activities. However, there were some limitations in areas where particular content could only be examined through test and quiz grades. Modifications Made to Assessment Methods/Documenting Student Knowledge. Weekly assignments grade, online exams, classwork problems for the students to complete in class to allowing for checking for understanding; Exams are completed during scheduled times; students scan exams using smartphone Apps and submit it to instructors via email. Instituted Projects Day. Faculty gauged content understanding through "review questions" derived from quizzes, student provided answers through chat room and online exams Posting and broadcasting of resolved Q&A from students to the entire class made a positive
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tweet. If you manage a brand orpolitical campaign, for example, it may be important to keep track of your popularity, andsentiment analysis provides a convenient way to take the pulse of the tweeting public.Final Project Format I. Introduction to Big Data Analytics in general. Discuss importance, applications (e.g., politics, health, industry, etc.) and perspectives. In a second paragraph, discuss importance of sentiment analysis from Twitter data as a special application of big data. Check out some examples from this search result from PLOS ONE that list various papers that used Twitter for their study: http://journals.plos.org/plosone/search?from=globalSimpleSearch&filterJournals=PLo SONE&q
homework assignment. 4 Data Collection and AnalysisOur data consisted of short, written responses collected electronically from students in reply toassignment questions as part of metacognition modules. While we intentionally collected datathat could tell many stories regarding the intervention, we selected the following assignmentquestions to answer our research questions:Table 1: Intervention Assignment Questions Relevant to Research Questions Research Assignment Question (Q) Module Week Question (RQ) RQ1. What Q1. What is your primary learning strategy for problem
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to data mine associations between different joints on a human body (red circles in Figure4) and actions that students are performing. Figure 4: Multi-modal data acquisitionThe skeletal data is transformed into numeric XYZ values for each of the joints, as seen in Figure4, with a new data sample captured once every q milliseconds, depending on the hardware Page 26.178.6capabilities. For example, for the Left Hand Node in Figure 4, the first instance of data capturedis 2.4634 (Left Hand Node X), 2.8739 (Left Hand Node Y) and 0.4105 (Left Hand Node Z),representing the 3D position of that particular joint at
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evaluator).# Debriefing. Onboarding. Campus tours. (WEEK) RESEARCH PROJECT EXPERIENCE (VIP TEAMS) PROFESSIONAL DEVELOPMENT (COE USRG)* May Define project objectives, methodology, timeline Welcome breakfast. Orientation. General lab (Week-1) & outcomes. Ethics training courses. safety training. Welcome Bar-B-Q. Ethics. Jun. Research plan due! Overview of metrology/ GRE workshop: What to expect. Seminar: TAMU (Week-2) inspection principles & labs. Safety courses. early admissions program. Jun. Research questions & tasks. Training & practice GRE workshop: Maximize your study time. (Week-3) on relevant laboratory equipment. Seminar: Applying to graduate school
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Measurement Output Adaptive Analog Discovery 2 Q BPF Test Bench FPAA Board Laptop PowerFigure 2: A typical FPAA enabled test setup that can be used for education that uses a an analog Discovery (Digilent),and laptop computer. This system is showing measurements for an Adaptive-resonance bandpass filter circuit. Thesetechniques allow students to quickly transition between a classroom setting to
Exposition, Columbus, OH, 2017.9 H. Gao, Q. He. The interaction of nanoparticles with plasma proteins and the consequent influence onnanoparticles behavior. Expert Opin Drug Deliv.11(3):409-20, 2014.10 T.M. Göppert, R.H. Müller. Adsorption kinetics of plasma proteins on solid lipid nanoparticles for drugtargeting. Int J Pharm.302(1-2):172-86, 2005.11 J.L. Perry, K.G. Reuter, M.P. Kai, K.P. Herlihy, S.W. Jones, J.C. Luft, M. Napier, J.E. Bear, J.M.DeSimone. PEGylated PRINT nanoparticles: the impact of PEG density on protein binding, macrophageassociation, biodistribution, and pharmacokinetics. Nano Lett. 12(10), 5304-10, 2012.12 H. Zou, Z. Wang, M. Feng. Nanocarriers with tunable surface properties to unblock bottlenecks insystemic drug and gene
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then meas-ure the temperature change of heated water pumped through the artificial skin. The rate of heat transfer isproportional to the exposed surface area (q=hA∆T). Yet, students tend to equate surface area with vol-ume, limiting their ability to enhance heat transfer by increasing surface area. Therefore, in addition tostudying the heat transfer across the artificial skin, the students will also create a second skin with an un-branched channel of an approximately equal volume, and then compare the resulting heat exchange. Atthis level, the module can be completed by lowerclassmen in our lower-level Engineering Clinic se-quence. In specialized heat transfer courses (e.g. junior-level Heat Transfer Processes), we will also in-corporate
generate and solve linearcircuit analysis problems, which accepts a rich variety of student inputs. Three tutorials usingthe software have been implemented. Laboratory based studies show a statistically significantand large (~1.21 standard deviation) increase in student learning as a result. Further work willfocus on expansion and completion of this system.AcknowledgmentThis work was supported by the National Science Foundation through the TransformingUndergraduate Education in Science, Technology, Engineering and Mathematics Program underGrant No. DUE-1044497. We thank Daniel Sayre of John Wiley & Sons, Inc. for providing thetextbook copies used in our laboratory experiment.References1 C. D. Whitlatch, Q. Wang, and B. J. Skromme, “Automated
13 Manning, A., Brueck, T., Isbell, M., & Brink, P. (2008). Workforce planning for water utilities - successfulrecruiting, training, and retaining of operators and engineers. Denver, Colorado: AWWA Research Foundation.Retrieved from http://www.waterrf.org/PublicReportLibrary/91237.pdf14 Lacey, M. & Boepple-Swider, T.M. (2008). A regulator’s perspective on workforce issues: Water andwastewater operators. Journal: American Water Works Association, 132-135. Retrieved fromhttp://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&ved=0CD4QFjAB&url=http%3A%2F%2Fwww.workforwater.org%2FWorkArea%2Flinkit.aspx%3FLinkIdentifier%3Did%26ItemID%3D307&ei=kTHmUNCnEcjY2gWQzoGYBA&usg