caring that includes both comfortwith faculty and empathetic faculty understanding from the same author.Discrimination (25 items)Discrimination is an active process that influences belonging in engineering (McGee, 2020). Toaccount for this potential, we adapted and included five items across five different identity-axes(race/ethnicity, gender, sexual orientation, (dis)ability, and socioeconomic status) from Bahnsonet al.’s (2022) work on discrimination in engineering graduate student experiences.Comfort and Team Inclusion (19 items)We believe feelings of discrimination and differences in belonging are also seen through students’comfort and inclusion on their team. As such, we included items based on these topics. Like othersabove, these scales
influenced by. Like individual socioeconomics,these characteristics reflect hierarchical social and economic ranking amongst people. Importantly,they reflect Keynes (1936) argument that socioeconomics are group mentalities that organizepeople’s positions amongst society. Keynes (1936) illustrated that individuals with similar incomeslive together (household) or near one another (neighborhood/school) and likely have a similaroccupation. Given these features, we consider the following relational socioeconomic factors:1. Family/household income, occupation, and education are representations of the total, combinatory income(s), prestige, or educational status of the household. Household socioeconomic status has also been inferred based on what
of universities is another task al-together that’s equally important. By building upon continued efforts, future directions can drivemeaningful progress toward equity in STEM education. Such efforts will ensure that STEM fieldsaccurately reflect the overall diversity of the population as a whole, as well as create innovationand excellence for every student engaging in STEM curriculum.AcknowledgeThis work is supported in part by the National Science Foundation (NSF) under Grant No. 2301868and the National Institute of Food and Agriculture (USDA NIFA) Grant No. 2023-70020-40570 .References [1] S. R. Howe, “Culture at work: A comparative analysis of advertising for
ConclusionThis paper presents preliminary work of the implementation of object detection on Raspberry Pi for asenior design project. We run a mobile deep learning model, SSD-MobileNet, on Raspberry Pi todetect various objects. Preliminary valudation results demonstrate the effectiveness of thisimplementation. Moreover, the on-going work is to improve weapon detection. Future work will focuson completing comprehensive and systematical validation on weapon detection in different testingscenarios. References1. Dave, E. (2011). How the next evolution of the internet is changing everything. The Internet of Things.2. Islam, S. R., Kwak, D., Kabir, M. H., Hossain, M., and Kwak, K. S. (2015). The internet
particular, researchers performanalyses of the environments associated with a microgreens market using a PESTLE framework –which identifies the political (P), economic (E), sociocultural (S), technological (T), legal (L), andenvironmental (E) forces influencing a market. The political environment (P) is favorable towardsincreased microgreen production. For example, the Farm Bill of 2018 provided the USDA’s NationalInstitute of Food and Agriculture with up to $10 million of annual funding toward a competitive grantprogram supporting the development of urban, indoor, and emerging agriculture practices (USDA)2.The economic environment (E) is perceived to be favorable for a microgreens market. Microgreenstrade at a premium when compared to other
of the 2022 ASEE Gulf-Southwest Annual Conference Prairie View A&M University, Prairie View, TX Copyright © 2022, American Society for Engineering Education 7 References1. Sumarni, S., 2016, "Think Pair Share effect of understanding the concept and achievement," in Proceeding of the International Conference on teacher Training and Education, Vol. 2, No. 1, pp. 783-787.2. Deshpande, A. and Salman, B., 2016, "Think-pair-share: application of an active learning technique in engineering and construction management classes," in Associate Schools of Construction, 52nd
) further narrowing the list down to a “short list” for an on-site, in-personinterview, 5) deciding which candidate(s) will receive an offer, and 6) negotiation. In somecases, steps three and four are skipped, and only one round of interviews is completed. The faculty hiring process is fraught with bias, including racial bias [1], gender bias inletters of recommendation [2], and search committee members seeking to hire people whoseresearch areas are most similar to their own [3]. Hiring people similar to oneself extends beyondresearch areas. Many search committees look for candidates who would be a good “fit”(generally, scientifically, programmatically) [4, 5]. However, “fit” is highly subjective and opento the evaluator’s personal biases
. Review of General Psychology, 19(4), 408–424. https://doi.org/10.1037/gpr00000536. Graham, J., Nosek, B. A., Haidt, J., Iyer, R., Koleva, S., & Ditto, P. H. (2011). Mapping the Moral Domain. Journal of Personality and Social Psychology. https://doi.org/10.1037/a00218477. Clancy, R. F. (2021). The Relations between Ethical Reasoning and Moral Intuitions among Engineering Students in China. 2021 ASEE Virtual Annual Conference Content, July 2021.8. Graham, J., Haidt, J., & Nosek, B. A. (2009). Liberals and Conservatives Rely on Different Sets of Moral Foundations. Journal of Personality and Social Psychology, 96(5), 1029–1046. https://doi.org/10.1037/a00151419. Graham, J., Meindl, P., Beall, E., Johnson, K. M., & Zhang, L
-thematic in the design and decision-making process [14]. Moreover, the proposed holisticengineering design education prevailing over the restricted use of key technical macro-thematicfactors, allow for the design of equitable and inclusive solutions through the consideration of thediverse influences associated with the project. This is an especially critical feature given that keytechnical macro-thematic factors used for traditional engineering design may be developed basedon specific group(s) of our society. Therefore, not accounting for the uniqueness and diversity thatlocal-thematic may impose, and even demand, from the respective solution, e.g., Smart Gridprojects for a high- and low- income regions significantly differ on its design features
National Science Foundationunder Grant No. 1943811. Any opinions, findings, and conclusions or recommendationsexpressed in this material are those of the author(s) and do not necessarily reflect the views ofthe National Science Foundation.References[1] Josiam, M., Lee, W., Johnson, T., Pee, C., & Hall, J. (2022, August). Beyond Selecting aMethodology: Discussing Research Quality, Ethical, and Equity Considerations in QualitativeEngineering Education Research. In 2022 ASEE Annual Conference & Exposition.[2] D. M. Cable and J. R. Edwards, “Complementary and supplementary fit: A theoretical andempirical integration.,” Journal of Applied Psychology, vol. 89, no. 5, pp. 822–834, 2004.[3] P. M. Muchinsky and C. J. Monahan, “What is person
to feel comfortable with both their peers and their TA tobe able to recover from a setback quickly. 1. Student experiences a setback (lab does not go as planned). 2. Student looks to a) lab partner(s) or peers, and/or b) TA, and/or c) class and lab materials to decide how to respond. 3. Student's ability to move past the setback depends on whether a) others experience the same setback, b) others normalize setbacks, and c) they know where to look to help them troubleshoot. These factors impact whether they can effectively manage their frustration in the moment.Figure 1. Student Response to Setbacks in Lab Settings FlowchartConclusion To summarize, students’ ability to recover from
focus groups to understand participants’lived experiences around identity-mediated interest changes and enrollment choices. Thelongitudinal element of this work allows us to evaluate when a new interest was identified andthe choice(s) participants made regarding pursuing that interest as these two elements often donot occur in the same semester. A singular data point would not fully capture the story ofchanging interests and choices, rather we utilize focus group data from participants’ first sixsemesters in an undergraduate engineering program. Data were analyzed using directed contentanalysis to support the exploration of the phenomenon while allowing for the integration of atheoretical framework including identity and interest. Matrix
Practices and Processes,” Hollylynne S. Lee etel. developed a framework using the work of statistics educators and researchers to investigatehow data science practices can inform work in K–12 education. Their framework buildsfundamental practices and processes from data science [19]. The math field has contributed to data science research via the Common Core StateStandards Initiative (CCSSI), which is a joint project to develop common K–12 reading andmath standards designed to prepare students for college and careers. The CCSSI includes a datascience section for elementary students that focuses on data collection, data type, function,analysis type, and sample [20]. Similarly, the Launch Years Data Science Course Frameworkprovides broad
the career development of women. Journal of Vocational Behavior, 18(3), 326–339. https://doi.org/10.1016/0001- 8791(81)90019-1 [4] Hurst, M. A., Polinsky, N., Haden, C. A., Levine, S. C., & Uttal, D. H. (2019). Leveraging research on informal learning to inform policy on promoting early stem. Social Policy Report, 32(3), 1–33. https://doi.org/10.1002/sop2.5 [5] Removed for Double Blind Review [6] Lester, S., & Ruth, K. D. (2022, August). ’ook Who's Talking: Exploring the DEI STEM Librarianship Conversation. In 2022 ASEE Annual Conference & Exposition. [7] Roy, J. (n.d.). Engineering by Numbers - ira | ASEE. ASEE. Retrieved February 8, 2023, from https://ira.asee.org/wp-content/uploads/2019/07/2018
. How well this process is conducted is the primary focus of quality in narrative research.Indicators of Quality in Narrative SmoothingRecent work has sought to establish frameworks capable of assessing the quality of qualitativeresearch methods. In line with Walther et al.'s work, we define quality interpretative research asresearch that is "idiographic in nature, in that it emerges from the unique perspective ofindividuals or groups but is transferrable to and meaningful for other contexts" [22]. We findgreat utility in tools such as Walther & Sochacka’s Q3 framework, which provides a versatileguide for implementing quality across various qualitative methods[23] . Tools such as this helpresearchers assess how they produce and manage
professional development model as a lens.Participants were nine sixth grade science teachers from three rural and Appalachian schoolsystems who engaged in the first year of the VT-PEERS project. The participants wereinterviewed prior to the first intervention activity, at the end of the first academic year, observedduring interventions, and asked to fill out an online questionnaire to capture their demographicinformation. The interviews lasted approximately 30-minutes. Pertinent questions for thisanalysis were: “What influenced your decision to participate in this project?”; What role(s) doyou expect to have during this collaboration?”; “What role(s) do you expect other partners(Industry or University) to have?”Through open coding (Miles, Huberman
/sunday/the- asian-advantage.html[2] D. E. Naphan-Kingery, M. Miles, A. Brockman, R. McKane, P. Botchway, and E. McGee, “Investigation of an equity ethic in engineering and computing doctoral students,” Journal of Engineering Education, vol. 108, no. 3, pp. 337–354, 2019, doi: 10.1002/jee.20284.[3] National Science Board, “The State of US Science and Engineering 2022,” National Science Foundation, Alexandria, VA, 2022. Accessed: Dec. 02, 2022. [Online]. Available: https://ncses.nsf.gov/indicators[4] L. D. Patton and S. Bondi, “Nice white men or social justice allies?: using critical race theory to examine how white male faculty and administrators engage in ally work,” Race Ethnicity and Education, vol. 18, no. 4, pp. 488–514
]. Founded in 2013, the focus of this capstoneprogram is to develop innovative technical solutions to pressing clinical and translational healthchallenges. Undergraduate and graduate students across engineering disciplines (e.g.,mechanical, electrical, biomedical, chemical, and materials science) are partnered with healthprofessionals (e.g., physicians, nurses, dentists, therapists, pharmacists) to solve unmet healthchallenges. In the first quarter, teams of 3–5 students work closely with the health professional(s)who originally proposed the unmet health challenge to develop a deep understanding of theunmet health need, including potential markets, stakeholder psychologies, prior solutions,intellectual property considerations, regulatory
collection. Through GORP, the observer can select codes forobserved classroom activity for both the instructor(s) and students. Observations are coded in 2-minute intervals until the class session is over. If the observer makes a mistake, they can note itduring the next interval, and adjust the data accordingly by hand, after class. Data isautomatically analyzed in GORP and can be exported to a spreadsheet for further analysis.The COPUS evaluation process was also part of the development of this Work-in-Progress. Wefollowed the clustering convention put forth by Stains et al. [86] in order to better capture thebroader types of instructor and student behaviors that we were interested in at this stage in thestudy -- who's talking, who's working, who's
informstheir presentation.Acknowledgement: This material is based upon work supported by the National ScienceFoundation under Grant #s 1758317 and 1339951.Disclaimer: Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.References[1] R. W. Bybee, Case for STEM Education: Challenges and Opportunities, Arlington, VA, USA: National Science Teachers Association, 2013.[2] United States Department of Education, Fundamental Change: Innovation in America’s Schools Under Race to the Top, Washington, DC, USA, Nov. 2015. Available: https://www2.ed.gov/programs/racetothetop/rttfinalrptfull.pdf[3] United
information about the program and its successes at a wide variety ofconferences and meetings. A list of such presentations is given in Appendix B for the readerwho would like more detailed information about a particular aspect of STEER. The reader isalso encouraged to contact members of the leadership team directly.AcknowledgementThis project was supported in part by National Science Foundation IUSE grant No. DUE-1525574. We are grateful to the Office of Decision Support at the University of South Floridafor the permission to publish the course and institutional data presented here.References[1] G. Meisels, R. Potter, P. Stiling, J. Wysong, and S. Campbell, “Systemic transformation ofevidence-based education reform (STEER),” 2019 ASEE Annual
the author(s) and do not necessarily reflect theviews of the National Science Foundation.References[1] I. A. Toldson, I, “Why historically black colleges and universities are successful with graduating black baccalaureate students who subsequently earn doctorates in STEM (editor’s commentary),” J. Negro Educ., vol. 87, no. 2, pp. 95–98, 2018.[2] R. Winkle-Wagner and D. L. McCoy, “Feeling like an “Alien” or “Family”? Comparing students and faculty experiences of diversity in STEM disciplines at a PWI and an HBCU,” Race Ethn. Educ., vol. 21, no. 5, pp. 593-606, 2018.[3] R. T. Palmer, R. J. Davis, and T. Thompson, “Theory meets practice: HBCU initiatives that promote academic success among African Americans
students and faculties to understand the mindset behindthis project.https://engineeringunleashed.com/card/2479References:Adusumilli, P. S. et al. (2004) ‘Left-handed surgeons: Are they left out?’, Current Surgery, 61(6), pp. 587–591. doi: https://doi.org/10.1016/j.cursur.2004.05.022.Axt, J. R. and Lai, C. K. (2019) ‘Reducing discrimination: A bias versus noise perspective.’, Journal ofPersonality and Social Psychology. Axt, Jordan R.: Social Science Research Institute, Duke University,334 Blackwell Street #320, Durham, NC, US, 27701, jordan.axt@duke.edu: American PsychologicalAssociation, pp. 26–49. doi: 10.1037/pspa0000153.Blaser, B., Steele, K. M. and Burgstahler, S. E. (2015) ‘Including universal design in engineering coursesto attract diverse
://magazine.scienceforthepeople.org/vol22-1/lessons- from-the-long-sixties-for-organizing-in-tech-today/.Arcia, A., Suero-Tejeda, N., Bales, M. E., Merrill, J. A., Yoon, S., Woollen, J., & Bakken, S. (2016). Sometimes more is more: iterative participatory design of infographics for engagement of community members with varying levels of health literacy. Journal of the American Medical Informatics Association, 23(1), 174-183.Atman, C. J., & Bursic, K. M. (1998). Verbal protocol analysis as a method to document engineering student design processes. Journal of Engineering Education, 87(2), 121–132.Atman, C. J., Adams, R. S., Cardella, M. E., Turns, J., Mosborg, S., & Saleem, J. (2007). Engineering design processes: A comparison of students and expert
attention to such detail inEnvironmental is listed as one of the “Elite Eight” realistic the engineering design projects in future years? Theconstraints, but its listing within the CSM draws the authors hypothesize that the early introduction of thesefollowing distinctions based on the source, where “T-4” is the concepts will have a lasting affect throughout thecode for the technically-sourced attribute, and “S-3” is the remaining years of the student’s engineering program.code for the societally-sourced attribute:• [T-4. Environmental] Can the operational environment REFERENCES negatively impact the product through normal use? [1] ABET
a secondoffering is planned for 2017 albeit with a more accessible project.References1. Goldman, S., & Carroll, M., & Zielezinski, M. B., & Loh, A., & Ng, E. S., & Bachas- Daunert, S. (2014, June), Dive In! An Integrated Design Thinking/STEM Curriculum Paper presented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana.2. Biggers, M., & Haefner, L. A., & Bell, J. (2016, June), Engineering First: How Engineering Design Thinking Affects Science Learning Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana.3. Menold, J., & Jablokow, K. W., & Kisenwether, E. C., & Zappe, S. E. (2015, June), Exploring the Impact of Cognitive Preferences on