEM Education (IUSE) program.One of the strategies developed