Paper ID #33746Critically Quantitative: Measuring Community Cultural Wealth on SurveysDaiki Hiramori, University of Washington Daiki Hiramori is a Graduate Research Assistant at the Center for Evaluation & Research for STEM Equity (CERSE) at the University of Washington. His research interests include quantitative methodology, queer and feminist studies, sexuality and gender stratification, demography of sexual orientation and gender identity, and Japanese society. In addition to an MA in Sociology and a Graduate Certificate in Feminist Studies from the University of Washington, he holds a BA in Sociology with a minor
, workshop handout “A formula for motivation: M = E + V – C,” James Madison University, 2018. [Online]. Available: https://www.aacu.org/sites/default/files/files/STEM15/EVC%20_formulaandsourceshand out%20AACU%20F15%20final%20version.pdf.[21] L. Eby, T. Allen, S. Evans, T. Ng, and D. DuBois, “Does mentoring matter? A multidisciplinary meta-analysis comparing mentored and non-mentored individuals,” Journal of Vocational Behavior, Vol. 72, no. 2, pp. 254–267, 2008.[22] C. Halupa and M. Henry, “Using VineUp to match students with alumni industry mentors in engineering: a pilot study,” International Journal of Higher Education, Vol. 4, no. 4, pp. 105-112, 2015.[23] M. Dagley, N. Ramlakhan, C. Young, and M
themselves as engineers and the work that engineering entails.The overarching goal of our research agenda is to facilitate future research aimed atunderstanding how working in teams influences the emergence of professional identity andcapability among undergraduate engineering students. The purpose of this study is to advancedevelopment of a tool, the Within-team Task Choice Survey (WTCS), for collecting data abouthow students spend time, select tasks, and envision their role in the context of a team-baseddesign project.Literature Review: Team-based learning in engineering designWidely used as a pedagogical strategy for developing technical skills and professionaldispositions, team-based learning is commonly leveraged in design courses in chemical
link these surveystogether. As a result, the student’s identity is not known, but the pre/post surveys can be linkedfor the same student. Three instruments (1-3, below) comprised the survey and tookapproximately 5-10 minutes to complete. Each section of the survey provided data tooperationalize study variables identified in the PEERSIST model (Fig. 1), namely, engineeringself-efficacy, engineering identity, institutional identity, and supports and barriers.(1) Engineering Self-Efficacy Beliefs. Three items comprised this variable, adapted for this studyfrom Lent et al. [19]: confidence to (1) pass all remaining technical courses in the engineeringmajor, (2) pass all remaining design courses in the engineering major, and (3) graduate with
accepted to fill out the survey and 93 eventually completed it (completion rate = 29.5%).III. Survey distributionThe survey was emailed by the College of Engineering at our institution to all the undergraduate(and some graduate) students enrolled in engineering courses in the summer 2020 semester. Theinvitation email for the survey was sent at the end of the summer semester, followed by the firstand the second reminders with a gap of four days between each.ResultsThe accuracy of this survey was ensured by getting it reviewed by an external researcher and byconducting a small-scale pilot test before sending it to the engineering population for large-scaletesting.I. Survey TestingStep 1: External review – The survey was sent for review to an
[24]. We believe that this is why Community Involvement, as a supporting object[24] emerged so strongly at different times through scholars’ processes. We theorize that findinga new domain with a supporting community – a home – was crucial for their continuation andsuccess in EER.The feeling of homelessness was a central theme observed in the results of an autoethnographyconducted by the third author [6]. This research was based on McAlpine et al.’s identity-trajectory network framework [25], and unlike our pilot study, which focused on internationallysuccessful academics, their study focused on graduate students studying engineering educationresearch in Canada. The themes in Seniuk Cicek et al.’s [6] study not only resonate with thestruggles
learning. Our five-member FLC was formed toinvestigate this critical teaching and learning issue of developing Engineering students’troubleshooting skills and explore the scope and techniques for improving outcomes throughinnovative teaching methods and/or by developing new ancillary learning resources. To achievethe ultimate goal of improving troubleshooting skills, it is important to first assess the currentability of students at troubleshooting and then formulate a plan to invoke improvement measuresin a few courses as a pilot study before a general strategy can be developed to apply to the entireundergraduate curriculum. Our FLC team in this project formulated and focused on the followingrelevant research questions (RQs):RQ1. What did previous
campusculture [9], [10]. In these studies, campus culture considered (1) classroom experiences, (2)faculty-staff relationship, (3) institutional support services, (4) peer interactions, (5) studenteffort to learn, (6) goal development and management, and (7) institutional commitment. As aresult, we integrated these components of campus culture into our understanding of institutionalclimate to ground our data collection approach and provide a helpful framework for uncoveringways in which institutional climate can impact how a Black HBCU undergraduate engineering orcomputing student navigates their post-graduate planning and decision-making.Identity and SuccessUnderstanding how an institution’s culture and climate support students’ personal identities is
activities had yet to be designed and implemented at the technicalcolleges. Student participants were still recruited and selected from the target population: transferstudents in Engineering and Computer Science from two of the technical colleges in differentregions of the state. The intention then was that cohort experiences at the technical collegeswould begin August 2020.Fall 2019, six students began the program in the pilot cohort. They had not been together as agroup prior to August 2019 and engaged in the S-STEM program activities without the benefit ofcohort-based learning experiences during their last year at their technical colleges. Given thisdifference, we treated them as a pilot group for testing certain survey and interview questions
—orbelieves, as we do—that all of the EOP competencies are important for students toexperience by the time they graduate, it behooves us to think about how to deliver thesecompetencies across a curriculum.The engineering curriculum in which this study occurred is designed to provide at least onePjBL class each semester. We envision a delivery of different subsets of the EOP frameworkcompetencies across the project-spine to ensure meaningful engagement is achieved for allcompetencies. This approach allows for at least two synergistic pedagogical and researchopportunities: 1) emphasizing a different subset of EOP competencies in different PjBLcourses allows students to see the interdependencies between those competencies in moredepth; and 2) spreading
. Jonassen, J. Strobel, and C. B. Lee, “Everyday Problem Solving in Engineering: Lessons for Engineering Educators,” J. Eng. Educ., vol. 95, no. 2, pp. 139–151, Apr. 2006.[25] J. W. T. Kan and J. S. Gero, Quantitative methods for studying design protocols. Springer, 2017.[26] A. Kirn and L. Benson, “Engineering Students’ Perceptions of Problem Solving and Their Future,” J. Eng. Educ., vol. 107, no. 1, pp. 87–112, Jan. 2018.[27] A. F. McKenna, “An investigation of adaptive expertise and transfer of design process knowledge,” J. Mech. Des. Trans. ASME, vol. 129, no. 7, pp. 730–734, Jul. 2007.[28] R. M. Marra, B. Palmer, and T. A. Litzinger, “The Effects of a First-Year Engineering Design Course on