ateam. The MRP roles include the team and students, engineering expert(s), the client(s) andbusiness expert(s). There are strong evidences form the literature that including the soft skillssuch as management, entrepreneurship and leadership can boost the retention and enrollment inengineering programs. Entrepreneurship education has been found to boost GPA and retentionrates of the engineering students, provides the students with the skills and attitudes needed toinnovatively contribute to the existing organizations and pursue their own ventures, and has thepotential to address current and anticipated workforce demands. We strongly believe that byintegrating entrepreneurship into engineering courses, specifically in the ones that are
results were summarized in [29] as follows. A majority of the respondents thought that theirpromotion was a result of their hard work alone. Half of the respondents indicated that theirprogress might have been easier if they were male, and half of them stated that children were ahindrance to progress. Female students were largely prevented from pursuing higher education until the 19thcentury. Before then, female seminaries were the primary alternative for women who wished toearn a higher degree. However, women’s rights activists fought for higher education for femalestudents, and college campuses turned out to be fertile ground for gender equality activism [30].In the early 1900’s, at the University of London, all degrees were available to
Evaluation Association affiliate organization and is a member of the American Educational Research Association and American Evaluation Association, in addition to ASEE. Dr. Brawner is also an Exten- sion Services Consultant for the National Center for Women in Information Technology (NCWIT) and, in that role, advises computer science and engineering departments on diversifying their undergraduate student population. She remains an active researcher, including studying academic policies, gender and ethnicity issues, transfers, and matriculation models with MIDFIELD as well as student veterans in engi- neering. Her evaluation work includes evaluating teamwork models, broadening participation initiatives, and S-STEM and
the knowledge and skills that student veterans bring to higher education and toengineering education.23Following Minnis and Wang’s research on military veterans’ career decisions17 and Musgrove’sinvestigation of career planning of military veterans enrolled in college,24 our study draws onSampson et al.’s Cognitive Information Processing (CIP) approach to career intentions anddecision making.25 This theoretical framework has been used to better understand veterans’transitions into the workforce.20 Our student interviews highlight how two elements of thisapproach, Developing Self-Knowledge and Building Occupational Knowledge, may apply toSVE’s decision to enter the engineering education pathway. As a foundational step, developingself-knowledge
, “Students’ agency beliefs involve how students see andthink about STEM as a way to better themselves and the world along with being a critic ofthemselves and science in general [20, p. 939]. The critical thinking perspective is intimately tiedto engineering agency beliefs, where students become “evaluator[s] of STEM as well as becomecritics of themselves and the world around them through self-reflection” [39, p. 13]. In essence,agency beliefs in this framework are based on a spectrum of how students view engineering as away to change their world or the world at large.Most agentic frameworks in engineering education used qualitative research methods. However,Godwin and colleagues [40] and Verdín and Godwin [41] used quantitative measures to
found allthree cost subscales were significantly and negatively related with students’ intentions to persistin science, with the effort subscale having the strongest negative relationship with persistence.Informed by Perez et al.’s evidence of potential multidimensionality of the cost construct, Flakeet al.21 developed a new cost scale intended for broader use in an academic context. Similar tothe scale developed by Perez and colleagues, Flake et al.’s scale included task effort, loss ofvalued alternatives cost, and emotional cost. Flake et al. also suggested a new dimension, thecost of outside efforts, related to other demands on an individuals’ time and energy that mayincrease the cost associated with a particular task. Their preliminary
design.However, some educators have described an important empathic requisite or antecedent:designers must adopt a user-centric mindset. For example, Postma et al. discussed moving designstudents from an “expert” mindset, where the designer thinks they know best, to a “participatory”mindset, where the designer perceives their self and user(s) both as experts.48 Forming thismindset is important, as student designers who hold an expert mindset tend to exclude theirproject partner throughout a design process.49 Hence, educators ought to prompt students to thinkabout engineering with a user as opposed to for a user12,50 as this may catalyze the utilization ofempathy while simultaneously alleviating absolutist/positivistic biases.414.2 Service
Services at Utah State University. Her research centers the intersection identity formation, engineering culture, and disability studies. Her work has received several awards including best paper awards from the Journal of Engineering Education and the Australasian Journal of Engineering Education. She holds a Ph.D. in Engineering Education from Virginia Tech as well as M.S. and B.S. degrees in civil engineering from the South Dakota School of Mines and Technology.Dr. Bruk T Berhane, Florida International University Dr. Bruk T. Berhane received his bachelorˆa C™s degree in electrical engineering from the University of Maryland in 2003. He then completed a masterˆa C™s degree in engineering management at George
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
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