diversity ofperspective and experience. To help all students develop the skills necessary to attract, retain,and consider the needs of diverse populations, engineering students need to consider socialresponsibility in the context of their engineering careers and scope of practice [6].To help promote engineering students’ ability to develop their social responsibility capacity, theUniversity of Massachusetts Lowell S-STEM program began with an initial plan to recruit threecohorts of 8 low-income, high-achieving students (24 students total) who wish to pursue a careerin higher education (e.g., faculty at community colleges or universities) and engage them inongoing social responsibility and identity formation curriculum. Supporting scholars from
; andshare the responses of students discussing the strengths, weaknesses, and suggestedimprovements for the course. The work presented in this article is part of an overall line ofresearch with the intent of demonstrating qualitative community-based participatory research isan essential skill of the nurse+engineer.MethodsInstitutional context. Today’s Missouri University of Science and Technology (S&T) wasestablished in 1870 as the Missouri School of Mines and Metallurgy. Located in Rolla, Missouri,S&T is a comprehensive public research university, which offers approximately 100 degreeprograms. With an undergraduate student enrollment of approximately 5,500 students, a graduatestudent enrollment of approximately 1,500 students, and average
is for novice programmersAbstractIn this work-in-progress paper, the emphasis is to understand the perceptions about whichlanguage should be the first programming language. Computer programming is a fundamentalskill for novice engineers. However, over time, multiple programming languages have emergedand are being used as the first language for students. While in modern times, many schoolsaround the globe, particularly in the USA, consider Python’s syntax simplicity and versatility asa way to go, other places and traditional computer scientists consider C++’s efficiency as theirchoice. Similarly, many engineering schools introduce MATLAB as the first programminglanguage. While these decisions are made at the
assistant professor in the Department of Mechanical and Materials Engineering at Florida International University. Dr. Dickersonˆa C™s research agenda contains two interconnected strands: 1) systematic investigatiDr. Matthew W. Ohland, Purdue University Matthew W. Ohland is the Dale and Suzi Gallagher Professor and Associate Head of Engineering Education at Purdue University. He has degrees from Swarthmore College, Rensselaer Polytechnic Institute, and the University of Florida. His research on the longitudinal study of engineering students and forming and managing teams has been supported by the National Science Foundation and the Sloan Foundation and his team received for the best paper published in the Journal of
improveretention, researchers have applied asset-based perspectives to studying retention of marginalizedstudents. This approach often emphasizes the role of social capital [1], [11] and socializers [12]–[14] as primary drivers of motivation to pursue STEM education and careers. This present paperbegins to unpack the unique relationship between socializers and the decision students atminority serving institutions (MSIs) make to pursue STEM. We report on the experiences ofstudents gathered using qualitative methods and examined through the lens of expectancy valuetheoretical framework.Theoretical Framework: Expectancy-ValueMotivation to pursue a career in STEM can be modeled through Eccles et al.'s Expectancy-Valuetheory (EV) [15]. EV establishes a direct
Education During the Pandemic: Responses to Coronavirus Disease 2019 From Spain," Frontiers in Psychology, Original Research vol. 12, 2021.[2] A. Bashir, S. Bashir, K. Rana, P. Lambert, and A. Vernallis, "Post-COVID-19 Adaptations; the Shifts Towards Online Learning, Hybrid Course Delivery and the Implications for Biosciences Courses in the Higher Education Setting," Frontiers in Education, Original Research vol. 6, 2021.[3] S. R. Jayasekaran, S. Anwar, K. Cho, and S. F. Ali, "Relationship of students' engagement with learning management system and their performance-An undergraduate programming course perspective," 2022.[4] I. A.-O. DeCoito and M. A.-O. Estaiteyeh, "Transitioning to Online Teaching
have been calls to develop and deploy graduate STEM education modelsthat prepare students for careers outside academia. Few innovations have emerged to meet students attheir current skill and preparation levels when entering their graduate studies while also consideringstudents' individual desired career paths. The U.S.'s current approach to graduate STEM education doesnot emphasize preparing students with professional skills and experience outside the lab. Further,students from differing socioeconomic and underserved backgrounds are often not adequatelysupported. Through a National Science Foundation Innovations in Graduate Education (IGE) award, theUniversity of Pittsburgh Swanson School of Engineering is creating and validating a
panel, interdisciplinary collaboration results inan emergent field [ABC] that requires a complete rethinking and development frominterdisciplinary fields A, B, and C. In the bottom panel, multidisciplinary collaboration, overtime, might bring A, B, and C disciplines “closer” but does not result in an emergent discipline.Note that //’s on the dashed lines denote the independence between the disciplines while the solid||’s represents the existence of commonalities between disciplines.Over time, these organic fusions induced by inter-/trans-disciplinary approaches cannot beeffectively and exhaustively categorized into any single, isolated, independent mother fields(e.g., squares A, B or C Figure 1, top left panel). The field of interdisciplinary
included adoption of contextualculturally relevant teaching practices, recognizing indigenous worldviews, respecting communityand family, and supporting indigenous knowledge systems.MethodologyKhan et al. established a process for conducting a systematic literature review: [6] (1) frame thequestion, (2) identify relevant work, (3) assess study quality, (4) create a summary, and (5)interpret findings. We have framed the question in the previous section. Khan et al.’s final twosteps, summary and interpretation, are found in the Results and Discussion sections below.In addition to following the Khan et al. methodology, we also observed the guidelines found inthe PRISMA 2020 statement, [7] specifically the paper and abstract checklists. Figure 1 is
(S-STEM) grant to increase engineering degree completion of low-income, high achievingundergraduate students. The project aims to increase engineering degree completion byimproving student engagement, boosting retention and academic performance, and enhancingstudent self-efficacy by providing useful programming, resources, and financial support (i.e.,scholarships). This work is part of a larger grant aimed at uncovering effective strategies tosupport low-income STEM students’ success at HBCUs. The next section will discuss thebackground of this work.Keywords: Historically black colleges/universities (HBCUs), learning environment,undergraduate, underrepresentationBackgroundA public historically black land-grant university in the southeastern
publications in the context of US No data range Include all publications until the date of the literature searchAbstract Review To test the initial inclusion criteria, a pilot abstract review was conducted. Thisabstract review was conducted using Rayyan (https://www.rayyan.ai), a collaborative systematicliterature review software for organizing, sharing, managing, and preserving records and data.Following Polanin et al.'s (2022) best practice guidelines, only 10% of the retrieved literature wasreviewed for the pilot study. The objectives were two-fold: 1) Search strategy refinement, aimingto further refine the inclusion criteria and their working definitions, and 2) Project management,to estimate an approximate number or
the object to learn about the different parts of theobject. The current supplemental videos provide a high-level view of the concepts, but theycould be split into smaller chunks or more targeted concepts/misconceptions to help the students.For future work, our team is focusing on developing the baseline VR/AR tool on normalsurfaces, as illustrated in this paper, the supplemental video, and the next integration of theenvironment and the video. We plan to pilot the tool in summer and fall classes this year.References[1] S. A. Sorby, N. Veurink, and S. Streiner, “Does spatial skills instruction improve STEM outcomes? The answer is ‘yes,’” Learn Individ Differ, vol. 67, pp. 209–222, Oct. 2018, doi: 10.1016/j.lindif.2018.09.001.[2] S
other contexts were not considered.• The research should incorporate at least one significant finding related to the discrimination encountered by Asian engineering students, even if this is not the primary research question the study aims to address. After refining the search criteria, we identified nine studies. These studies arelisted in Table 1.Table 1Selected Studies 1 Bahnson, M., Hope, E., Satterfield, D., Alexander, A., Briggs, A., Allam, L., & Kirn, A. (2022). Students’ Experiences of Discrimination in Engineering Doctoral Education. 2022 ASEE Annual Conference & Exposition. https://peer.asee.org/41006.pdf 2 Lee, M. J., Collins, J. D., Harwood, S. A., Mendenhall, R., & Huntt, M. B
of some complexity, and case participants need todiscuss and come to some solution(s) or plan(s) for the case. Shapiro’s book [9] lists the basicprocess as: 1. Case learners prepare for the case by reading and analyzing it 2. Optionally - students can perform a deeper preparation by having a priori small group discussions 3. An in-class discussion is done for the case 4. An end-of-class summary is provided by the facilitatorAs there are many books on the case method, our approach uses ideas from Rosenthal andBrown’s book for examples of pedagogically strong cases [10], and Barnes, Christensen, andHansen’s book [11] on how to teach cases (readers should note that this book is not only good forlearning about the case method, but
follow a similar set of rules.In general, any property that needs to be “accounted” for during a process would lend itself wellto be represented visually. A summary of such properties, their definition, and the courses thatthey are encountered in presented in Table 1. Before proceeding though, it is important toestablish the generalized accounting principle and define some nomenclature that will be usedthroughout the rest of this work.Table 1 Properties that can be accounted for, their definition, and course(s) in which they primar-ily appear — Ek , Ep , Usys , Eother are kinetic, potential, internal, and other sources of energy in thesystem; s is entropy per unit mass; T0 and P0 are the dead state (thermodynamic term) temperatureand pressure
, I think, because anybody can use the tool to give me a summary. I guess my view on that would be that maybe assessments can start looking at students' ability to critically analyze these summaries that GenAI tools provide, to reason about what is accurate, what is not accurate.’ (George)Our findings also aligned with Nikolic et al.'s (2023) suggestion for a shift in assessment fromonline to oral or in-person exams. A similar conclusion was reached by Qadir (2023), whobelieved a shift in assessment methods towards oral exams or individual projects could reducethe risks posed by GenAI, while the traditional way of assessment can be used as daily exercisewith less focus on the students’ final grades.Hillary proposed
that VR-based simulators were useful as a means of improving training in prostatepalpation through virtual prostate palpation simulator. Also, Singh et al. [18] study comparedthe effectiveness of VR videos to traditional 2D videos in fostering immersive experiencesfor interdisciplinary teams addressing clinical problems. Their study highlighted that VRenhanced collaboration and communication skills among participants, potentially extendingvirtual immersion to global clinical settings for broader student awareness in BME education.In addition, the study by Wilkerson et al.'s [19] explored the efficacy of VR videos inengaging students and improving their understanding in an undergraduate course. While thestudy revealed positive impacts on
]. Available: https://www.mass.edu/stem/documents/student%20interest%20summary%20report.pdf[6] S. Bhattacharyya, T. P. Mead, and R. Nathaniel, “The Influence of Science Summer Camp on African-American High School Students’ Career Choices: Influence of Science Summer Camp,” Sch. Sci. Math., vol. 111, no. 7, pp. 345–353, Nov. 2011, doi: 10.1111/j.1949- 8594.2011.00097.x.[7] K. A. Henderson, L. S. Whitaker, M. D. Bialeschki, M. M. Scanlin, and C. Thurber, “Summer Camp Experiences: Parental Perceptions of Youth Development Outcomes,” J. Fam. Issues, vol. 28, no. 8, pp. 987–1007, Aug. 2007, doi: 10.1177/0192513X07301428.[8] D. E. Chubin, G. S. May, and E. L. Babco, “Diversifying the Engineering Workforce,” J. Eng. Educ., vol. 94, no. 1
Faculty of the Faculty Cluster Initiative’s Learning Sciences Cluster at the University of Central Florida. Her research focuses on measuring self-regulated learning across research and learning contexts, such as STEM classrooms.Prof. Hyoung Jin Cho, University of Central Florida Professor Hyoung Jin Cho is the Associate Chair of the Department of Mechanical and Aerospace Engineering at the University of Central Florida. He coordinates two undergraduate programs – B. S. Mechanical Engineering and B. S. Aerospace Engineering. He has published over 130 peer-reviewed journal and proceeding papers. He has 12 and 6 patents granted in the U.S. and Korea, respectively, in the areas of sensors, microfluidic devices, and micro
]. Both face and contentvalidity search to decide the degree to which a construct is accurately translated intooperationalization. Face validity examines the operationalization at face value to determinewhether it is a good translation of the construct [26], while content validity examines theoperationalization compared to the construct’s relevant content area(s) (i.e., the appearance thatthe instrument measures what it is intended to measure) [27].Survey items were written by the first author and then reviewed and critiqued by various groups.The authors’ research lab group initially provided feedback on the survey questions’ clarity andreadability, and whether the items are relevant and right for measurement. This research groupbrings expertise
. This module emphasizes theimportance of practicing technology-life balance.The fourth module, Practicing and Promoting Technology-Life Balance, equips students with therelevant tools to rethink and reconstruct their relationship(s) with digital technology. It providesstudents with examples of ways to improve their technology-life balance and encourages an opengroup discussion surrounding the topic. Students are also encouraged to ask questions to developa deeper understanding of the module content thus far.The fifth and final module, Personal Reflection, is an individual reflection assignment gearedtowards encouraging long-term retention of the information provided. The assignment promptsstudents to create four obtainable goals related to
Tech University Virgil Orr Professor of Chemical Engineering Director of Biomedical and Chemical Engineering ©American Society for Engineering Education, 2024 Improving First-Year Engineering Student Success with Targeted Financial Assistance, Supplemental Instruction, and Cohort Team BuildingAbstractThis complete research paper assesses the first-year implementation of an NSF-funded S-STEMeffort, the SUCCESS Scholars Program (SSP), established in the Fall of 2022 at Louisiana TechUniversity.Louisiana Tech University is a Carnegie High Research Activity University that hasapproximately 20% of its 7500 undergraduates as engineering majors, is geographicallydistanced
credibility of the subject matter before wider dissemination andimplementation.References[1] M. H. Temsah, I. Altamimi, A. Jamal, K. Alhasan, & A. Al-Eyadhy, ChatGPT surpasses 1000 publications on PubMed: envisioning the road ahead. Cureus, 15(9) 2023.[2] G. Conroy, Surge in number of extremely productive authors’ concerns scientists. Nature, 625(7993), 14-15. 2024.[3] R. Van Noorden and J. M. Perkel, AI and science: what 1,600 researchers think. Nature, 621(7980), 672-675, 2023.[4] M. Binz, S. Alaniz, A. Roskies, B. Aczel, C. T. Bergstrom, C. Allen, C. and E. Schulz, How should the advent of large language models affect the practice of science?. arXiv preprint arXiv:2312.03759, 2023.[5] E. M. Bender, T. Gebru, A. McMillan-Major, S
research at the graduate level. However, studying creativity at thegraduate level is essential because creativity is required to generate new knowledge throughresearch. This study seeks to address the gap in knowledge about graduate-level creativitythrough a thematic analysis of five semi-structured interviews with engineering graduatestudents. These interviews are part of a larger mixed-methods research project with the goal ofcharacterizing the creative climate of graduate-level engineering education. In the interviews, weasked participants about their creative endeavors, how they define creativity, and theirperceptions of creativity within engineering. We used Hunter et al.’s (2005) creative climatedimensions as a theoretical framework to
project.BMC As a TemplateIn order to develop a framework that gives a detailed description of the project developmentprocess for an engineering or technology course, the Business Model Canvas was used as a basestructure. The Business Model Canvas (or BMC) is a tool used by industries worldwide to createan initial business model [6]. It is a blank framework that is comprised of nine individual “blocks.”The nine blocks include: ● Customer Segments - The customer(s) the company is trying to reach. ● Value Proposition - The product for that customer(s). ● Customer Channels - Ways in which they will connect with the customer(s). ● Customer Relationships - Focuses on the processes of getting, keeping, and growing the customer base
: 10.1002/j.2168-9830.2005.tb00833.x.[2] B. Balamuralithara and P. C. Woods, "Virtual laboratories in engineering education: The simulation lab and remote lab," Computer Applications in Engineering Education, vol. 17, no. 1, pp. 108-118, 2009, doi: 10.1002/cae.20186.[3] J. Ma and J. V. Nickerson, "Hands-on, simulated, and remote laboratories: A comparative literature review," ACM Computing Surveys (CSUR), vol. 38, no. 3, pp. 7-es, 2006, doi: 10.1145/1132960.1132961.[4] M. D. Koretsky, D. Amatore, C. Barnes, and S. Kimura, "Enhancement of Student Learning in Experimental Design Using a Virtual Laboratory," IEEE Transactions on Education, Article vol. 51, no. 1, pp. 76-85, 2008
work supported by a National Science Foundation DUEGrant No 2215807. Any opinions, findings, conclusions, or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the National Science Foundation’sviews.References[1] Litzinger, T., Lattucca, L., Hadgraft, R., & Newstetter, W. (2011). “Engineering education and the development of expertise.” Journal of Engineering Education, 100(1), 123-150.[2] Hake, R. R. (1998). “Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses.” American journal of Physics, 66(1), 64-74.[3] Streveler, R. A., Brown, S., Herman, G. L., & Montfort, D. (2015). Conceptual change and
, numerical, quantitative, and DM qualitative data. 13 Understanding the structure and characteristics of diverse datasets. DM 14 Merging or joining datasets from different sources to create a unified dataset. DM, 15 Using appropriate tools to visualize data distributions of missing values, duplicate values, inconsistency types, and outliers. DM 16 My ability to inform decisions to standardize or normalize values as needed, depending on project requirements. S, ML, B 17 In making informed decisions on handling invalid data. Based on the visualized data distributions and stakeholders
student interest and attitudes [17]. Interest in engineering has also been shown toincrease with outreach [18]. Additional work has shown that students participating in anengineering camp were more likely than control students to take STEM courses in high school[19].STEM identity describes the extent to which an individual sees themselves as a “science person”,“math person”, etc. [20]. STEM identity has also been linked to youth enrolling inpost-secondary STEM education [21]. Fit or belonging is also believed to be a factor in gendergaps in STEM enrolment, where explanations based on abilities, interest, and self-efficacy fallshort [22].While we list a number of possible constructs above, it is unclear which one(s) (such as STEMidentity and self
(S < 29) 31 (~57%) Neglected (29 <= S < 31) 12 (~22%) Reversed (31 <= S) 11 (~20%)The results above suggest that, for practicing engineers making decisions with data presented intabular form, targeting the consequences of variability is relatively difficult: Whereasengineering students readily targeted variability in scenarios with “everyday” variability (>90%of individuals targeted), in this pilot only ~57% of participants targeted variability correctly. It ispossible that the ~20% of participants with “reversed” responses were attempting to targetvariability, and that in a more deliberate setting (i.e., in the workplace), they would have