undergraduate students NicholasInsinga, David Lentz, Dylan Letcher, Alfred Marchev, and Ryan Petzitillo who assisted in thedevelopment of the interview protocol and identification of the initial emergent codes.References[1] A. Godwin and A. Kirn, “Identity‐ based motivation: Connections between first‐year students’ engineering role identities and future‐time perspectives,” J. Eng. Educ., vol. 109, no. 3, pp. 362–383, 2020, doi: https://doi.org/10.1002/jee.20324.[2] D. R. Simmons, J. Van Mullekom, and M. W. Ohland, “The Popularity and Intensity of Engineering Undergraduate Out‐of‐Class Activities,” J. Eng. Educ., vol. 107, no. 4, pp. 611–635, Oct. 2018, doi: 10.1002/jee.20235.[3] R. S. Adams, S. R. Daly, L. M. Mann, and G. Dall’Alba
of communicating learning achievement since theearly 1900’s [1]. Despite grades having the very practical purpose of communicating our levelsof learning or performance achievement to both the learners and the educational system morebroadly [2], [3], when reflecting on the moments and instances in which we remember receivinggrades we likely don’t only remember the learning material or content. Intertwined with thesememories of receiving grades are likely emotional reactions - sometimes incredibly strong. Thejoy and pride of achieving a good grade, the disappointment or frustration with a bad grade, orthe anticipatory excitement or fear related to either preparing for a graded event such as an examor presentation, or even waiting for a grade
to figure out which elements on project teams are prompting the development and practiceof professional skills on project teams to understand if those elements can be replicated in other settings.Not all students or institutions have the resources or availability to expand or participate in project teams.However, by understanding which structures or elements have been useful for developing professionalskills, instructors can introduce similar tactics into classroom settings so more students have opportunitiesto develop their professional skills.References[1] L. Bland, S. Kusano, and A. Johri, “Engineering Competitions as Pathways to Development of Professional Engineering Skills,” in 2016 ASEE Annual Conference & Exposition
, et al. (2021, Between Level Up and Game Over: A Systematic Literature Review of Gamification in Education. Sustainability 13(4).[5] L. Sardi, A. Idri, and J. L. Fernández-Alemán, "A systematic review of gamification in e-Health," Journal of Biomedical Informatics, vol. 71, pp. 31-48, 2017/07/01/ 2017.[6] K. Robson, K. Plangger, J. H. Kietzmann, I. McCarthy, and L. Pitt, "Game on: Engaging customers and employees through gamification," Business Horizons, vol. 59, pp. 29-36, 2016/01/01/ 2016.[7] A. Behl, P. Sheorey, A. Pal, A. K. V. Veetil, and S. R. Singh, "Gamification in E- Commerce: A Comprehensive Review of Literature," Journal of Electronic Commerce in Organizations (JECO), vol. 18, pp. 1-16, 2020
NationalCenter for Education Statistics (NCES), many university students in the United States are non-traditional. Despite these challenges, non-traditional students excel because they understand thevalue of a college degree in today's job market, particularly for certain engineering disciplineswhere a degree is required. Hispanic/Latino(a) students are often non-traditional and face unique challenges andobstacles in their pursuit of their degree. Hispanics/Latino(a)s are more likely than otherdemographic groups to work while attending college [2]. The high rate of labor forceparticipation among Hispanic/Latino(a) students can be seen as an example of intersectionality[3], as it is influenced by multiple factors, including their race, ethnicity
shows three contexts that influence engineering instructors offundamental engineering courses (FECs) in using tests in their courses: 1) autonomy, 2) coursecontext, and 3) inertia. These contexts are largely consistent with the literature, but also revealsome research gaps that the engineering education community should think about addressing toimprove our education processes. In addition, the community can use our findings to raisequestions about test usage, introducing intentionality with test usage in engineering classrooms.ReferencesAbadi, M. G., Hurwitz, D. S., & Brown, S. (2017). Influence of context on item-specific self- efficacy and competence of engineering students. International Journal of Engineering Education, 33(4
work is consideredrigorous engineering research? What work is considered to have the most value? What is valuedby the dominant cultural and political voices? This work-in-progress paper provides currentfindings as a brief narrative exploration of literature on engineering research culture, and theparadigm(s) that lead engineering research work that was guided by the following question: whatare the research and cultural paradigms that guide engineering research?As this question is ambiguous and broad, I would like to explicitly note that this paper does notreport on preliminary findings from the first stages of a scoping literature review, but it is anarrative literature review to lay a foundation for further exploration. This paper serves as
particular focus on their hidden identity, mental health, and wellbeing. Her work aims to enhance inclusivity and diversity in engineering education, contributing to the larger body of research in the field.Mr. Syed Ali Kamal, University at Buffalo, The State University of New York Syed Ali Kamal is a doctoral candidate in the Department of Engineering Education at University at Buffalo. His research interests lie in the area of diversity, equity and Inclusion, mental health and wellbeing.Matilde Luz Sanchez-Pena, University at Buffalo, The State University of New York Dr. Matilde S´anchez-Pe˜na is an assistant professor of Engineering Education at the University at Buffalo – SUNY where she leads the Diversity Assessment
the importance of recognizing issues and variationsin emotional responses, particularly in students facing math difficulties. They highlight the dynamicnature of these emotional states, which can significantly shift across diverse learning activities andinfluence the engagement level [37]. For example, negative emotions raise frustration levels whichcan be helpful during focused learning and problem–solving s but when the time constraint isinvolved, the same emotion can be the reason for a lower engagement level [1].The second research question focused on the specific emotions have researchers proposed aspotential indicators of deeper cognitive engagement in educational settings. When we are talkingabout specific emotional indicators
]. • Honoring the language(s) and cultural practices of minoritized communities, recognizing how racialized ideologies shape engineering education [21]. Curriculum and students • Fostering cultural competencies and social justice through culturally responsive engineering curriculum [22], [23]. • Link between social and technical aspects [24] - [26]. Learning • Learning centered in students’ funds of knowledge Profession and education • Expanding pathways into engineering Broader issues, the • Contextualizing the work in
inattentive responders. The finalanalytical sample included 834 students. Participant gender identity, race/ethnicity, nationality,sexual identity, and disability status are reported in Table 1. Participants self-identified theirdemographics by selecting from categorical response options including write-in text options. Thesample is predominantly men (65%), and white (66%), which reflects the general populationcharacteristics among contemporary U. S. engineering undergraduates. Most participantsidentified as heterosexual/straight (88%) with 9% identifying as asexual, bisexual, gay, lesbian,pansexual, queer, or another sexual identity. Students reported a range of disabilities, withpsychological conditions predominating at 13% of the sample.Table 1
Council for Research on Women, 11 Hanover Square,20th Floor, New York, NY 10005.[3] Hill, C., Corbett, C., & St Rose, A. (2010). Why so few? Women in science, technology,engineering, and mathematics. American Association of University Women. 1111 SixteenthStreet NW, Washington, DC 20036.[4] Fouad, N. A., Hackett, G., Smith, P. L., Kantamneni, N., Fitzpatrick, M., Haag, S., &Spencer, D. (2010). Barriers and supports for continuing in mathematics and science: Gender andeducational level differences. Journal of Vocational Behavior, 77(3), 361-373.[5] Sullivan, A., & Bers, M. U. (2013). Gender differences in kindergarteners’ robotics andprogramming achievement. International journal of technology and design education, 23,691-702.[6
conceptualresearch, Strobel et al. [30] analyzed 1058 engineering education literature related to authenticity througha systematic literature review and proposed a four dimensions concept framework based on Brab et al.’s 3research work [31], which includes context authenticity, task authenticity, impact authenticity, as well aspersonal and value authenticity.Authentic learning has a long history in engineering fields like apprenticeship [28], in which the learnerscould finish some real-world tasks and solve ill-defined problems. The features of work-place engineeringproblems, such as ill-structured, complex, conflicting goals, multiple solution methods, beyond engineeringsuccess standards or constraints
participants to expand upon previousanswers and provide additional insights into their relationships with their advisor(s). Thequestions are included in Table 3 in Appendix A.The survey was reviewed by a group of graduate students outside of the participant pool acrossmultiple institutions and by our grant’s external advisory board. The survey was revised based onfeedback to improve clarity and ensure the appropriateness of selected subscales. Once responsesto the recommendations from the external feedback sources were implemented, the final surveywas administered via Qualtrics and was made available to participants for four weeks. Theresearchers’ Institutional Review Boards approved this study (HUM00230743, #23-901).ParticipantsThe survey was
- Revised (SLQ- R) Sherman, D. K., 2021 Frontiers in Doctoral USA Perceived Adapted Zimet et al. (1988) Ortosky, L., Psychology students Social support Leong, S., Kello, C., & Hegarty, M. (2021) Smith, A. B., 2021 Nurse education Doctoral USA Collaboration DevelopedUmberfield, E., today students of LeadershipGranner, J. R., and Innovation Harris, M., in MentoringLiestenfeltz, B
, alsohave the highest level of tentativeness in the LIWC analysis, suggesting that their leadership isexpressed in a way that invites others’ input. The GCA analysis (Fig. 4) is somewhat at variancewith the others, suggesting that S1 and S4 are the greater participators. The overallresponsiveness scores are very similar for all team members, but the social impact scorescorroborate the observation that S3 seems disempowered.Figure 3 - Scores for each member (S1-S4) of each team for each of the three LIWC constructs. Theresults for team F22 are skewed by S4’s very small number of utterances.Figure 4 - Scores for each member (S1-S4) of each team for each of the three GCA constructs. The resultsfor team F22 are skewed by S4’s very small number of
' cultural backgrounds and departmental culture might influencestudents’ motivational orientations.References[1] A. Wigfield and J. S. Eccles, “Expectancy-value theory of achievement motivation,” Contemp. Educ. Psychol., vol. 25, no. 1, pp. 68–81, 2000, doi: 10.1006/ceps.1999.1015.[2] J. Guo, P. D. Parker, H. W. Marsh, and A. J. S. Morin, “Achievement, motivation, and educational choices: A longitudinal study of expectancy and value using a multiplicative perspective,” Dev. Psychol., vol. 51, no. 8, pp. 1163–1176, 2015, doi: 10.1037/a0039440.[3] J. Allen and S. Robbins, “Effects of Interest-Major Congruence, Motivation, and Academic Performance on Timely Degree Attainment,” J. Couns. Psychol., vol. 57, no. 1
experiences.Future research should consider exploring teamwork dynamics in diverse URPs across differentgeographical and disciplinary contexts to generalize the findings as well as compare teamworkexperiences across various URPs to understand the impact of different institutional cultures andprogram structures. Additionally, longitudinal studies could offer a deeper understanding ofhow teamwork skills developed in URPs impact students’ professional careers. References[1] K. W. Bauer and J. S. Bennett, “Alumni Perceptions Used to Assess Undergraduate Research Experience,” J. High. Educ., vol. 74, no. 2, pp. 210–230, 2003.[2] D. Lopatto, “Undergraduate Research Experiences Support Science Career Decisions and Active Learning,” CBE—Life Sci. Educ., vol
. 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] C. B. Zoltowski, P. M. Buzzanell, A. O. Brightman, D. Torres, and S. M. Eddington, “Understanding the Professional Formation of Engineers through the Lens of Design Thinking: Unpacking theWicked Problem of Diversity and Inclusion,” ASEE Annu. Conf. Expo. Proc., Jun. 2017, Accessed: Dec. 06, 2022. [Online]. Available: https://par.nsf.gov/biblio/10036285-understanding-professional-formation-engineers- through-lens-design-thinking-unpacking-thewicked-problem-diversity-inclusion[2] B. Frank, D. Strong, R. Sellens, and L. Clapham
factors overscientific or theoretical knowledge, implementing targeted interventions, thus adjusting theinstructional approach and refining the use of the tool. These efforts aim to strengthen theanalysis of the lesson design’s impact on learning outcomes and explore the potential integrationof emerging technologies for enhanced effectiveness in specific educational contexts.References [1] C. Vieira, R. Aguas, M. H. Goldstein, S. Purzer, and A. J. Magana, “Assessing the impact of an engineering design workshop on colombian engineering undergraduate students,” International Journal of Engineering Education, vol. 32, no. 5, pp. 1972–1983, 2016. [2] M. A. Feij´oo-Garc´ıa., H. H. Ram´ırez-Ar´evalo., and P. G. Feij´oo-Garc´ıa., “Collaborative
understanding of how the design problem-solving behaviors ofundergraduate engineering participants differ based on their levels of spatial ability while, whysuch differences exist and how they might affect their learning outcomes is yet to be known. Futureresearch provide us some insight into it.ACKNOWLEDGMENTSThis work was made possible by a grant from the National Science Foundation (NSF #2020785).Any opinions, findings, and conclusions, or recommendations expressed in this material arethose of the authors and do not necessarily reflect the views of the National Science Foundation. 11REFERENCES 1. R. Gorska and S. Sorby, "Testing instruments for the
sampling(KMO = 0.91) and sufficient factor correlations (χ2171 = 2562.3, p < 0.001). Phase 2 also showedsuitable results (KMO = 0.92) and (χ2171 = 2690.6, p < 0.05). Table 3. Cronbach Alpha’s Value for Both Study Phases. Phase 1 Phase 2 Cronbach’s alpha Cronbach’s alpha Searching (S) 0.78 0.80 Planning (P) 0.73 0.77 Managing (M) 0.77 0.82 4 Implementing People (IP
Paper ID #38459Work in Progress: Engineering Identity Development after Two Years ofUndergraduate EducationJanet Aderemi Omitoyin, Janet Omitoyin is a PHD student in the Department of Curriculum and Instructions, University of Illinois at Chicago (UIC). An astute scholar, Janetˆa C™s quest for a solution to the problems of mathematics learning based on her experience as a student andDr. Renata A. Revelo, The University of Illinois, Chicago Renata Revelo is a first-generation college student, migrated from Ecuador to the United States as a teenager with her parents and sister. She is the first in her family to obtain a
found a noticeable but insignificant difference in scores. All calculations wereperformed using Microsoft Excel. Table 2. Summary of results. Mean Standard Shapiro-Wilk Mann-Whitney Result Duration (s) Deviation (s) Normality U test Normal Pre-COVID 149 84 Statistically (p>0.05) U=329 significant
Revolution to Industry 4.0: A Literature Review,” in 2020 ASEE Virtual Annual Conference Content Access Proceedings, Virtual On line, Jun. 2020, p. 35318. doi: 10.18260/1-2--35318.[4] S. R. Brunhaver, R. Korte, S. Barley, and S. Sheppard, “Bridging the Gaps between Engineering Education and Practice,” in U.S. Engineering in a Global Economy, University of Chicago Press, 2018, pp. 129–163. doi: 10.7208/chicago/9780226468471.001.0001.[5] K. Tonso, “Teams that work: Campus culture, engineer identity, and social interactions,” J. Eng. Educ., vol. 95, no. 1, pp. 25–37, 2006.[6] A. C. Loignon, D. J. Woehr, M. L. Loughry, and M. W. Ohland, “Elaborating on Team- Member Disagreement: Examining Patterned Dispersion in Team-Level Constructs
materialare those of the author(s) and do not necessarily reflect the views of the National ScienceFoundation. References[1] Council of Graduate Schools, “Ph.D. completion and attrition: Analysis of baseline data from the Ph.D. completion project,” Council of Graduate Schools, Washington, DC, USA, 2008.[2] C. Wendler et al., “The path forward: The future of graduate education in the United States,” Educational Testing Service, Princeton, NJ, USA, 2010.[3] J. M. Jones, “The dual pandemics of COVID-19 and systemic racism: Navigating our path forward,” School Psychol., vol. 36, no. 5, pp. 427-431, Sep. 2021, doi: 10.1037/spq0000472.[4] C. Davies, C. A. Arbeit, and M. Yamaner
objectives and cognitive load. Literature is also silent on howmany learning objectives are pursued in a typical laboratory activity.Consequently, relating laboratory activities to cognitive load requires more work. Theoreticaland qualitative work can define better categorizing features of a laboratory, and ensure thosefeatures predict learning and perceptions of difficulty. Quantitative work can probe theunsupported relationships in the logic model. Finally, specialization is probably a widespreadbehavior, and more work qualitative and quantitative should document stories of specialization,the conditions that create specialization, and how specialization affects learning.REFERENCES[1] E. Byrnes, Y. A. Mahsud, S. Rosen, and M. Spencer, “A Survey
. Qualitative Research in Psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oaBrunhaver, S. R., Bekki, J. M., Carberry, A. R., London, J. S., & McKenna, A. F. (2018). Development of the Engineering Student Entrepreneurial Mindset Assessment (ESEMA). Advances in Engineering Education, 7(1), 1-12. Retrieved from https://files.eric.ed.gov/fulltext/EJ1199672.pdfCampbell, J. D., Trapnell, P. D., Heine, S. J., Katz, I. M., Lavallee, L. F., & Lehman, D. R. (1996). Self-concept clarity: measurement, personality correlates, and cultural boundaries. Journal of Personality and Social Psychology, 70(1), 141-156. https://doi.org/10.1037/0022-3514.70.1.141Carter, N., Bryant-Lukosius, D., DiCenso