marginalized students in the engineering college, which consists of 12 disciplinary departments [1]. Our previous quantitative studyfound that students marginalized on the bases of gender, race/ethnicity, and/or household incomelevel experienced both disproportionately low representation rates and diminished outcomes. Weare interested in determining how the quantitative results are impacted by a focus specifically onaerospace engineering students.Existing research on retention of diverse students in aerospace engineering undergraduate programs is scarce. General reports of demographical representation are published annually by theAmerican Society of Engineering Education [2]. Orr et al.’s 2015 study [3] was effectively thefirst study to
. Mosterman et al., “Virtual engineering laboratories: Design and experiments,” J. Eng. Educ., vol. 83, no. 3, pp. 279–285, 1994, doi: 10.1002/j.2168- 9830.1994.tb01116.x.[3] M. Abdulwahed and Z. K. Nagy, “The impact of the virtual lab on the hands-on lab learning outcomes, a two years empirical study,” Proc. 20th Annu. Conf. Australas. Assoc. Eng. Educ. Eng. Curric., no. March, pp. 255–260, 2009.[4] M. D. Koretsky and A. J. Magana, “Using technology to enhance learning and engagement in engineering,” Adv. Eng. Educ., vol. 7, no. 2, pp. 1–53, 2019.[5] R. Heradio, L. De La Torre, D. Galan, F. J. Cabrerizo, E. Herrera-Viedma, and S. Dormido, “Virtual and Remote Labs in Education: a Bibliometric Analysis
and places it for assembly 3) Robot 3 assembles the cap on the markerworking of multiple robots controlled safely with the PLC. Three teams work on three differentrobots to program individual tasks.The color of the markers, blue, red and pink are chosen in the increasing order of contrast. Thebelt being black in color makes it difficult for the robot to detect the dark colors such as blue.The students have to adjust the environment lighting and create enough brightness for the camerato detect the blue contrast. The caps are placed in the search region of robot 3 and the openmarkers are placed in the region of robot 2. The robot 2’s vision system detects the markersposition and orientation in ascending order of contrast (blue, red and pink
things in nature (e.g., butterflies, rocks) Page 26.1552.5 star Observed or studied stars and other astronomical objects group Participated in science groups/clubs/camps comp Participated in science/math competition(s) nonfic Read/Watched non-fiction science Abbreviation Reported Interest/Experience scifi Read/Watched science fiction game Played computer/video games prog Wrote computer programs or designed web pages talk Talked with friends or family about scienceResults and
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
based learning environment. She was previously an engineering education postdoctoral fellow at Wake Forest University supporting curriculum development around ethics/character education.Dr. Diana Bairaktarova, Virginia Tech Dr. Diana Bairaktarova is an Assistant Professor in the Department of Engineering Education at Virginia Tech. Through real-world engineering applications, Dr. Bairaktarovaˆa C™s experiential learning research spans from engineering to psychology to learning ©American Society for Engineering Education, 2023 Empathy and mindfulness in design education: A literature review to explore a relationshipAbstractLearning to design in undergraduate
Paper ID #37422Board 398: The Effects of COVID-19 on Students’ Tool Usage in AcademicMakerspacesMr. Samuel Enrique Blair, Texas A&M University Samuel Blair is a Graduate student in Mechanical Engineering program at Texas A&M University in College Station, TX. His research interest include bio-inspired design of complex systems for human networks.Claire CroseDr. Julie Linsey, Georgia Institute of Technology Dr. Julie S. Linsey is a Professor in the George W. Woodruff School of Mechanical Engineering at the Georgia Institute of Technological. Dr. Linsey received her Ph.D. in Mechanical Engineering at The University
currently working at a start-up andperceives the climate to be much more positive than P0’s previous employer (a largecompany). P0 attributes this difference to the fact that it is a smaller company, and thuspeople are more apt to rely on and get to know each other.The interviewees used a variety of approaches to deal with their situations. P0 “never feltconnected with the Black [company employees]” and eventually left that company for asmall start-up. P1 did not expect to feel connected when first hired. Instead, P1’s approachwas to focus on the technical aspects of the job and “when I want to see Black folks I justdrive home.” P5 has decided,that I’m not pushing the envelope, I’m just sitting there collecting my paycheck…The less I dothe more
kg ρ(air density) 1.2 kg/m3 Coefficient of Drag CD 0.5Mass of Propellant 0.0625 kg dm/dt 0.03676 kg/s Trust T (constant) 80.35 N 2 Agravity 9.8 m/s t(burn) 1.7 s Mass ratio 0.85 2 θ 0 Frontal area A 0.0034211 m Total Impulse 136.6 N-s Time step analysis Vi+1= Vi+[Ti-Di-Migcosθi](Δt/Mi
thisprocess, students are bringing a variety of ideas of areas they are interested in studying, includingwater quality, air quality and walkability of their city. Using the refined ideas, the research teamadapts the sensors to the students’ question(s), and the student team(s) deploys the sensors. Theteams also simultaneously engage in qualitative data collection that provides more face-to-faceand in depth data about the identified community issue. Students then monitor and analyze datafrom the sensors to answer their question, and present their findings and potential solutions tocommunity members, parents and family members, other youth, and city officials. While also allowing the research team to evaluate CPS technology as a
focuses on policy and regulatory issues related to developing efficient and low-carbon energy sources [21]–[24].Future WorkAs we move into Year 2 of the project, we plan to develop the learning objectives and coursematerials for the energy course to be offered in Spring 2020. We will explore opportunities forhands-on student engagement with data analysis techniques, innovative homework problems, andlab activities. We will conduct assessment and evaluation to determine the impact of CSPs andmake improvements for the next offering of the course in Spring 2021.References[1] G. D. Hoople, J. A. Mejia, D. A. Chen, and S. M. Lord, “Reimagining Energy: Deconstructing Traditional Engineering Silos Using Culturally Sustaining Pedagogies
scientists and engineersfor the coming generations. Page 26.945.3IntroductionBentley and Kyvik, 2012 found in their studies that faculty members spend more than 50hours of their time every week on the job, out of which only 20 hours are spent doing theactual teaching. Depending on the faculty status, either Tenure-Track or Tenured, or even asa function of the nature of the institution in which one find himself/herself, research orientedor purely teaching institutions as the case may be, these hours can be much higher (Bentley,P.J., and S. Kyvik, S.).It would be needed to inculcate time-efficient teaching practices into these new courses fromhere-on in order to give the students the best and facilitate their learning in
(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
] S. Brunhaver, R. Korte, S. Barley, and S. Sheppard, “Bridging the gaps between engineering education and practice,” in Engineering in a Global Economy, R. Freeman and H. Salzman, Eds. Chicago: Chicago University Press, 2018, pp. 129–165.[3] C. Carrico, K. Winters, S. Brunhaver, and H. M. Matusovich, “The pathways taken by early career professionals and the factors that contribute to pathway choices,” Proceedings of the 2012 American Society for Engineering Education Annual Conference & Exposition, San Antonio, TX., June 2012.[4] C. J. Atman, S. D. Sheppard, J. Turns, R. S. Adams, L. N. Fleming, R. Stevens, R. A. Streveler, K. A. Smith, R. L. Miller, L. J. Leifer, K. Yasuhara, and D. Lund
asked to reflect on their experiences using the followingquestion:How often have you been in courses where some educational technology tools, especiallymobile applications, have been used? Tell us something about your experience. a. Please state the name of the application(s) or other technology tools (e.g., Clicker, CATME, Socrative, Any quiz software, etc.). b. What you liked about that application(s) and why? c. What you didn’t like and why? d. Were those applications academically relevant? If yes, why, if no, why not?Data AnalysisThe study focuses on exploring the students’ perceptions of using educational technology toolsin postsecondary STEM classrooms. To inform our study, we employed
to my 2.81 1.38transfer.I spoke to former transfer students to gain insight about their adjustment experiences. 2.63 1.38Scale: 1-Strongly disagree, 2-Disagree, 3-Neither agree nor disagree, 4-Agree, 5-Strongly agree; Meansare of weighted data. 1 Participants in co-enrollment program(s) were exempt from this survey item.Table 2. Perceptions about the "transfer process" while students were enrolled at [SI] Construct Sub-items Mean Std. Error (N = 1024)1 of Mean
for an intensive planningand analysis session. All of the focus groups have been transcribed and where possible, thespeakers have been identified so that textual analysis can be made by branch of service andmajor, among other things. The transcripts have been uploaded into Atlas.ti (a qualitative dataanalysis software program) and speakers will be identified with their salient characteristics asthey reported on their pre-qualification surveys. As analysis progresses, this will allow theresearch team to, for example, compare experiences and responses of Navy veterans to Armyveterans or mechanical engineering students to electrical engineering students.Preliminary Focus Group FindingsFrom: C. E. Brawner, C. Mobley, J. B Main, S. M. Lord, M. M
Davis S. Lewis Associate Professor in the Georgia Tech School of Aerospace Engineering Page 26.1129.1 c American Society for Engineering Education, 2015 Managing and Exchanging Knowledge Underlying Aerospace Engineering Design DecisionsIntroductionThe engineering design process is a complex, iterative process through which individuals andteams solve ill-defined, multidisciplinary problems by integrating domain-based technicalknowledge.1,2 Aerospace engineering integrates technical components from many differentdisciplines, such as aerodynamics, combustion, avionics
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
tailoredinterventions and resources to foster an environment conducive to profound transformation foreach student, addressing students' specific needs based on their current category oftransformation and facilitating their transition to the profound transformation category.References[1] M. A. Hutchison‐Green, D. K. Follman, and G. M. Bodner, "Providing a voice: Qualitativeinvestigation of the impact of a first‐year engineering experience on students' efficacy beliefs,"Journal of Engineering Education, vol. 97, no. 2, pp. 177-190, 2008.[2] S. S. Courter, S. B. Millar, and L. Lyons, "From the students’ point of view: Experiences infreshman engineering design course," Journal of Engineering Education, vol. 87, no. 3, pp. 283-288, 1998. [Online]. Available: https
entire MLprocess, fostering computational thinking and problem-solving [18]. Kajiwara et al. employed agamified ML role-playing game, simplifying concepts for high school students [15]. Ethicalconsiderations were integrated through projects like VotestratesML, which explored AI's societalimpacts in democratic contexts [20], and Kong et al.’s collaborative projects addressing fairnessand bias in AI systems [16].3.5 Results for RQ4: Which of the AI4K12 Five Big Ideas frameworks are being included?The AI4K12 Five Big Ideas rubric assessed studies on Perception, Representation & Reasoning,Learning, Natural Interaction, and Societal Impact, scoring from 0 (not addressed) to 4 (thoroughintegration). Results highlighted strengths in Learning
, quizzes (fixed-choice questions from the original workbook), and the software should be madeavailable to students on the university LMS.References[1] I. M. Smith, Spatial ability: its educational and social significance. San Diego, Calif.: R.R. Knapp, 1964.[2] D. L. Shea, D. Lubinski, and C. P. Benbow, “Importance of assessing spatial ability in intellectually talented young adolescents: A 20-year longitudinal study,” Journal of Educational Psychology, vol. 93, no. 3, pp. 604–614, 2001.[3] M. Kozhevnikov, M. A. Motes, and M. Hegarty, “Spatial Visualization in Physics Problem Solving,” Cognitive Science, vol. 31, no. 4, pp. 549–579, 2007, doi: https://doi.org/10.1080/15326900701399897.[4] S. Y. Yoon and E. L. Mann, “Exploring
with the search quadcopter. The sensors and technologies used on the rescuequadcopter are similar to that of the search quadcopter. The main difference was that an electropermanent magnet is utilized in this system to hold and release the rescue package to be deliveredto the survivor (s).Figure 10 shows the collision avoidance system being tested for the search quadcopter. The firstflight test was conducted by hovering the quadcopter roughly 3 feet above the ground andactivating the altitude hold flight mode. The copter was then slowly pitched forward towards awall until the safety zone was breached and the Arduino took over the pitch control.The students presented their work both at student conferences and a professional conference.20
National Center for Women in Information Tech- nology (NCWIT) and, in that role, advises computer science and engineering departments on diversifying their undergraduate student population. She remains an active researcher, including studying academic policies, gender and ethnicity issues, transfers, and matriculation models with MIDFIELD as well as student veterans in engineering. Her evaluation work includes evaluating teamwork models, statewide pre-college math initiatives, teacher and faculty professional development programs, and S-STEM pro- grams.Dr. Joyce B. Main, Purdue University, West Lafayette (College of Engineering) Joyce B. Main is Assistant Professor of Engineering Education at Purdue University. She
on Education, Vol. 48, No. 3, pp. 462–471, August 2005. 3. R. W. Ives, B. L. Bonney and D. M. Etter, “Effect of Image Compression on Iris Recognition”, IEEE Instrumentation and Measurement Technology Conference, Ottawa, Canada, May 17—19, 2005. 4. S. Cotter, “Laboratory Exercises for an Undergraduate Biometric Signal Processing Course”, ASEE Annual Conference and Exposition, Louisville, Kentucky, June 2010. 5. S. Cotter, “Assessing the Impact of a Biometrics Course on Students’ Digital Signal Processing Knowledge”, ASEE Annual Conference and Exposition, Vancouver, Canada, June 2011. 6. S. Cotter and A. Pease, “Incorporating Biometrics Technology into a Sophomore Level
students in Texas. Students accumulate transfer student capital, or knowledge about thetransfer process, at sending institutions (i.e., the place(s) where students begin their degreepaths), receiving institutions (i.e., the final degree-granting institution), and potentially from non-institutional sources. The development of transfer student capital may come from experiencesrelated to learning and study skills, course learning, perceptions of the transfer process, academicadvising and counseling, and experiences with faculty. Upon arriving at the receiving institution,students must adjust to the new environment academically, socially, and psychologically, all ofwhich may influence a variety of educational outcomes. Figure 1
, pp. 151–185, 2011.[6] Elementary science teachers’ sense-making with learning to implement engineering design and its impact on students’ science achievement[7] C. M. Cunningham and G. J. Kelly, “Epistemic Practices of Engineering for Education,” Science Education, vol 1010, no. 3, pp. 486–505, 2017.[8] T. J. Moore, A. W. Glancy, K. M. Tank, J. A. Kersten, K. A. Smith, and M. S. Stohlmann, “A Framework for Quality K-12 Engineering Education: Research and Development,” Journal of Pre-College Engineering Education Research (J-PEER), vol. 4, no. 1, 2014.[9] American Society for Engineering Education and Advancing Excellence in P12 Engineering Education. Framework for P-12 Engineering Learning, 2020
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
. Raghavan serves as a Professor and Associate Dean of Research and Graduate Studies at Embry Rid- dle Aeronautical University. Her research interests are in the areas of Mechanics of aerospace structures and materials. She joined UCF in Fall 2008 after completing her doctoral studies at Purdue University, Indiana, School of Aeronautics and Astronautics in the area of Structures & Materials. She obtained her M.S., Aeronautical Engineering in Structures at ISAE-SUPAERO, Toulouse, France where she also worked with Messier Bugatti in Velizy, Paris (S-92 wheels and brakes testing). Prior to this, she com- pleted her B.Eng in Mechanical Engineering at Nanyang Technological University, Singapore. She has 7 years of