attention and assistance [17], while working-class children are encouraged to solveproblems independently, leading to a developing a sense of constraint with authoritative figures[18]. These studies reflect on the challenges that can hinder student participation in their learningenvironments.Gender is a significant factor when discussing group work. The effects of gender diversity onteams depend on the context, but including women in team collaboration and performancesgenerally has improved intelligence, social sensitivity, and conversation equity [20]. Increasingwomen’s participation in STEM fields can foster better processes and team productivity.Inclusivity in collaborative learning environments would encourage students to participate
impact.This paper explores two critical aspects of the RIDE Ecosystem: (1) the partnership ecosystem—how key stakeholders collaborate to bridge the gap between research and practicalimplementation—and (2) an initial framework for the RIDE model, outlining its core principlesand its potential for replication in other contexts. By examining the structure and impact of thesepartnerships, this paper seeks to provide reflective insights for equitable, community-drivenengineering initiatives and invite further engagement from academic institutions interested inhumanitarian engineering and sustainable development.The Partnership EcosystemA well-structured partnership ecosystem is essential for bridging the gap between research,innovation, and real-world
presented work was supported by the National Science Foundation under Grant No. DUE-1930282. Any opinions, findings, conclusions or recommendations expressed in this paper arethose of the authors and do not necessarily reflect the views of the National Science Foundation.6. References[1] Cybersecurity Supply/Demand Heat Map, https://www.cyberseek.org/heatmap.html. [Accessed April 25, 2025].[2] Bureau of Labor Statistics https://www.bls.gov./ooh/computer-and-information- technology/information-security-analysts.htm. [Accessed April 25, 2025].[3] B.S. in Cybersecurity, West Virginia University, https://admissions.wvu.edu/academics/majors/cybersecurity. [Accessed April 25, 2025].[4] Area of Emphasis in Cybersecurity, West Virginia University
-based survey. To maximize thenumber of participant responses received, students were encouraged to share the survey withtheir peers at the same university, following a snowball sampling approach. To further scope thefindings from this work-in-progress paper, only the first 977 responses were considered in theanalysis. Future work will reflect the entirety of the sample. All respondents who completed thesurvey were entered into a drawing for a $20 gift card. All recruitment and sampling procedureswere approved by the university’s IRB office.PopulationAll respondents to the questionnaire were students enrolled at a single Western University, withthe majority of respondents in the 18 – 23 age range. In total, 977 students responded to thesurvey
accurately reflected the interviews and research questions. Defining and naming Each theme was named appropriately and succinctly. These themes analyzed and organized themes were used to describe the experiences of Korean international students, including their decisions to study abroad and their current academic lives.Results We identified three core themes based on semi-structured interviews with the fourparticipants related to their major selection and experience in their college majors.Strong personal interest An inherent interest in computers was the primary reason the four participants chosecomputer-related majors
groups. I was pleasantly surprised to see that thestudents from class families continued to work together in the same groups. Many of them alsoinformed that they did internships together, registered for other courses together and this mademe realize the lasting impact of these early connections.Challenges and Improvements Along with the positive feedback, some challenges emerged. One student in the seniorclass reported feeling overburdened with work in the sophomore class as other class familymembers were not as cooperative and that student pulled a lot of weight for the weekly quizzesand lab reports. Unfortunately, this issue was not brought to my attention during that semester,which prevented timely intervention. Reflecting on this, I
materials to reflect their unique strengths and perspectives. Theprogram director played a critical role by assisting with extensions for scholars who had not yetsecured positions, ensuring they had the time and resources needed to transition successfully.This collective response to systemic failure underscores the importance of adaptability andsupport in postdoctoral programs. By combining mentorship, peer collaboration, and institutionalflexibility, the program not only supported individual scholars but also provided a model for howacademic institutions can mitigate the impacts of abrupt policy changes and systemic barriers.Faculty Development Division References[1] “DEI Legislation Tracker,” The
assemblebuilding structures of up to three stories using modular components that represent key structuralelements such as joists, beams, girders, and columns. Through this hands-on assembly, studentsare able to visualize how loads are transferred through the structure, bridging the gap betweenabstract 2D representations and three-dimensional real-world systems.The model was designed using SolidWorks CAD software to reflect realistic structuralrelationships and typical construction sequences. A 1:25 scale was selected to preserve spatialaccuracy while ensuring the components remain manageable in a classroom environment. Allparts were fabricated using a Bambu Lab P1P FDM 3D printer with black PLA filament, chosenfor its durability and high visual contrast
as the strategy advances to incorporate new findings and address shifting priorities. • The Applied AI Community of Practice involves faculty early adopters who actively investigate the potential of AI to enhance productivity, curriculum design, and pedagogy. Their evaluations of tools such as Microsoft 365 Copilot, as well as experiments with task-specific copilots and Copilot agents within courses, provide valuable insights for broader institutional adoption. The group's activities continuously adapt to reflect ongoing advancements in AI tools and educational practices.These efforts establish an initial foundation for MSOE’s rAIder strategy. The rAIder strategy isactively being implemented, and
”, which providesnot only an excellent pedagogy resources to educate next generation of engineers on conceptsrelated Industry 4.0., also an outstanding research infrastructure for Smart Manufacturing.AcknowledgementThis work was supported by a subaward from GENEDGE through the Department of Energy GrantNo. DE-MS0000029. 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 DOE andGENEDGE.Reference[1] MTConnect® Standard Part 1 - Overview and Protocol, Version 1.3.0, 2014[2] MTConnect®Standard Part 2 –Device Information Model, Version 1.3.1, 2015[3] https://pypi.org/project/requests/[4] https://pypi.org/project/xmltodict/[5] https://pypi.org
the National Science Foundation under Grant No.2229260. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the author(s) and do not necessarily reflect the views of the National ScienceFoundation.References[1] K. VanLehn, “The relative effectiveness of human tutoring, intelligent tutoring systems, andother tutoring systems, ” Educational Psychologist, vol.46, no. 4, pp. 197-221, 2.11.[2] A. Celepcikay, and Y. Yildirim, “Artificial intelligence and machine learning applications ineducation,” Eurasian Journal of Higher Education, vol. 2, no. 4, 2021.[3] X. Wang, N. Anwer, Y. Dai and A. Liu, “ChatGPT for design, manufacturing, and education,“Proceedings of the 33rd CIRP Design Conference, 2023, pp
Support and DisclaimerThis material is based upon work supported by the National Science Foundation under Grant No.2221638.Any opinions, findings, and conclusions or recommendations expressed in this material are thoseof the author(s) and do not necessarily reflect the views of the National Science Foundation.References[1] National Center for Education Statistics, "Back to school statistics." [Online]. Available: https://nces.ed.gov/fastfacts/display.asp?id=37#fr1. [Accessed: Jan. 2, 2025].[2] National Center for Education Statistics, "Undergraduate retention and graduation rates," U.S. Department of Education, NCES 2018-434, Feb. 2018. [Online]. Available: https://nces.ed.gov/pubs2018/2018434.pdf. [Accessed: Jan. 2, 2025].[3] Eris, O
based upon work supported by the National Science Foundation under Grant No.2220260. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References[1] U.S. Bureau of Labor Statistics, “Computer and information technology occupations,” Occupational Outlook Handbook [Online], 2020. Available: https://www.bls.gov/ooh/computer-and-informationtechnology/home.htm[2] Economic Modeling Specialists International, Occupation overview: 11 computer and information systems occupations in Miami-Dade County, FL, 2022.[3] Economic Modeling Specialists International, Job posting analytics: 11 computer and
also strengthen thequality of the relationship with their mentors and provide mentors with more insight into thepersonal background of the students. Students’ feedback will be taken into account to improvethe offered mentoring program going forward, and further feedback will be elicited from futurescholarship students to ensure the continuous improvement of the program.AcknowledgmentThis material is based upon work supported by the National Science Foundation under Grant #1742627. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References[1] N. L. Smith, J. R. Grohs, and E. M. Van Aken, “Comparison of
should be interviewed to better reflect challenges, needs, and successes.Conclusions and Next StepsThe collaborative and equitable ideation process in the FuSe Workshop to create betterworkforce development educational experiences resulted in a cohesive multi-university fundedprogram through NSF INCLUDES. A kickoff meeting, Faculty/Graduate mentorship trainingmeeting, and initial meeting with mentees occurred in the Fall semester. Challenges thus farincluded creating asynchronous methods of conveying information for a few participants withschedule conflicts; industry members and faculty mentors must find mutually acceptable ways toevaluate student experiences and skills beyond GPA; and finally, the experience of mentors andmentees should be
highlights how effective,targeted educational initiatives have the propensity to impact students in rural communities. Bybolstering student opportunity to explore STEM content and careers, the project was able tomove the needle on student STEM knowledge. As educators and policymakers look for ways tobridge the opportunity gap inherent for rural underserved students, DeSIRE can serve as a designblueprint for other programs.AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant No.1949454. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References[1] National Center
connectwith professors, more emphasis on government and industry work, and additional representationamong majors in the program. Participants largely reported feeling grateful to have participatedin the UK NRT program. In summary, UK NRT graduates reported experiencing a high-qualityeducation, having opportunities to practice technical and professional skills, making personal andprofessional connections, exploring multiple types of jobs, and particularly enjoying thetransdisciplinary nature of the program. One graduate reflected, “I think it’s important for peopleto interact with people that are outside of their immediate scope of influence because that’s theway it’s going to be throughout most of your career.”AcknowledgementThis material is based
State University.AcknowledgementThis work is supported by the National Science Foundation Grant EEC-2023275 and partiallyfunded by Grant 1953745. Any opinions, findings, conclusions, or recommendations expressedin this material are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation. We would also like to thank the leadership team, education team, and theevaluation team of all partner ERCs, for their support and participation in knowledge sharing,data collection, and offering constructive feedback.References[1] M. V. Melo de Lyra, A. Carberry, J. S. Larson, Z. Zhao, A. Godwin, A., W. Savenye, and C. Barr (2023). Design and Testing of a Quantitative Instrument to Evaluate Engineering
attrition was labeled as 1 and student persistence was denotedas −1. Figure 1b provides a detailed description of the overall training procedure.The classification results were assessed using common classification metrics, namely, accuracy(proportion of correct predictions made by the model across all instances, students who persistedand those who did not), recall or sensitivity (ratio of correctly identified at-risk students, empha-sizing model’s capacity to identify as many at-risk students as possible), precision (ratio reflect-ing model’s ability to minimize false alarms, e.g., 80% precision indicates that 8 out 10 studentsflagged by the model are actually at-risk), and f1-score (precision and recall harmonic mean). (a) Adopted undersampling
laboratories, automotive, energy,aerospace, and NASA. In the comments section of the survey, many reflected on the impact of their REUexperience, describing it as “a wonderful program that opened many doors to my career”; “incrediblyimpactful… many opportunities in networking and career development have been especially beneficial tome”; “REU was honestly one of the best parts of my undergrad for so many reasons…growing up shy andunconfident, the position helped me build confidence, interact with peers from other schools and helped mefeel much more confident when applying for first jobs in my career…”; “Honestly, I had a wonderfulexperience in the program and I wouldn’t have even been interested in research if I didn’t do this program!I’m in the
work andthe experiences that prepared them for their global job tasks (RQ3).AcknowledgementsThis material is based upon work supported by the National Science Foundation (EEC-2308607).Any opinions, findings, and conclusions or recommendations expressed in this material are thoseof the author(s) and do not necessarily reflect the views of NSF.References[1] J. M. Grandin and E. D. Hirleman, “Educating engineers as global citizens: A call for action / A report of the national summit meeting on the globalization of engineering education,” Online J. Glob. Eng. Educ., vol. 4, no. 1, pp. 1–28, 2009.[2] K. A. Davis and D. B. Knight, “Comparing students’ study abroad experiences and outcomes across global contexts,” Int. J. Intercult. Relat
succeed.This study's findings were obtained by grouping codes from the established codebook andconnecting related codes to the main themes. The central question of this study is why Blackstudents choose or are placed into engineering technology (ET) programs versus otherengineering programs.The choice of engineering major reflects students' initial interest in engineering, influenced byearly experiences and opportunities in STEM and the impact of high school staff. Programs likeProject Lead the Way (PLTW) and university-sponsored initiatives connected students to thePolytechnic College, influencing their decision to choose ET. High school advisors played alimited role in choosing, focusing more on graduation requirements than specific careerguidance
understandings while fostering the affective and motivationalfoundations for long-term engineering participation. As educators and policymakers work toaddress persistent inequities in engineering education, these findings point to the value ofdesigning interventions that intentionally connect students’ lived experiences while providinginteractive, culturally affirming learning environments.AcknowledgmentThis material is based upon work supported by the National Science Foundation under AwardNo. 2225306. 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] D. Bourland, “The Effects of an Agricultural Migratory
understanding, such as Q1 (My team hasgeneral ideas of specific team tasks) and Q3 (My team knows the relationship betweenvarious task components), consistently received high ratings, with the majority of studentsreporting “High” to “Very High”. This indicates that the MR-shared environment effectivelyenhanced the students’ shared understanding of task objectives and relationships betweencomponents. Additionally, questions addressing communication, such as Q11 (My teamcommunicates with other teammates) and Q28 (My team informs each other about 3different work issues), were similarly rated, reflecting the module’s success in allowing foropen and effective
-STEM program under awardnumber 2221696. 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] Arco-Tirado, J., Fern´andez-Mart´ın, F., and Fern´andez-Baloa, J.-M. (2011). The impact of a peer-tutoring program on quality standards in higher education. Higher Education, 62(6):773–788.[2] Bettinger, E. and Baker, R. (2014). The effects of student coaching an evaluation of a randomized experiment in student advising. Educational Evaluation and Policy Analysis, 36(1):3–19.[3] Conefrey, T. and Smyth, D. S. (2023, December 31). eportfolios to promote equity, engaged learning, and professional
were at acomparable point in their degree program. Of the 22 students in the two cohorts, 10 graduatedwithin 4 years, 10 are on track to graduate within 4 years while 2 are progressing toward degreecompletion within an extended timeline of 4.5 years. Key successes included full placement ininternships or research experiences, which proved to be vital for both professional and academicdevelopment. Additionally, graduates of the program achieved high rates of professionalplacement or entry into graduate programs. These outcomes underscore the program’s ability toeffectively prepare students for success in their careers or further education, reflecting the robustsupport and opportunities provided throughout their participation in the ECS Scholars
expressed inthis material are those of the authors and do not necessarily reflect the views of the NationalScience Foundation.We would like to thank all of the students who participated in this study, as well as the groupsthat helped us to distribute the study across institutions. We would also like to thank the ThriveLab community members and the Engineering Education graduate students at Virginia Tech whoprovided feedback on the survey. Lastly, we would like to thank our advisory board members,Drs. Ann McKenna, Holly Matusovich, and Joi-Lynn Mondisa, who provided invaluableguidance in the early stages of this study.References[1] L. L. Baird, “Helping graduate students: A graduate adviser’s view,” New Dir. Stud. Serv., vol. 1995, no. 72, pp
Program through Minnesota State University, Mankato. She has a Ph.D. in Engineering Education, an M.S.Ed. in Curriculum and Instruction - Science Education, and a B.S. in Materials Science and Engineering.Dr. Michelle Soledad, Virginia Polytechnic Institute and State University Michelle Soledad, Ph.D. is a Collegiate Assistant Professor in the Department of Engineering Education at Virginia Tech. Her research and service interests include teaching and learning experiences in fundamental engineering courses, faculty development and support initiatives – including programs for the future engineering professoriate, and leveraging institutional data to support reflective teaching practices. She has degrees in Electrical
assist us with addressing our remaining researchquestions over the last two years of the project. AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grant No.IIS-2302787 and IIS-2302788. Any opinions, findings, and conclusions or recommendationsexpressed in this material are those of the authors and do not necessarily reflect the views of theNational Science Foundation. References [1] Yuan, Y., Tang, X., Zhou, W., Pan, W., Li, X., Zhang, H. T., Han, D., & Goncalves, J. (2019). Data driven discovery of cyber physical systems. Nature communications, 10(1), 1-9. [2] Burke, R., Mussomeli, A., Laaper, S., Hartigan
meetingsor unsolicited advice when things are going well. Team advising data focuses on the first twoyears after enrollment, during which students work with peer and university advisors. Afterward,students are expected to develop self-efficacy and autonomy, though they retain access to a facultyadvisor (the same for all NSF scholars) for any questions. One university advisor noted mostinteractions occur when students struggle academically, highlighting that seeking advice onlywhen needed is acceptable. Some students engage with advisors more frequently than others,reflecting varied use of advising services.AcknowledgmentThis material is based upon work supported by the National Science Foundation under GrantNumber 2030731.References[1] Wendy G