. Traditionallyused measures of self-efficacy include The General Engineering Self-Efficacy Scale and theEngineering Skills Self-Efficacy Scale and both instruments have been proven reliable, valid,and useful in the assessment of undergraduate engineering students [23].Self-efficacy as an independent variable ESE has long been studied to determine its relation to retention, persistence, and overallsuccess among students in the field. Aleta [24] reported that students who judged their ownengineering backgrounds as strong and positive were more likely to perform well in engineeringprograms and on engineering exams, and their engineering self-efficacy was also shown to becorrelated with academic achievement. Other research has been dedicated to the
interventions and scale up across the College of Engineering. Page 1 of 8The ApproachAlthough we arrived at a set of scalable and cost-effective interventions through iterativeexperimentation in the classroom, each of the interventions are grounded in three well-understoodaffective learning categories—belongingness, self-efficacy, and metacognition.Extensive measurements show a correlation between student persistence and feeling connected toothers—their sense of belongingness [19] – [21]. Students who feel disconnected from their peers,major, or institution will often leave; this is particularly true for women, transfer students, andunderrepresented minorities [22], [23]. While many studies measure
professional STEM careers. These students all live in the sameresidence hall and are afforded opportunities such as peer mentoring, on-site tutoring,professional certification opportunities, and social and community activities. Through this study,we attempt to answer the following questions: What are the essential elements of WISER thatcontribute to student academic and career development? What learning experiences embedded inWISER directly or indirectly increase student self-efficacy and positive outcome expectations inengineering?Literature ReviewThe theoretical framework for this study will be the social cognitive career theory (SCCT).SCCT is grounded in Bandura’s social cognitive theory and is used to explain how academicinterest along with career
Support Transfer credit assistance Orientation Course Academic Excellence Workshop Academic advising/counseling Dedicated Student study center and Tutoring Professional and Career development Links with Engineering Professional Student Orgs Industry advisory partnerships & Internships www.WashingtonMESA.orgResearch Questions 7 What influences do MESA Community College Program activities have on early college student STEM self- efficacy? What activities are most influential? Academic vs Social? MCCP influence on persistence & completion of STEM degrees
is important to understand which beliefs arerelevant to academic performance and how these frameworks of thought differ betweenadvantaged and disadvantaged students. These beliefs that students have relevant to theireducation are related to academic performance. If disadvantaged students enter college withmaladaptive beliefs, they may act as compounding obstacles in addition to financial strains andother external variables.A. Self efficacy Self-efficacy, or the beliefs about one’s ability to successfully complete a task, is criticalfor student retention and persistence through adversity [9]. Even when an individual possessesthe abilities necessary for success, their beliefs in personal capability to perform the taskinfluence their
Program for Elementary/ Middle School YouthWomen’s historical underrepresentation in Science, Technology, Engineering and Math (STEM)is evident at all junctures of the pipeline from elementary education to industry. Providingstudents with STEM experiences is one method of alleviating this gender imbalance and building21st Century Skills. At Worcester Polytechnic Institute (WPI), outreach programs in roboticstend to be primarily boys. Based on WPI’s success in offering single-gender programming tobuild self-efficacy, the university added a section of robotics for girls only. To measureoutcomes, WPI collaborated with the PEAR Institute: Partnerships in Education and Resilienceat Harvard Medical School and McLean Hospital
making. 1 The SCCT model posits thatperson-centered variables of domain-specific self-efficacy coupled with interests and realisticoutcome expectations about the field propel individuals to pursue particular careers. Careerchoice is further influenced by a combination of supportive and inhibiting contextual factors.Supportive factors associated with pursuing computing include: early exposure, access to highquality learning experiences, supportive parents, and peer groups.2, 3 Inhibiting factors includelimited access, subtle and not-so-subtle racism and sexism, geographic location, and lower socio-economic status.3, 4 Importantly, SCCT incorporates gender and race/ethnicity explicitly in its model, whichrenders it appropriate for work with
significant association betweenacademic self-efficacy and first-semester grades. It is not known how many weeks a summer bridge program should be to besuccessful (however success is defined) or how many or how few additional supportcomponents during the academic year are necessary to increase retention andgraduation rates. The 11 published summer bridge studies reviewed by Sablan (2014)were stand-alone interventions and not part of larger comprehensive support programs.A stand-alone bridge program may be adequate if the goal is modest, circumscribed,and measured close in time to the conclusion of the bridge program, such as increasingscores on a math-placement exam. However, more long-term and challenging goalssuch as graduation with a STEM
-economic backgrounds incomputing fields.Research surrounding women’s engagement in computing has been on the rise in recent years. Itbegan with the realization that computer science is the only STEM field that is experiencing asteady decline of female enrollment since the 1980’s, 37% to 18% [5]. Since this revelation,rigorous research has highlighted the barriers to computing which include environment andclimate, stereotypes, and self-efficacy, to name a few [6-8, 23]. Exploration has also includedinitiatives by various organizations and universities that have proven to be successful atattracting and retaining women in computer science [9-10].Another demographic with paltry representation within the fields of computing garneringattention in the
the results of the study in context, the authors conducted a literature review of related workon the study of women and URM students in STEM programs. The primary focus was on thechallenges and the causes for success and failure. Allen-Ramdial & Campbell [1] state thatisolation is one of the biggest challenges faced by URM students in STEM fields. One way tosolve this challenge and promote diversity in education is to achieve a critical mass. Unfortunately,this may not be quickly remedied in most environments, thus other intermediary options must beembraced. Isolation may diminish self-efficacy and re-affirm the negative stereotype of the lackof suitability of URM students for STEM study. The presence of peers has been shown to have
. [39] F. Pajares, & M. J. Johnson, “Self‐efficacy beliefs and the[27] J. S. Nevid, & N. McClelland, “Measurement of implicit writing performance of entering high school and explicit attitudes toward Barack Obama,” Psychology students,” Psychology in the Schools, vol. 33, no. 2, pp. & Marketing, vol. 27, no. 10, pp. 989-1000, 2010. 163-175, 1996.[28] A. J. Pantos, & A. W. Perkins, “Measuring implicit and [40]D. B. Kaufman, R. M. Felder, & H. Fuller, (2000). explicit attitudes toward foreign accented Accounting for individual effort in cooperative learning speech,” Journal of Language and Social teams. Journal of
women and URM students in engineering.Reference [4] lists the most common retention techniques and institutions that implemented them. Theauthors divide the strategies into three groups: student-focused, faculty-focused, and institutional anddepartment-focused strategies and provide many examples from literature and submissions frominstitutions.Blaisdell and Cosgrove explain how self-efficacy (one’s belief about how well they can perform giventask or behavior) affects women choosing engineering as their field of study and persisting in it [5]. Theyadvocate for interventions designed using the theory of self-efficacy and give an example of such aprogram. Sullivan and Davis [8] found that commitment to engineering and confidence in engineeringare
, innovation and member college engagement. Prior to joining UNCF, Dr. Reid was Associate Dean of Undergraduate Education and Director of the Office of Minority Education at the Massachusetts Institute of Technology (MIT). Dr. Reid earned both his Bachelor’s and Master’s of Science degrees in Materials Science and Engineering from MIT, and his Doctorate of Education from the Harvard Graduate School of Education. His research interests include exploring the relationships between racial identity and self-efficacy, and their influence on the academic achievement of African American males in higher education.Dr. Trina L. Fletcher, University of Arkansas at Pine Bluff Dr. Fletcher is currently an Assistant Professor at the
the participants to women beyond the Mentoring Network.Previous workshop topics have included “Innovative Teaching and Improving TeachingEvaluations”, “Self Efficacy, Self Advocacy, and Negotiation”, “What Does it Mean to TeachScience?” and “Successful Strategies in Writing and Publishing.” Several of these topics havebeen so successful as measured through post workshop surveys that they have been repeated formultiple years. Two semi-annual STEM-UP Symposia have also been considered core workshopopportunities. These have included Symposia on Collaborative Research Opportunities andInnovative Teaching and Improving Teaching Evaluations with presentations from STEM-UPmembers and other faculty at regional institutions.During the years of the
quota.’ ‘Anybody else smell affirmative action?’ ‘Looks like they got their headcount.’ ‘Here comes the Quota Queen!’(Locke, 2017).These stereotypes and biases can materialize in a number of ways that shape team dynamics,student learning and experience, and team productivity. For example, Meadows et al. (2015)found that these assumptions that women and students of color are not up to the task shape whattasks they are assigned on teams, whether or not their ideas are heard or validated, whether or nottheir work is acknowledged, as well as their self-efficacy and feelings of belonging.Since the fall of 2016, the authors have been engaged in a research project investigating thepresence of bias and stereotyping on first year project teams at