session lasted for more than an hour. Session 1’s duration was 86minutes, Session 2 lasted for 78 minutes, and Session 3 lasted for 74 minutes. A total of 238minutes (3 hours 180 minutes) worth of qualitative data was obtained. 3.4. Data AnalysisThe qualitative data was prepared, cleaned, and subjected to the MMCS analytical approachstarting with the thematical analysis [33]. The thematic analysis involved open coding,allowing for the initial identification and labeling of significant concepts within the data [34],[35], [36]. Subsequently, the generated codes were organized into meaningful categories,laying the foundation for the development of coherent themes that encapsulate the essence ofthe data. Next was to develop the teamwork or team
] S. Negash, “Business intelligence,” Communications of the association for information systems, vol. 13, no. 1, p. 15, 2004. [5] S. Siuly and Y. Zhang, “Medical big data: neurological diseases diagnosis through medical data analysis,” Data Science and Engineering, vol. 1, pp. 54–64, 2016. [6] D. A. Jenkins, M. Sperrin, G. P. Martin, and N. Peek, “Dynamic models to predict health outcomes: current status and methodological challenges,” Diagnostic and prognostic research, vol. 2, no. 1, pp. 1–9, 2018. [7] J. Chen, K. Li, H. Rong, K. Bilal, N. Yang, and K. Li, “A disease diagnosis and treatment recommendation system based on big data mining and cloud computing,” Information Sciences, vol. 435, pp. 124–149, 2018. [8] L. Sun, C. Liu
Republic). 8Participants primarily described the technical or disciplinary skills and knowledge they appliedto developing and implementing the project when asked “What contribution(s) did you make tothe MOM program?” These skills included clinical skills, public speaking, data collection andanalysis, language translation, and lesson planning and delivery. The skills highlighted variedbased on the program and its individual goals.Conclusions & RecommendationsThis study reflected the effectiveness of the MOM program at Mercer University on theconstructs of program preparedness, global competency, and knowledge transfer. This evaluationwas done through pre- and post-program surveys completed by
observations 1. What was the most important thing with students from another country about your interactions with your you learned from this collaborative might impact what you learn in this partner(s) as you work with them in experience? course? the online environment. 2. Please describe how doing this 2. How do you think the way you see 2. Describe how your course has been experience with international and understand the world might impacted by connecting with a class partners impacted your learning change by connecting with students from another country. experience. in another country
informed by our literature review and included questions aboutparticipants’ advisor(s), perceptions of their advisors’ work-life balance, research group climate,and department climate [4]. This paper focuses on responses to two questions from the largerstudy’s interview protocol: 1) What advice does your PhD advisor give you about your suitability and preparation for your desired career path? 2) Are there some aspects of your plans you don’t feel like you can openly discuss with your PhD advisor?3.3 | Data analysis We completed two rounds of inductive coding using transcripts from the interviews [29].In the first round of coding, we identified the five major themes of participant-advisorrelationship, participant's
advisor with my own needs, Overall, my relationship with my advisor isgood. Participants indicated their agreement with the items on a scale from Strongly Disagree (1)to Strongly Agree (5) on a series of questions on advisor relationships. The mean of these itemsis used as the advisor relationship variable. The scale demonstrated strong internal reliability(Cronbach’s alpha = .94).The demographic questions included: "How do you describe your gender identity?" with theoptions: Woman, Man, Genderqueer, Agender, Transgender, Cisgender, Non-binary/third gender,Prefer not to say, and a text write-in option. Race/ethnicity was collected with the question,“With which racial and ethnic group(s) do you identify?" The options included American Indianor
. Colab Number 49 Stocking 3.306 Parameters Normala, b Deviation 0.664 Estd. Absolute 0.088 More Positive 0.078 Extreme Difference Negative -0.088 s Test Statistics 0.088 Asim. Sig (2
and Engineering, 27(1).[2] Markle, R. S., Williams, T. M., Williams, K. S., deGravelles, K. H., Bagayoko, D., & Warner,I. M. (2022, May). Supporting historically underrepresented groups in STEM higher education:The promise of structured mentoring networks. In Frontiers in Education (Vol. 7, p. 674669).Frontiers Media SA.[3] Zambrana, R. E., Ray, R., Espino, M. M., Castro, C., Douthirt Cohen, B., & Eliason, J.(2015). “Don’t leave us behind” The importance of mentoring for underrepresented minorityfaculty. American Educational Research Journal, 52(1), 40-72.[4] Griffin, K. A. (2019). Institutional barriers, strategies, and benefits to increasing therepresentation of women and men of color in the professoriate: Looking beyond thepipeline
with their faculty mentors. Students’ research self-efficacy increased, gainedvaluable research skills and experience, and had positive perceptions about going to graduateschool.AcknowledgementThis material is based upon work supported by the National Science Foundation under Grant No.2243722.References[1] A. L. Zydney, J. S. Bennett, A. Shahid, and K. W. Bauer, “Impact of Undergraduate Research Experience in Engineering,” J. Eng. Educ., vol. 91, no. 2, pp. 151–157, Apr. 2002, doi: 10.1002/J.2168-9830.2002.TB00687.X.[2] D. S. Raicu and J. D. Furst, “Enhancing undergraduate education,” ACM SIGCSE Bull., vol. 41, no. 1, pp. 468–472, Mar. 2009, doi: 10.1145/1539024.1509027.[3] M. G. Norton and D. F. Bahr, “How to run a
Accessibility and Universal Design for Learning. He was the recipient of the Foundation Excellence Award, David S. Taylor Service to Students Award and Golden Apple Award from Boise State University. He was also the recipient of 2023 National Outstanding Teacher Award, ASEE PNW Outstanding Teaching Award, ASEE Mechanical Engineering division’s Outstanding New Educator Award and several course design awards. He serves as the campus representative and was the past-Chair for the ASEE PNW Section. His academic research interests include innovative teaching and learning strategies, use of emerging technologies, and mobile teaching and learning strategies.Dr. Angela Minichiello PE, Utah State University Angela (Angie) Minichiello
including studentfamiliarity with the method(s), incoming student skills, student risk tolerance, environmentalconstraints (e.g. class size), perceived risks (e.g. on grades), perceived workload, socialinfluences, and context-specific motivations [3]. Other research has identified that these barriersto student engagement can differ between individual students, or between communities ofstudents. Felder and Brent described the challenges of active learning, where some students arecomfortable whereas others may struggle [1].For specific communities of students like Indigenous students, for example, the importance ofthe experience is critical to many learners. Leddy and Miller stated that “scaffolded experientiallearning is a mainstay in Indigenous
behaviors. In the future, this will be taught and reinforced throughout the semester boththrough guided reflection and more traditional assignments and activities with better-designedassessment.references (1) Springer, Leonard, Mary Elizabeth Stanne, and Samuel S. Donovan. "Effects of small- group learning on undergraduates in science, mathematics, engineering, and technology: A meta-analysis." Review of educational research, vol. 69, no.1, pp. 21-51, 1999. (2) ABET, 2025, “Criteria for Accrediting Engineering Technology Programs, 2025-2026.” https://www.abet.org/2025-2026_etac_criteria/ (3) Wolfe, J., Powell, B. A., Schlisserman, S., and Kirshon, A., 2016, “Teamwork in Engineering Undergraduate Classes: What
first three authors).The second study was conducted as a focus group with seven Black faculty mentors speakingabout their experiences mentoring Black Ph.D. students in engineering. A parallel studyexploring the experiences of these Black Ph.D. mentees is underway and will be presented ina future publication.2.2 Research Quality The validation process incorporated multiple rounds of evidence gathering, informed byHall et al.'s perspectives on multidisciplinary approaches to understanding complex socialrelationships [33]. This included peer debriefing sessions, member-checking, and thoroughdocumentation of the research process. The data analysis phase employed systematic codingand theme development, with all team members participating to
, and plant biology. R EFERENCES [1] S. Fathalla, S. Vahdati, S. Auer, and C. Lange, “Metadata analysis of scholarly events of computer science, physics, engineering, and mathematics,” in Digital Libraries for Open Knowledge, E. M´endez, F. Crestani, C. Ribeiro, G. David, and J. C. Lopes, Eds. Cham: Springer International Publishing, 2018, pp. 116–128. [2] E. Dagien˙e, “Mapping scholarly books: library metadata and research assessment,” Scientometrics, vol. 129, no. 9, pp. 5689–5714, 2024. [Online]. Available: https://doi.org/10.1007/s11192-024-05120-1 [3] A. Mierzecka, “The role of academic libraries in scholarly communication. a meta-analysis of research,” Studia Medioznawcze
21st, 2025.[4] Cervone, G., Franzese, P., Ezber, Y., and Boybeyi, Z. “Risk assessment of atmospheric emissions using machine learning”, Nat. Hazards Earth Syst. Sci., 2009, 8, 991–1000.[5] Chen, J., Kong, H., Su, Y., and Zhang, H. “Indoor air quality monitoring system for smart buildings: A comprehensive review”. Building and Environment, 2021, 196, 107786.[6] Cuesta-Mosquera, A., Močnik, G., Drinovec, L., Müller, T., Pfeifer, S., Minguillón, M. C., Briel, B., Buckley, P., Dudoitis, V., Fernández-García, J., Fernández-Amado, M., Ferreira De Brito, J., Riffault, V., Flentje, H., Heffernan, E., Kalivitis, N., Kalogridis, A.-C., Keernik, H., Marmureanu, L., Luoma, K., Marinoni, A., Pikridas, M., Schauer, G., Serfozo, N
and by Spanish- and English-language preferences. Table 1shows the family composition and languages spoken by the ten families in each of the threerounds.Table 1Family Composition and Language Preferences for Each Round Family ID Language(s) Spoken Family Composition 1 Spanish and English Adult and child 5 Spanish and English Adult and three children 6 Spanish* Adult and three children** 7 Spanish and English Adult and two children 10 English Adult and child 11 English Adult and child 13 English
, and conclusions or recommendations expressed in this material are those of theauthor(s) and do not necessarily reflect the views of the National Science Foundation.REFERENCES[1] T. L. Cross, B. J. Bazron, K. W. Dennis, and M. R. Isaacs, “Towards a Culturally Competent System of Care: A Monograph on Effective Services for Minority Children Who Are Severely Emotionally Disturbed | Office of Justice Programs.”[2] A. N. Washington, “When Twice as Good Isn’t Enough: The Case for Cultural Competence in Computing,” in Proceedings of the 51st ACM Technical Symposium on Computer Science Education, in SIGCSE ’20. New York, NY, USA: Association for Computing Machinery, Feb. 2020, pp. 213–219. doi: 10.1145/3328778.3366792.[3] “CRA Taulbee
belong there, I don’t feel like I connect with the school … I just have that mentality of, “I just need to go through this part. I’m just passing by” … And I’m fine with that, that doesn’t bother me anymore [interview 4]Decades of research focused on college student’s college departure affirm that students are morelikely to withdraw from their institution, all together, when they are not sufficiently integratedsocially and academically [31]–[38]. Kitatoi’s resignment to “just passing by” and her lack ofconnectedness with the institution are worrisome. Seymour and Hewitt [39] and Marra et al.’s [40]work emphasized that women who leave STEM disciplines decide to switch into non-engineeringdegree programs due to feeling as though they didn’t
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