inengineering, or women in STEM (Science, Technology, Engineering, Mathematics) [2] ,[3], [4],[5]. Even if the model is not explicit, components of engineering identity such ascompetency/self-efficacy and recognition (from herself and others) are still discussed [6], [7].Godwin’s Engineering Identity Model [2] for early post-secondary students (as thisautoethnography fits into this category) is situated in the idea of “role identity” in that “theindividual attaches to the context of a social and cultural role. An individual has as many selvesor identities as he or she has groups of people with which he or she interacts. Some identitiesbecome more salient based on the particular context and social situation in which an individual isimmersed” [2]. The
still in its infancy, studying the HC in engineering is gaining momentum across nationaland international circles [2]-[16]. Traditionally viewed as implicit messaging for women inengineering learning and research environments [2], [3], Villanueva [4] (re)introduced the HC asa structural framework that contains several interconnected pathways (awareness, emotions, self-efficacy, and self-advocacy; each are described in the paragraph below). According to sociologyscholars [17]-[19], structural frameworks consider how moving parts of a system (e.g., commonnorms, customs, traditions, and cultures) are structurally supported and sustained to promotestability and solidarity amongst its actors (individuals or groups). In HC, the interconnected
follows: 1) ethnic enrollment, 88% Hispanics, 2) graduation rates: fouryears (Fall 2020: 24%), six years (Fall 2020: 46%), 3) commuter school, approximately 60% ofstudent population, and 4) 84.6% of the student body receives financial assistance (e.g., 65%receive Pell Grants).I.2 Bootcamp BackgroundThe bootcamp was conducted prior to the start of the 2021-2022 academic year and developedwith the intention of adhering to the ongoing academic mission of UTRGV (Figure 1), which is toincrease student persistence and self-efficacy in STEM fields, particularly serving the HispanicRGV population. An area of opportunity for many Hispanic Serving Institutions (HSI) is retentionrates. According to the retention rates from Texas Public Universities, UTRGV
in their skill development, and to enhance student confidence in their self-efficacy related to non-technical skills” [18].Anecdotally, students have mentioned that while this assignment can be painful, it provides a veryuseful tool for self-reflection and self-improvement. Notably, presentation scores increased inrecent semesters by about 4-6% from the first presentation to the second presentation.Student comments about the content and structure of the communications component of thecourse are positive, with end-of-the-semester survey rankings for the course and the technicalcommunications instructor about 4.8 out of 5, where an average score at the institution is about4.3. A sampling of comments from 2019 indicates student reaction to the
Self-Efficacy,” Journal of Engineering Education, vol. 98, no. 1, pp. 27–38, 2009.[12] M. Ong, N. Jaumot-Pascual, and L. T. Ko, “Research literature on women of color in undergraduate engineering education: A systematic thematic synthesis,” Journal of Engineering Education, vol. 109, no. 3, pp. 581–615, 2020.[13] L. Leyva, T. McNeill, and A. Duran, “A Queer of Color Challenge to Neutrality in Undergraduate STEM Curriculum and Instruction,” Journal of Women and Minorities in Science and Engineering, Dec. 2022.[14] M. W. Ohland, C.E. Brawner, M.M. Camacho, R.A. Layton, R.A. Long, S.M. Lord, M.H. Wasburn, “Race, Gender, and Measures of Success in Engineering Education,” Journal of Engineering Education, vol. 100, no
transformative experience as the altruism-focusedinterventions. This research has shown that framing engineering as an altruistic career path canlead to meaningful changes in students’ definitions of engineering and their connection ofengineering to their career interests.IntroductionThe Goal Congruity Framework (GCF)[1, 2] predicts that students will experience greatercommitment to a career when there is alignment of their career values and their perceptions of thefield in terms of what values it can align with. Similarly, Social Cognitive Career Theory (SCCT)explains how students’ learning experiences can inform their career identity development throughtheir self-efficacy, outcomes expectations (perceptions in GCF), and values for their career.[3
]. Available: http://ies.ed.gov/pdf/CommonGuidelines.pdf.[16] U.S Department of Labor [DOL]. (2010, February 2). Advanced manufacturing competency model [Online]. Available: http://careeronestop.org/Advanced- Manufacturing.pdf.[17] U.S Department of Labor [DOL]. (2020). Advanced Manufacturing competency model [Online]. Available: https://www.careeronestop.org/competencymodel/competency- models/advanced-manufacturing.aspx.[18] C. C. Chen, P. G. Greene, and A. Crick, "Does entrepreneurial self-efficacy distinguish entrepreneurs from managers?," Journal of Business Venturing, vol. 13, pp. 295-316, 1998.[19] J. Cheng, "Intrapreneurship and exopreneurship in manufacturing firms: An empirical study of
, particularly family, on the interests and careersthat students choose. Students develop higher self-efficacy and STEM outcome expectancieswhen parents stress the importance and value of these subjects and support STEM experiencesboth in- and out-of-school [7]. Parental encouragement including toy selection, access totechnology, and high-quality community resources and formal schooling can provide childrensubstantial advantages during elementary and secondary schooling [8]. The STEM community’sgoal should be to create culturally responsive partnerships with diverse families. Thesepartnerships should be authentic and equal, empowering the families to become activeparticipants, allowing them to show who they really are and celebrating the strengths
, we find increased perceptionsof self-efficacy, increased belief that the subject matter of the course is related to future careeraspirations, increased belief that it is possible to improve computing skills within the timespan ofone semester, a sharp reduction in feelings of anxiety associated with coding, and an increasedbelief that computing is a collaborative activity. Perhaps most intriguingly, the data also showthat students have a decreased belief that computing skill is an innate talent possessed by otherpeople (in other words, investment of effort can yield improvements even if one does not startout strong in this area) with a simultaneously increased belief that they themselves possess innatetalent!Beyond these measures of changed
2020 Literature,” Society of Women Engineers - Magazine, Mar. 15, 2021. https://magazine.swe.org/women-in-engineering-a- review-of-the-2020-literature/ (accessed Feb. 12, 2022).[11] F. A. H. A. Kader and M. A. Eissa, The Effectiveness of Time Management Strategies Instruction on Students’ Academic Time Management and Academic Self Efficacy, vol. 4, no. 1. 2015, pp. 43–50. Accessed: Feb. 12, 2022. [Online]. Available: https://eric.ed.gov/?id=ED565629[12] C. Gopalan and M. C. Klann, “The effect of flipped teaching combined with modified team-based learning on student performance in physiology,” Adv. Physiol. Educ., vol. 41, no. 3, pp. 363–367, Sep. 2017, doi: 10.1152/advan.00179.2016.[13] “Flipped classroom
student’s self-efficacy andperceptions on the utility of the course [6] . Some studies suggest that delaying giving feedbackcan improve students learning [3]. Traditionally, the graded handwritten assignments includenotes from the instructor or the course TA pointing at the student’s mistake [7]. It is assumed thatif the graded work is returned to the students with enough delay, students would review theirown work and correct their mistakes for the next assignment/quiz/exam. However, there is noclear evidence to show this method is effective and to ensure that the students have reviewed thegraded assignments.In this article, I present early results using descriptive analysis comparing student grades inElectronics I from groups who participated in
equity, access, and inclusion in engineering and computing and worked to develop programs and activities that supported diverse students in these disciplines. Today, Dr. Waisome is an incoming Assistant Professor in the Department of Engineering Education where she conducts research on broadening participation in science, technology, engineering, mathematics, and computing (STEM+C). She is particularly interested in understanding how formalized mentoring programs impact student trajectories and self-efficacy. In her teaching, she utilizes the learner-centered approach to instruction.© American Society for Engineering Education, 2022 Powered by www.slayte.com Characterization of Problem Types in Engineering
prepared them to cope with the challenges ofgraduate education. Recent trends in engineering education show an increased effort to mitigate the rateof attrition in graduate programs. Previous work has identified several factors that correlate with studentdeparture, including academic environment, interest, advisor-advisee relationship, self-efficacy, andSocialization. Furthermore, underrepresented groups in graduate education often contend with elevated oradditional challenges to their preparation and Socialization because of their historically marginalizedsocial identities. Various programs and initiatives, such as the Ronald E. McNair PostbaccalaureateAchievement Program (or McNair, for short), have sought to increase graduate enrollment among
outreach efforts by schools and robotics organizations, girls do not participate in pre-college robotics at the same rate as boys [1]. Sullivan et al. reported low confidence in technicalactivities related to robotics as a reason for the participation disparity [2]. An analysis of pre-college extracurricular activities and their mapping to engineering majors showed the disciplineswith high percentages of male students, such as mechanical engineering and electrical engineering,had more students tinkering with electrical and mechanical components outside of school prior tostarting college [3]. When girls are not part of extracurricular robotics programs, they miss vitalopportunities to develop tinkering self-efficacy. Attracting more girls to
the team. For example, we examined the pre-post workshop survey to determine theprincipals’ understanding of the value of an equitable CS education. We asked teachers to com-plete a survey that measured their self-efficacy teaching CS equitably pre- and post-professionaldevelopment. There were multiple points of data collection (each quarter over a 12-month period,pre- and post-workshops, pre- and post-training, etc.), which are too many to list within the contextof this paper. However, we provide greater context of evidence that supports or refutes a hypoth-esis in the next section in an effort to illustrate how we used the ToI model to report back to theintervention team.Using the evidence gathered from the schools various team members, we
.), Children's needs III: Development,prevention, and intervention (pp. 59–71), 2006. https://psycnet.apa.org/record/2006-03571-005(accessed Feb. 10, 2022).[3] D. Barni, F. Danioni, and P. Benevene, “Teachers' self-efficacy: The role of personal valuesand motivations for teaching,” Frontiers, 01-Jan-1AD. [Online]. Available:https://www.frontiersin.org/articles/10.3389/fpsyg.2019.01645/full. [Accessed: 02-Feb-2022].[4] A. Wigfield and J. S. Eccles, “Expectancy–Value Theory of AchievementMotivation,” Contemporary Educational Psychology, vol. 25, no. 1, pp. 68–81, Jan. 2000, doi:10.1006/ceps.1999.1015.[5] J. Schuitema, T. Peetsma, and I. van der Veen, “Longitudinal relations between perceivedautonomy and social support from teachers and students’ self
aforementionedUDL principles to assess to what extent the LMS was supporting UDL best practices. Forresponse reliability, we used the individual Cronbach’s α coefficients to measure the reliability ofeach of the question groups.Survey QuestionsThe survey consisted of four groups of questions organized into six system-wide constructs [12]and four usage / satisfaction constructs: 1. Student demographics (including disability status, conditions inhibiting attendance, gender, course they’re responding about, course being online) 2. General course website preferences and functionalities (representing educational equity, performance impact, information quality, system quality, service quality, self-efficacy) 3. Usage and satisfaction pertaining
, which used a groundedtheory method to gain insight into the formation of these individuals as leaders. The secondsource in the Scoping Set is the Troost leadership institute at University of Toronto [2, 15, 17,27], which researched how leader identity is perceived in the profession. More, it did so in termsof professional values, which provide the engineering student an opportunity to “…[recognize]themselves as members of a leadership profession” [15]. The third scoping literature sourceconsists of three articles, based on leadership development in bioengineering courses atUniversity of Illinois Urbana-Champaign [26, 28, 29]. The largely quantitative exploration ofengineering leadership development measured various aspects of leadership growth
University of Arkansas. During intersessionstudents had the opportunity to see the production of American Mariachi at Theatre Squared, alocal professional theatre that donated tickets for all program participants. Students also visitedCrystal Bridges Museum of American Art. At both venues, students were welcomed by leadershipof the institutions and learned about volunteer opportunities at both.SurveysAn innovation inventory survey [75] was deployed to measure the bridge program students’innovation capacity and behavior at the beginning (pre-survey) and again at the end (post-survey)of the 2-week summer bridge program. The objectives of the surveys were to: 1) assess whetherthe bridge program’s course helped develop students’ innovation mindset and
. Towle, J. Mann, B. Kinsey, E. J. O’Brien, C. F. Bauer, and R. Champoux, “Assessing the self efficacy and spatial ability of engineering students from multiple disciplines,” in Proceedings Frontiers in Education 35th Annual Conference. IEEE, 2005, pp. S2C–15. [6] L. McGarvey, L. Luo, Z. Hawes, S. R. S. Group et al., “Spatial skills framework for young engineers,” in Early engineering learning. Springer, 2018, pp. 53–81. [7] N. S. Newcombe, “Picture this: Increasing math and science learning by improving spatial thinking.” American educator, vol. 34, no. 2, p. 29, 2010. [8] N. W. Hartman and G. R. Bertoline, “Spatial abilities and virtual technologies: Examining the computer graphics learning environment,” in Ninth
activity involving computer simulation and/orinteractive visualization.Surveys measured teacher’s self-efficacy in a number of areas including research literaturereview, design, data collection and analysis, communication of research results, ability to relatereal world research problems to teaching, and use of simulation and visualization tools forresearch and teaching. There was a measured improvement between pre-summer experience andpost-summer experience in all categories, with the largest improvements involving ability todiscuss research ideas and ability to use simulation/visualization tools for research and teaching.Follow-up activities are ongoing during the teacher’s academic school year, including assistancefrom the RET to carry out
research suggests that engineering students do not leave solely because they are notperforming well academically [4], [6], [10] and that historically marginalized populations inengineering leave at higher rates [11]–[13]. Geisinger and Raman found six broad factors thatinfluence retention or attrition including: grades and conceptual understanding, student self-efficacy and confidence, interest and career goals, identity, and climate [3]. They found that overhalf of the studies they explored in their extensive literature review mentioned climate as a factorfor students’ leaving engineering programs.Climate includes the attitudes, perceptions, and expectations associated with an institution andcan be informed by interactions with individuals within
manufacturing pillars1.1 Product DesignProduct design is an integral part of manufacturing. Product Design is the process of definingproduct characteristics such as dimensions, appearance, materials, tolerances, etc. It starts withclearly defined customer needs, which are translated into measurable target specifications.Concepts of the product will then be generated, selected, tested, and final specificationsdetermined. For a product to make its way successfully to the market, various aspects of designneed to be carefully analyzed and modeled. One main advantage of computer modeling in product design is that various tests can beperformed on the model that are otherwise dangerous or costly to be done on actual products. Mostreal-life systems are
with experienced researchers in a Community of Practice (e.g.,faculty, postdoctoral researchers, and graduate students in a laboratory setting). Outcomes ofthese experiences include increased STEM knowledge and experience, scientific researchpractices, career awareness, and STEM self-efficacy and identity. RET programs typically aim tosupport translation of research into classroom practices through curricular development by aProfessional Learning Community, which leads to improvements in STEM teaching andlearning, and includes outcomes such as increased persistence in STEM teaching andpedagogical content knowledge (Krim et al., 2019).The Berkeley Engineering Research Experiences for Teachers plus Data Science (BERET+D) isan example of one such
primaryconstructs influencing their choice: self-efficacy, expectations and personal goals.From a student’s perspective, a lack of sufficient knowledge about various majors along with commonuniversity requirements to declare a major before or during their first year presents a series ofchallenges. Issues that arise from choosing a major they later desire to opt out of can delay graduationby a year or more. Consequent costs of an ill-fitting choice in majors can go beyond additionalcoursework and financial setbacks to include social-emotional considerations such as degrading theirself-confidence and sense of belonging, particularly in the engineering field.Further studies on first year engineering programs highlight a trend where in-coming students showhigh
EngagementWell supported academic makerspaces provide students with open access to resources that helpthem develop their problem-solving skills, provide opportunities for collaboration, increase self-efficacy, and develop sense of belonging [9, 10]. Sense of belonging generally relates to self-perceptions of fit within a given context and has been well established as a theoretical constructthroughout the literature [11, 12]. The context in question can be formal, such as an educationalsetting or STEM discipline, or informal, such as friendships or affinity groups. The positiveimpacts of a strong sense of belonging on academic achievement and persistence in STEMmajors are well documented [13-15]. When students interact in positive ways with diverse peers
learning environment (Cooper, Blattman,Hendrix, & Brownell, 2019). Three features of a learning environment contribute to students’development of project ownership: discovery, iteration and collaboration, with the last twofeatures being responsible for students’ development of emotional ownership of their projects(Corwin et al., 2018). A growing sense of project ownership helps students become more tolerantof obstacles and to persevere when facing challenges (Ryoo & Kekelis, 2018; Corwin, Graham,& Dolan, 2015) which in turn increases students’ self-efficacy and motivation (Corwin et al.,2015), encourage students to pursue a long-term career goals in science (D. I. Hanauer et al.,2012), and helps students achieve a better understanding
. Journal of Formative Design in Learning, 2017. 1(1): p. 31-44.23. Okita, S.Y., The relative merits of transparency: Investigating situations that support the use of robotics in developing student learning adaptability across virtual and physical computing platforms. British Journal of Educational Technology, 2014. 45(5): p. 844-862.24. Stork, M.G., Supporting twenty-first century competencies using robots and digital storytelling. Journal of Formative Design in Learning, 2020. 4(1): p. 43-50.25. Durak, H.Y., Yilmaz, F.G.K., and Yilmaz, R., Computational thinking, programming self-efficacy, problem solving and experiences in the programming process conducted with robotic activities. Contemporary Educational
Institute (ABI), ComputingResearch Association (CRA-W), Center for Minorities and People with Disabilities inInformation Technology (CMD-IT), among others, have been established to increase therepresentation of women and minorities in computing studies and beyond, and they haverecorded success thus far25-26.Apart from the immediate results on academic performance, recruitment, persistence across thecomputing pipeline, self-efficacy, etc., what is the impact of these schemes on the eventualemployment outcome of the underrepresented minorities?Many BPC efforts in the existing literature have designed and deployed solutions aimed atremoving one or more barriers to representation, after which the impact (of the solution) on therepresentation of
self-efficacy questions in the pre-camp survey and then repeated them inthe post-camp survey. The post-camp survey also asked them to reflect on their knowledge of thetopics before the camp. Students can judge their abilities only to the extent that they are exposedto a topic since they do not know the threshold for a learning outcome. Therefore, repeating thosequestions in the post-camp revealed some insights.Figure 7: (a) Choice of major pre-camp survey (N=24), (b) Choice of major post-camp survey(N=36) In the two surveys, students were asked to rate their skills on a scale of 1-10 in response to thefollowing four prompts: 1. How confident are you about designing, building, and programming robots? 2. How would you rate your circuits