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inglobal identity development have evolved over time. We also plan to expand the sample toinclude students from various academic disciplines and cultural backgrounds, that will enhancethe generalizability of the findings. Moreover, integrating qualitative methods, such as in-depthinterviews or focus groups, with the BEVI can provide richer, more detailed insights into theunderlying factors influencing gender differences in intercultural competence.References[1] A. J. Magana, T. Amuah, S. Aggrawal, and D. A. Patel, “Teamwork dynamics in the context of large-size software development courses,” Int. J. STEM Educ., vol. 10, no. 1, p. 57, Sep. 2023, doi: 10.1186/s40594-023-00451-6.[2] A. J. Magana, A. Jaiswal, T. L. Amuah, M. Z. Bula, M. S. Ud
Press, 2020.[2] R. Benjamin, Race after technology: Abolitionist tools for the new Jim code. Cambridge: John Wiley & Sons, 2019.[3] S. U. Noble, Algorithms of Oppression: How Search Engines Reinforce Racism. New York: NYU Press, 2018.[4] “U.S. Department of Education, Institute of Education Sciences, National Center for Education Statistics, National Assessment of Educational Progress (NAEP), High School Transcript Study (HSTS), 2019 Mathematics Assessment.” Accessed: Aug. 07, 2024. [Online]. Available: https://nces.ed.gov/[5] M. Williams, “Embracing Change Through Inclusion: Meta’s 2022 Diversity Report,” Meta, Jul. 19, 2022. Accessed: Aug. 16, 2024. [Online]. Available: https://about.fb.com/news/2022/07/metas
Interdisciplinary and Transdisciplinary Contributions,” TJES, vol. 1, no. 1, 2010, doi: 10.22545/2010/0003.[7] G. Tembrevilla, S. Nesbit, N. Ellis, and P. Ostafichuk, “Developing transdisciplinarity in first- year engineering,” Journal of Engineering Education, vol. 112, no. 1, pp. 43–63, 2023, doi: 10.1002/jee.20497.[8] A. Bruce, C. Lyall, J. Tait, and R. Williams, “Interdisciplinary integration in Europe: the case of the Fifth Framework programme,” Futures, vol. 36, no. 4, pp. 457–470, May 2004, doi: 10.1016/j.futures.2003.10.003.[9] M. Borrego and L. K. Newswander, “Characteristics of successful cross-disciplinary engineering education collaborations,” J Eng Educ, vol. 97, no. 2, pp. 123–134, 2008, doi
/10217/239771ATLAS.ti Scientific Software Development GmbH. (2024). ATLAS.ti Mac (version 24.0.0.29576) [Qualitative data analysis software]. https://atlasti.comBraun, V., & Clarke, V. (2021). One size fits all? What counts as quality practice in (reflexive) thematic analysis? Qualitative research in psychology, 18(3), 328-352. https://doi.org/10.1080/14780887.2020.1769238Braun, V., & Clarke, V. (2022). Thematic analysis: A practical guide. Sage Publishing.Brunhaver, S. R., Jesiek, B. K., Korte, R. F., & Coso Strong, A. (2021). The Early Career Years of Engineering: Crossing the Threshold Between Education and Practice. Engineering Studies, 13(2), 79-85. https://doi.org/10.1080/19378629.2021.1961570Cech, E
as academic performance and retention. ethodsMThis particular study is part of a larger project investigating “chosen family” in engineering education [9],[22]. Authors [22] describechosenfamilyas“person[s]outsideofthe[student’s] traditional family with individual or institutional power who genuinely and empathetically support and uplift [students] disrupting the [student’s] place amongst the structure- agency dialectic,andinturn,instillingastrongsenseofbelonging”(p.2-3).Inshort,chosenfamiliesare families students choose, who help the student enact agency in light of
ECE. Data was aggregated fromthe HSI’s Office of Institutional Analysis for the 2021-2022 academic year.increase their influence in the learning process and their success [10, 11]. However, research hasfound that a lack of sense of belonging is a determinant factor in a student’s decision to leaveengineering [12]. The relationships a student develops with their peers, teachers, and faculty canaffect that sense, influencing student performance, well-being, and the decision to stay/leave theirengineering program [13, 12]. The students who appear to have greater difficulty with their senseof belonging are those who are often underrepresented in the STEM/Engineering field(s), such aswomen or students with minoritized racial/ethnic identities [10
industry offers many tools to helpwith project management, planning, scheduling, and control, all of which strive to simplify the otherwisetricky and labor-intensive duties.The main objective of this study is to provide information on the Application of Primavera P6 withsimple examples for construction planning and scheduling courses at the institution of higher educationto prepare graduates using Primavera P6. Primavera P6 is one of the most well-known software programs for scheduling and constructionmanagement—Primavera P6's scalability, adaptability, and efficiency in managing intricate constructionprojects. Essential features include project scheduling, resource allocation, resource leveling, Projectmonitoring, and cost control.Primavera's
2.2 1.8 youtube.com/watch?v=vq956X1TC6UCM2 = Construction Matters 2 CFF = Construction Fast Facts Views are as of January 2025The first series is a single video exhibiting the multi-faceted roles within the transportationinfrastructure workforce by filming a single day of Interstate 269’s (I-269’s) construction, aswell as interviews with associated professionals off the construction site. The video highlightsdifferent backgrounds, interests, ethnicities, genders, and personalities so that any number ofaudience members could see themselves in at least one of those positions. The video alsohighlights the sheer number of jobs comprised within transportation infrastructure by showing 22examples. The I-269 video was made to be a
. Inside the air chamber is images. The minimum exposure time for our camera (1 ms)the Bluetooth module, which is visible in this image, and the was still significantly longer than the exposure timeSPS30, which is not. necessary to get clear images of the particles (~10 µs), so we instead took long, 1 s exposure images with a brief 10 µs The microscope (AMScope, B100, Irvine, CA) shown in flash of light provided by a light emitting diode (LED) toFig. 3 was used for the prototype. One reason was its high achieve an effective exposure time of
questions and refining their responses iter- for Responsible and Effective Usage IV. R ESULTS AND F INDINGS P OST-C OURSE S URVEY RESULTS . At the end of the semester, a follow-up survey was con- P RE -C OURSE S URVEY RESULTS . ducted to assess the impact of the AI integration framework To establish a baseline understanding of how students in the Algorithms and Complexity course.utilized AI tools and perceived their role in academic work, The survey evaluated changes in students’ perceptions,a survey was conducted at the
engineering student performance and retention. II. Rural/urban student differences,” Journal of Engineering Education, vol. 83, no. 3, pp. 209-217, 1994.[7] DeUrquidi, K. A. “Exploring the pathway of rural students into the engineering field,” Dissertation, Purdue University, School of Engineering Education, 2019.[8] Hynes, M. M., Mathis, C., Purzer, S., Rynearson, A., & Silverling, E. “Systematic review of research in P-12 engineering education from 2000–2015,” International Journal of Engineering Education, vol. 33, no. 1, pp. 453-462, 2017.[9] Knight, D., Bielefeldt, A., Polman, J., & Hannigan, M. “Design & Development: Colorado Science and Engineering Inquiry Collaborative,” Grant Proposal, National Science
of female Middle Eastern engineeringstudents, especially those who are Iranian. In this project, the student aims to explore women'scareer and academic challenges as well as their process of engineering identity formation. Thiswork is expected to offer recommendations for the creation of successful policies and programs toimprove the conditions of Middle Eastern women. These policies can support their success in theengineering field.Reference[1] S. J. Ceci, D. K. Ginther, S. Kahn, and W. M. Williams, “Women in Academic Science: A Changing Landscape,” Psychol Sci Public Interest, vol. 15, no. 3, pp. 75–141, Dec. 2014, doi: 10.1177/1529100614541236.[2] O. Bataineh, A. Qablan, S. Belbase, R. Takriti, and H. Tairab, “Gender Disparity in
-Champaign she • Leads the strategy enhancing the Grainger College of Engineering (GCOE)’s commitment to diversity, equity, inclusion, and access. • Develops robust structures to support faculty and staff appropriately to ensure an equitable, inclusive, and supportive workplace and learning community. • Collaborates with the Associate Dean (AD) to 1) define strategic priorities and examine policies, and 2) develop DEI goals and objectives for the College and its units. • Utilizes data collection and analysis to identify challenges, enhance transparency, establish accountability measures, propose effective solutions, and define metrics for evaluating progress within the college’s units and other assigned areas. • Leads and
. Crafted by S2D participantswith the support of writing coaches, personal statements written during the program reflectparticipant stories and the effectiveness of programming and staff. The exit survey providesfeedback on programming from the participant perspective which will help administrators takesteps toward enhanced curriculum building. Currently, research is being conducted to performpost program analysis. The research details where past S2D participants are now, how S2Dcontributed to their academic journeys, and which component(s) of past S2D programming pastS2D participants found most useful. Post program analysis provides administrators with insightregarding long term outcomes of S2D programming.BiasTwo types of bias to be highlighted
theProfessoriate (AGEP) Program Solicitation." NSF21-576, 2021. [Online]. Available:https://www.nsf.gov/pubs/2021/nsf21576/nsf21576.pdf[19] P. Felder, "On Doctoral Student Development: Exploring Faculty Mentoring in the Shapingof African American Doctoral Student Success." Qualitative Report, vol. 15, no. 2, 2010, pp.455-474.[20] R. W. Lent and S. D. Brown, (2019). “Social cognitive career theory at 25: empirical statusof the interest, choice, and performance models.” J. Vocat. Behav, 115, 2019. doi:10.1016/j.jvb.2019.06.004[21] R. W. Lent, H.-B. Sheu, M. J. Miller, M. E. Cusick, L. T. Penn, and N. N. Truong,“Predictors of science, technology, engineering, and mathematics choice options: A meta-analytic path analysis of the social–cognitive choice model
faculty, administrators, andcoordinators of peer mentoring programs to re-examine the support structures for their mentorsand seek action to further improve these experiences.References[1] J. H. Lim, P. T. Tkacik, S. Dika, B. P. Macleod, “Peer mentoring in engineering: (un)sharedexperience of undergraduate peer mentors and mentees”, Mentoring and Tutoring: Partnershipin Learning, vol. 25, no. 4, pp. 395-416, Nov. 2017, doi: 10.1080/13611267.2017.1403628[2] L. Mohandas, N. Mentzer, A. Jaiswal, S. Farrington, “Effectiveness of UndergraduateTeaching Assistants in a First-Year Design Course”, Presented at the 2020 ASEE Virtual AnnualConference Content Access, [Online], June 2020, doi: 10.18260/1-2--34503[3] Q. Tahmina, “Assessing the Impact of Peer
was taken once a steady state was reached. For batch tests, thepressure was increased once the data for the desired pressure value had been taken. Heat Source I T1 I TH n n s s u T2 u l l a a Speciment
VI. REFERENCES [1] Rose, S. J., Allen, D., Noble, D., & Clarke, J. A. (2017). Quantitative analysis of vocalizations of captive Sumatran tigers (Panthera tigris sumatrae). Method Accuracy False False Processing Bioacoustics, 27(1), 13–26. https://doi.org/10.1080/09524622.2016.1272003 Positives Negatives Time [2] X. Kong, D. Liu, A. Kathait, et al., "Behavioral-psychological motivations encoded in
Mathematics Teacher artin High School STEM Academy, Arlington ISD M Abstract s part of UT Arlington’s Research Experience for Teachers (RET) in Engineering and ComputerAScience program, K-12 STEM teachers participated in research with the UTA faculty and graduate students with the goal to translate this research experience into classroom activities that will broaden the student’s awareness of participation in computing and engineering pathways. High school teachers C. Lugo from Fort Worth ISD and M. Treadway from Arlington ISD researched with Dr. K. Hyun, Civil Engineering, UT Arlington and graduate students, A. Imran, and M
Networks Curve Fitting”, 2024. (Last accessedproduct, besides data science statistical computation as an AI March 2025) https://lucidar.me/en/neural-networks/curve-fitting-product? The Students’ responses: data collection automation nonlinear-regression/is AI (8 out of 8)[4] J. Wittenauer, “Neural Newo rks”, 2016. (Last accessed Feb 2025) (Last [10] J. Sohl-Dickstein, E. Weiss, N. Maheswaranathan, and S. Ganguli. accessed Feb 2025) https://www.johnwittenauer.net/machine-learning- “Deep Unsupervised Learning using Nonequilibrium Thermodynamics”, exercises-in-python-part-6/ 2016 https://arxiv.org/abs/1503.03585[5
-source GNU Radio software, and SDR hardware such as ADALM Pluto, along with affordable benchtop equipment, enhances learning and understanding of key concepts. REFERENCES [1] “Modern Digital and Analog Communication Systems”, B.P. Lathi and Zhi Dong, Oxford University Press, Fifth Edition, 2019. [2] Pierre, J., & Hossain, M. S., & Hosur, S
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Stability for Fiber-Optic Mach-Zehnder Interferometer Filter”, 3rd International Conference on Microwave and Millimeter Wave Technology Proceedings, 0-7803-7486-/X/02, pp. 1087-1089, 2002.3. Vizoso Beatriz, Vazquez Carmen and Civera Rafael, “Amplified Fiber-Optic Recirculating Delay Lines” IEEE Journal of Lightwave Technology, Volume 12, No. 2, pp 294-304, February 1994.4. M. Ferdjallah and H. Bouchareb, “A New Synthesis Procedure for Designing Digital Filters Based on Optical Fiber Structures”, ASEE North Central Section Conference, Morgantown WV, 2023, March 24-25, 2023.5. D. Fye, " Practical limitations on optical amplifier performance," IEEE J. Lightwave Tech. 2,403-406 (1984).6. S. S. Wagner
processingtime stamps without user intervention), plot the data, allow users to select the portion of data tobe analyzed, determine a time constant using one or more methods, and visually display thetheoretical response(s) on the same plot as the experimental data. Furthermore, in order toaccommodate all students using the tool on their computers simultaneously if desired, the toolshould not rely on proprietary software to which the students do not have free access.To meet these objectives, the author created the TC Tool as a graphical application on the GNUOctave platform. GNU Octave is free to download and use, is available on multiple operatingsystems, and has graphical interface capabilities; and the author was already comfortable writingprograms in
totalsto visually observe the relationship between the variables and found a positive, monotonicrelationship (Figure 1). We calculated Spearman’s correlation coefficient using the ranks of thetotals and found a moderate positive correlation between the variables (r s=0.59). Mostrespondents had a favorable disposition to diversity, equity and inclusion, on both the personaland professional scales.Items that scored least favorably (i.e., average scores less than 3.5 on the scales are summarizedin Table 4. The table shows that faculty hold less favorable personal and professional beliefsabout linguistic differences; this may infer that respondents place English learning as a priority inand outside the classroom. The table also shows that faculty hold
/. [Accessed 22 Dec. 2024].[16] C. DellaMea, "Appalachian Coal Fields," CoalCampUSA, [Online]. Available:https://coalcampusa.com/nowv/index.htm. [Accessed 20 Dec. 2024].[17] B. Lego and J. Deskins, "Coal production in West Virginia: 2017-2040.," West VirginiaUniversity, 2017.[18] R. Pollin, J. Wicks-Lim, S. Chakraborty and G. Semieniuk, "Impacts of the ReImagineAppalachia and Clean Energy Transition for West Virginia: Job Creation, Economic Recovery,and Long-Term Sustainability-Summary. In ReImagine Appalachia: Healing," ReImagineAppalachia: Healing the Land and Empowering the People, pp. 445-461, 2024.[19] West Virginia Office of Energy, "Renewable Energy," West Virginia Office of Energy,[Online]. Available: https://www.energywv.org/wv-energy-profile
. Texas Semiconductor Leadership. Texas Economic Development, Texas Governor’s Office. Accessed: Jan. 1, 2024. [Online]. Available: https://gov.texas.gov/business/page/texas-semiconductor-leadership2. Ash, A. J., & Stine, J. E., & Dyke, E., & Hu, J. (2024, June), Board 422: What Does It Take to Implement a Semiconductor Curriculum in High School? True Challenges and The Teachers’ Perspectives Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2—470123. Adams, S., & Vargas, C. E., & Hynes, M. M., & Douglas, K. A., & Bermel, P., & Ely, D. R., & Grisez, H. J. (2024, June), Evaluation of High School Semiconductor and Microelectronics Summer Program
-gemini- claude-meta-ai-which-is-the-best-ai-assistant-we-put-them-to-the-test [4] Vox, “Deepseek is bad for silicon valley. but it might be great for you.” 2025, accessed: Feb. 2, 2025. [Online]. Available: https://www.vox.com/technology/397330/deepseek-openai- chatgpt-gemini-nvidia-china [5] D. A. R. Team, “Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning,” arXiv, 2025, https://arxiv.org/abs/2501.12948. [6] L. S. Maia and G. A.ˆ B. Lima, “A semantic-relations taxonomy for knowledge representa- tion,” Brazilian Journal of Information Science, no. 15, p. 23, 2021. [7] Z. Wang, S. Peng, J. Chen, X. Zhang, and H. Chen, “Icad-mi: Interdisciplinary concept association discovery from the