Employers Students 0.0 20.0 40.0 60.0 80.0 100.0 Very well prepared Well prepared Fairly prepared Somewhat prepared Not at all prepared Don't know/unsureFigure 1. Overall sentiment about the preparedness of Materials Engineering graduates in theMaterials Science and Engineering industryThe stakeholders were further asked to reflect on the relevance of key knowledge and skillsobtained from Materials Engineering degree (i) when applying for jobs and (ii) in relation tothe actual duties performed in their roles. a. Relevance of key knowledge and skills obtained
also experienced by students in the class. The authors found that a simple,extended pause after asking a question can be a wonderful place to start promoting studentengagement. Usually (eventually) someone spoke up to start a dialogue when the silence wasallowed to linger. Active learning strategies are the next step, shown to increase studentengagement and knowledge retention [28] active or cooperative learning strategies consist ofpauses and time for students to reflect on and further absorb course content. These methods arevaried by discipline and take many forms, but the result is a delineation from traditional lectures[29] to combat fatigue experienced by both students and educators [19].Building positive student-centered learning
student groups receiving funding from the student activitiesbudget that they must take attendance at all events. This attendance is taken through a phone appclub leaders have to scan or check in attendees to events. The authors accessed this data from theuniversity repository for team meetings for the academic years of 2021-2022, 2022-2023, and thefall of 2023 in which the observations of the team took place.ResultsThe authors decided to break the results into three subcategories of belonging, identity andinteractions which impact the participation of women and minority students within theengineering design and build team. The subcategories reflect three key areas which wereobserved over the study during in person observation and review of field
conducted theinterviews. The first author’s experience created a bias that undoubtedly informed their responseto the participants and motivated the probing questions they offered. The first author engaged inself reflection in the attempt to recognize their assumptions between interviews. They are stillworking to identify their implicit biases. The first author provides an in-depth consideration oftheir current and historical understanding of their positionality on their websitedcbeardmore.com.The second author (she/her/hers) has experienced dis/ability through close family members’challenges with depression, cancer, anxiety, ADHD, and hearing loss. She has also workedclosely with students facing an array of dis/abling conditions and non-normative
havegraduated and pursued distinct paths. Student A is now pursuing a Ph.D. in robotics, and StudentB is now the CEO of a tech startup in AI. The interviews aimed to explore the lasting impact ofthe Inno Wing on their development. When reflecting on the impact of the center during theirstudies, both students emphasized its role as a unique infrastructure supporting students'innovations and prototyping. Student A articulated, “It supports students' engineeringexplorations and crazy ideas. We put our theoretical innovations of robotic fish design intoimplementations here…,”.Regarding the perceived value of the Inno Wing, both students referred to it as a hub whereengineering enthusiasts, great ideas, and achievements converge, creating a stimulating
bondswith the community at an early age.Role models and their representationsThe feeling of isolation, balancing an engineering career with family life, academicdissatisfaction, and lack of minority role models on campuses can reduce representation. Thereis a need for equitable access of students to role models of similar gender and race. Most femalesindicated that encouragement and validation from someone like them can help build theirengineering confidence and level of self-efficacy. College administrators should seek diversefaculty to reflect the student body and to encourage/motivate an increase in femalerepresentation.Quality Teachers with engineering knowledgeThe participating students emphasized the need for early exposure to engineering via
, synthesis, reflection, and evaluation of thematerial being taught [38]. This approach includes a range of teaching methods such as briefreflective writing assignments, think-pair-share activities, flipped classroom models, inquiry-based learning, and cooperative learning strategies. These methods not only enhance students'engagement and personal commitment to their studies but also improve motivation, enjoyment,depth of learning, critical thinking abilities, as well as retention rates and academic performancein classroom settings. Classrooms that offer students the chance to engage in mathematicalInterest & Engagement Tactics for Success 5exploration, communication, and collaborative
Engineering from the University of Science and Culture in Tehran, Iran. Her research interests include software engineering, cloud computing, data visualization, and Machine learning.Mr. Rohit Hemaraja, The University of Arizona Rohit Hemaraja is a Master’s student in Data Science at the School of Information at the University of Arizona. He is a Graduate Research Assistant with the Analysis of Higher Education Research Group. He earned his Bachelor of Engineering degree in Computer Science. His research focuses on machine learning, large language models and data management. His academic and professional interests lie at the intersection of these disciplines, reflecting his commitment to advancing the capabilities and
Keating, Jessica Rivera, Louie Rodriguez, Deana Pennington, Elsa Villa,John Wiebe, Lucina Zarate. The authors would also like to thank the reviewers who contributedto improving the paper's quality.This material is based upon work supported by the National Science Foundation under Grant No.2122607 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] A. S. Bryk, “2014 AERA Distinguished Lecture: Accelerating How We Learn to Improve,” Educational Researcher, vol. 44, no. 9, pp. 467–477, 2015, doi: 10.3102/0013189X15621543.[2] A. Kezar, “Higher Education Change and Social Networks: A Review of
analysis of the and reflectively expected results with the theoretical model and the experimental results obtained.In the laboratory classes, the students were divided into teams of three or four members.Each team was provided with a spring and one type of an elastic bands (each one can beassociated with a specific color): a) The minimum resistance – yellow one; b) Low-intermediate resistance - blue one; c) Upper-intermediate resistance - red one; and d) Themaximum resistance – black one. Both materials were characterized for an interval rangingfrom 0 to 40 cm with a 2.0 cm step. Then the characteristic curves (force as function ofelongation) were obtained and the data was analyzed using
, also influential in this process is the presence of a mentor or rolemodel. Previous studies of undergraduate females suggest the greatest need for role models is forthose students pursuing a nontraditional career [16]. This outlook is reflected in several aviationstudies that address both recruitment and retention of female pilots. A lack of a visible femalerole model was cited as one of the top barriers to outreach [17] [18]. Females in aviation maintenance also experience this challenge. One study found that thetop three barriers preventing women from pursuing a career in aviation maintenance are theabsence of role models, mentors, and personal contacts [20]. Further, a study that investigated, inpart, the appropriateness of aviation
guest speakers from academia andindustry, individual homework assignments where students reflected on what they learned fromthe speakers, and a group project to design a sustainable human habitat on the planet Mars. InFall 2023, a new instructional team (1 lead professor, 2 undergraduate and 1 graduate courseassistants, and 1 education specialist) was mentored by an instructional team in the Chemical andBiological Engineering Department to redesign the course. The course redesign features twogroup socio-technical design challenges and weekly individual homework for students toresearch disciplinary sub-specialties and career opportunities. During the first month ofinstruction, students are oriented to campus, the major, resources within the
much-needed environments to foster success.AcknowledgmentsThis material is based upon work supported by the National Science Foundation under AwardNumber #REDACTED. Any opinions, findings, and conclusions, or recommendations expressedin this material are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.References[1] X. Wang, “Upward Transfer in STEM Fields of Study: A New Conceptual Framework and Survey Instrument for Institutional Research,” New Dir. Institutional Res., vol. 2016, no. 170, pp. 49–60, Dec. 2016, doi: 10.1002/ir.20184.[2] Sansing-Helton, Coover, and Benton Jr, “Increasing STEM Transfer Readiness Among Underrepresented Minoritized Two-Year College Students
we learned about in theundergraduate mechanical engineering curriculum such as Materials Science and Engineering.An example is provided where we have attempted to reflect on the experimental data that iscollected based on fundamentals of mechanical property behavior that we learned about in thatcourse. This research work presents unique challenges we have faced in getting involved andperforming the assigned work. This paper can be used as a platform for other institutions withsimilar populations on practices and instruction that can get non-traditional students involved inimpactful research and in the process gain invaluable knowledge and a meaningfulundergraduate experience.IntroductionUVU is an open-admissions public teaching institution
work that they could include in their design portfolio, whichwas not a concern voiced during iteration 2. Of course, many of these differences in attitudescould be due to reasons unrelated to the course structure and delivery, such as the personalities ofthe students.The biomedical engineering students’ attitudes, captured only from iteration 2, were generallyvery positive, with most of the negative opinions isolated to the two groups who were pairedwith the weakest performers from the product design class. The results overall suggested that thecollaboration was a more positive experience for the biomedical engineering students than theproduct design students. This is reflected in the responses to the final question about whetherthey would
NationalScience Foundation research. Any opinions, findings, and conclusions or recommendationsexpressed in this material are those of the author and do not necessarily reflect the views of theOffice of Naval Research or the National Science Foundation.References[1] B. K. Townsend and K. Wilson, “A hand to hold for a little bit: Factors facilitating thesuccess of community college transfer students to a large research university,” Journal ofCollege Student Development, vol. 47, no. 4, pp. 439-456, 2006. [Online]. Available:https://doi.org/10.1353/csd.2006.0052.[2] D. D. Buie, “Beyond a deficit view: Understanding the experiences of first-generationstudents who participate in college access and success community-based organizations,” Ed.D.dissertation
andthe R.O.S.E Research Group at the University of Cincinnati. Without your support and guidanceduring the writing process, this document would not be what it is. We are honored to be a part ofthese outstanding groups of scholars.This work is based on research supported by the National Science Foundation Grant Awardunder Grant No. 2212690. 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] K. J. Jensen and K. J. Cross, “Engineering stress culture: Relationships among mental health, engineering identity, and sense of inclusion,” J. Eng. Educ., vol
student engagement, critical thinkingskills, and overall learning outcomes. The current study contributed to the discourse on thetransformative potential of hands-on learning in the context of biology education.Massachusetts Institute of Technology (MIT) Digital Learning Lab, in one of their articles [26],conceptualized hands-on learning as a cyclical process that encompasses concrete experience,reflective observation, abstract conceptualization, and active experimentation. A few studieshave shown how hands-on learning improves student outcomes, including motivation andengagement, conceptual knowledge, critical thinking, and problem-solving development. Tofurther substantial the ongoing discussions, some studies [27], [28] have found that hands
activities of the course studied?” Our datasuggest that students’ learning of the literacies of HCD is reflected through the different stages oftheir capstone project. Moreover, they used the literacies as tools for honoring the voices andexperiences of the community where they implemented their project.Our study offers implications for engineering education. Foremost, although not directly theobject of this paper, it is impossible to understand learning without considering teaching. In aphenomenographic study, Zoltowski et al.[46] argue that students’ ways of understanding andexperiencing HCD have different degrees of comprehensiveness. Our data show that focalstudents seem to present a comprehensive perspective of HCD: The main issue with the
supported by the National Science Foundation under GrantNumbers 2346868 and 2144698. Any opinions, findings, and conclusions 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 Team Y for participatingin this study and for their willingness to open their meetings to us and provide feedback on theinitial drafts of this paper. We would also like to thank Dr. Nicola Sochacka for her insightfulfeedback and discussions as we analyzed our initial data. Finally, we would like to thank themembers of the ENLITE research team who gave feedback to the drafts of this paper.References[1] M. Borrego and L. K. Newswander
judgements), the appreciation of the idea (appreciatingfeedback) and managing the emotions associated with the idea (managing affect). Thus, anappropriate framework for idea acceptance would comprise of the same three areas, justworded to reflect their association to any idea as opposed to feedback literacy. This modelcan be seen in Figure 3. Apprecia�ng the Topic Evalua�ng the Idea Managing Affect Idea AcceptanceFigure 3: The Proposed Idea Acceptance Model. The model contains three dimensions: Appreciating the Topic, Evaluatingthe Idea and Managing Affect. All three dimensions are required to achieve Idea Acceptance.This model is also inspired by the
Communication 161 Total 962Also not reflected in these numbers is the use of our materials by our industrial stakeholders.After working with us as consultants, two of our industrial consultants requested access to thevideos for use in onboarding new employees. We gave them access to our videos, but we werenot able to give them access to our learning management system and the ability to earn badges,since Brightspace usage is restricted to Purdue affiliated users.Table 2 and Figures 1-3 contain selected comprehensive results of the feedback surveys fromstudents in the pilot courses. We chose to present comprehensive results (rather than results byclass, gender, etc.) since our aim for the pilot
, the simplicity of the project naturally yields the project to be used in awide variety of learning environments and student learners. When implementation does occur, the generatedresults would need to be studied and further modifications would be made to the teaching approach.Eventually, the module and learning materials along with the project will be made highly accessible toeducators through a centralized soft robotic teaching website being developed at Rowan University.AcknowledgementsThis material is based upon work partially supported by the National Science Foundation under Grant No.2235647. Any opinions, findings, conclusions, and recommendations expressed in this material are thoseof the authors(s) and do not necessarily reflect the
could be’, 2019, doi: 10.1007/s11186-019-09345-5.[26] S. Hunziker and M. Blankenagel, ‘Single Case Research Design’, Research Design in Business and Management, pp. 141–170, 2021, doi: 10.1007/978-3-658-34357-6_8.[27] R. H. Horner and J. Ferron, ‘Advancing the Application and Use of Single-Case Research Designs: Reflections on Articles from the Special Issue’, Perspectives on Behavior Science , vol. 45, pp. 5–12, 2021, doi: 10.1007/s40614-021-00322-x.[28] V. S. Athota and A. Malik, ‘Within-Case Qualitative Analysis’, Managing Employee Well-being and Resilience for Innovation, pp. 95–174, 2019, doi: 10.1007/978-3-030- 06188-3_5.[29] I. Halevi Hochwald, G. Green, Y. Sela, Z. Radomyslsky, R. Nissanholtz-Gannot, and O
lecture series program Q7. How did the [component] Mean 3.875 3.333 affect your sense of belonging in the research group? Std. dev. 0.696 0.471PALS surveyThe Patterns of Adaptive Learning Scales (PALS) survey is demonstrated in the literature toaccurately predict the motivation and persistence among students that engage in researchexperiences [15 ,11][19 ,18]. This instrument can assess the perceptions of student’s goals,which include orientations that are classified as mastery (or task), performance-approach, andperformance-avoidance. The revised scales were used in this study to reflect the adaptation of thePALS survey to measure goal
has been known to significantly increase success, retention, and graduationrates. We noticed the differences in the level of preparedness and its influence on the student’sperception of their journey. We also explored the influence of soft skills, outlook, scholarlyattributes, and support on the perception of the journey through the program. Although ourparticipants have reported that they did not perceive any overt sexism or racism, we present thefindings correlated with gender and race/ethnicity.Our future work will include fine-tuning the protocol to explore intersectionality and reflect uponthe situations where the students might feel minoritized. Additionally, the students in the futurestudy will be purposefully selected to examine
CS.Next, the theme of collaboration was also found to be beneficial for students’ formation of bondsin CS. This result is reflected in prior work whose results suggest that the long-term impacts ofproject-based learning in STEM transcend traditional learning outcomes to also includeprofessional advancement and friendships [60]. Further, authors demonstrate that students’exposure to collaborative assignments are a significant, positive predictor of their persistence inCS [26]. Interestingly, however, the more recent work of Lehman et al. [32] found that students’exposure to collaborative pedagogy in introductory CS courses was a significant, negativepredictor for persistence. In their discussion, they suggest that the surprising result may
betelling of how students approach learning with the affective domain [14]. Also, returning to theidea that the domains are connected is reflected in the fact that many of studies found focus on twodomains at a time instead of only one domain at a time [4-7], [14-19]. Several studies exist thatresearch the domains, but they focus on testing a specific class within engineering or non-engineering majors [4-6], [9], [14-16], [18], [20]. Similarly, the studies that focus on math orchemistry classes may not have tested solely engineering students, which could still distort or skewresults towards conclusions that may not apply to engineering students overall [4-5], [21]. Theproblem with these studies is that their findings cannot be generalized for all
items passed the .32 criteria, and together, the model explained a totalof 46.26% variance. Therefore, we proceeded with the more parsimonious one-factor solution.The one-factor CFA model fitted poorly to the data. Therefore, we explored the modificationindices. By allowing error covariances of similarly worded items (i.e., between items 16 and 18,19 and 21, 17 and 23, 19 and 22, 19 and 20, and 20 and 21), we reached an acceptable model fitfor the one-factor solution of the CFA sample (χ2 = 137.52, df = 16, p < 0.001, RMSEA = 0.1095% CI [0.085, 0.116], CFI = 0.96, TFI = 0.93). All items loaded above .50 onto the mindsetfactor. These modifications reflected the covariance among items that focused on intelligenceand among items that focused on