distribution of years at the institution in required upper-level courses. Many students at thisinstitution engaged in cooperative education, and this participation helps account for the studentswho had beyond four years of enrollment. A total of 129 students indicated that they were male(56.7%), 45 students indicated that they were female (19.7%), three students indicated that theywere a non-binary gender (1.3%), and the rest preferred not to answer. Students were also askedto report their self-identified race and/or ethnicity. A total of 141 students indicated they werewhite (49.0%), two students indicated that they were Black or African-American (0.9%), 15students indicated that they were Asian (6.6%), one student indicated that s/he was
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Student Group PortfoliosFigure 5. Overall Rankings for Student Portfolios and Rankings by Students, Instructors, and Practicing Engineers Notably, group 5’s work was ranked #1 by practicing engineers and #2 by students butdid not make the top-ten for instructors while group 6’s work was ranked very similarly by allthree groups. Group 19 was ranked #1 by the instructors, #3 by the students, but did not makethe top-ten for industry members while group 18 was ranked almost identically by all threegroups. These similarities and stark differences in perceptions of comparative quality
. 12, 2018.[2] L. Wimsatt, A. Trice, and D. Langley, “Faculty Perspectives on Academic Work and Administrative Burden: Implications for the Design of Effective Support Services.,” Journal of Research Administration, vol 30, no. 1, pp. 77–89, 2009.[3] K. M. Hannum, S. M. Muhly, P. S. Shockley-Zalabak, and J. S. White, “Women leaders within higher education in the United States: Supports, barriers, and experiences of being a senior leader,” Advancing Women in Leadership, vol. 35, pp. 65–75, 2015.[4] E. Judson, L. Ross, and K. Glassmeyer, “How Research, Teaching, and Leadership Roles are Recommended to Male and Female Engineering Faculty Differently,” Research in Higher Education, vol. 60, no. 7, pp. 1025–1047
autism spectrum disorders during the transition to adulthood. J. Autism. Dev. Disord. 41 (5), 566–574. doi:10.1007/s10803-010-1070-312. Kouo, J. L., Hogan, A. E., Morton, S., & Gregorio, J. (2021). Supporting students with an autism spectrum disorder in engineering: K-12 and beyond. Journal of Science Education for Students with Disabilities. 24(11).13. Ehsan, H., & Cardella, M. E. (2019). Investigating Children with Autism’s Engagement in Engineering Practices: Problem Scoping (Fundamental). Proceedings of the ASEE Annual Conference & Exposition, 15027–15043.14. Steinbrenner, J. R., Hume, K., Odom, S. L., Morin, K. L., Nowell, S. W., Tomaszewski, B., Szendrey, S., McIntyre, N. S., Yücesoy-Özkan, S., & Savage, M
the NationalScience Foundation.References[1] D. F. Lohman, “Spatial Ability and G.” 1993.[2] K. S. McGrew, “CHC theory and the human cognitive abilities project: Standing on the shoulders of the giants of psychometric intelligence research,” Intelligence, vol. 37, no. 1, pp. 1–10, Jan. 2009, doi: 10.1016/j.intell.2008.08.004.[3] H. B. Yilmaz, “On the Development and Measurement of Spatial Ability,” International Electronic Journal of Elementary Education, vol. 1, no. 2, pp. 83–96, Mar. 2009.[4] C. Julià and J. Ò. Antolì, “Enhancing Spatial Ability and Mechanical Reasoning through a STEM Course,” International Journal of Technology and Design Education, vol. 28, no. 4, pp. 957–983, Dec. 2018.[5] M. Stieff and D. Uttal, “How
of growth mindsets than their White peers,yet they also reported lower levels of fixed mindsets [13]. Said differently, Ge et al.’s [13] cross-sectional study showed that White engineering students demonstrate a higher predispositiontowards a growth mindset and a higher predisposition towards endorsing a fixed view of theirabilities. An exploratory study aimed at understanding the relationship between students’engineering identity and mindsets longitudinally found that both a fixed and a growth mindsetwere positive predictors of identity [14]. However, the authors did acknowledge that there may bemoderating effects not considered in the model, such as course difficulty, that may also helpexplain the positive relationships [14]. The studies
the percentage of thestudents who submitted each of the lab assignments, for one section of the lectures and onesection of the labs, with the same instructor. There was a total of 6 lab assignments during Fall2018 (F’18) and Spring 2019 (SP’19). Starting Fall 2019 (F’19), we introduced additional labassignments. In Table 1, we are providing the mapping of the labs used in F’18 and S’19, to thenew labs used in F’19, Spring 2020 (S’20), and Fall 2020 (F’20) for consistency. The labassignments are mapped based on the complexity of implemented designs, language constructsused, and level of tool skills needed. We will continue to use the names for new labs (1 - 8). Percentage of submitted labs
motivation and positive engagement [11], [28]-[30]. Onthe contrary, controlling teacher behaviors have been shown to lead to negative motivation typesand restricted engagement [31], [32]. Using structural modeling, Fortier et al. (1995) demonstratethe positive influence of perceived competence and self-determination on autonomousmotivations and academic performance [7]. Greene et al. (2004) illustrate linkages betweenautonomy support and self-efficacy, mastery goals, strategy use, and achievement [33]. Walkeret al.’s path model shows that self-efficacy and intrinsic motivation can predict meaningfulcognitive engagement, while extrinsic motivations predict shallow cognitive engagement [8].Although empirical research that directly links different
increased active learning in programs topromote student success. Improving students’ abilities in engineering graphics benefits theengineering field by establishing a larger prepared workforce. A limitation of this study is thatnot all metrics possess an equal number of responses which can enable a balanced comparison ofresults. Further limitations include the characteristics of the institutions at which the studyapplied. Engineering degree programs and communities vary across the nation. How studentsreact at these two universities may vary from how students at other institutions react to the samemodel.References[1] Mason, G. S., Shuman, T. R., & Cook, K. E. (2013). Comparing the effectiveness of an inverted classroom to a traditional
in an academic support program(ACADSUPP; 0=no, 1=yes). We operationalize belongingness in out-of-class experiences withthe sense of belonging construct (SENSE_BELONG; continuous) and a variable measuring thefrequency of students’ interactions with close friends at their college (FRIENDS; 0=twice a termor less, 1=one to two times a month, 2=at least weekly).Table 2Model components (and related construct [28]) and survey items [26], [27] Model components Item/s (construct or survey) Precollege characteristics & experiences Gender Sex of respondent; Survey choices: Female, Male Financial resources Parents’ income
the Science and Engineering Road Show mobile lab and creates programs for local youth to educate and entertain with hands-on projects to challenge students’ engineering and science skills.Tala Katbeh, Texas A&M University at Qatar Tala Katbeh is a STEM Instructor and Program Coordinator at Texas A&M University at Qatar (TAMUQ) where she applies her enthusiasm for engineering to create curricula and engineering courses for school students. Katbeh is currently also pursuing her PhD at Texas A&M University, having graduated from TAMUQ with a BSc and MSc both in chemical engineering.Hassan Said Bazzi, Texas A&M University at Qatar Dr. Hassan S. Bazzi is the senior associate dean for research and
/TheLinkWing.pdf. [Accessed Dec. 26, 2022][2] E. Beheshti, D. Weintrop, H. Swanson, K. Orton, M. Horn, K. Jona, and U. Wilensky, “Computational thinking in practice: How STEM professionals use CT in their work,” in American Education Research Association Annual Meeting, San Antonio, TX, Apr., 2017.[3] J. Malyn-Smith, I. Lee, F. Martin, S. Grover, M. Evans, and S. Pillai, “Developing a framework for computational thinking from a disciplinary perspective, “ in Proceedings of the International Conference on Computational Thinking Education, International Conference on Computational Thinking Education, Hong Kong, HK, Jun., 2018.[4] L. Hood and L. Rowen, “The human genome project: big science transforms
students who took the survey were also satisfied with the program as indicatedby the 77% of survey respondents who agreed or strongly agreed that they would apply to be inthe ImageSTEAM program again. More than half of the students agreed or strongly agreed theywould recommend someone like them to attend the ImageSTEAM program (62%).AI workshops, in this paper, are viewed as problem-solving events using critical thinking toexplore ways and methods to improve learning using available tools. A comprehensive paperwill be made, when the third and final workshop is made in summer 2023. Lessons learned fromthe workshop experiences will be shared with the community.Acknowledgement: The authors thank the U. S. National Science Foundation for sponsoring
/S) transition, software-defined radio, through-the-wall radarimaging (TWRI)I.INTRODUCTION Materials common in construction are reinforced concrete or cement-based materials.Occasionally, these materials naturally develop cracks due to deterioration throughout their lifecycle. The detection of cracks, erosion, voids, and gaps in walls and structural supports is criticalin preventing structural failures. Microwave-based, non-invasive techniques such as Non-Destructive Testing (NDT) are preferred to detect structural anomalies since there is no impacton the integrity of the structure or material due to the penetration ability of microwaves intodielectric materials. Current NDT equipment have several limitations and drawbacks, such asbeing
these programsthrough learning how participants in K12 STEM outreach programs define mentoring. Thispaper focuses on one research question from our pilot study: How do university student mentor definitions of “mentoring” compare to those of faculty / staff program coordinators?Theoretical FrameworkTo categorize participants’ definitions of mentoring, the research team utilizes Pfund et al.’s [14]attributes of effective mentoring relationships, which are “supported by the literature andsuggested by theoretical models of academic persistence” [p. S238]. This framework was chosenbecause of the ample existing metrics and examples of measurable learning objectives provided,which can be mapped to experiences participants share in their
multidisciplinaryapproach, Proceedings of the 7th International Management Conference, "New Management forthe New Economy", November 7th-8th, 2013, Bucharest, Romania[7] F. C. Bothma , S. Lloyd & S. Khapova (2015). Chapter 2 Work Identity: Clarifying theConcept, pp. 23-51, Springer Science+Business Media Dordrecht, 2015 23 P. G .W. Jansen, G.Roodt (eds.), Conceptualising and Measuring Work Identity, DOI 10.1007/978-94-017-9242-4_2[8] R. L. Cruess, S. R. Cruess, J. D. Boudreau, L. Snell & Y. Steinert (2015). A schematicrepresentation of the professional identity formation and focialization of fedical students andresidents: A guide for medical educators. Academic Medicine, vol. 90(6), June 2015[9] K. Adams, S. Hean, P. Sturgis & J. M. Clark, (2006
., Brooke, C., Mickelson, S., and Freeman, S. (2009). Assessing student work to support curriculum development: An engineering case study. Journal of Learning Communities Research, 3(3), Dec 2008/Jan 2009, 47-62. 5. Richter, D.M. and Paretti, M.C. (2009). Identifying barriers to and outcomes of interdisciplinarity in the engineering classroom. European Journal of Engineering Education, 34(1), 29-45. 6. Seidel, V.P. and Fixson, S.K. (2013). Adopting design thinking in novice multidisciplinary teams: The application and limits of design methods and reflexive practices. Journal of Product Innovation and Management, 30(S1), 19-33. 7. Adams, R.S. and Felder, R.M. (2008). Reframing professional development: A systems approach to preparing
. Tversky, Eds. New York, NY: Cambridge University Press, 1982, pp. 201–208. their career when encountering with participants. coding and thematic coding. The quantitative 2 N. J. Roese, “Counterfactual Thinking,” Psychol. Bull., vol. 121, no. 1, pp. 133–148, 1997. 3 K. D. Markman, I. Gavanski, S. J. Sherman, and M. N. McMullen, “The Mental challenging situations, such
Technology (PCAST. ) “Transformation and opportunity: The future of the U.S. research enterprise”, Report to the President, 2012.[5] C. Wendler, B. Bridgeman, R. Markle, F. Cline, N. Bell, P. McAllister and J. Kent. Pathways Through Graduate School And Into Careers. Princeton, NJ: Educational Testing Service, 2012.[6] H. S. Barrows, Practice-Based Learning: Problem-Based Learning Applied To Medical Education. Springfield, IL: Southern Illinois University, 1994.[7] H. S. Barrows, How To Design A Problem-Based Curriculum For The Preclinical Years. New York, NY: Springer, 1985.[8] I. Choi, Y. C. Hong, H. Park, and Y. Lee, “Case-based learning for anesthesiology: Enhancing dynamic decision-making skills through
theperception of stress as part of engineering culture stress perception can also attract more studentsfrom marginalized groups.References1 Schneider, L. in A Paper Presented at St. Lawrence Section Conference. Toronto, Canada. Retrieved from: www. asee. morrisville. edu.2 Ross, S. E., Niebling, B. C. & Heckert, T. M. Sources of stress among college students. Social psychology 61, 841-846 (1999).3 Goldman, C. S. & Wong, E. H. Stress and the college student. Education 117, 604-611 (1997).4 Hudd, S. S. et al. Stress at college: Effects on health habits, health status and self-esteem. College Student Journal 34, 217-228 (2000).5 Macgeorge, E. L., Samter, W. & Gillihan, S. J. Academic Stress
motivating them to choose a career path in thearea of UAV technologies.AcknowledgementThe project is funded by the NSF’s EEC Program. We would also like to thank Lockheed MartinCorporation and Northrop Grumman Corporation, and NASA Armstrong Flight Research Centerfor hosting the participants and giving them a tour their research labs and facilities. We wouldalso like to thank Northrop Grumman Corporation and Lockheed Martin Corporation for theircontinued support of the UAV Lab at Cal Poly Pomona.References[1] S. Bhandari, Z. Aliyazicioglu, F. Tang, and A. Raheja, “Research Experience for Undergraduates in UAV Technologies,” Proceedings of American Society of Engineering Education Annual Conference, Salt Lake City, UT, 25-28 June 2018
-making andconflict management practices thereby enhancing productivity. In addition, support systems forinclusivity and accountability such as the responsibility matrix, team building ice breakers oractivities, and action items trackers facilitated trust management and relationship building [24].Furthermore, team management artefacts such as project schedule(s), task list(s), meeting notes,procurement and budget tracker(s) supported students’ efficient time management practices.While the project schedule facilitated planning of design project activities, the task listsfacilitated work transparency; meeting notes enabled progress tracking of tasks, and theprocurement tracker allowed for cost transparency of design project purchases. The
culturewith a focus on better supporting traditionally underrepresented students. Subsequent researchwill explore how student participation in these types of engagement activities correlate to thedevelopment of an inclusive makerspace and engineering education culture.Acknowledgement – This material is based upon work supported by the National ScienceFoundation S-STEM program under Grant No. 1834139. Any opinions, findings, andconclusions or recommendations expressed in this material are those of the authors and do notnecessarily reflect the views of the National Science Foundation.References[1] M. Galaleldin, F. Bouchard, H. Anis and C. Lague, "The impact of makerspaces on engineering education," in Proceedings of the Canadian Engineering
. Bilec, A. Dukes, A. Nave, A. Landis, and K. Parrish, “Developing and Sustaining Inclusive Engineering Learning Communities and Classrooms.” In 2022 ASEE Annual Conference & Exposition, Minneapolis, MN, 2022.[3] D. T. Rover, M. Mina, A. R. Herron-Martinez, S. L. Rodriguez, M. L. Espino, and B. D. Le, “Improving the Student Experience to Broaden Participation in Electrical, Computer and Software Engineering,” in 2020 IEEE Frontiers in Education Conference (FIE), 2020, pp. 1–7.[4] L. Long and J. A. Mejia, “Conversations about Diversity: Institutional Barriers for Underrepresented Engineering Students,” J. Eng., vol. 105, no. 2, 2016.[5] M. E. Matters, C. B. Zoltowski, A. O. Brightman, and P. M. Buzzanell
• Academic calendar timing challenges • Resources 17Call to ActionWhat’s Next?• Data informed decisions• Faculty development• Improve MP process• Course coordination• Improve classroom space 018DiscussionReferences:[1] G. C. Wolniak, M. J. Mayhew, and M. E. Engberg, “Learning's Weak Link to Persistence,” The Journal of Higher Education, vol. 83, pp. 795-823. 2012.[2] M. W. Ohland, A.G. Yuhasz, and B.L. Sill, “Identifying and removing a calculus prerequisite as a bottleneck in Clemson's General Engineering Curriculum.” Journal of Engineering Education, vol.93, no.3, pp.253-257. 2004.[3] J. Handelsman, S. Elgin, M. Estrada, S. Hays, T. Johnson, S. Miller
. Expansion to other campuses and disciplines, using a self-sustaining model such as theone employed in Supplemental Instruction may ensure that the value WATTS provides is able toendure.AcknowledgementThe authors are grateful to the National Science Foundation for their generous funding of thiseffort at PSB, IUPUI, and UTRGV. The authors are also grateful for the lasting contributions ofMr. Jon Meckley, who was not only a key contributor to this research effort but also a kind,witty, and caring human being. He will be greatly missed.References[1] S. Wu, S. Zha, and S. Mattson, “Integrating team-based learning modules to improve civil engineering students’ technical writing skills,” Journal of Civil Engineering Education 146, no. 3, 2020.[2
MSIPP DE-NA0003980.The authors are thankful to the support of the DOE/NNSA program manager and the colleaguesat participating universities and national labs. Special thanks to Dr. Stephen Egarievwe atMorgan State University for his constant support and collaboration.References 1. J. Kennedy, P. Abichandani and A. Fontecchio, “An initial comparison of the learning propensities of 10 through 12 students for data analytics education,” IEE Frontiers in Ed- ucation Conference, Oklahoma City, OK, pp. 916-918, 2013. 2. Hirsch, D. D. (2013). The glass house effect: Big Data, the new oil, and the power of analogy. Me. L. Rev., 66, 373. 3. Iqbal, R., Doctor, F., More, B., Mahmud, S., & Yousuf, U. (2020). Big data analytics
tuition and other funding purposes, studentsenrolled in the 3+2 Program are treated as undergraduate students, and thus they are eligible forfunding as they work on multiyear projects with undergraduate students.Note that the project described here does not entirely fit the VIP Program definition from the VIPConsortium [15]. Namely, students may take research credits which are graded S/U. If they takethese credits as Independent Study, then they are graded A-F. Also, Senior Seminar is graded S/Uwhile Senior Design Project is graded A-F. So, there is a mix of grading types that was agreedupon by the program faculty.Moreover, stipends to fund participating students are secured through grants. About $2000 perstudent team for a senior design project
up disproportionate space 6 (0.42%) *Not coded as either inclusive or 967 (68.39%) marginalizing Inclusive Moves(1) Encouraging sharing. One way students increased the participation of other students was by encouraging sharing, which we define as proactively putting out an open-ended call for others’ input. To be coded as an encouraging sharing move, a student’s utterance had to go beyond simply asking for affirmation or refutation of an idea they themselves had stated. For example, when working on a problem about a firefighting hose, S made an encouraging sharing move when they put out a call for a peer’s idea: S: Yeah. What do you think Abe? What should we do?(2) Acknowledging
work supported by the National Science Foundation under AwardNumbers 2114241 and 2114242. 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.ReferencesBartlett, R. (2013). Playing with meaning: using cartoons to disseminate research findings. Qualitative Research, 13(2), 214-227.Berhane, B., Secules, S., & Onuma, F. (2020). Learning While Black: Identity Formation and Experience for Five Black Men Who Transferred Into Engineering Undergraduate Programs. Journal of Women and Minorities in Science and Engineering, 26(2), 93–124. https://doi.org/10.1615/JWomenMinorScienEng