contributions of Philipp Müller and Adam Probst of the TechnicalUniversity of Munich, Shanon Gilmartin, and the support of all of our colleagues in theDesigning Education Lab at Stanford University. This work was supported by the NationalScience Foundation as a collaborative research grant (NSF-DUE-1020678, 1021893, 1022024,1022090, and 1022644). Any opinions, findings and conclusions or recommendations expressedin this material are those of the authors and do not necessarily reflect the views of NSF.Bibliography1. Byers, T., Seelig, T., Sheppard, S., & Weilerstein, P. (2013). Entrepreneurship: Its Role in Engineering Education. Summer Issue of The Bridge on Undergraduate Engineering Education, 43(2), 35-40.2. Bonnett, C., &
the conceptual design phase andabout 75% of the preliminary design phase. Teams had presented a Conceptual Design Reviewand Preliminary Design Review to the AerosPACE Advisory Board. The purpose of this sectionis to demonstrate what the multi-disciplinary, multi-university teams were able to accomplishafter one semester.Figure 4 shows Team 1’s interpretation of the UAV mission profile. Each team was asked torespond to the RFP and throughout the conceptual and preliminary design phases a clearunderstanding of the mission requirements was emphasized. Figure 4. Team 1 PDR RequirementsAn important outcome of the conceptual design phase is a constraint diagram to identify feasibledesign space based on takeoff, maximum
senior-level undergraduatestudents with a minority of graduate students. The course is a four-credit class, and involvesboth a lecture and a laboratory component. The lectures, however, do not introduce any newfundamental principles in the fluid and thermal sciences. Instead, the lectures serve to reviewand apply principles that have already been taught in introductory classes in thermodynamics,fluid mechanics and thermal energy transport. The laboratory component is strictly gearedtoward design, synthesis and evaluation, utilizing knowledge, and comprehension learned inprevious courses.The Fluid and Thermal System Design course was instituted in the 1970’s to be the primary fluidand thermal design experience for graduating seniors. As a four
act with respect to context, or to a string ofcorrelated events. For our purposes, we need an agent that is able to make a judgment based onthe current information it has about what a user has done thus far in a problem situation. This“internal state” defines each step of a proof in the context of what has already been attempted.The basic operation of such an agent is shown in Figure 4. This will be our basic architecture forour first experiments. Figure 4: Algorithm for Reflex Agent with StateGoal-Based AgentsAt the heart of all tutoring systems lies the a priori knowledge of expert(s) in the chosen domain
E S ALL EE COURSES A V E R A G E Q U A L IT Y O F O P P O R T U N IT Y 54 .5 43 .5 32 .5 21 .5 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 E D U C A T IO N A L O U T C O M E S ALL EE COURSES A V E R A G E A C H IE V E M E N T 54 .5 43 .5 32 .5 21 .5 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 E D U C A T IO N A L O U T C O M E S Figures 3 A, B, and C Student Survey Results for All EE
Ensure code quality through automated continuous testing.Data Collection and AnalysisTo examine how the semester-long experience impacted students, we regularly requestedstudents to reflect on the learning experience. After each SET lesson, we asked the followingfour reflection questions: - What is/are the most important concept(s) you have learned? - How will you use the skills you have developed from this workshop for your project? - What might be the challenges or barriers to implementing ideas from this workshop? - What support would be helpful to have in implementing ideas from this workshop?At the end of the semester, an exit survey was conducted with the following questions: - What was the most useful thing you have learned
experiences.Future research should consider exploring teamwork dynamics in diverse URPs across differentgeographical and disciplinary contexts to generalize the findings as well as compare teamworkexperiences across various URPs to understand the impact of different institutional cultures andprogram structures. Additionally, longitudinal studies could offer a deeper understanding ofhow teamwork skills developed in URPs impact students’ professional careers. References[1] K. W. Bauer and J. S. Bennett, “Alumni Perceptions Used to Assess Undergraduate Research Experience,” J. High. Educ., vol. 74, no. 2, pp. 210–230, 2003.[2] D. Lopatto, “Undergraduate Research Experiences Support Science Career Decisions and Active Learning,” CBE—Life Sci. Educ., vol
fiveundergraduates identify as disabled [11]. Yet, in engineering such substantive data is almostentirely unavailable. The National Science Foundation (NSF)’s 2023 Diversity and STEM:Women, Minorities, and Persons with Disabilities report states, “compared with data for othergroups, data on postsecondary degrees earned by persons with disabilities are limited” [1] and assuch, provides no data on disabled engineering undergraduate students and diminutive data ondisabled engineering doctoral students. Whether it be funding, available statistics, access, orsupport, the lack of care toward disabled students in engineering is apparent and intentional [12]–[16].This paper explores the availability of data for disabled students in postsecondary engineeringprograms
components (usedefinitions below)? (Note: the percentages should total 100--do not type % sign, just numbers).Enter 0 for a component if not a part of your course grade. NOTE: Please be as accurate aspossible, but exact percentages are not necessary if you can provide a good “ballpark” number. Attendance Class participation (beyond just attending) Final exam - deliverable that is normally expected to be completed by an individual student at the end of the course, but may involve group work. Typically covers multiple modules of a course, often cumulative. Midterm(s)/Exam(s) - deliverable that is normally expected to be completed by an individual student, but may involve group work. Typically covers multiple lessons
abilities.”6 These objectives were achieved utilizing a variety of Page 22.1605.3active learning methods, including lecture, demonstration, problem solving, collaborative work,formal team work, and peer learning. The assessment was done as formative assessment via oraland written reports and tests; and summative assessment with the completion of theimplementation of the website for the final grade. Interviews were conducted to acquire feedbackfrom the students on their perception of the learning experience using the Lesson‟s Learnedapproach.Course DescriptionIT Project Management was designed with two pedagogical approaches to learning
, they must also understand theory of speed-up and scaling, both scale-up and scale-outas well as co-processor scaling. Students are challenged at the end of the course to pick aprogram to design or re-design and to show significant speed-up, comparing results to Amdahl’slaw, based on parallel hardware and parallel programming methods used5,6. Modern systemshardware can make selection of the appropriate value for scaling factor used in Amdahl’s law,“S,” a non-trivial decision. Amdahl’s law and a very convenient algebraic equivalence I callSiewert’s law makes analysis simple since speed-up (SU) can be measured with time-stamps andP computed if S is well understood. 1Equation 1: Amdahl’s law is SU
Affecting the Future Career Pathway Decisions of Lower-income Computing Students1. IntroductionWithin research on broadening participation in computing, the experience and perspectives ofundergraduate students have been important elements of exploration. As undergraduate studentsare experts of their own experience, conducting research that focuses on understanding theirperspective can help those who organize programmatic efforts to respond to student needs andconcerns. This paper emerges from the context of a specific National Science Foundation (NSF)-funded Scholarships in Science, Technology, Engineering, and Mathematics (S-STEM) program.As with all S-STEM programs, Florida Information Technology Graduation
+ stress OR Latin* student + stress OR Indigenous student + stress”, “Black student + distress OR Latin* student + distress OR Indigenous student + distress”, “Black student + trauma OR Latin* student + trauma OR Indigenous student + trauma.”To appropriately scope the literature review, we used multiple exclusion criteria. First, anyliterature focusing on faculty, graduate students, or postdoctoral students was omitted. Second,literature published before the year 2000 was excluded as much has changed in the field oftrauma studies since the 1990’s. Lastly, any guest editorials or conference proceedings that didnot include a paper were excluded from the literature review.After an initial search through the journal databases, we screened the
, “Software Carpentry: Getting scientists to write better code by making them more productive,” Computing in Science & Engineering (CiSE), vol. 8, no. 6, pp. 66–69, Nov. 2006. [8] A. Simperler and G. Wilson, “Software Carpentry – get more done in less time,” arXiv:1506.02575, Jun. 2015. [9] B. K. Weaver, “The efficacy and usefulness of Software Carpentry training: A follow-up cohort study,” Master’s thesis, The University of Queensland, 2019.[10] A. Berg, S. Osnes, and R. Glassey, “If in doubt, try three: Developing better version control commit behavior with first year students,” in ACM Technical Symposium on Computer Science Education (SIGCSE), Feb. 2022, pp. 362–368.[11] V. Garousi, G. Giray, and E. T¨uz¨un, “Survey of the
/10.1364/AO.32.001154.[2] P. K. Koech, M. Ogini, S. Mohan, A. Alice Francis, M. Deo, S. Albin, and K. B. Sundaram, “Characterization of Silicon Nanowires Reflectance by Effective Index Due to Air-Silicon Ratio,” ECS Transactions, 89(4), 17–30, 2019. https://doi.org/10.1149/08904.0017ecst[3] S. Patchett, M. Khorasaninejad, O, N., and S. S. Saini, “Effective index approximation for ordered silicon nanowire arrays,” Journal of the Optical Society of America B, 30(2), 306. 2013. https://doi.org/10.1364/josab.30.000306.[4] F. Kimeu, S. Albin, K. Song, and K. C. Santiago, “ALD-passivated silicon nanowires for broadband absorption applications,” AIP Advances, 11(6), 065101, 2021. https://doi.org/10.1063
Feb 12, 2023].[3] R. B. Sepe and N. Short, “Web-based virtual engineering laboratory (VE-LAB) for collaborative experimentation on a hybrid electric vehicle starter/alternator,” IEEE Transactions on Industry Applications, vol. 36, no. 4, pp. 1143-1150, July 2000.[4] H. Hodge, H. S. Hinton, and M. Lightner, “Virtual circuit laboratory,” Journal of Engineering Education, vol. 90, no. 4, pp. 507-511, Oct. 2001.[5] H. Gurocak, “E-Lab: An electronic classroom for real-time distance delivery of a laboratory course,” Journal of Engineering Education, vol. 90, no. 4, pp. 695-705, Oct. 2001.[6] M. Koretsky, C. Kelly, and E. Gummer, “Student perceptions of learning in the laboratory: Comparison of industrially situated virtual
startup and casting safety protocols aspart of her M.S. project.Referencesi R. W. Heckel, W. W. Milligan, C. L Nassaralla, J. Pilling, M. R. Plichta, “Benefits of CapstoneDesign Courses in Materials Education,” Science and Technology of Polymers and AdvancedMaterials, P. N. Prasad, J. E. Mark, S. H. Kandil, Z. H. Kafafi, (eds), Springer, Boston, MA., 1998.https://doi.org/10.1007/978-1-4899-0112-5_75ii M. Schaefer, “Use of Casting Simulation and Rapid Prototyping in an Undergraduate Course inManufacturing Processes,” ASEE Annual Conference & Exposition, 2016.iii K. Molyet, “Providing a Meaningful Lab Experience for a Manufacturing Processes Course,”(,” ASEE IL-IN Section Conference, 2019. https://docs.https://docs.lib.purdue.edu/aseeil
factors were attributed to the nativelanguage being English (yes/no).Results and DiscussionTable 1 Breakdown of averaged Turnitin scores for each submission (S). Turnitin Scores (%) All YES Eng NO Eng YES Biol NO Biol YES Native NO Native S #1 20 ± 19 22 ± 12 15 ± 16† 20 ± 19 23 ± 19 14 ± 12 25 ± 21† S #2 14 ± 14* 13 ± 10** 10 ± 13* 12 ± 10** 19 ± 18† 10 ± 7** 17 ± 16**,†YES/NO refers to their background in: Biol = Biological Sciences, Eng = Engineering. *,**denotes statistically significant differences (t-test) between submissions (*p<0.05, **p<0.01); †between YES and NO categories (†p<0.01
address this need, thisstudy examined the relationship between student cognitive engagement in iSTEM and itshypothesized predictors: curricular opportunities for STEM content integration, engagement inmultiple solution development, agency in STEM practices, evidence-based reasoning, datapractices, and collaboration. The study is guided by Roehrig et al.’s (2021) Detailed ConceptualFramework of Integrated STEM and Moore et al.'s (2014) framework for Quality K-12Engineering Education. We utilized multinomial logistic regression (MLR) analysis due to thepolytomous categorical distribution of the outcome variable. This study used classroom videodata from previous work that examined the presence of critical features of K-12 iSTEM. Scoresusing a novel
are asked to reflect on and discuss where they haveencountered a similar problem in their home or community and are invited to discuss and sharetheir ideas using whichever language(s) are most useful to them. For example, students mightdiscuss: Where do they see plastic polluting the environment? Have they had challenges crossingan intersection as a walker, biker, or skateboarder? How much light do they like in their room asthey go to sleep? By inviting students to reflect on related experiences, students can approach aproblem, even a new problem, with a focus on what knowledge and skills they bring that caninform their investigations and solutions.Develop familiarity with materials, tasks, and terminology. Students’ background knowledge
suggestions that engineering faculty members’ beliefs about knowledge and aboutteaching and learning may be linked to the difficulties in improving engineering education(Montfort et al., 2014). Our research question is: how do engineering faculty members at a singleinstitution describe good teaching? Methods1 This material is based upon work supported by the Kern Family Foundation (KFF) and the Kern EntrepreneurialEngineering Network (KEEN). Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the KFF or KEEN.WHAT MAKES “GOOD” ENGINEERING PEDAGOGY
Jacob Marszalek Kathleen O’Shea University of Missouri-Kansas City Dan Justice Metropolitan Community College-Penn ValleyAbstractIn this paper, we explore the lived pandemic experiences of civil and mechanical engineeringstudents participating in a S-STEM scholarship program during the 2020-2021 academic year.The program, launched in 2020, is designed to facilitate the transfer of students from acommunity college to an urban-serving research university co-located in a Midwestern city.Findings reveal how the pandemic both challenged students and illuminated resiliency andsources of on- and off-campus support. A description of how findings have informed programgoals and implementation is
improve the undergraduate engineering experience through evaluating preparation in areas, such as mathematics and physics, evaluating engineering identity and its impact on retention, incorporating non-traditional teaching methods into the classroom, and engaging her students with interactive methods.Benjamin Caldwell (Associate Provost) (LeTourneau University)Julie S Linsey (Professor) Georgia TechTracy Anne Hammond (Professor) Dr. Tracy Hammond is the current Secretary of the Faculty Senate and passionate about Faculty governance. Hammond is Director of the TAMU Institute of Engineering Education & Innovation and Professor of Computer Science & Engineering. Hammond holds a Ph.D. in EECS and FTO (Finance
inclusion in STEM fields. This includes evaluation of NSF ADVANCE, S-STEM, INCLUDES, and IUSE projects, and climate studies of students, faculty, and staff. Her social science research covers many topics and has used critical race theories such as Community Cultural Wealth to describe the experiences of systemically marginalized students in engineering.Sriram Mohan (Professor of Computer Science & Software Engineering) Sriram Mohan is a Professor of Computer Science and Software Engineering at Rose-Hulman institute of Technology.Selen GülerSelen Güler is a PhD student in Sociology at the University of Washington and a research assistant in the University ofWashington’s Center for Evaluation & Research for STEM Equity (UW
). In terms of student teamcollaboration context, Woods et al. (2021) used Sharma’s survey instrument on ten personalcultural orientations, expanded from Hofstede et al.’s (2018) national cultural dimensions, topredict students’ reported power distance by their uncertainty avoidance and metrics of countryculture. Alternatively, Wei et al. (2019) examined the cultural influence on peer ratings ofteammates between international and domestic students by considering team members’ culturalorientation on individualism based on their internationality. Following Wei et al. (2019), we defineteams consisting of students born in different countries as multicultural teams, as a more
. Sigmund and K. Maute, “Topology optimization approaches,” Structural and Multidisci- plinary Optimization, vol. 48, no. 6, pp. 1031–1055, 2013. [3] C. Li, I. Y. Kim, and J. Jeswiet, “Conceptual and detailed design of an automotive engine cradle by using topology, shape, and size optimization,” Structural and Multidisciplinary Optimization, vol. 51, no. 2, pp. 547–564, 2015. [4] C.-H. Chuang, S. Chen, R.-J. Yang, and P. Vogiatzis, “Topology optimization with additive manufacturing consideration for vehicle load path development,” International Journal for Numerical Methods in Engineering, vol. 113, no. 8, pp. 1434–1445, 2018. [5] P. D. Dunning, B. K. Stanford, and H. A. Kim, “Coupled aerostructural topology optimization
addressed through the program in detail. The activities included theoreticalclasses, practical labs, and games. In the last activity, all the students worked in different groupsso that they could interact more with the rest of their peers. Topic 2D design 3D design Electronics 1 Replication Electronics 2 Project Exhibition Days 1 and 2 3 4 and 5 6 7 and 8 9 10 Content Basic concepts Bases for Theory of Basis of Presentation Design Requirement of dimensional three- electricity mass of electronic methodology s design (color, dimensional (voltage
0.600 Includes considerations of audience, purpose, and circumstances surrounding the writing task(s). Content Development 28 0 3 1.36 0.731 Genre and Disciplinary 28 1 3 1.64 0.678 Conventions: Formal and informal rules inherent in the expectations for writing in particular forms and/or academic fields." Sources and Evidence 28 0 2 0.14 0.448 Control of Syntax and Mechanics 28 1 3 2.32 0.670Table 2: Summary statistics for student papers, post-tutoring N Minimum Maximum Mean Std
, J., & Merrill, T., & Sood, S., & Greene Ryan, J., & Attaluri, A., & Hirsh, R. A. (2017,June), Clinical Immersion and Team-Based Design: Into a Third Year Paper presented at 2017 ASEEAnnual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28040[7] Muller-Borer, B. J., & George, S. M. (2018, June), Designing an Interprofessional EducationalUndergraduate Clinical Experience Paper presented at 2018 ASEE Annual Conference & Exposition,Salt Lake City, Utah. 10.18260/1-2—30279[8] Zapanta, C. M., & Edington, H. D., & Empey, P. E., & Whitcomb, D. C., & Rosenbloom, A. J. (2017,June), Board # 18: Clinical Immersion in a Classroom Setting (Work in Progress) Paper presented at 2017ASEE Annual