, in order to doeveryday homework and to perform well in the lab tests. The students spent the last three days ongroup work for their final project. The two instructors monitored the teams’ progress on theirprojects and had constant discussion and feedback sessions. On the last day of the program, eachteam made a presentation on its final project followed by a Q/A session. The final presentationwas evaluated by the two instructors from SIUE, a faculty member from Universiti TeknologiMalaysia (UTM) and the TU professors (the authors of this paper).After the final presentation was done, an assessment form was handed out to the students tocollect the program evaluation from the students. The questions used in the assessment formwere as follows
academic calendar). Some sessions would begin with a warm-upactivity, continue to a longer activity followed by a discussion, and end with a wrap-up in theform of short “one-minute” papers [13]. The specific activity completed during the class sessionvaried, ranging from a “data dive” into the American Society for Engineering Education (ASEE)online engineering college profiles [14] to “I Like, I Wish” worksheets centered on culturalchange. Other times the class would begin with a brief introduction by one of the instructors thatwas then followed by a lecture from a guest speaker (see below) and then by a Q&A session.Each session lasted for 80 minutes. The class was scheduled relatively early in the morning, 9am, so breakfast pastries and
mayhamper critical thought or effort. Our goal instead is to focus in on the specific errors that yieldexcessive struggle. In future work, we will build debugging activities focused on reducing theerrors found in this paper. We also hope to automatically detect these common errors and toprovide custom hints. Both approaches we hope will reduce student struggle.References[1] Mahmoud, Q. H.; Dobosiewicz, W. & Swayne, D. Making computer programming fun andaccessible Computer, IEEE, 2004, 37, 106-108.[2] Beaubouef, T. & Mason, J. Why the high attrition rate for computer science students: somethoughts and observations, ACM SIGCSE Bulletin, ACM, 2005, 37, 103-106.[3] Spohrer, J. C.; Soloway, E. & Pope, E. A goal/plan analysis of buggy Pascal
9.2°C 1 Inputs at the optimum ACL=2000 [kW-hr/yr] Cuac=250 [$/m^2] i=0.03 [-] A c=1.80 [m^2] cue=0.15 [$/kW-hr] n=25 [-] A e=1.59 [m^2] Q dot,e=0.4 [kW] e=1.5 [-] U c=0.02 [kW/m^2-K] ccc=300 [$/kW] Cuae=200 [$/m^2] ETA=0.78 [-] U e=0.031 [kW/m^2-K] 2 10 100
participants and professors and studentsfrom the Columbia College Chicago. After each presentation, there is a session of Q&A, wherethe teens can explain specific topics of their work more in detail.ComEd Youth Ambassadors (ComEd)In the ComEd Youth Ambassadors program, participants develop a better public understandingof the “Energy Infrastructure Modernization Act” (EMIA). The community engagement teamfrom the Science and Mathematics department at Columbia College Chicago developed the“Smart Grid and You” curriculum. In addition to promoting the contents relevant to the SmartGrid and its impact in the common citizen, the goal of this program is to generate a positiveenvironment in which teens that are inclined but not yet convinced to explore
pointed out, a key to teaching the course well is to have “a willingness to go through thesame process that the students will go through.” To date, two cohorts have completed thisintensive training, with a third scheduled to attend the week-long training in summer 2018.The Fundamentals of Innovation and Entrepreneurship course for students, which is taught in thejunior year at our university, is composed of three modules: Design Thinking, Entrepreneurship,and Growth and Leadership. Most sessions include a variety of activities: mini-lecture,discussion, interactive activities in class, and open Q&A. The course materials for each sessionconsist of specified learning outcomes, concepts, layouts, PowerPoint presentations andresources that include
established, the sharing, using, improving, and changing of all thedeveloped concepts become easier without the limitation geographically. Certainly, anyunexpected incident or technical difficulty can be easily resolved among faculty or students withsimple Q and A, email, or traditional phone calls. A real-time video conferencing can be addedeasily whenever there is a need to resolve more complex problems and issues. The overall goal of this project is to create an on-line learning community for facultymembers nationwide. An active on-line learning environment provides the opportunity for theteam to achieve their instructional goals. Many faculty members have developed the knowledgeand teaching practices of embedded system designs by
✓ ✓ ✓ ✓f. Codes and Standards ✓ ✓ ✓g. Quantity Estimating ✓ ✓ ✓h. Permitting ✓ ✓ ✓i. Health and Safety ✓ ✓ ✓j. Application Programming ✓ ✓ ✓k. Cost Estimating ✓ ✓ ✓l. Construction Document ✓ ✓ ✓ Packagingm. Contracts ✓ ✓ ✓n. Quality Assurance and Quality ✓ ✓ ✓ Controlo. Technical Documents ✓ ✓ ✓p. Specialized Software ✓ ✓ ✓q. Project Management
Boothroyd-Dewhurst method To redesign a product and reduce B Hitachi method 5 assembly cost, I am aware of C Lucas method standard tools. D Critical Path method E All of the above Table 9 Sample Syllabus Focus survey to be used in EDM Q. no. Question Question mapping 1 How vital is customer assessment for the success of any project? Learning outcome How confident am I to successfully use customer assessment tools such as for 2
supporting documents (analysis, bill of materials, etc.) arepresented.Module 2: Measurement Uncertainty ModuleThe overall objective of this module is to learn and apply techniques for quantifying experimentaluncertainty. Two short experiments are completed to provide context for applying the various tech-niques. Each experiment ends with an assignment focused on writing an executive summary.The first experiment involves the measurement of volumetric discharge (Q) with a nozzle meter.Students are exposed to an explanation of how a nozzle meter works as a measurement device.This includes developing the various equations and explaining the variables involved. Two of thevariables in the nozzle meter equation are postulated to have experimental
consists of a series of waveformsoccurring in a repetitive order. These waveforms arise from a flat baseline called the isoelectricline. Any deflection from the isoelectric line denotes electrical activity.As seen in Figure 4, five major deflections on a normal EKG are designated by the letters P, Q,R, S, and T. One heart cycle is represented by a group of waveforms beginning with the P wave,followed by the QRS wave complex, and ending with the T wave. The P wave represents thedepolarization of the atria and is associated with their contraction. The ventricular activation isrepresented by the QRS complex. The T wave results from ventricular repolarization, which is arecovery of the ventricular muscle tissue to its resting state.Figure 5 depicts
Engagement in the Minimizing over stimulation, whilst encouraging engagement. environment. Document visit to Museum of Science & Technology (MOST). Guest speaker Angela First round of ideation. Gaige, Education Director at List of questions for Chelsea Leonard, Occupational Therapist. MOST. 4 Transcript of Q&A with Ideation, preliminary prototypes. Chelsea Leonard. Photograph models for the process book. Design and prototype. 5 Design and prototype. Ideation, secondary prototypes. Photograph models for the process book. 6 Design and
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have beenclear or complete to everyone’s liking: “I would like to say that some important parts of the documentation for CRTS were really poor. Especially the beginning parts of the CRTS manual which lacks clarity [...] I am not an expert in using Ubuntu[....]The CRTS manual can be improved by providing easier and user friendly methods [to perform] various tasks.” (5) Instructions for each phase of the competition were not always clear or timely: “There should be some better source that we can go and see up to date instructions and Q&A for each step. Mail group is not that efficient, since everyone cannot reach. I joined to contest in the second phase, and could not see previous
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tion ire im en Pr lysi se ce Bo ool on i n Pr nin In ycl Ri Pro ictio sig In en el ctu an me n Ag ri Ri an ypi isi q u S l C st
])) = (𝑇𝑎𝑟𝑔𝑒𝑡[𝑛] − 𝑓(𝑖[𝑛])) ∙ 𝑓′(𝑖[𝑛]) (5) 𝑤( [𝑛] + 𝐿𝑒𝑎𝑟𝑛𝑅𝑎𝑡𝑒 ∙ 𝑟P𝑇𝑎𝑟𝑔𝑒𝑡[𝑛], 𝑓 (𝑖[𝑛])Q ∙ 𝑥( [𝑛] 𝑤( [𝑛 + 1] = M 𝑤* [1] = 𝑊𝑒𝑖𝑔ℎ𝑡* (6) 𝑤8 [1] = 𝑊𝑒𝑖𝑔ℎ𝑡8While a trained model needs only equations 3 and 4, training the perceptron utilizes all theequations listed. When in training mode, an input of the Target value of the perceptron is required.Other initialized values not taken as inputs to the perceptron are Weight1, Weight2, and LearnRatethat are included in the Perceptron module. These values can be changed according to the desiredvalue in code
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