student learning outcomes and promotethe adoption of modern pedagogy and methodologies for knowledge transfer and retentionassessment. The authors hope the proposed framework will be useful for others seeking to improvetheir curricula and enhance student learning.References[1] “The Integrated Postsecondary Education Data System.” Accessed: Apr. 13, 2023. [Online].Available: https://nces.ed.gov/ipeds/use-the-data[2] “ACCE | Accreditation for Construction Education.” Accessed: Feb. 07, 2024. [Online].Available: https://www.acce-hq.org/[3] “Home - ABET.” Accessed: Feb. 07, 2024. [Online]. Available: https://www.abet.org/[4] V. B. Salakhova, L. V Shukshina, N. V Belyakova, A. V Kidinov, N. S. Morozova, and N. VOsipova, “The Problems of the COVID-19
freehand tab was used to jog the robot joints. The import library was used toimport a tool to attach to the robot. A table was imported for the tool to operate on. Targets wereset on the four corners of the table. A path was created between the four corners and. A path can betaught instructions by manually jogging joints. When the path between the four corners wasdefined, the robot was made to move along the path. This was simulated at different speeds of 200,400, 600, 800, and 1000 mm/s and the cycle time to go along the path was recorded. The cycle timedecreased as speed increased. This decrease was the steepest from 200 to 400 mm/s and keptgetting less and less steep.The experiment demonstrated how RobotStudio can be used to mimic the function
. Research Team Dr. Walter Lee Malini Josiam Artre Turner Crystal Pee Taylor Johnson Dr. Janice Hall Associate Professor PhD Student PhD Student PhD Student PhD Student Postdoc This material is based upon work supported by the National Science Foundation under Grant No. 1943811. "Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation
. Ballen, C. Wieman, S. Salehi, J. B. Searle, and K. R. Zamudio, “Enhancing Diversity inUndergraduate Science: Self-Efficacy Drives Performance Gains with Active Learning,” LSE,vol. 16, no. 4, p. ar56, Dec. 2017, doi: 10.1187/cbe.16-12-0344.[3] K. Ellis, “The impact of perceived teacher confirmation on receiver apprehension,motivation, and learning,” Communication Education, vol. 53, no. 1, p. 2, Jan. 2004, doi:10.1080/0363452032000135742.[4] S. Freeman et al., “Active learning increases student performance in science, engineering,and mathematics,” Proc. Natl. Acad. Sci. U.S.A., vol. 111, no. 23, pp. 8410–8415, Jun. 2014, doi:10.1073/pnas.1319030111.[5] A. Skulmowski and G. D. Rey, “Embodied learning: introducing a taxonomy based on
,findings could inform guidelines and professional development for faculty and administrators onfacilitating constructive race dialogues among student populations. Outreach targeting familiesand communities may also be warranted to align messaging across spaces. Future work can delvedeeper into student backgrounds including where students spend their formative years and thetype of college they currently attend.References[1] K. Lajtha and S. Saini, “Biogeochemistry statement on #ShutDownSTEM and Black Lives Matter,” Biogeochemistry, vol. 149, no. 3, pp. 237–237, Jul. 2020, doi: 10.1007/s10533-020- 00682-7.[2] N. Subbaraman, “How #BlackInTheIvory put a spotlight on racism in academia,” Nature, vol. 582, no. 7812, Art. no. 7812, Jun. 2020
expressed in this material are those of the author(s) and donot necessarily reflect the views of the National Science Foundation.REFERENCES[1] E. O. McGee, “Interrogating Structural Racism in STEM Higher Education,” EducationalResearcher, vol. 49, no. 9, pp. 633–644, Dec. 2020, doi: 10.3102/0013189X20972718.[2] Y. A. Rankin, J. O. Thomas, and S. Erete, “Real Talk: Saturated Sites of Violence in CSEducation,” in Proceedings of the 52nd ACM Technical Symposium on Computer ScienceEducation, Virtual Event USA: ACM, Mar. 2021, pp. 802–808. doi: 10.1145/3408877.3432432.[3] E. W. Huff et al., “Going Through a Process of Whitening: Student Experiences WithinComputer Science Education,” in Proceedings of the 52nd ACM Technical Symposium onComputer
Paul, Oregon State University ©American Society for Engineering Education, 2023 Lab Safety Awareness in Incident and Near-miss Reporting by Students Participating in Engineering Societies: A Case StudyAcademic laboratory safety has gained considerable attention from researchers and researchinstitution administrators since several high-profile incidents in the late 2000’s. Another part ofstudent learning in engineering, though informal, occurs in co-curricular activity such asengineering societies and team competitions where students conduct hands-on activities toachieve certain objectives, usually with minimal (if any) authoritative figures in presence. Thesafety aspect of these co-curricular
. [Accessed: 06- Mar-2021].[4] R. Miller and B. Linder, “Is Design Thinking the New Liberal Arts of Education?,” 2015.[5] A. F. McKenna, “Adaptive Expertise and Knowledge Fluency in Design and Innovation,” in Cambridge Handbook of Engineering Education Research, A. Johri and B. M. Olds, Eds. Cambridge: Cambridge University Press, 2014, pp. 227–242.[6] M. J. Safoutin, “A methodology for empirical measurement of iteration in engineering design processes,” Citeseer, 2003.[7] A. F. McKenna, J. E. Colgate, G. B. Olson, and S. H. Carr, “Exploring Adaptive Expertise as a Target for Engineering Design Education,” in Volume 4c: 3rd Symposium on International Design and Design Education, 2006, vol. 2006, pp
Paper ID #21841Impact of Undergraduate Research Experiences on Diverse National and In-ternational Undergraduate ResearchersDr. Jacques C. Richard, Texas A&M University Dr. Richard got his Ph. D. at Rensselaer Polytechnic Institute, 1989 & a B. S. at Boston University, 1984. He was at NASA Glenn, 1989-1995, taught at Northwestern for Fall 1995, worked at Argonne National Lab, 1996-1997, Chicago State, 1997-2002. Dr. Richard is a Sr. Lecturer & Research Associate in Aerospace Engineering @ Texas A&M since 1/03. His research is focused on computational plasma modeling using spectral and lattice Boltzmann
creatively and effectively. Leaders alsoneed to constantly develop skills and intellectual tools to understand soft skills or people skillsand build relationships internally [48]. Results of Gitsham et al.’s [28] survey of CEOs and other executives focus on how softskills and hard skills are beneficial for leaders at all levels of the organization. Specifically,acquisition of interpersonal skills may provide added benefits of knowing and understanding ofhow to interact with people with different cultures and apply the skills to improve organizationalperformance. Soft skills are a set of interpersonal and social skills, whereas hard skills includethe technical or administrative procedures in which the results are quantifiable and measurable[43
interventionthat can be employed broadly to improve the self-efficacy of both pre-service and in-serviceteachers for teaching engineering, thus preparing future generations to make a global impact.References[1] C. Riegle-Crumb, K. Morton, C. Moore, A. Chimonidou, C. LaBrake, S. Kopp, “Do Inquiring Minds Have Positive Attitudes? The Science Education of Preservice Elementary Teachers,” Sci. Educ. vol. 99, pp. 819-836, 2015.[2] C. Alexander, G. Mayes, S. Hopper, S. Thiruvadi, and G. Knezek, “An Investigation of the Impact of Digital Fabrication Projects on Pre-Service Teachers’ Attitudes and Skills” in Proceedings of th Society for Information Technology and Teacher Education International Conference, SITE 2012 Austin, TX
civil engineers do.AcknowledgementsThis material is based upon work supported by the National Science Foundation under AwardNo. EEC-1733636. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation. We would also like to thank our participants, who have given generously oftheir time to help us better understand their experiences.References[1] M. W. Ohland, S. M. Lord, and R. A. Layton, “Student Demographics and Outcomes in Civil Engineering in the United States,” J. Prof. Issues Eng. Educ. Pract., vol. 141, no. 4, p. 7, 2015.[2] C. Groen, L. D. McNair, M. C. Paretti, D. R. Simmons, and A. Shew, “Exploring
analytic lens may contribute to understanding about how co-peersand peer-designers might most effectively play roles in changing faculty practice, and ultimately,in creating more inclusive learning environments for diverse students.AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grant No.#1623105. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References[1] M. Meyer and S. Marx, "Engineering dropouts: A qualitative examination of why undergraduates leave engineering," Journal of Engineering Education, vol. 103, no. 4, pp. 525-548, 2014.[2] S. E
Ensure code quality through automated continuous testing.Data Collection and AnalysisTo examine how the semester-long experience impacted students, we regularly requestedstudents to reflect on the learning experience. After each SET lesson, we asked the followingfour reflection questions: - What is/are the most important concept(s) you have learned? - How will you use the skills you have developed from this workshop for your project? - What might be the challenges or barriers to implementing ideas from this workshop? - What support would be helpful to have in implementing ideas from this workshop?At the end of the semester, an exit survey was conducted with the following questions: - What was the most useful thing you have learned
experiences.Future research should consider exploring teamwork dynamics in diverse URPs across differentgeographical and disciplinary contexts to generalize the findings as well as compare teamworkexperiences across various URPs to understand the impact of different institutional cultures andprogram structures. Additionally, longitudinal studies could offer a deeper understanding ofhow teamwork skills developed in URPs impact students’ professional careers. References[1] K. W. Bauer and J. S. Bennett, “Alumni Perceptions Used to Assess Undergraduate Research Experience,” J. High. Educ., vol. 74, no. 2, pp. 210–230, 2003.[2] D. Lopatto, “Undergraduate Research Experiences Support Science Career Decisions and Active Learning,” CBE—Life Sci. Educ., vol
fiveundergraduates identify as disabled [11]. Yet, in engineering such substantive data is almostentirely unavailable. The National Science Foundation (NSF)’s 2023 Diversity and STEM:Women, Minorities, and Persons with Disabilities report states, “compared with data for othergroups, data on postsecondary degrees earned by persons with disabilities are limited” [1] and assuch, provides no data on disabled engineering undergraduate students and diminutive data ondisabled engineering doctoral students. Whether it be funding, available statistics, access, orsupport, the lack of care toward disabled students in engineering is apparent and intentional [12]–[16].This paper explores the availability of data for disabled students in postsecondary engineeringprograms
Affecting the Future Career Pathway Decisions of Lower-income Computing Students1. IntroductionWithin research on broadening participation in computing, the experience and perspectives ofundergraduate students have been important elements of exploration. As undergraduate studentsare experts of their own experience, conducting research that focuses on understanding theirperspective can help those who organize programmatic efforts to respond to student needs andconcerns. This paper emerges from the context of a specific National Science Foundation (NSF)-funded Scholarships in Science, Technology, Engineering, and Mathematics (S-STEM) program.As with all S-STEM programs, Florida Information Technology Graduation
, “Software Carpentry: Getting scientists to write better code by making them more productive,” Computing in Science & Engineering (CiSE), vol. 8, no. 6, pp. 66–69, Nov. 2006. [8] A. Simperler and G. Wilson, “Software Carpentry – get more done in less time,” arXiv:1506.02575, Jun. 2015. [9] B. K. Weaver, “The efficacy and usefulness of Software Carpentry training: A follow-up cohort study,” Master’s thesis, The University of Queensland, 2019.[10] A. Berg, S. Osnes, and R. Glassey, “If in doubt, try three: Developing better version control commit behavior with first year students,” in ACM Technical Symposium on Computer Science Education (SIGCSE), Feb. 2022, pp. 362–368.[11] V. Garousi, G. Giray, and E. T¨uz¨un, “Survey of the
+ stress OR Latin* student + stress OR Indigenous student + stress”, “Black student + distress OR Latin* student + distress OR Indigenous student + distress”, “Black student + trauma OR Latin* student + trauma OR Indigenous student + trauma.”To appropriately scope the literature review, we used multiple exclusion criteria. First, anyliterature focusing on faculty, graduate students, or postdoctoral students was omitted. Second,literature published before the year 2000 was excluded as much has changed in the field oftrauma studies since the 1990’s. Lastly, any guest editorials or conference proceedings that didnot include a paper were excluded from the literature review.After an initial search through the journal databases, we screened the
/10.1364/AO.32.001154.[2] P. K. Koech, M. Ogini, S. Mohan, A. Alice Francis, M. Deo, S. Albin, and K. B. Sundaram, “Characterization of Silicon Nanowires Reflectance by Effective Index Due to Air-Silicon Ratio,” ECS Transactions, 89(4), 17–30, 2019. https://doi.org/10.1149/08904.0017ecst[3] S. Patchett, M. Khorasaninejad, O, N., and S. S. Saini, “Effective index approximation for ordered silicon nanowire arrays,” Journal of the Optical Society of America B, 30(2), 306. 2013. https://doi.org/10.1364/josab.30.000306.[4] F. Kimeu, S. Albin, K. Song, and K. C. Santiago, “ALD-passivated silicon nanowires for broadband absorption applications,” AIP Advances, 11(6), 065101, 2021. https://doi.org/10.1063
factors were attributed to the nativelanguage being English (yes/no).Results and DiscussionTable 1 Breakdown of averaged Turnitin scores for each submission (S). Turnitin Scores (%) All YES Eng NO Eng YES Biol NO Biol YES Native NO Native S #1 20 ± 19 22 ± 12 15 ± 16† 20 ± 19 23 ± 19 14 ± 12 25 ± 21† S #2 14 ± 14* 13 ± 10** 10 ± 13* 12 ± 10** 19 ± 18† 10 ± 7** 17 ± 16**,†YES/NO refers to their background in: Biol = Biological Sciences, Eng = Engineering. *,**denotes statistically significant differences (t-test) between submissions (*p<0.05, **p<0.01); †between YES and NO categories (†p<0.01
. 4ReferencesAnderson, E.L., Williams, K.L., Ponjuan, L., & Frierson, H. (2018). The 2018 Status Report onEngineering Education: A Snapshot of Diversity in Degrees Conferred in Engineering, Association ofPublic & Land-grant Universities: Washington, D.C.Anzaldúa, G., & Moraga, C. (1981). This bridge called my back. New York: Kitchen Table.Conchas, G. Q., & Acevedo, N. (2020). The Chicana/o/x dream: Hope, resistance, and educationalsuccess. Harvard Education Press.Hurtado, A. (2003). Voicing Chicana feminisms: Young women speak out on sexuality and identity (Vol.1). NYU Press.McAlear, F., Scott, A., Scott, K., & Weiss, S. (2018). “Women and girls of color in computing.” Databrief. Kapor Center, 2018. Available: https://www.wocincomputing.org
Regional Education Board.Brophy, S., Klein, S., Portsmore, M., & Rogers, C. (2008). Advancing engineering education inP‐12 classrooms. Journal of Engineering Education, 97(3), 369-387.Gottfried, M. A., & Plasman, J. S. (2018). Linking the timing of career and technical educationcoursetaking with high school dropout and college-going behavior. American EducationalResearch Journal, 55(2), 325-361.Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do studentslearn?. Educational psychology review, 16, 235-266.Lynch, S. J., Peters-Burton, E., Behrend, T., House, A., Ford, M., Spillane, N., Matray, S., &Means, S. (2017). Understanding inclusive STEM high schools as opportunity structures forunderrepresented students: Critical
this work was provided by the USA National Science Foundation's ImprovingUndergraduate STEM Education (IUSE) program under Award No. 1836504. Any opinions,findings, and conclusions or recommendations expressed in this material are those of the authorsand do not necessarily reflect the views of the National Science Foundation.References[1] L. Gelles, S. M. Lord, G. D. Hoople, D. A. Chen, and J. A. Mejia, “Compassionate Flexibility and Self-Discipline: Student Adaptation to Emergency Remote Teaching in an Integrated Engineering Energy Course during COVID-19,” Education Sciences, vol. 10, no. 11, p. 304, 2020. https://doi.org/10.3390/educsci10110304[2] B. Momo, G. D. Hoople, D. A. Chen, J. A. Mejia, and S. M. Lord, “Broadening
of students. References[1] S. Olson and D. G. Riordan, "Engage to Excel: Producing One Million Additional College Graduates with Degrees in Science, Technology, Engineering, and Mathematics. Report to the President," Executive Office of the President, 2012.[2] A. W. Astin, "College retention rates are often misleading," Chronicle of Higher Education, vol. 40, no. 5, pp. A48-A48, 1993.[3] A. W. Astin, "What matters in college? Four critical years revisited," San Fran, 1993.[4] R. M. Hall and B. R. Sandler, "Out of the Classroom: A Chilly Campus Climate for Women?," 1984.[5] S. M. Lord, M. M. Camacho, R. A. Layton, R. A. Long, M. W. Ohland, and M. H. Wasburn
: Undergraduate Academic Policy Trends across Institutions over the Last Thirty Years INTRODUCTIONMIDFIELD (Multiple Institution Database for Investigating Engineering LongitudinalDevelopment) is a database, made up of multiple higher education institutions across the U.S.,which is intended to allow for the easy comparison of the institutions. The MIDFIELD databaseincludes data from the late 1980’s until present, which encompasses the SAT/ACT scores,students’ GPA and major for each semester, students’ attained degrees, year graduated, and otherpieces of data. However, in order to better understand the differences across institutions, anunderstanding of academic policies should be conducted
interested who transferred to Virginia Techfrom regional community colleges. To date we have interviewed 28 individuals, including fivefocus group participants. The pool includes 11 women, one (male) underrepresented student,seven first-generation college students, and 14 students who transferred from communitycolleges.AcknowledgementsThis material is based upon work supported by the National Science Foundation under GrantNumber 1734834. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation. We also wish to thank Ms. Claudia Desimone for help with data collection.References[1] M. Boynton, C. A. Carrico, H. M
GRIT with retention-to-graduation with the correlation of admissions variables to retention-to-graduation. Admissions variables were originally selected because they predict retention; the study will examine whether GRIT is more, less or additionally predictive of student success.Introduction“Let me tell you the secret that has led to my goals. My strength lies solely in my tenacity.”Louis PasteurThe Grit Scale was developed by Dr. Angela Duckworth in 20071 to measure the personalitytraits of perseverance and passion for long-term goals. In Duckworth 20092 The Short Grit Scale(Grit–S) was shown to have internal consistency, validity and improved psychometric properties.Various studies have associated GRIT, as measured by the Grit-S scale, with
‘selection’ (shown in yellow)or ‘non-selection’ (shown in pink) of renewable energy were described in a box. Figure 7. Group 1’s (girls) decision-making Figure 8. Group 2’s (girls) decision-making process in the first discussion
GPA at thetime of graduation.References1. S. Sorby, “Educational Research in Developing 3-D Spatial Skills for Engineering Students,” International Journal of Science Education, vol. 31, no. 3, pp. 459-480, 2009.2. J. Wai, D. Lubinski, and C. P. Benbow, “Spatial ability for STEM domains: Aligning over 50 years of cumulative psychological knowledge solidifies its importance,” Journal of Educational Psychology, vol. 101, no. 4, pp. 817-835, 2009.3. M. B. Casey, E. Pezaris, E., and R. L. Nuttall, “Spatial ability as a predictor of math achievement: the importance of sex and handedness patterns,” Neuropsychologia, vol. 30, pp. 35-40, 1992.4. D. Halpern, D., “Sex differences in cognitive abilities, Third Edition,” Mahwah, NJ