retrospective reflections regardingthe impact participating in our program had on their education and career choices.Alumni tracking for the three comparison environmental engineering REU Programs found thatover 60% of participants of the Clarkson REU attended graduate or professional school [9],approximately 60% of the CU-Boulder Program’s participants continued on to graduate studies,and nearly 50% of participants of the Water REU at Virginia Tech were attending or hadattended graduate school [10]. Thus, our outcomes for students attending graduate school aresimilar to single-campus REUs in the same discipline.Challenges and opportunitiesOperating an REU Site across multiple campuses presents a number of logistical challenges, asothers have described
they enjoy finally being able tobegin building their project. During the Week 7’s construction week, many report struggles,setbacks and trouble with coding, resulting in a decrease in motivation. Week 8 is the lastconstruction and testing week. Some teams report their design starts functioning properly whileothers still struggle to get it to work. Week 9 is the presentation and demo day. Many reflect theyenjoy growing together as a team, have fun building the project and learn a lot. Some complainabout uncooperative team members and challenges of the project. 7 6 Self-Determination Index (SDI) 5 4
analytical thinking pervades engineering design activities,the integration of the performance of components and sub-systems is vital to the success of allbut the simplest design problems. Consequently, the role of systems thinking is vital in solvingcomplex engineering design challenges while simultaneously considering environmental issues,safety, ethical implications, and economic factors [11]. Systems thinking permits students “tobreak out of the narrow definition of a problem and reflect on the relevant systems and how theyaffect, and in turn are affected by, new and improved technologies” [12]. By integrating systemsthinking experiences into early engineering design challenges, students may become moreexcited about engineering, while learning
under-represented minorities in the sample is too small to draw strongconclusions.When survey results were filtered according to students’ academic year of study, third yearstudents reported the most interest in the certificate program. 48% of third year students wereinterested in the certificate program. Fourth year students, on the other hand, reported the leastinterest across academic year. This is a likely a reflection of the fact that fourth-year studentswho have not already begun to complete the certificate will not have an opportunity to do sowithout delaying graduation. Although there was no difference regarding interest in the programfor males, females on average were less likely to be interested (23%). Additionally, first-generation
approaches of incorporating active learning andstudent interaction is a discussion board [3], [4]. To make the process more dynamic, use of studentgenerated audio and videos are suggested as a way of engagement and reflection about the coursematerials [5]. This setup can be useful in some settings. However, perhaps less so for moreanalytical courses such as Business Analysis [6]. It may also be more in use for small classroomsettings [7]. Beyond the setting, some other issues with this approach entail students feelingburdened with the additional time spent on producing content for the discussion board andsustaining student interest to encourage participation. The structure of the blended format’s in-person classes, where some students are in class
? What are some potential concerns? (c) What simple design changes could you make, and what performance tradeoffs would result?Lab survey questionsPlease complete this survey after you have submitted your lab report. Participation in this survey will earn you 1point towards your lab report score. As you answer the questions, reflect on all aspects of the lab activity.Please indicate how much you agree or disagree with these statements based on your most recent labexperience in this course:Scale: Strongly disagree, Disagree, Neutral, Agree, Strongly agree 1. I am in control of setting the goals for this lab activity. 2. I am in control of choosing the appropriate analysis tools to evaluate experimental data. 3. I have the
the possibilities that surround me, and along with them…beauty.Circling a new role, now not who I am but what I do, yet more than that.A minister, literally, to be a servant, one who serves, reflecting my values unveiled and embraced.Circling fluidly between identities and roles grounded in who I am, a leader, a husband, a father, a teacher, a student, still…a servant.My eyes gazing outward, not on a goal nor an identity, external or internal, but anchored to a purpose found within myself yet beyond myself, to live for others, to serve humanity, particularly the “least of these.”Crashing into labels and stereotypes, Slowly circling, while negotiating the
- academia collaborations in software engineering: A systematic literature review. Information and Software Technology, 2016. 79: p. 106-127.[8]. Weagle, D., D.B. Ortendahl, and A. Ahern P.E., Universities and Industries: A Proactive Partnership Shaping the Future of Work, in 126th ASEE National Conference. 2019: Tampa, FL.[9] Harrisberger, L., Experiential Learning in Engineering Education. 1976.[10] Banks, S., et al., Focus on EMPLOYABILITY SKILLS for STEM Workers - Points To Experiential Learning, S.I.T. Force, Editor. 2015, STEMconnector: Washington, D.C.[11] Moon, J.A., A handbook of reflective and experiential learning: Theory and practice. 2004: Psychology Press.[12]. Hauhart, R.C. and J.E
) decreasing over time (c) staying about the same (d) unsure.”Questions 10 and 11 of the Qualtrics Survey were more reflective in nature than the previousnine questions. While the previous questions took a data-based route, these two questions wereimportant to understand how institutions and ARL libraries were supporting the needs ofstandards acquisitions. Question 10 asked if librarians felt that institutions understood the needsfor standards access, while question 11 asked if library administration understood the needs forstandards access. In figure 8, both questions show their results in a bar-chart form with 49% ofrespondents marking that they felt their institution understood the need to standards access and46% of respondents marking that they
well as thediscussion that occurred as the participants discussed each action research presentation.Additionally, some participants submitted a final report using a template provided by NationalAlliance for Partnerships in Equity, where participants shared information on their actionresearch issue, strategies applied, number of students reached, results, reflections, goals for nextyear, and other additional information (see Figure 2 in Appendix A). Additional data have beencollected throughout the project that will provide added content for analysis in the future,especially as it relates to the findings from this preliminary study. These data include student andschool team surveys, focus group interviews, and artifact collection and review
HBCU, met and exceededthe diversity of most REU programs across the nation. In terms of broadening participation inengineering, note that the majority of the participants were African-American, while a significantnumber were non-African American. The last cohort showed more gender and ethnic diversity,with ethnic diversity reflecting just as many African-American participants as non-AfricanAmerican participants; gender percentages were also equal by the final year of the program.evaluation methodologyThe evaluation plan included a hypothesis of increased modeling self-efficacy from pre-test topost-test. Yildirim et al. [4] developed an Engineering Modeling Self-Efficacy (EMSE) instrumentwith 36 items and 7 dimensions drawn from Tsang’s (1991
#1926330. Any opinions, findings, and conclusions or recommendationsexpressed in this material are those of the authors and do not necessarily reflect the views of theNational Science Foundation.7. REFERENCES[1] “Code of Ethics | National Society of Professional Engineers.” https://www.nspe.org/resources/ethics/code-ethics (accessed Apr. 19, 2021).[2] D.-L. Stewart, “Racially Minoritized Students at U.S. Four-Year Institutions,” J. Negro Educ., vol. 82, pp. 184–197, Jul. 2013, doi: 10.7709/jnegroeducation.82.2.0184.[3] M. T. Williams, “Microaggressions: Clarification, Evidence, and Impact,” Perspect. Psychol. Sci., vol. 15, no. 1, pp. 3–26, Jan. 2020, doi: 10.1177/1745691619827499.[4] E. A. Cech, “Culture of Disengagement in Engineering
∗ (11) ME,z ∗ ∗ We now have to evaluate whether the ARCs ME,x and ME,z are required for static equilibrium. From Table 2, since we currently have as many equations as unknowns, the ARCs will be needed for static equilibrium and thus, should be treated as needed reaction couple, as reflected in the final equations/unknowns Table 3. Table 3 Final equations/unknowns table for Example 1 Equations Unknowns (7) RE,x (8) RA,z (9) RE,z
reflective practitioner: Toward a new design for teaching and learning in the professions. Jossey-Bass.18. Wenger, Etienne, Richard A. McDermott, and William Snyder (2002). Cultivating communities of practice: a guide to managing knowledge. Boston, MA: Harvard Business School Press.
, students will: o Construct an optical encoder using reflective photosensors and a circular disc o Program a microcontroller to count rotations of an optical encoder6. Lab 5: Hall Effect Encoder Learning Outcomes: By the completion of this lab exercise, students will: • Count rotations using a hall effect encoder6. Lab 6: Interrupt task execution Learning Outcomes: By the completion of this lab exercise, students will: • Program a microcontroller to manage robotic platform tasks using interrupts7. Lab 7: IMU with filtering Learning Outcomes: By the completion of this lab exercise, students will: • Program a microcontroller to read and filter IMU data8
challengebecame when one of the learning community’s faculty members was removed from teaching thiscourse to teach another course outside of the learning community based on other program needsfor that semester. This difficulty was managed by bringing in another faculty member from theprogram who effectively delivered the course for the learning community’s initial offering.After the first year of implementing the themed-learning community (TLC), “Designers in theMaking,” the initial faculty team reviewed course content and reflected on goals and outcomes.All concurred that the format would remain as originally developed to be used again for fall of2019 and 2020. For the second offering, again one of the learning community faculty membersneeded to be
for the week.The rest of the time was spent with the students performing introductory tasks in the online sketchingenvironment. They took turns sharing their screens and assisting each other with the virtual sketching tasks.These class interactions accounted for a small amount of the course grade. The majority of the grade wasassociated with completing the online training modules described previously. Short reflections were alsoa required part of the course. The students read articles or watched videos related to visualization orvisualization training, and then wrote 200 – 300 words about their reactions. Three of these assignments © American Society of Engineering Education, 2021 2021 ASEE Illinois-Indiana Section
aggregation.Using the TriQL QB interface, students can immediately query the database without any priorknowledge of any database programming language.TriQL lab 2, which will succeed all SQL, MongoDB, and Neo4J labs, will include open-endedquestions that encourage students to use TriQL to solve problems and reflect on the differencesbetween the relational, graph, and document-oriented models and their query languages. We willdesign this lab to showcase the advantages and disadvantages of each data model. For example,students can work on a scenario in which data entities are highly connected. Cypher (graph) and ©American Society for Engineering Education, 2021 9 2021 ASEE Illinois-Indiana Section
. However, the shortcoming of themodel [1] is that uniform inflow is introduced at the inlet. If the uniform flow is considered, a largeregion needs to be modeled on the upstream side of the building to develop the logarithmic velocityprofile before the flow approaches the building. This would increase the computational time andsubsequently the computational cost. Hence, to optimize, a logarithmic velocity profile can beselected for the inlet, which saves both computational time and cost and at the same time resemblesa closer reflection to real-world atmospheric flows.1.6. Standard Wall FunctionFurthermore, the velocity gradient close to the wall is very high near the ground due to groundfriction. Therefore, to solve flow correctly, we need to
andtechnology aspects of sustainability.Sutherland et al. (2003) reported on the development of the MTU sustainability curriculum thatled to establishing the SFI. In the late 1980s and early 1990s, coursework in traditionaldisciplines (e.g., Chemical Engineering, Mechanical Engineering, and the Social Sciences) beganto reflect the growing importance of the environment. An Environmental Policy graduateprogram was established that complemented the existing Environmental Engineering program.Efforts from across campus led to the Engineering for the Environment and, later,Environmentally Responsible Design and Manufacturing courses to address interdisciplinaryenvironmental issues. Involved faculty began to serve on graduate committees outside of
largeengineering class may involve students with these learning styles, and more, which requiresinnovative methods to teach them. Learning styles of engineering students and teaching styles ofengineering professors are often incompatible [36]. Most engineering classes encourage studentsto be passive. Students do not experiment actively or reflect which disables them to learneffectively. Active learning serves as an alternate to lectures [37]. The proof of what is beingtaught in class is in the fabrication and implementation of hands on experiences. BenjaminFranklin said, “Tell me, and I forget. Teach me, and I may remember. Involve me, and I learn.”Hands-on engineering learning happens naturally in industry settings. Internships and co-opscomplement the
perspective added to the informalsurveys conducted by students in the field.To build a business case regarding particular technologies, a capital investment analysis wasperformed using cost of capital rates reflective of risk associated with operating in a particularregion, investment and business risk, financial risk, and failure risk. The information from theengineering analysis, business data, informal surveys, formal surveys, and capital investmentanalysis were then evaluated to obtain overall conclusions regarding the business feasibility of agiven water purification technology in the regions studied.Using qualitative information and quantitative data allowed for a comprehensiverecommendation regarding the business feasibility of water
were askedto provide the narratives.12Another response to Boyer’s call for SoTL resulted in the National Effective Teaching Institute(NETI), which was first offered at the 1991 Annual ASEE Conference in New Orleans,Louisiana. NETI has been attended by 992 professors from 216 different schools. The NETI hasmotivated many of its participants to adopt or increase their use of proven teaching strategiesknown to correlate with improved student learning; made them more student-centered, scholarly,and reflective in their teaching practice; and induced many of them to engage in instructionaldevelopment and educational scholarship.13 SDSU has sent several faculty members to NETIover the last few years, an indicator of College of Engineering support for
functionallity. The program runs continuously and monitors the ho ouse. In order to keep thecode more organized and easier to understaand, a stacked sequence is utilized. Each circuit subsystemm has its own frame. Forexample, the HVAC sense and control struuctures are housed in a separate frame from the lights. In n each frame, the specificpins for the subsystem are read. The GUI iss then updated to reflect the new data as read from the seensors. The sensor data iscompared to user settings for certain subsyystems. The predominant comparison method is to use logical l expression blockssuch as AND, OR, IF. The results of thesse comparisons cause
example 2 , start the topic by discussing the generalmicrocontroller structure, most of others just jump to the particular microcontroller used by thebook. And even those that discuss the general microcontroller structure, they do so very spar-ingly without planting the necessary seeds to make the topic understandable to students. This ineffect is reflected in how the class ends up being taught in many schools, see for example 7–12 . Assuch students are forced to learn on type of microcontroller as if it is the only one in the market.These student tend to get stuck when required to decide for themselves which microcontroller touse in a particular design, or when required to work with a different type of a microcontroller.Their knowledge tend to
intelligence (AI), biomanufacturing, regulation, cyber- becoming standard regulations and industry practice. Thisphysical system risk management and automation, biology, and framework includes an iterative process as shown in Figure 1biochemistry guides a multifaceted capstone project. This below. One pivotal element of this framework is transformingproject focuses on developing an interdisciplinary, modularized the validated innovative research to education and industryand extensible STEM education and industry workforce life- workforce training and ultimately reflecting conceptlong training platform. This advanced educational initiative applications in industry practices; see for example [2].offers
intelligence (AI), biomanufacturing, regulation, cyber- becoming standard regulations and industry practice. Thisphysical system risk management and automation, biology, and framework includes an iterative process as shown in Figure 1biochemistry guides a multifaceted capstone project. This below. One pivotal element of this framework is transformingproject focuses on developing an interdisciplinary, modularized the validated innovative research to education and industryand extensible STEM education and industry workforce life- workforce training and ultimately reflecting conceptlong training platform. This advanced educational initiative applications in industry practices; see for example [2].offers
intelligence (AI), biomanufacturing, regulation, cyber- becoming standard regulations and industry practice. Thisphysical system risk management and automation, biology, and framework includes an iterative process as shown in Figure 1biochemistry guides a multifaceted capstone project. This below. One pivotal element of this framework is transformingproject focuses on developing an interdisciplinary, modularized the validated innovative research to education and industryand extensible STEM education and industry workforce life- workforce training and ultimately reflecting conceptlong training platform. This advanced educational initiative applications in industry practices; see for example [2].offers
intelligence (AI), biomanufacturing, regulation, cyber- becoming standard regulations and industry practice. Thisphysical system risk management and automation, biology, and framework includes an iterative process as shown in Figure 1biochemistry guides a multifaceted capstone project. This below. One pivotal element of this framework is transformingproject focuses on developing an interdisciplinary, modularized the validated innovative research to education and industryand extensible STEM education and industry workforce life- workforce training and ultimately reflecting conceptlong training platform. This advanced educational initiative applications in industry practices; see for example [2].offers
intelligence (AI), biomanufacturing, regulation, cyber- becoming standard regulations and industry practice. Thisphysical system risk management and automation, biology, and framework includes an iterative process as shown in Figure 1biochemistry guides a multifaceted capstone project. This below. One pivotal element of this framework is transformingproject focuses on developing an interdisciplinary, modularized the validated innovative research to education and industryand extensible STEM education and industry workforce life- workforce training and ultimately reflecting conceptlong training platform. This advanced educational initiative applications in industry practices; see for example [2].offers