Paper ID #47250Deconstructing School-to-Work Transitions in Engineering: A Scoping ReviewAnimesh Paul, University of Georgia Animesh (he/they) was born and raised in Tripura, India, within a liberal ”brown” military upbringing. He earned a bachelor’s degree in Electronics and Electrical Engineering from KIIT University. Currently, he is a Ph.D. candidate at the Engineering Education Transformation Institute, advised by Dr. Racheida Lewis. His research focuses on engineering education, specifically exploring user experience in engineering classrooms and students’ transition experiences.Dr. Racheida S Lewis, University of
, Chile.Mrs. Monique S. Ross, The Ohio State University Monique Ross earned a doctoral degree in Engineering Education from Purdue University. She has a Bachelor’s degree in Computer Engineering from Elizabethtown College, a Master’s degree in Computer Science and Software Engineering from Auburn University ©American Society for Engineering Education, 2025 Exploring Tenure and Promotion Policies in Engineering Colleges Through Policy Discourse AnalysisDescription of Research Brief PapersTenure is vital for academic freedom, job security, and integrity in American higher education. Itensures that faculty can express their views, publish their work, and share their research
development and strategy of over 30 commercial videogames including the popular Borderlands games, and brought science research and videogames together through the development of the Borderlands Science ”citizen science” game that supported genomic research with millions of game players repairing genetic sequences.Dr. Michael S Rugh, Texas A&M University Dr. Michael S. Rugh is an Associate Research Scientist at the LIVE Lab at Texas A and M University and Director of STEM Education Research for the Aggie Research Program. He leads interdisciplinary research teams investigating game-based learning and the impact of educational technologies, including video games, simulations, apps, and virtual environments created by
. Jennifer S. Brown, University of Georgia Dr. Jennifer Brown earned her PhD in Engineering and Science Education (2023) and her M.S. in Mechanical Engineering (2020) from Clemson University. She is currently working as a postdoctoral scholar with the Elevate research team in the Engineering Education Transformations Institute at the University of Georgia. Her primary research foci include using asset-based frameworks in student and faculty development, graduate well-being, and mentorship of women and others with marginalized identities in STEM. Her engineering background is in advanced manufacturing and design. ©American Society for Engineering Education, 2025Empirical Study of Growth Mindset of
interventions to improve student success. He was most recently recognized by INSIGHT Into Diversity Magazine as an Inspiring STEM Leader, the University of Illinois at Urbana-Champaign with the College of Liberal Arts & Sciences (LAS) Outstanding Young Alumni Award, Career Communications Group with a Black Engineer of the Year Award for college-level promotion of engineering education and a National Science Foundation CAREER Award in 2023 to advance his work that centers engineering identities of Black men in engineering.Dr. Sherri S Frizell, Prairie View A&M University Sherri S. Frizell is a Professor in the Computer Science Department at Prairie View A&M University. She has a B.S. in Computer Science from
double coded. A Cohen’sKappa value of κ = 0.72 across all three rounds was achieved, indicating strong inter-raterreliability and agreement beyond chance [39].3. ResultsSince this is a research brief, only the results of the Delphi study after round 3 will be presentednext. The full set of results from rounds 1 through 3 will be presented in a forthcoming article.Relevance Ratings. The average relevance ratings (on a 1-5 scale) and standard deviations (s)for the various conceptions of judgment given in Table 1 during the final Delphi round rangedfrom 3.00 (s=1.17) to 4.88 (s=0.33) based on n=17 responses. Decision making (item 7 in Table1) had the highest average relevance of 4.88 and the smallest standard deviation of s=0.33,indicating the
questions that relied heavily within the applying, analyzing,and evaluating levels of knowledge from Bloom’s revised taxonomy, building upon the lowerlevels of knowledge like remembering and understanding, but not asking questions that focusedwithin those lower levels. Differences between these collected domain-specific studies are basedheavily on the intentions of the surveys. Turner et al. [31]’s survey is intended for a widerpopulation of US adults and to establish a concept inventory for energy and power grid knowledge.Basic energy knowledge questions are included in Turner et al.’s survey, but a majority of thequestions require higher-level energy knowledge applied specifically to power grid use andinfrastructure. While Prince et al. [32]’s
computing education and its longitudinal impact on ethical decision making. Futurestudies could also measure the framework’s impact on students’ problem-solving abilities,especially when dealing with even more complex, real-world security or privacy challenges.AcknowledgementThis research is supported by the National Science Foundation (Award #: 2335681).AppendixS. Shin, J. Lee, S. Lim, and S. Shin. “Draft of ethical motivation and behavioral intention surveyin engineering education,” American Society for Engineering Education Annual Conference,June 22-25, 2025, Montreal, Canada, 2025.Sample Survey Items for Ethical Motivation and Behavioral IntentionWe used a 6-point Likert scale (including “Don’t Know” as an option) for this survey. Thesurvey is
of conversationalways, that students could discover during their analysis of the interviews and include in theirworkstation designs.Table 1: Human-centered Design (HCD) Problem Workstation Design: You have been asked to design the workstations The workstation, at a minimum, that will be constructed in each faculty and staff private office for a should account for: brand-new Industrial Engineering building at the university. Each University assigned desktop computer private office will have a window. This is a workstation meant for a and monitor(s), placement of the sitting individual while working with a desktop computer. There are computer tower / central processing about the same number of male and females
engineering.ConclusionThis study described underrepresented students’ own perceptions of sense of belonging,highlighting the multiple and varied ways that students describe what belonging in engineeringmeans to them. Responses demonstrated the ways in which students described belonging asmeaning (a) having competence, (b) positive experiences in the learning environment, and (c)finding meaningful social connections. These findings, part of a broader mixed-methods study onsense of belonging in engineering students, can inform further research, helping to contextualizestudent interpretations of belonging and providing strategies to improving learning environmentsto support student sense of belonging.References[1] C. E. Foor, S. E. Walden, and D. A. Trytten, “’I wish
, orresearch competency development among engineering graduate students.Main and Wang [3] are two of the only researchers to date who have conducted interculturalcompetency research among engineering doctoral students, and the results demonstrate that femaleengineering doctoral students are more likely to score higher on the MGUDS-S than maleengineering doctoral students. Proficiency in multiple languages is positively associated withdoctoral students’ intercultural competency.Several additional papers assessing the current status of graduate students [3], [4] recommendhaving work/volunteer-related international experience due to the positive correlation ofinternational experiences to the development of intercultural/global competencies in their
, 2000, doi: 10.1037/0003-066X.55.1.68.[7] M. Gopalan and S. T. Brady, “College Students’ Sense of Belonging: A National Perspective,” Educ. Res., vol. 49, no. 2, pp. 134–137, 2020, doi: 10.3102/0013189X19897622.[8] A. Master and A. N. Meltzoff, “Cultural Stereotypes and Sense of Belonging Contribute to Gender Gaps in STEM,” Int. J. Gender, Sci. Technol., vol. 12, no. 1, pp. 152–198, 2020.[9] K. Rainey, M. Dancy, R. Mickelson, E. Stearns, and S. Moller, “Race and gender differences in how sense of belonging influences decisions to major in STEM,” Int. J. STEM Educ., vol. 5, no. 1, pp. 1–14, 2018, doi: 10.1186/s40594-018-0115-6.[10] C. U. Lawrence and E. Lee, “WIP: Sense of Belonging Research in
: Springer International Publishing, 2018, pp. 217–239. doi: 10.1007/978-3-319-66659-4_10.[11] S. Baker, P. Tancred, and S. Whitesides, “Gender and Graduate School: Engineering Students Confront Life after the B. Eng.,” J. Eng. Educ., vol. 91, no. 1, pp. 41–47, 2013, doi: 10.1002/j.2168-9830.2002.tb00671.x.[12] K. J. Jensen and K. J. Cross, “Engineering stress culture: Relationships among mental health, engineering identity, and sense of inclusion,” J. Eng. Educ., vol. 110, no. 2, pp. 371–392, 2021, doi: 10.1002/jee.20391.[13] “How To Meet the Increasing Demand for Engineers | National Society of Professional Engineers.” Accessed: Apr. 29, 2025. [Online]. Available: https://www.nspe.org/career- growth/pe-magazine/spring-2021
degree program at a large, public, research-intensive(R1) university in the southern U.S.Data Collection Co-creators were recruited through emails sent by each university’s disability resourceoffice and engineering department(s) to undergraduate students. These emails outlined eligibilitycriteria, which required co-creators to be currently enrolled undergraduate engineering studentsat that university who identify as disabled or as a person with disabilities. The emails invitedeligible individuals to participate in the study by reflecting on their disability-related experiencesat their university. Additionally, the emails detailed the participation process and offered a $40gift card as compensation upon completing the interview. To ensure
] witheach differing in focus and scope. Some tools emphasize broad abilities, while others targetspecific subskills. Some prioritize language over culture or focus on international differenceswhile overlooking intracultural variation. Others remain ambiguous, with unclear objectives[58], [59]. A summary of some of these tools is provided in [58], including those designed forindividuals, teams, leaders, and organizations [59].In the process of identifying a suitable theoretical framing for this study, we reviewed severalinstruments, each offering unique perspectives on cultural awareness and interaction. TheMiville-Guzman Universality-Diversity Scale - Short Form (MGUDS-S), for instance, measuresindividuals' awareness and acceptance of similarities
Identity measures and the Research-Science/tist Identity measures here.Recognition measurements between all three identities were particularly strongly correlated(r>0.999), suggesting these constructs largely measure the same (or very similar) underlyingidentity component(s) in engineering doctoral students.The relative contribution of identity subconstructs to overall identity strength was examinedthrough ridge regression against implicit association scores. This approach differs from previouswork with this instrument [24] where recognition, performance, and interest were weightedequally in identity calculations. The regression revealed recognition as the dominant predictor,with performance contributing moderately and interest showing a
-efficacy and STEM identity in the context of structural inequalities,pointing to directions for future research for both SCCT and PVEST.References[1] R. W. Lent and S. D. Brown, “Social cognitive model of career self-management: Toward a unifying view of adaptive career behavior across the life span.,” J Couns Psychol, vol. 60, no. 4, pp. 557–568, 2013, doi: 10.1037/a0033446.[2] Y. Yang, Y. Maeda, and M. Gentry, “The relationship between mathematics self-efficacy and mathematics achievement: Multilevel analysis with NAEP 2019,” Large Scale Assess Educ, vol. 12, no. 1, 2024, doi: 10.1186/s40536-024-00204-z.[3] A. V. Maltese and R. H. Tai, “Pipeline persistence: Examining the association of educational
collaborative settingsstudents’ gesture production also leveraged various forms of speech, not only including formalizedspeech (i.e., speech explicitly used in theory-based or lab courses) but also non-formalized speech.Among these formalized and non-formalized components of speech, Grondin and colleagues [12]identified instances of engineering students’ speech as referring to either the structure (S) orfunction (F) of engineering objects. Structure refers to the static nature of an engineering object(e.g., the metallic rod or the geometry of the sample) whereas function refers to the dynamic ortime-dependent nature of an engineering object being acted upon (e.g., deformation due to torsion). Mechanical reasoning tasks elicit both static and
Get Inside the Head of Your Opponent: The Differential Effects of Perspective Taking and Empathy in Negotiations,” Psychol. Sci., vol. 19, no. 4, pp. 378–384, Apr. 2008, doi: 10.1111/j.1467- 9280.2008.02096.x.[2] C. D. Batson, S. Early, and G. Salvarani, “Perspective Taking: Imagining How Another Feels Versus Imaging How You Would Feel,” Pers. Soc. Psychol. Bull., vol. 23, no. 7, pp. 751–758, Jul. 1997, doi: 10.1177/0146167297237008.[3] S. Wu and B. Keysar, “The Effect of Culture on Perspective Taking,” Psychol. Sci., vol. 18, no. 7, pp. 600–606, Jul. 2007, doi: 10.1111/j.1467-9280.2007.01946.x.[4] J. L. Hess, J. Strobel, and A. O. Brightman, “The Development of Empathic Perspective- Taking in an Engineering Ethics Course
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
the development ofteamwork behaviors in the first-year engineering context. The overarching research question thatmotivated this review of relevant theory is ‘How might faculty leverage generative AI to providepersonalized feedback to intentionally promote students’ teamwork and feedback literacybehaviors?’ With the research question and chosen theoretical framework as guides, theresearchers worked to develop a codebook for the reflection data. The next section will detailhow the framework was used to develop a codebook.From Framework to CodebookTo analyze the reflection data, the researchers chose to deductively code feedback literacybehaviors. With the five constructs from Dawson et al.’s conceptual framework as a basis (seekfeedback
] K. Edström and A. Kolmos, “PBL and CDIO: complementary models for engineering education development,” Eur. J. Eng. Educ., vol. 39, no. 5, pp. 539–555, Sep. 2014, doi: 10.1080/03043797.2014.895703.[5] Y. Xia, S. Cutler, and D. McFadden, “Collaborative Project-based Learning Approach to the Enculturation of Senior Engineering Students into the Professional Engineering Practice of Teamwork,” in 2020 ASEE Virtual Annual Conference Content Access Proceedings, Virtual On line: ASEE Conferences, Jun. 2020, p. 34299. doi: 10.18260/1-2--34299.[6] S. Habibi et al., “A Modernized Student- and Equity-Centered Teaching Strategy,” Adv. Eng. Educ., vol. 11, no. 3, 2023, doi: 10.18260/3-1-1153-36049.[7] S. Howe and J. Goldberg
or recommendationsexpressed in this material are those of the author(s) and do not necessarily reflect the views ofthe National Science Foundation. We would like to express gratitude to the research groups whoparticipated in this study and for their willingness to open their meetings to us and providefeedback on the initial drafts of this paper. Finally, we would like to thank the members of theENLITE research team who gave feedback on the drafts of this paper.References[1] Van den Beemt, A., M. MacLeod, J. Van der Veen, A. Van de Ven, S. Van Baalen, R. Klaassen, and M. Boon, “Interdisciplinary engineering education: A review of vision, teaching, and support,” Journal of engineering education, vol. 109, no. 3, pp. 508-555
). LGBTQ Inequality in Engineering Education. Journal of Engineering Education, 107(4), 583–610. https://doi.org/10.1002/jee.20239[2] Hughes, B. E. (2018). Coming out in STEM: Factors affecting retention of sexual minority STEM students. Science Advances, 4(3), eaao6373. https://doi.org/10.1126/sciadv.aao6373[3] Hughes, B. E. (2017). “Managing by Not Managing”: How Gay Engineering Students Manage Sexual Orientation Identity. Journal of College Student Development, 58(3), 385– 401. https://doi.org/10.1353/csd.2017.0029[4] Haverkamp, A., Butler, A., Pelzl, N. S., Bothwell, M. K., Montfort, D., & Driskill, Q. (2019). Exploring Transgender and Gender Nonconforming Engineering Undergraduate Experiences through
in Residence for the Engineering and Innovation Living Learning Community (2014 - 2021). He was the inaugural Faculty Associate for Mobile Learning and the Faculty Associate for 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
Curricular Complexity Faced by Transfer Students: 2+2, Vertical Transfers, and Curricular Change,” in 2022 ASEE Annual Conference & Exposition, ASEE, 2022. doi: 10.18260/1-2--41462.[13] R. Molontay, N. Horvath, J. Bergmann, D. Szekrenyes, and M. Szabo, “Characterizing Curriculum Prerequisite Networks by a Student Flow Approach,” IEEE Transactions on Learning Technologies, vol. 13, no. 3, pp. 491–501, Jul. 2020, doi: 10.1109/TLT.2020.2981331.[14] G. L. Heileman, C. T. Abdallah, A. Slim, and M. Hickman, “Curricular Analytics: A Framework for Quantifying the Impact of Curricular Reforms and Pedagogical Innovations,” Nov. 2018, [Online]. Available: http://arxiv.org/abs/1811.09676[15] S. M. Padhye, D
data saturation has not yet been fully achieved in this WIP study [11]. Twocodes—reverse thinking and risk management—were identified by only one participant,indicating that additional data collection may offer further insights. As we expand this study inthe future, we intend to increase the sample size to allow for a more comprehensive exploration. References[1] C. J. Atman, K. Yasuhara, R. S. Adams, T. J. Barker, J. Turns, and E. Rhone, “Breadth in problem scoping: A comparison of freshman and senior engineering students,” International Journal of Engineering Education, vol. 24, no. 2, p. 234, 2008.[2] R. S. Adams and C. J. Atman, “Characterizing engineering student design processes: An
focus our analysison domestic applicants to four engineering programs (aerospace, chemical, electrical, andmechanical) at a large public research university in the U.S. between 2010 and 2022. We focuson domestic applicants because previous research has found substantial cross-nationaldifferences in norms for writing LORs and we wanted to minimize the influence of thosedifferences [5]. We selected four programs to sample from to provide variation in program size,selectivity, and diversity.1 This research was initially funded by the National Science Foundation under Grant No. 2225209, awarded in 2022.Funding was discontinued by the NSF in April 2025 because the project’s focus on broadening participation inSTEM “no longer effectuate[s] the
codes and codes that were similar yet not matching the original intent of the code.Additional codes to connect to career goals and interests were included; however, ultimately amore open thematic approach appeared more beneficial for the data. We were able to bettercapture experiences related to students’ funds of knowledge, including accessing experienceswith mentors and past experiences working in different fields, showing support for studies thatshowed similar findings quantitatively [5].References[1] C. Spence, E. Siverling, and M. Soledad, “NSF S-STEM: Iron Range Engineering Academic Scholarships for Co-Op Based Engineering Education,” in American Society for Engineering Education National Conference, Montreal, Quebec, 2025.[2] A
,” Stud Sci Educ, vol. 44, no. 1, pp. 1–39, 2008, doi: 10.1080/03057260701828101.[2] B. S. Bloom, M. D. Engelhart, E. J. Furst, W. H. Hill, and D. B. Krathwohl, TAXONOMY OF EDUCATIONAL OBJECTIVES; The Classification of Educational Goals. 1956.[3] M. Scardamalia and C. Bereiter, “Text-Based and Knowledge Based Questioning by Children,” Cogn Instr, vol. 9, no. 3, pp. 177–199, Sep. 1992, doi: 10.1207/S1532690XCI0903_1.[4] S. R. Goldberg, C. Venters, and A. Masnick, “Refining a Taxonomy for Categorizing the Quality of Engineering Student Questions,” ASEE Annual Conference and Exposition, Conference Proceedings, Jul. 2021, doi: 10.18260/1-2--37649.[5] “Hugging Face – The AI community building the future