complicated impacts of learning technologies and design on K-12 STEM curriculum, pedagogy, and institutional policies in the Philippines and Canada.Prof. Andre Phillion, McMaster University AndrA©˜ Phillion is an Associate Professor in the Department of Materials Science and Engineering and Director of the facultyˆa C™s Experiential Learning Office at McMaster University, Hamilton, Canada. His research interests focus on mathematical modelling ©American Society for Engineering Education, 2023 First-Year Students in Experiential Learning in Engineering Education: A Systematic Literature ReviewDr. Gerald TembrevillaGerald Tembrevilla is an Assistant Professor at Mount Saint Vincent
aframework comprising 12 attitudes and 17 behaviors that align with the 3Cs.Parallel to the entrepreneurial mindset, we can define an innovation mindset as a set of beliefsand attitudes that lead to developing the capacity to produce valuable novelty. There is also adistinction between individual innovativeness and the innovation mindset. For example, Hunteret al.’s conceptual model of innovativeness [11] includes constructs such as knowledge, skills,and abilities, while the innovation mindset emphasizes dispositions, attitudes, and propensities[12]. Couros [13] describes eight characteristics of an innovator’s mindset: empathic, problemfinders/solvers, risk takers, networked, observant, creators, resilient, and reflective.This paper investigates
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majordifferences between coping networks of students who are able to successfully manage stress versusthose who are not able to? To answer these questions, we surveyed graduate engineering studentsat a mid-sized Mid-Atlantic institution. The survey consists of three major sections: (1) thePerceived Stress Questionnaire (S. Levenstein, et al. J. Psychosom. Res., vol 37, no. 1, pp. 19-32,1993.), which is a validated instrument that assesses an individual's perceived stress level, (2) asection for respondents to identify and rank major sources of stress, and (3) a section forrespondents to identify and rank major coping strategies. The survey identified research, grades,and issues relating to mental health as major stressors for all groups, and people
applying a holistic-content narrative analysis [70] to each interview,focus group, or journal. Next, we employ open coding which gleans from elemental methods:descriptive, in vivo, and process coding and affective methods: emotion, values, and evaluationto identify emerging patterns in the data [73]. Then, we apply axial coding to identify subthemes[74] and thereafter, group themes and sub-themes across all interviews and focus groups,formulate meaning through the clustering of themes [69], which will ultimately lead to theemergence of key findings.Research FindingsPreliminary Findings with EngWINS ParticipantsQuantitative Findings:Descriptive statistics from the S-STEM Pre (n=15) and Post (n=11) Surveys were calculated, asdisplayed in Table 3 and
test a substantiallygreater number of mutations and samples when compared to this work. However, the results inCheers et al. are unable to answer this paper’s research question because the purpose of Cheers etal.’s work is to measure similarity robustness in isolation, and does not attempt to evaluatedetection correctness [15, Sec. 4.1]. The gap between the work of Cheers et al. and this paper’sresearch question is filled by the development of the sensitivity preservation metric that considersonly the similarity robustness that is a result of correctly detected plagiarism. Additionally,Cheers et al. note that “...the interpretation of the second comparative metric poses a threat to thevalidity of results in this work. As discussed, it is not a
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, meaningful connections to existingstructures in the community will be leveraged to continue research and outreach. AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant No.1943098. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the author(s) and do not necessarily reflect the views of the National ScienceFoundation. References[1] C. A. Carrico, “Voices in the Mountains: A Qualitative Study Exploring Factors Influencing Appalachian High School Students’ Engineering Career Goals,” 2013.[2] S. Ardoin, College aspirations and access in working-class rural communities
projects. The preliminary learning outcomes and framework presented in this studycan guide students through multiple stages where incorporating contextual factors is relevant andprovide prompts for reflection and methods to do so iteratively throughout their designprocesses. The findings from this work have implications for engineering design pedagogy and,ultimately, the potential to improve engineering graduates’ abilities to develop contextuallysuitable solutions.References[1] C. B. Aranda-Jan, S. Jagtap, and J. Moultrie, “Towards A Framework for Holistic Contextual Design for Low-Resource Settings,” Int. J. Des., vol. 10, no. 3, p. 21, 2016.[2] P. Clyde et al., “25 Years of Health Care Delivery in Low- and Middle-Income Countries
dashboard to track COVID-19 in real time,” Lancet Infect. Dis., vol. 20, no. 5, pp. 533–534, May 2020. [3] S. X. Zhang, Y. Wang, A. Rauch, and F. Wei, “Unprecedented disruption of lives and work: Health, distress and life satisfaction of working adults in China one month into the COVID-19 outbreak,” Psychiatry Res., vol. 288, p. 112958, Jun. 2020. [4] A. El Masri and E. Sabzalieva, “Dealing with disruption, rethinking recovery: Policy responses to the COVID-19 pandemic in higher education,” Policy Design and Practice, vol. 3, no. 3, pp. 312–333, Jul. 2020. [5] A. F. Tasso, N. Hisli Sahin, and G. J. San Roman, “COVID-19 disruption on college students: Academic and socioemotional implications,” Psychol. Trauma, vol. 13, no. 1, pp
Metaphor F-M Perceptual metaphor F-M-P Figurative Language F Lexicalized metaphor F-M-L Personification F-P Simile F-S Synecdoche F-Y Metonymy F-M Analogy F-A Question S-Q Illustrative S-E Teaching Style S Example Imagination S-I Repetition
communication skill-building in engineering-specific technical communication classes,resulting in engineers who can more effectively propose, lead, and manage teams remotely [11,12]. Instructional technology has developed at the same time as pedagogical approaches haveexpanded to serve more diverse learners [13]. Engineers cross-trained in VMC in addition totheir discipline-specific skills will highly contribute to their professional growth.Professionalization also entails a successful life-stage transition from student to employee, whichcorresponds with a change of responsibilities and expectations. Transitioning, defined as “anyevent or non-event that results in changed relationships, routines, assumptions, and roles,” [14]includes four-S dimensions
University Dr. Ruth S. Ochia is a Professor of Instruction with the Bioengineering Department, Temple Univer- sity, Philadelphia, Pa. Her past research interests have included Biomechanics, primarily focusing on spine-related injuries and degeneration. Currently, her interests are in engineering education, curriculum development, and assessment at the undergraduate level. American c Society for Engineering Education, 2021Introduction:There has been much work on the development of entrepreneurial thinking in engineering students.[1,4,5] These studies emphasize the needs to train our students to be innovative and entrepreneurialminded to meet the changing technological
Paper ID #32725Broadening the Participation of Underrepresented Minorities in theMathematical SciencesProf. Tuncay Aktosun, University of Texas at Arlington Dr. Aktosun is a professor of mathematics at the University of Texas at Arlington. His research area is applied mathematics and differential equations with research interests in scattering and spectral theory, inverse problems, wave propagation, and integrable evolution equations. He is involved in various men- toring and scholarship programs benefiting students. He has been the GAANN Fellowship Director in his department since 2006, the NSF S-STEM Scholarship
followed by a series of plans which saw rapid ad-vancements in industry, agriculture and education. Engineering enroll-ments increased to over 75,000 each year. Engineering schools were ex-panded at home, and in addition, students were sent to study in Russianuniversities. At the same time, the government developed its philosophyof education. Mao s support during the liberation depended on the peasants and 1workers and while Mao recognized the need for an educated populace, hewanted to place restrictions on the development of an intellectual class.The result was that the state or rulers took the right and responsibilityto improve society by using education to improve the moral conduct of thepeople. While this may mean many different
suspension of disbelief on the part of the student. In Deshpande etal.’s [23] review of simulation games in engineering education, they found many advantages ofteaching engineering concepts through simulated environments over traditional classroominstruction, including but not limited to connecting theory to practice, customizability ofdifficulty to match students comprehension level, reduction of resistance to accepting innovativeideas and concepts, and greater retention of concepts over time. Another advantage ofsimulation-based learning is its compatibility with online learning, which continues to be agrowing trend, especially since the COVID-19 pandemic [11], [18], [31], [32].Using virtual systems to augment education is not only limited to
PBL assignment that incorporatesscientific principles into an engineering design course. The PBL assignment challenges studentsto evaluate the OneCarTM and then redesign, manufacture and assemble a modified design. Infuture work, this project is envisioned to be expanded to consider student feedback in an attemptto evaluate project effectiveness.References[1] H. A. Hadim and S. K. Esche, “Enhancing the engineering curriculum through project-based learning,” in 32nd Annual Frontiers in Education, Nov. 2002, vol. 2, pp. F3F-F3F, doi: 10.1109/FIE.2002.1158200.[2] K. Edström and A. Kolmos, “PBL and CDIO: complementary models for engineering education development,” Eur. J. Eng. Educ., vol. 39, no. 5, pp. 539–555, Sep. 2014, doi
extracurricular project-based experiential learning,” in 2017 ASEE Annual Conference & Exposition, 2017. [2] E. Wenger, Communities of Practice: Learning, Meaning, and Identity. Cambridge University Press, 1998. [3] A. Ostrowski, J. Lee, S. Daly, A. Huang-Saad, and C. Seifert, “Design in biomedical engineering: Student applications of design heuristics as a tool for idea generation,” in 2017 ASEE Annual Conference & Exposition, 2017. [4] R. M. Miller, S. Maiti, and M. E. Besterfield-Sacre, “Effect of a project-based learning activity on student intrinsic motivation in a biomechanics classroom,” in 2017 ASEE Annual Conference & Exposition, 2017. [5] J. Parry-Hill, P. C. Shih, J. Mankoff, and D. Ashbrook, “Understanding
STEM Career Choices: Using Expectancy-Value Perspective to Understand Individual and Gender Differences in STEM Fields," Developmental review : DR, vol. 33, no. 4, p. 10.1016/j.dr.2013.08.001, 09/13 2013.[4] D. B. Clark, E. E. Tanner-Smith, and S. S. Killingsworth, "Digital Games, Design, and Learning:A Systematic Review and Meta-Analysis," Review of Educational Research, vol. 86, no. 1, pp. 79-122, 2016.[5] C. S. Green and D. Bavelier, "Action-Video-Game Experience Alters the Spatial Resolution of Vision," Psychological science, vol. 18, no. 1, pp. 88-94, 2007.[6] N. Martín-Dorta, J. L. Saorín, and M. Contero, "Development of a Fast Remedial Course to Improve the Spatial Abilities of Engineering
, Page 14.575.2such as seniors and juniors, to supervise and mentor younger college students. A faculty advisorPage 14.575.3Page 14.575.4 The amount of students who choose Engineering Technology majors within thedepartment has increased from 12 to 14 percent and is expected to continue in this trend (seeTable 2). Table 2: Percent Engineering Technology Per Academic Semester F 08 S 05 14% 12% F 05 S 08
animation, interactive control of the simula-tion time is provided, so every change can be observed. Networks to be simulated are implemented by declaring the signals involved and connecting those signals to the componentinputs and outputs. The general format of component specification is: (, , cOutput(s)>);as C++ function invocations. Consider the following simple example, written in C++, of a two-input And gate activated by Switches and monitored by a digi-tal Probe: #include maino { Signal a, b, c; // Declaration of signals Switch (” la”, a, ‘a’ );// Position Switch at schematic position “la”, and associate keyboard ‘a’ key with Signal a Switch (” la
, plot the unit step response of thesystem for any point selected on the root locus, and turn on/off the grid. The system must berepresented by the transfer function in the following form:Y(s) ams m + am-1 sm -1 ... + a1s + a0s—— = ————————————U(s) bnsn + bn-1s n-1 + ... + b1s + b0s:The options in Design module allow the user to select any desired value for the gain, time andfrequency parameters of the system to see how the closed—loop poles will be affected.The time-domain design parameters that can be changed are rise time, delay time, time constant,settling time, maximum overshoot, peak time, damping factor, natural undamped frequency, anddamped frequency. The frequency-domain design parameters that are included in the programand can be
futurecurriculum renewal projectsAcknowledgementThis material is based upon work supported by the National Science Foundation under Grant No.EEC-0530638. 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.Bibliography1. Thompson, T., Flick, L, Gummer, E., and Fiez, T. (2004). Enhancing Campus Collaborations Through Design Research in Engineering Education Reform. Proceedings, ASEE Annual Conference and Exposition, Retrieved from http://www.asee.org/acPapers/code/getPaper.cfm?paperID=7942, 6 December 20052. Fisher, P. D., Fairweather, J. S., and Amey, M. (2001). Systemic Reform in Undergraduate Engineering
based on the following: Soft Skills(S), Technical Skills (T), Experience (E) and Managerial Skills (M).Table 2 – STEM Skills – Student and Industry Perspectives Skill (STEM Area) Students’ Practitioners’ Reference Perspective Perspective Team Work (S) X X “Good team players” (Salleh et al., 2015) “Collaboration” (Kappelman, Jones, Jonhnson, Mclean, & Boonme, 2016)Communication (S) X X “Confident communicators” (Salleh et al., 2015
for the NOT of a logic function. 44 Design a hierarchial carry-lookahead adder. 3 Create a truth table for a logic function. 45 Design an array multiplier for unsigned binary numbers. 4 Draw the logic network of gates that implements a logic function. 46 Multiply signed binary numbers with 2’s complement arithmetic. 5 Use Boolean Algebra to reduce a logic function. 47 Convert a fixed-point binary number to decimal. Give the decimal exponent range and precision of a single- or double- 6 Prove a
. 223–231, Jul. 2004.[6] K. Sheridan, E. R. Halverson, B. Litts, L. Brahms, L. Jacobs-Priebe, and T. Owens, “Learning in the Making: A Comparative Case Study of Three Makerspaces,” Harv. Educ. Rev., vol. 84, no. 4, pp. 505–531, Dec. 2014.[7] C. C. Bonwell and J. A. Eison, Active learning : creating excitement in the classroom. School of Education and Human Development, George Washington University, 1991.[8] Y. Y. Hong, C. S. Dweck, C. Y. Chiu, D. M. S. Lin, and W. Wan, “Implicit theories, attributions, and coping: A meaning system approach,” J. Pers. Soc. Psychol., 1999.[9] C. S. Dweck, “Implicit Theories,” in Handbook of theories of social psychology, V. 2., P. A. M. van. Lange, A. W. Kruglanski, and E. T
andsurface properties of new materials. A model consisting of several standard test methods waspresented in this paper. The equipment is used to perform the presented tests are the same as thatused for conventional materials and usually available in material science labs of universities.References[1] Y. Huang, M. C. Leu, J. Mazumder, and A. Donmez, "Additive manufacturing: current state, future potential, gaps and needs, and recommendations," Journal of Manufacturing Science and Engineering, vol. 137, no. 1, p. 014001, 2015.[2] S. Bland and N. T. Aboulkhair, "Reducing porosity in additive manufacturing," Metal Powder Report, vol. 70, no. 2, pp. 79-81, 2015.[3] J. R. C. Dizon, A. H. Espera Jr, Q. Chen, and R. C. Advincula
curriculum was designed through several iterative meetings with industry.The industry advisors identified the Knowledge, Skills, and Abilities (KSAs) that would help themost with the transition from student to professional. These KSAs led directly to the design ofthe Hatchery Unit (HU) courses. Forty professionals from twelve companies have participated inthe design and delivery of HU courses. The academic-industry collaboration has been critical ingetting acceptance from faculty and students.To date, we have offered 57 CS-HU sections with 1591 students (non-unique) enrolled in thesecourses. The five required CS-HU courses are Foundational Values (14 sections, 473 students),Navigating Computer Systems (12 sections, 354 students), Intro to
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