the role of mentors inattracting underrepresented students, previously constructed instruments from 12 in theirattitudinal study of CS in the Level Playing Field’s Summer Math and Science Honors Academy(SMASH) were used. Additional instruments were developed by the researchers to measurecultural competency. The survey uses a 5-point Likert scale (where 1 = Not Really, 3 = Neutraland 5 = Absolutely).Along with the surveys, interviews were conducted to get a deeper sense of the effectiveness ofthe BJC curriculum in attracting historically underrepresented students. These audio-recordedinterviews were conducted at the university with participants that either attended CS10, CS61A,or both. Furthermore, participants were carefully chosen to reflect
few days later and included the two itemsshe had requested. The salary was not quite the level Sarai had hoped for, but given her interestin remaining in the region and her success in receiving funding for both of her requests, shedecided against negotiating for a higher salary. All in all, the negotiation workshop had, in hereyes, paid off. Without it, she reflected, she would have just accepted the verbal offer withoutarticulating what else she needed to help her succeed in this new position.Administrative Level NegotiationsCase 3: College level budget negotiationState U had just hired a new provost. He was a biologist and one of his platforms was to launch anew STEM program. The university had, however, been weathering budget crises for
Harvard’s Gender-Science IAT and were required to submit a form reflecting on taking the IAT (students did not submit the results from taking the IAT) 3. Implicit bias presentation: a lecture was given to all classes revisiting implicit bias, discussing why students took the IAT, showing interviews with women from industry, and suggesting possible ways to address implicit bias; students shared their own stories during lecture and via online formAlong with these implicit bias activities, we wanted to know how our students’ perceptions ofstereotyped traits, learning environment, and perceived abilities changed over the course of thesemester. Student cohorts can change drastically even from semester-to-semester, so it
-five minutes and thelongest interview was fifty-eight minutes. We provided the participants with the interview questions severaldays in advance to allow them to reflect upon the questions.C. Data AnalysisThe interviews were audio-only, conducted via telephone, and recorded for later analysis. The audio datawere coded directly without transcription using qualitative analysis software (NVivo 11) with an initial codeset that had been developed from the research questions and the interview questions. The code set containedtwenty-two codes with four codes added as emergent codes during the coding process. One author(Fitzmorris) conducted the interviews and coded the interview data. Once the data were coded, all threeauthors listened to selected
is that the individual feels isolated and is able to identify potential sources of those feelings.• Mysterious Pathways: covers feelings of being stalled, stuck, or unable to move forward in a career. Originally classified as a result of not knowing the pathways to promotion or advancement, this category was expanded slightly to also reflect those career pathways that are stagnant or stalled for both men and women.• Diving Catch: refers to a tendency of some workplaces to put those who are risk averse at a disadvantage. In a diving catch work environment, the individual who feels less comfortable with risk feels more at a disadvantage with regard to advancement or performance because he or she is penalized by not
members.Upon review several modifications to the website were communicated to the HR specialist, whoalso acted as liaison between any and all constituents. A major modification reflected howmedium-to-large institutions receive and process applications. Through various communicationand performance difficulties on the part of the webmaster required that, the HR specialistworked closely with the webmaster over the next18 months in order for a majority of therequested changes to be implemented. Unfortunately, these changes were not completed tospecification or functioning.To address these technical limitations and frustrations, a local technology group was hired toexamine and to correct the architecture and functioning of the website. After six months
larger variety of sources. The most typical data collection tool usedwas interviews in multiple forms—including semi-structured, one on one, and focus groups.Similarly, open-ended surveys were also used as a form of collecting qualitative participantresponses. Some unique forms of data sources were online blogs (Jafer, 2015), online forumposts and emails (Blaser, Steele, & Burgstahler, 2015), student artifacts (Gray et al., 2016), panelproceedings (Genalo et al., 2015), and reflective journals (Brewer et al., 2015). Through theseexamples, we see that in order to contribute to these divisions and the conversation on diversitywe can look beyond the conventional methods of obtaining information and incorporate noveldata sources. 4.7
ScienceFoundation (2017) reflect college attendance at approximately the same rates for persons withand without disabilities, there are discrepancies in degree attainment between the two groups.Roughly 33% of people without disabilities hold a bachelor’s degree or higher, compared to only14% for their counterparts with disabilities (Erickson et al, 2016). That report further shows theemployment rate for people with disabilities (35.2%) is less than half that of people withoutdisabilities (78.3%) (Erickson et al, 2016). Though the employment gap is smaller amongscientists and engineers (nearly 85% and 65% employment rates for people with and withoutdisabilities, respectively), there are still notable differences between the two groups. Thisindicates that
any hand and lowers itto obtain control of the captions until another personraises a hand. The program continues to update thedisplay’s location if the speaker walks around on stage,as shown in Figure 4b.This form of control based on hand raising takesadvantage of social dynamics - when someone motionswith a hand, others know that person would like to speakor to add something to the conversation. It is a methodwhich reflects physical-world experiences. Figure 3: RTTD-MS - z axisLab Presentation ModeDuring a presentation-style setting where the speakers are standing or otherwise moving around on stageand giving a planned presentation, the program detects which speaker is closest to
There are multiple ways to contribute productively to a team“How many points do I get for this?” “How does this prepare me for practice?” Table 3: Discussion of traditional and revolutionary structures that support learningTraditional structures that support learning Revolutionary structures that support learningStandard course evaluations Evaluation of teaching that reflects learning and practiceBuying out of teaching Buying into teachingOne size fits all faculty evaluation and rewards Context-based individualized evaluationCounting underrepresented minorities (URMS) Developing ways to create an inclusive
improve university diversity through exemplary mentoring, merging students who transition between UTEP and EPCC to improve the graduation rate of students in STEM fields. She also encourages students with disabilities (or as one calls it ”special abilities”) to pursue degrees in STEM as well as break barriers for women in engineering to create a broad spectrum of opportunities and meet the 21st century STEM demands. Although having a passion of helping beyond students learning, Carolina also had advocated and helped students who major in Mechanical Engineering as an exemplary Teachers Assistant in the Mechanical Engineering department laboratory ”Lockheed Martin” to have a reflection of a real-world engineering
perceivethemselves to fit into a given group, in this case engineering,5 which in turn affects how theyprogress along the academic and career path in their field.6The engineering identity framework utilized in the study is partially based off a physics identitymodel composed of four basic factors: performance, competence, interest, and recognition.5,7Performance describes a student’s belief in their ability to perform in their classes or whenconducting engineering tasks.8 If a student performs poorly in class, they are less likely toidentify themselves as an engineer. Competence describes a student’s belief in their ability tounderstand engineering material, which is often similarly reflected in a student’s performance inclass.8 Interest describes how
.., 2010) and that afemale scientist needed 64 more impact points than an identical male scientist to be seen asequally competent—which translates into three extra papers in Nature or Science or 20 in lessprestigious journals (Wenneras & Wold, 1997).A second mechanism that fuels Prove-It-Again bias is in-group favoritism: in-groups, but notout-groups, tend to get the benefit of the doubt (Brewer, 1999; Brewer & Gardner, 1996;Hewstone, 1990). The Prove-It-Again phenomenon also reflects stereotype expectancy(Hamilton & Rose, 1980), aka confirmation bias (Mahoney, 1977): we see what we expect tosee. Because low-competence stereotypes set expectations low, more evidence will be requiredof out-groups, as compared with in-groups, to persuade
,” Academic Exchange Quarterly, 2007. 3. http://idea.ed.gov/explore 4. The State of Learning Disabilities, 3rd edition, 2013, National Center for Learning Disabilities. 5. “Academic accommodations for students with learning disabilities,” Disabilities, Opportunities, Internetworking, and Technology (DO-IT), University of Washington, 2012. 6. U.S. Department of Education, National Center for Education Statistics, 2016. 7. U.S. Department of Education, National Center for Education Statistics, 2011, Table 4. 8. “For your consideration… suggestions and reflections on teaching and learning,” University of North Carolina Center for Faculty Excellence, Nov. 2009. 9. Lyman, F. T. (1992). Think-Pair
authors and do not necessarily reflect the views of the National ScienceFoundation.References1. Committee on Equal Opportunities in Science and Engineering, “Broadening participation in America’s STEM workforce: 2011–2012 biennial report to Congress,” National Science Foundation, Arlington, VA, 2014. Retrieved from https://www.nsf.gov/od/oia/activities/ceose/reports/Full_2011- 2012_CEOSE_Report_to_Congress_Final_03-04-2014.pdf2. S. Hurtado, K. Eagan, and M. Chang, “Degrees of success: Bachelor’s degree completion rates among initial STEM majors,” Higher Education Research Institute at UCLA, 2010.3. M. Ong, C. Wright, L. Espinosa, and G. Orfield, “Inside the double bind: A synthesis of empirical research on undergraduate and graduate
% program I feel like I am successful in my 25% 43% 31% 2% engineering program I doubt my abilities to succeed in my 2% 8% 66% 25% engineering program*In my engineering classes, I feel like I 31% 34% 31% 3% matter. Always Most of the time Sometimes Never Findings from the focus group interviews are presented in order to reflect the majorfoci of the interviews: (1
inthis material are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation. The authors wish to thank the STRIDE team and the interview participantsfor their participation in the study.References[1] The United States Department of Education, “Stem 2026 A Vision for Innovation in Stem Education,” U.S. Dep. Educ. Work., p. 55, 2016.[2] D. P. Giddens, R. E. Borchelt, V. R. Carter, W. S. Hammack, L. H. Jamieson, J. H. Johnson, V. Kramer, P. J. Natale, D. a. Scheufele, and J. F. Sullivan, Changing the conversation: messages for improving public understanding of engineering. 2008.[3] N. S. Foundation, “Women, Minorities, and Persons with Disabilities in Science and Engineering: 2017