Educationaddressed the U.S.'s projected aviation maintenance worker shortage of 800,000 people over thenext two decades from different perspectives.Course OrganizationThe CST course is designed for 16 weeks of classes to cover the materials established on thesyllabus. The CST course had five components 1. Lectures, 2. HODAs, 3. Writing assignments,4. Exams, and 5. Semester-long project. During the first part of the course, the students wereintroduced to concepts such as critical thinking, systems archetypes thinking, and mental modelsin the lectures. At the beginning of the semester, the students were introduced to the final projectrequirements, and teams were established with students from diverse cultural and educationalbackgrounds. During the first eight
Education Conference (FIE), pp. 1-5, doi: 10.1109/FIE44824.2020.9274104.Hilton, E. C., Talley, K. G., Smith, S. F., Nagel, R. L., Linsey, J. S. (2020) Report on Engineering Design Self-Efficacy and Demographics of Makerspace Participants Across Three Universities. ASME. J. Mech. Des. October 2020. 142(10):102301. https://doi.org/10.1115/1.4046649.Isaacs, B. (2001) Mystery of the missing women engineers: A Solution. Journal of Professional Issues in Engineering Education and Practice. 127(2):85-91.Kulturel-Konak, S. (2021) Overview of Student Innovation Competitions and Their Roles in STEM Education. Paper presented at 2021 Fall ASEE Middle Atlantic Section Meeting, Virtually Hosted by the section. https://peer.asee.org
document structure (narrative, large blocks of text, lists, etc.) used. 10. Mechanics • Standard English usage supported reader’s understanding of the response. (grammar, spelling, • No or minimal misspellings or punctuation errors. punctuation, etc.) • Word choices are correct; no or minimal subject/verb agreement errors or run-on used appropriately. sentences, etc. 11. Drawings used to • Comment “N/A” below if drawings were not used. illustrate, explain • Comment if drawing(s) used as primary explanations / responses. • Drawing(s) helped explain and support points made in text. • Drawing(s) were
polarization projections for this test arepresented in Table 1, and shown in Figure 8, and with the final calculated value of S = 2.766 +/-0.010. The inequality is violated for S > 2. The result validates the polarization entanglement ofthe photons. Table 1. The Bell inequality test (HWP-A: Rotation angle of HWP A, HWP-B: Rotationangle of HWP B, A: single counts for detector A, B: single counts for detector B, AB:coincidence counts for A and B for ~10 ns time window) Test# State HWP-A HWP-B A B AB Accidentals 1 a',b 22.5 11.25 62598 52041 3495 26.0613 2 a',b+ 22.5 56.25 70929 52087 3995 29.55583 3
-level class, with twenty-eight survey responses, highlights of the surveyinclude the following: Constrained-response: the questions asked in this category are shown in Table 1. A quarter of the students who responded indicated they did not watch any of the recorded videos at all, leading to an average of only 2.74 videos (out of the thirty available videos) watched by each student. One reason for their failure to do so could be that the instructor stopped sending out weekly reminders that the videos were available for them to watch after the third week of instruction. For those who did watch, about 55% of the students watched the lecture videos in their entirety, while the rest watched only part(s) of the videos. None
and retention. A SWE and ASEE Fellow, she is a frequent speaker on career opportunities and diversity in engineering. Page 24.1275.1 c American Society for Engineering Education, 2014 Transfer Students: Lessons Learned Over 10 YearsAbstract.This paper will summarize the accomplishments of an NSF sponsored S-STEM program fortransfer students. This program had 97 students: 41.2% underrepresented minority, 28.9%female, and 60.8% either female and/or underrepresented minority. Therefore, this programoverrepresented minority engineering and computer science students in the university by
each student population.ReferencesAdelman, C. (1998), Females and Men of the Engineering Path. A Model for Analysts of Undergraduate Careers, U.S. Department of Education, Office of Educational Research and Improvement, Washington, D.C.; U.S. Government Printing Office.Bransford, J., A. Brown, and R. Cocking (Eds) (2000), How People Learn: Brain, Mind, Experience, and School: Expanded EditionBrown, S., L Flick, and T. Fiez (2009), “An Investigation of the Presence and Development of Social Capital in an Electrical Engineering Laboratory”, Journal of Engineering Education, 98(1). 93-102.Bordonaro, M., A. Borg, G. Campbell, B. Clewell, M. Duncan, J. Johnson, K. Johnson, R. Matthews, G. May, E. Mendoza, J. Sideman, S. Winters, and C
demonstrate differences in team performance for simulations and real robotexperiments. While simulations are good for quicker testing and a cheaper solution thanpurchasing equipment, conducting experiments with real robots allows for more accurate results.In physical experiments, there are many factors, such as robot interference, an unknownenvironment, and delayed communications, which can influence results. However, running realexperiments are required to accurately test the efficiency of an approach. Future work includesexamining these factors further.Bibliography[1] S. Dawson, B. L. Wellman, and M. Anderson, “Using simulation to predict multi-robot performance on coveragetasks,” in Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ
Paper ID #39376Instructor Experiences Teaching Model-Based Systems Engineering OnlineModules to Professional LearnersMr. Leonardo Pollettini Marcos, Purdue University, West Lafayette Leonardo Pollettini Marcos is a 2nd-year PhD student at Purdue University’s engineering education pro- gram. He completed a bachelor’s and a master’s degree in Materials Engineering at the Federal University of S˜ao Carlos, Brazil. His research interests are in assessment instruments and engineering accreditation processes.Ms. Tiantian Li, Purdue University, West Lafayette Tiantian Li (Olivia) is a dedicated Ph.D. student in Engineering
EXCHANGE it w hDr. Rachelle Pedersen Texas A&M UniversityDr. Justin Wilkerson wilkerson@tamu.eduLESSON DESCRIPTIONThis lesson is a mix of demonstrations and inquiry experiences intended to guide students throughconcepts of energy transformations (e.g., kinetic, elastic) and engineering concepts of snap-throughtransitions in both the natural and engineered world. Students will develop foundational understandingsof energy conservation with a simple ball bouncing demonstration and build to more complex conceptsof spring/elastic energy using the classic 90’s rubber popper toys to investigate the energytransformations in the system. Depending on the age of the students, we will extend this lesson
identified by the other model. The GPT-4 model tended to identifymore basic relationships, while manual analysis identified more nuanced relationships.Our results do not currently support using GPT-4 to automatically generate graphicalrepresentations of faculty’s mental models of assessments. However, using a human-in-the-loopprocess could help offset GPT-4’s limitations. In this paper, we will discuss plans for our futurework to improve upon GPT-4’s current performance.IntroductionAssessments are found in every engineering classroom and are an important part of our educationsystem [1]-[3]. Assessments play many different roles, including understanding studentimprovements in learning [4], acting as a tool to assist students with learning [5], [6
Number [EEC-1849430 & EEC-2120746]. Any opinions, findings andconclusions, or recommendations expressed in this material are those of the author(s) and do notnecessarily reflect those of the NSF. The authors acknowledge the support of the entire e4usaproject team.References[1] “The Standards | Next Generation Science Standards.” Accessed: Feb. 07, 2024. [Online]. Available: https://www.nextgenscience.org/standards[2] “Employment in STEM occupations : U.S. Bureau of Labor Statistics.” Accessed: Feb. 07, 2024. [Online]. Available: https://www.bls.gov/emp/tables/stem-employment.htm[3] “Motivational factors predicting STEM and engineering career intentions for high school students | IEEE Conference Publication | IEEE Xplore
each type, and strategies forunderstanding team members’ preferences and tailoring communication and collaborationstrategies. This model offers users insights into their personality preferences and psychologicaltype and incorporates an additional letter to accommodate five scales instead of four [12]. Themodel evaluates five personality dimensions, each representing opposite ends of a spectrum: (1)Energy: the interaction with the surrounding environment (Extraverted(E)/Introverted(I)); (2)Mind: the perception and processing of the world (Intuitive(N)/Observant(S)); (3) The processof making decisions and reacting to emotions (Thinking(T)/Feeling(F)); (4) Tactics: theapproach to work, planning, and decision-making (Judging(J)/Prospecting(P
(DE-NA0004115) , MSIPP-I AM EMPOWERED funded by the Department of Energy (DE-NA0004004), NSF-RISEfunded by the National Science Foundation (1646897), CREST Center funded by the National Science Foundation (1735968),RETREAT: Retaining Engineers through Research Entrepreneurship and Advanced Materials Training funded by the NationalScience Foundation (1950500), DREAM: Diversity in Research and Engineering of Advanced Materials Training. Funded by AirForce Research Laboratory (FA8651-18-1-0003) and Catalyst Project: A Two-Semester Driven Conceptualization Training ofManufacturing Intelligence in Materials Engineering (MIME) - A Froshmore FUTURES Program (2011853).References[1] M. L. Espino, S. L. Rodriguez, and B. D. Le, "A Systematic
gives them the language to describe their engagement with this aspect of theengineering design process as well as the values by which they select their exemplar concepts.Some even include the novelty scores as ratings for a creativity objective within their decisionanalyses.[1] E. P. Douglas, D. J. Therriault, M. B. Berry, and J. A. Waisome, "Comparing Engineering Students' and Professionals' Conceptions of Ambiguity," in 2022 IEEE Frontiers in Education Conference (FIE), 2022: IEEE, pp. 1-4.[2] J. J. Shah, N. Vargas-Hernandez, and S. M. Smith, "Metrics for measuring ideation effectiveness," Design Studies, vol. 24, pp. 111-134, 2003, doi: 10.1016/S0142- 694X(02)00034-0.[3] L. R. Murphy, S. R. Daly, and C. M
high school female students andcounselors.Furthermore, the study underscores the importance of addressing gender imbalance in CEMprograms and offers actionable insights to promote gender diversity and inclusion in theconstruction industry. By implementing these recommendations, educational institutions canwork towards creating more inclusive and diverse learning environments in CEM education andultimately contribute to a more equitable representation of women in the construction industry.Bibliography1. Archer, L., DeWitt, J., Osborne, J. F., Dillon, J. S., Wong, B., & Willis, B. (2013). ASPIRES Report: Young People’s Science and Career Aspirations, Age 10 –14. King's College London2. Amaratunga, D., Haigh, R., Shanmugam, M., Lee, A. J
, 2000). This place-basedfocus increases engagement (Polman & Hope, 2014; Tierney et al., 2020), and the application toreal-world issues involving community members and local sites creates the need and richcontexts with contextual scaffolds for problem solving (Bouillon, 2001). In Hynes et al.’s (2017)systematic review of the literature on engineering education, an important theme of researchbeyond learning concepts and practices was developing students’ perceptions, attitudes, beliefs,and motivations; SCENIC provides a promising opportunity to learn more about how studentsdevelop engineering mindsets toward solving rurally relevant environmental issues. All too often, a purely technocratic framing of problems is prominent in science
Ancestry, Technical Talent, and Learning Process. While AI-based learning showspromise for certain student groups, peer and internet-based reviews also play a vital role infostering engagement and knowledge retention. To this end, students should be wary of entirelyrelying on AI, as backgrounds, learning preferences, and deep analysis may be hurdles instead ofolder, standard approaches. Future research should explore the interactions between thesevariables in greater detail, perhaps using larger datasets and different learning environments.References[1] Ng, D. T. K., Leung, J. K. L., Chu, K. W. S., & Qiao, M. S. (2021). ai literacy: definition,teaching, evaluation and ethical issues. Proceedings of the Association for Information Scienceand
Results (n.d.). https://keystonetech.widen.net/s/smlrbffkx7/kteb-232-uv-is-measured in 1990. Additionally, the Act set goals to have 70% of n-p_vd1state electricity generated from renewable energy by 2030, and a •KTEB-332-UV-IS-N-P_VD1.pdf.transition to 100% zero-emission electricity by 2040
most girls reporting a loss ofinterest in STEM around the age of twelve 9, there are now many studies reporting cases10 where womenenrollment is much higher than men in engineering societies. The collaborative environment of theactivities arranged by these societies may be a contributing factor in the change.Historically, about one-third of all bachelor’s degrees have been awarded in science and engineering.Even though women are 56% of the college population, women earned only 19.5% of engineeringbachelor's degrees in 200511. Despite this high retention rate, in the long run we observe an increasingtrend: Since 1970, the number of bachelor’s degrees in science and engineering (S&E) awarded annuallyto men has fluctuated around 200,000
new electrochemical glucose sensing technique using the contact lenses has manypotential advantages over currently existing invasive and non-invasive methods. A highlyprecision voltage source, accurate electrical components including electronically embeddedcontact lens, and a sophisticated analyzing system such as precision current monitor will be usedin this study. The contact lens glucose sensing method introduced in this work can beminiaturized using current integrated circuit and semiconductor technology, and has the potentialto provide a low cost, fast, stable, and compact non-invasive glucose sensor for the diabeticpatients within near future. References: [1] Coster S.; Gulliford M.C.; Seed P.T.; Powrie J.K.; Swaminathan R
in class greatly improved their ability to comprehend course material. Moreover, thestudents gained a stronger understanding of engineering in general, while developing self-confidence needed to excel in engineering related fields. Others felt valued by being treated asstudents in top tier institutions, while a few mentioned the rigor of the course is needed to ensurethe quality of education. These results were also reflected in student responses from the tier-oneinstitution.REFERENCES[1] Alon, S., 2007. The influence of financial aid in leveling group differences in graduating fromElite institutions. Economics of Education Review 26, (3), in press.[2] Bidwell, C. E., & Kasarda, J. D. (1980). Conceptualizing and measuring the effects of
. Students also integrate artinto the design to create an organic shape of fish and craftily shape the fins and tail into the moldto get fish features.3.2 ParticipantsThe participants were students in an Industrial Engineering course at a tribal university withABET Accredited Engineering programs. Six students participated in the course, consisting offive males and one female, aged 20- 36.3.3 Data Collection Instrument(s)The results were collected using a metacognitive reflection assignment consisting of twosections, Part 1 - Photovoice Reflection Prompts and Part 2 - Open-Ended Reflection Questions,with three questions in each area. Each student received a Metacognitive Reflection Assessmentwith Part 1- Photovoice Reflection Prompts and Part 2
and Operations Research from the Pennsylvania State University. ©American Society for Engineering Education, 2023 Navigating Intersectional Identities in Civil Engineering Education and Practice1 Introduction:Underrepresentation is a well-known and researched topic in academia, specifically forengineering that remains a White, male-dominated field [1]. Underrepresentation is defined by “apopulation’s representation in education and employment that is smaller than their representationin the U.S population.” It is also defined by the uniformity of representation by field, forexample, “Although women have reached parity with men among S&E bachelor’s degreerecipients—half
, belts, and chains, and other components. 7. Perform work in accordance with safety rules and procedures.3.3 Data Collection Instrument(s)Data collection instruments are detailed by Bosman and Shirey [33]. Upon completion of themodule, students submitted photovoice metacognitive reflection. Prompts are provided in insert2: Photovoice Reflection Prompt A (Entrepreneurial Mindset): The entrepreneurial mindset is defined as “the inclination to discover, evaluate, and exploit opportunities.” Explain how participating in the newly developed curriculum incorporated the entrepreneurial mindset, and lessons learned relevant to the entrepreneurial mindset. Photovoice Reflection Prompt B (STEAM): STEAM (science, technology, engineering, arts, math) goes
thepostdoc program is to create well-rounded scholars versed in research, teaching, and service.Using artifacts and postdoc reflections, this study aims to explore the experiences of the firstcohort of LEGACY postdoc scholars to understand how a newly created intersectionalmentorship model facilitates scholars’ progression toward faculty positions while curating aninclusive community and culture for scholars. The intersectional mentorship model framing this postdoc program is based on researchconducted by Dr. Cox, with some adaptations from Walker et al.’s (2009) The Formation ofScholars, which presents a multiple apprenticeship framework that offers a holistic approach tomentoring for scholars. The three mentor types in the program are primary
Example(s) Coded Example(s)PROBLEM Asking for help resolving a debugging "What does your for loop look like? for ?Students looking for assistance by either error = ? to ?"asking or stating an issue they are facing Stating that MATLAB is giving an error "can anyone help me with part A? it says and they do not know how to resolve it my frequency and length are [1 8 ] instead of [8 1] im not sure how to fix it"EXPLANATION
Professionalization Workshop (SPW)– theme and example quote(s) Writing a resume and/or research statement • I learned the format for a research resume. • The fact that we had our personal statements and resumes checked gave me more confidence while applying for different things. • Being able to have a research statement ready for future opportunities.” • …that I learned how to build a stronger resume. • …the ability to receive training that was very helpful in guiding our preparation for different career paths be it be from our written assignments like the resume… Learning about professional conduct, ethics, or environment in the field • It gave me examples of …how to professionally conduct myself in a field that
Cleveland Economic Commentary (2004): 1.12. Berger, Suzanne. "Why manufacturing matters." Manufacturing is not merely about giving people jobs. The next generation of technological innovations is intimately tied to production processes (2011).13. Brundiers, Katja, and Arnim Wiek. "Do we teach what we preach? An international comparison of problem-and project-based learning courses in sustainability." Sustainability 5.4 (2013): 1725-1746.14. Vogler, Jane S., et al. "The hard work of soft skills: augmenting the project-based learning experience with interdisciplinary teamwork." Instructional Science 46.3 (2018): 457-488.15. Brassler, Mirjam, and Jan Dettmers. "How to enhance interdisciplinary competence—interdisciplinary problem-based
conclusions or recommendationsexpressed in this material are those of the author(s) and do not necessarily reflect the views ofthe National Science Foundation.References[1] X. Chen, “STEM Attrition: College Students' Paths into and out of STEM Fields,” Statistical Analysis Report. NCES 2014-001. National Center for Education Statistics, 2013.[2] President’s Council of Advisors on Science and Technology (PCAST) “Engage to excel: Producing one million additional college graduates with Degrees in Science, Technology, Engineering, and Mathematics,” Washington, DC: The White House, 2012.[3] J. G. Cromley, T. Perez, & A. Kaplan. “Undergraduate STEM achievement and retention: Cognitive, motivational, and institutional factors and solutions