Undergraduate Engineering Programs Emphasize? A Systematic Review,” J of Engineering Edu, vol. 106, no. 3, pp. 475– 526, Jul. 2017, doi: 10.1002/jee.20171.[4] C. Young and M. L. Pate, “Compact Power Equipment Troubleshooting Training: Formative Assessment using Think-Aloud Pair Problem Solving,” in 2013 Kansas City, Missouri, July 21-July 24, 2013, American Society of Agricultural and Biological Engineers, 2013, p. 1. Accessed: Sep. 18, 2024. [Online]. Available: https://elibrary.asabe.org/abstract.asp?aid=43359[5] S. Ramachandran, R. Jensen, J. Ludwig, E. Domeshek, and T. Haines, “ITADS: A Real-World Intelligent Tutor to Train Troubleshooting Skills,” in Artificial Intelligence in Education, vol. 10948, C. Penstein Rosé
, and plant biology. R EFERENCES [1] S. Fathalla, S. Vahdati, S. Auer, and C. Lange, “Metadata analysis of scholarly events of computer science, physics, engineering, and mathematics,” in Digital Libraries for Open Knowledge, E. M´endez, F. Crestani, C. Ribeiro, G. David, and J. C. Lopes, Eds. Cham: Springer International Publishing, 2018, pp. 116–128. [2] E. Dagien˙e, “Mapping scholarly books: library metadata and research assessment,” Scientometrics, vol. 129, no. 9, pp. 5689–5714, 2024. [Online]. Available: https://doi.org/10.1007/s11192-024-05120-1 [3] A. Mierzecka, “The role of academic libraries in scholarly communication. a meta-analysis of research,” Studia Medioznawcze
., vol. 95, no. 2, pp. 139–151, Apr. 2006, doi: 10.1002/j.2168-9830.2006.tb00885.x.[3] J. Trevelyan, The Making of an Expert Engineer, 0 ed. CRC Press, 2014. doi: 10.1201/b17434.[4] ABET, “Criteria for accrediting engineering programs,” Baltimore, MD, 2024. Accessed: Oct. 27, 2024. [Online]. Available: https://www.abet.org/accreditation/accreditation-criteria/criteria- for-accrediting-engineering-programs-2024-2025/[5] H. Chaibate, A. Hadek, S. Ajana, S. Bakkali, and K. Faraj, “A Comparative Study of the Engineering Soft Skills Required by Moroccan Job Market,” Int. J. High. Educ., vol. 9, no. 1, p. 142, Dec. 2019, doi: 10.5430/ijhe.v9n1p142.[6] M. S. Rao, “Enhancing employability in engineering and
21st, 2025.[4] Cervone, G., Franzese, P., Ezber, Y., and Boybeyi, Z. “Risk assessment of atmospheric emissions using machine learning”, Nat. Hazards Earth Syst. Sci., 2009, 8, 991–1000.[5] Chen, J., Kong, H., Su, Y., and Zhang, H. “Indoor air quality monitoring system for smart buildings: A comprehensive review”. Building and Environment, 2021, 196, 107786.[6] Cuesta-Mosquera, A., Močnik, G., Drinovec, L., Müller, T., Pfeifer, S., Minguillón, M. C., Briel, B., Buckley, P., Dudoitis, V., Fernández-García, J., Fernández-Amado, M., Ferreira De Brito, J., Riffault, V., Flentje, H., Heffernan, E., Kalivitis, N., Kalogridis, A.-C., Keernik, H., Marmureanu, L., Luoma, K., Marinoni, A., Pikridas, M., Schauer, G., Serfozo, N
their evidence-based practices. Theanalysis is ongoing and will be presented in a future paper to highlight how they are used toupdate our change framework and activities.AcknowledgementsThis material is based upon work supported by the National Science Foundation under AwardDUE- 2021532. 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 NationalScience Foundation.References[1] Chan Hilton, A.B. (2024). Board 429: Work in Progress: Capacity-Building for Change Through Faculty Communities Exploring Data and Sharing Their Stories. ASEE 2024 Annual Conference and Exhibition, NSF Grantees Poster Session, Portland, OR, June 2024
and by Spanish- and English-language preferences. Table 1shows the family composition and languages spoken by the ten families in each of the threerounds.Table 1Family Composition and Language Preferences for Each Round Family ID Language(s) Spoken Family Composition 1 Spanish and English Adult and child 5 Spanish and English Adult and three children 6 Spanish* Adult and three children** 7 Spanish and English Adult and two children 10 English Adult and child 11 English Adult and child 13 English
, and conclusions or recommendations expressed in this material are those of theauthor(s) and do not necessarily reflect the views of the National Science Foundation.REFERENCES[1] T. L. Cross, B. J. Bazron, K. W. Dennis, and M. R. Isaacs, “Towards a Culturally Competent System of Care: A Monograph on Effective Services for Minority Children Who Are Severely Emotionally Disturbed | Office of Justice Programs.”[2] A. N. Washington, “When Twice as Good Isn’t Enough: The Case for Cultural Competence in Computing,” in Proceedings of the 51st ACM Technical Symposium on Computer Science Education, in SIGCSE ’20. New York, NY, USA: Association for Computing Machinery, Feb. 2020, pp. 213–219. doi: 10.1145/3328778.3366792.[3] “CRA Taulbee
’ conation iv. Person-item distribution map (PIDM) using the Rasch model to investigate students’ perception of agreement or disagreement towards each itemInstrument analysis using Rasch Model The 96-items GOI was first introduced by Kathryn S. Atman, who previously studiedthe goal accomplishment style and psychological types amongst middle school students in theUnited States [8]. In this study, the GOI instrument was distributed to different populations andenvironments, which is the first-year engineering students in one of the universities inMalaysia, which may affect the items’ reliability and validity. The Rasch measurement model is used to assess the psychometric properties in termsof reliability and
and aquatic ecology from the University of Michigan. He is married and has two children who all love to travel.Okechukwu Ugweje (Professor)Chad S. Korach (Associate Professor and Director, School of Engineering)Ethan Andrew Shirley © American Society for Engineering Education, 2022 Powered by www.slayte.com Advancing Global Competencies within a Required Global Engineering Course During COVID-19While COVID-19 adversely affected every aspect of education, hands-on experiences and study-abroad programs were perhaps hardest hit. The University of Mount Union prides itself on theunique training it offers students for the global engineering
well asteamwork. Table 2 provides a description of the components of Module 7 as well as a list ofpossible points that may be earned by a student completing the optional components of themodule. Because CArE 5619 uses a “straight scale” without a curve, and because “required”assignments resulted in a minimum grade of “70 points = C”, students were made aware that thesuccessful completion of all optional assignments included in Module 7 would raise a student’sgrade from a “C” to a “B” (i.e., 70+10 pts).Details of the “story board” / “poster” communication exercise, including a grading rubric, areprovided in Appendix D.Table 2. Details of design work associated with Module 7) Fully understanding the problem Possible Details of assignment(s
the loading area, take them to a specific workstation, and go back to the loading area. For your reference, the company provides the layout of one of its warehouses. Each trip must take the minimum time and always be safe for both robots and workers. In case of a collision with a wall, the AGV breaks when it has a momentum of 220 kg*m/s or more
entrepreneurs' definitions, but mentioned only afew times throughout student interviews, for example, Participant 42 stated; "Entrepreneurialmindset is really just creating a new form of mental habits that will allow you to see the biggerpicture of things to make connections and values through what your work is." However, it seemsthat some of the more frequent codes such as Innovation and Business Skills were nothighlighted by entrepreneurs in previous studies. This could be due to students' lack ofexperience in the field and the fact that students are only learning about entrepreneurial mindsetin the classroom, as opposed to entrepreneurs who have real world experience with the benefitsof EM.Faculty in Zappe et al.’s study said that they believe that
on designer one “frequently if not always” for transitional tasks such asplanning, setting team goals, and developing strategies. The number “1” in the (1,2) positiondepicts designer 2’s reliance on designer 1 for the same function. The relations reflect the surveyresponses of the designers and are directional and of equal magnitude. The disconnect of nodesthree, four, and five to the other designers in this DSM indicates a weak connection of the networkat this particular threshold and function [61]. Twelve DSMs are constructed representing the threeleadership functions and three communications modes at two distinct frequency levels. Designer (Sink) 1
belong there, I don’t feel like I connect with the school … I just have that mentality of, “I just need to go through this part. I’m just passing by” … And I’m fine with that, that doesn’t bother me anymore [interview 4]Decades of research focused on college student’s college departure affirm that students are morelikely to withdraw from their institution, all together, when they are not sufficiently integratedsocially and academically [31]–[38]. Kitatoi’s resignment to “just passing by” and her lack ofconnectedness with the institution are worrisome. Seymour and Hewitt [39] and Marra et al.’s [40]work emphasized that women who leave STEM disciplines decide to switch into non-engineeringdegree programs due to feeling as though they didn’t
ateam. The MRP roles include the team and students, engineering expert(s), the client(s) andbusiness expert(s). There are strong evidences form the literature that including the soft skillssuch as management, entrepreneurship and leadership can boost the retention and enrollment inengineering programs. Entrepreneurship education has been found to boost GPA and retentionrates of the engineering students, provides the students with the skills and attitudes needed toinnovatively contribute to the existing organizations and pursue their own ventures, and has thepotential to address current and anticipated workforce demands. We strongly believe that byintegrating entrepreneurship into engineering courses, specifically in the ones that are
judgement, the instructors decided to allow studentswith appropriate prior experience/practice in land surveying also enroll in this course withoutmeeting the course prerequisite.Student Learning Outcomes: The objective of this course is to expose students to the fundamentalsof T-LiDAR and engage them in specialized activities involving this modern technique tosuccessfully complete 3D point-cloud models of real, service-learning projects. The course wasdesigned to attain the following four Student Learning Outcomes (SLOs): 1. Know the operation of laser-based scanner(s) to acquire spatial, color, and light intensity data. 2. Attain intermediate-level proficiency on the use of computer software to generate virtual 3D point-cloud models
? response describes their action(s) relevant to the situation Why? Any specific examples where you and task. used verbal communication to articulate an 3. Results - rate the degree to which the student's important point? Were you successful? response describes the results of their actions. Any specific examples where you used written communication to articulate and important point or communicate something important? Were you successful?3.2 Qualitative AnalysisToward understanding the ways in which student mock interview responses may have changedfrom pre to post, we conducted a qualitative analysis of the interview
thismaterial are those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References[1] A. T. Purcell and J. S. Gero, "Design and other types of fixation," Design Studies, vol. 17, no. 4, pp. 363-383, 1996.[2] J. A. Plucker, R. A. Beghetto, and G. T. Dow, "Why isn't creativity more important to educational psychologists? Potentials, pitfalls, and future directions in creativity research," Educational psychologist, vol. 39, no. 2, pp. 83-96, 2004.[3] C.-y. Chiu and L. Y. Kwan, "Culture and creativity: A process model," Management and Organization Review, vol. 6, no. 3, pp. 447-461, 2010.[4] A. F. Osborn, Applied imagination. New York, NY: Scribner, 1957, p. 379.[5] P. A
micro-narratives included above interpreted their stories onthis triad.In the SenseMaker analyst software, the original micro-narratives can be accessed by selectingeither a single or a group of dots. The text of the relevant micro-narratives is then shown besidethe triad. This functionality enables researchers and, most importantly, participants, to explorethe system of interest and identify patterns in the data.There are many patterns that can be identified across the multiple visualization outputs thatSenseMaker can generate (for more information we direct readers to [2 pp 7-8, 11]. Arguably themost powerful pattern, however, is the idea of identifying areas that indicate existing potential inthe system (see “adjacent possible[s]” in step 4
results were summarized in [29] as follows. A majority of the respondents thought that theirpromotion was a result of their hard work alone. Half of the respondents indicated that theirprogress might have been easier if they were male, and half of them stated that children were ahindrance to progress. Female students were largely prevented from pursuing higher education until the 19thcentury. Before then, female seminaries were the primary alternative for women who wished toearn a higher degree. However, women’s rights activists fought for higher education for femalestudents, and college campuses turned out to be fertile ground for gender equality activism [30].In the early 1900’s, at the University of London, all degrees were available to
Evaluation Association affiliate organization and is a member of the American Educational Research Association and American Evaluation Association, in addition to ASEE. Dr. Brawner is also an Exten- sion Services Consultant for the National Center for Women in Information Technology (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 engi- neering. Her evaluation work includes evaluating teamwork models, broadening participation initiatives, and S-STEM and
freedom. No. of variables V No. of equations E V – E = degrees of freedom.A point has no freedom. The intersection of 3 equations in 3 variables might consist of isolatedpoints. A curve has one degree of freedom. From any particular point one can move onlyforward or backward. The coordinates of the points on a space curve can all be described asfunctions of one variable, say t for time or s for distance from an origin. The parametric form ofa space curve is then; x = f(t) y = g(t) z = h(t) .The number of variables
, such as relative to others in their peergroup or in the field. Consider one student’s diagram:Figure 1: This student’s deep expertises included Linux, technical problem-solving, and “going through airports (transport).” The shallow expertises included cycling, compilers, digital circuits, and signal processing.The student commented that s/he was keeping the order of deep expertises increasing down thevertical axis, to represent expertise as a distribution with more general knowledge up towards thetop of the vertical bar and more esoteric knowledge down at the bottom, where “you’re like0.001%” of the experts at this level (see bottom right of Figure 1). S/he placed “Russia” outsidethe T diagram
). Page 11.52.2© American Society for Engineering Education, 2006A Hands-on, Interdisciplinary Laboratory Program andEducational Model to Strengthen a Radar Curriculum for Broad DistributionIntroduction Severe and hazardous weather such as thunderstorms, downbursts, and tornadoes can takelives in a matter of minutes. In order to improve detection and forecast of such phenomenausing radar, one of the key factors is fast scan capability. Conventional weather radars, suchas the ubiquitous NEXRAD (Next Generation Radar developed in the 1980’s), are severelylimited by mechanical scanning. Approximately 175 of these radars are in a national networkto provide the bulk of our weather information. Under the development for weather
the knowledge and skills that student veterans bring to higher education and toengineering education.23Following Minnis and Wang’s research on military veterans’ career decisions17 and Musgrove’sinvestigation of career planning of military veterans enrolled in college,24 our study draws onSampson et al.’s Cognitive Information Processing (CIP) approach to career intentions anddecision making.25 This theoretical framework has been used to better understand veterans’transitions into the workforce.20 Our student interviews highlight how two elements of thisapproach, Developing Self-Knowledge and Building Occupational Knowledge, may apply toSVE’s decision to enter the engineering education pathway. As a foundational step, developingself-knowledge
image or images comes to mind when you think of engineers or engineering? 4. In your view, what is science? What is its purpose? 5. Do you agree with the statement “engineering is applied science? Why, or why not? 6. In what way are science and engineering similar? 7. What are the differences between science and engineering? 8. If two engineering firms are given the same job (to design a new cell phone), would the product be more or less the same? Why, or why not? 9. Please answer the following three questions based on the statement here. Imagine that another bridge is going to be built over the Colorado River. a. What do engineers need to consider in the process in planning this? b. What component(s) of this task will be
, “Students’ agency beliefs involve how students see andthink about STEM as a way to better themselves and the world along with being a critic ofthemselves and science in general [20, p. 939]. The critical thinking perspective is intimately tiedto engineering agency beliefs, where students become “evaluator[s] of STEM as well as becomecritics of themselves and the world around them through self-reflection” [39, p. 13]. In essence,agency beliefs in this framework are based on a spectrum of how students view engineering as away to change their world or the world at large.Most agentic frameworks in engineering education used qualitative research methods. However,Godwin and colleagues [40] and Verdín and Godwin [41] used quantitative measures to