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
the seven principles ofgood feedback practice7. The quizzes 1) helped clarify what a good performance was, 2)facilitated the development of self-assessment (reflection) in learning, 3) delivered high qualityinformation to student about their learning, 4) encouraged teacher and peer dialogue aroundlearning, and 5) provided information that we could use to modify our teaching. The studioformat and flipped nature of the course were key to supporting these basic feedback principles.Experiment ResultsThe most significant effect of the latest method of flexible assessment was seen in its impact onthe final overall course grade and one of the final exams. Table 2 shows the lab and lecture finalexam averages from the previous (Spring & Fall 2018
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
achieved solo and to make learning complete, thelearner must find ways to learn from the team. The pre-recorded videos are not used directly forteam-work as such, however, students are provided an online forum (in the form of Google docas it is very easy to post pictures and screen shots as well on a Google doc) to ask questions andparticipate in discussions related to the videos. It is not mandatory for them to participate indiscussion and post questions, but they are encouraged. This forum is used in three semestersalready and it stays very active. It is easy for students to pose the question on the Discussion docat any convenient time when they are watching the videos or reflecting on it. Then other studentsand instructor comment and discuss.In
oscilloscope to visualize the digital signals at the output of the receiver and identifysimilarities among the different codes generated by pushing the different keys in the remotecontrol as shown in Figure 3. Students are also asked to modify the angle of incidence betweentransmitter and receiver that results on a code being generated which results on mapping out theallowable area for the remote control to work correctly. They are also asked to experiment onhow the signals are affected by distance between transmitter and receiver, reflections, etc.Figure 3: Codes generated by a TV remote controlBasic Oscillator with 555 timer.- Freshman EE/EET students typically do not have theopportunity to work with integrated circuits. This experiment aims to
break immediately and will take many hours of work tokeep working every school year.The capstone team and Ohio Northern University are concerned with all of the different metrics,as their reputations are on the line if the project fails to meet expectations. Especially importantare the security concerns, as a breach of security/privacy would reflect poorly on the groups, andan especially egregious breach could have more tangible consequences.3. Existing Hallpass System OptionsThere are a few competing products on the market that could be used as a substitute for theproject. The largest competition is the hallpass monitoring system that is already in place. Theother competition to the project is digital forms of hallpass monitoring that is done
ofimplementing it in an engineering lab environment. Nonetheless, this Co-robot system has thepotential to help students better understand and experience firsthand how HF&E principles andmethods can be applied, as well as how they could reduce the risk of WMSDs and improve theergonomics of a task. This has the potential to improve and expand engineering studentknowledge of HF&E, which is essential for their future career. Fall 2017 Mid-Atlantic ASEE Conference, October 6-7 – Penn State BerksAcknowledgement This research is funded by the National Science Foundation NSF NRI #1527148. Anyopinions, findings, or conclusions found in this paper are those of the authors and do notnecessarily reflect the views of the
data of first year students in college of identified community needs and (b) reflect on the serviceengineering. Considering the result of the study, the activity in such a way as to gain further understanding ofprinciple goal of this program is to increase the retention course content, a broader application of the discipline and anstatistics for engineering students. Each of these fellows enhanced sense of civic responsibility” [1]. Consideringhas been assigned to one engineering department. Using society’s needs, students are led in solving real-worldthe help of this graduate fellow in the Civil and engineering problems using the concepts of their engineeringEnvironmental Engineering
AcknowledgmentThis research is funded in part by NSF NRI # 1527148. Any opinions, findings, or conclusionsfound in this paper are those of the authors and do not necessarily reflect the views of thesponsors.References1. Vest C. Context and challenge for twenty-first century engineering education. J Eng Educ. 2008;97(3):235-236.2. Lauche K. Job design for good design practice. Des Stud. 2005;26(2):191-213. doi:10.1016/j.destud.2004.09.002.3. Egan PF, Leduc PR. Utilizing emergent levels to facilitate complex systems design: Demonstrated in a synthetic biology domain. ASME 2013 Int Des Eng Tech Conf Comput Inf Eng Conf. 2013:V03AT03A045-V03AT03A045.4. Ben Ammar M, Neji M, Alimi AM, Gouardères G. The Affective
. It may be that the students who responded to thesurvey only reflected a limited view of the perceptions in the graduate student climate. TheCLIMATE AND ENGINEERING GRADUATE STUDENTS 13questions that were included on the survey were limited to looking at peer and faculty advisorinteractions. Additional research could identify additional factors that comprise campus climateto better discern what elements of the graduate experience influence perceptions of campusclimate. Despite these limitations, the findings from our study did provide unique and newinsights to perceptions of climate among three different groups. Findings show that minoritystudents are more likely to indicate
process is not the first aspect of the program promoted to students, it isexplained on the webpage. It is also reflected in the online application, which only requestsstudent identity, major, year in school, requested team, number of credit hours (1 forsophomores, 1 or 2 for juniors and seniors, and 3 for Senior Design), and comments. Thecomment box is unassuming, and usually elicits a few sentences from students explaining whythey’re interested. Unlike most research experiences, students do not have to write essays, fillout lengthy forms, or polish their resumes. Interested students apply and are accepted on a spaceavailable basis. Returning students are automatically accepted back onto their teams, and teamsare marked “full” when no more space
shown in Fig. 3. knowledgeDuring the first meeting, the instructors and students took turnsintroducing themselves, including indicating their gender pronouns. Students were also asked what theywanted to discuss in the course and they indicated a number of topics related to identity, technology, and art.Among the identities mentioned by students were asexual people, queer people of color, and trans people,which often reflected their own identities. Students were introduced to the Arduino microcontroller, which isdescribed in product literature as “an open-source electronics prototyping platform based on flexible easy-to-use hardware and software…intended for artists, designers, and inventors…”[7]. Students were asked toindicate, via survey
well below the current estimates of Nationalrepresentation of women in undergraduate engineering programs of 22% [6]. Student distributionsby gender, department, and student level (i.e. freshman through senior) are shown in Figure1. Fresno State classifies student level based on the number of units a student has completed andmay not necessarily reflect their progress in their degree program. Because many students takemore units than that are required for a degree program, ‘seniors’ are disproportionately representedusing this classification system. Because of the ethnic diversity surrounding Fresno State, theuniversity serves multiple underrepresented minority populations and is officially designated as aHispanic-Serving Institution (HSI) and
ofConvergence in Vermont, New York, and Berlin in 2018.We conclude with four quotes from faculty and students involved in the making of Convergencethat illustrate the project’s impact.Matt Burnett, the faculty project lead and artistic author, remarked that by combining the skillsets, working methods and perspectives of several people, the resulting production vastlyexceeded the capabilities of the involved individuals. “It can be difficult for an artist to give up creative control; but this is perhaps more reflective of arts in the 21st century; a switch from the model of artist as “isolated genius” to “project manager.” The whole is greater than the sum of its parts - which is the thematic spirit of Convergence in the first place
set D. The Posterior probability could be calculated as 𝑃𝑃(𝜃𝜃)𝑃𝑃�𝐷𝐷 �𝜃𝜃 �𝑃𝑃(𝜃𝜃|𝐷𝐷) = 𝑃𝑃(𝐷𝐷) , where the Likelihood 𝑃𝑃 (𝐷𝐷|𝜃𝜃) is the probability of realizing anexperimental data D given a set of parameters θ ; the denominator 𝑃𝑃(𝐷𝐷) is the probability of theevidence and could be considered as a normalizing factor; 𝑃𝑃(𝜃𝜃) is the reflected known value ofthe considered parameters, also called as Prior. The MH algorithm is an improved algorithmbased on Markov chain Monte Carlo (MCMC) simulation. The MH algorithm externallimitations and targets are set or approximated before the simulation for better efficiency. ThePosterior probability is then generated using the MH
Satisfied unsatisfiedQ10. Please use this space to provide any additional comments, questions, or suggestions. Also,please let me know if you would like to discuss this project further. Appendix B. Teammate Participation Rubric Reflecting on your teammates’ participation within the group project, rate each teammate usingthe following rubric. Add your teammates’ names on the next page and corresponding pointsyou award them. The teamwork points will be averaged and figured into your teammates’ finalgrade. Trait Criteria 1 2 3 4
context of the student’s temperaments as determined by the Keirsey Temperament Sorter.Results are presented discussing the impact of team composition on both team and peer ratings.Literature ReviewEngineering curricula have been historically very technically focused, with larger classes focusedon a specific engineering topic1. This style of instruction does not accurately reflect anengineer’s job requirements, which often include multi-disciplinary problem-solving andworking in groups. Under recent ABET guidance, there has been an increased push for project-based learning that integrates complex, group problem-solving to better align with employer’sneeds2. There is a large body of research related to how to best select individuals for