A National Analysis Of Computer And Information Sciences Faculty Workloads: Examining Teaching, Research, Service, And Administration

The professoriate is a foundational component of higher education and impacts program success.  This study describes computer and information sciences (CIS) faculty workloads empirically.  The role of faculty in higher education is characterized in terms of research, teaching, service, and administration.  Specifically, this study examines the relationships of faculty individual characteristics, occupational characteristics, and organizational context across the percent of effort allocations in regards to workload.  The data used for this study was the National Center for Education Statistics most recent examination of the faculty, the 1999 National Survey of Postsecondary Faculty (NSOFP-99) data.  Specifically, this study describes CIS faculty on selected individual characteristics, occupational characteristics, and institutional context; describe the actually and preferred effort allocations of CIS faculty; determines if significant differences exists between the actually and preferred effort allocations in workload of CIS faculty; determines if a relationship exists between the actual allocation of workload of CIS faculty and individual characteristics, occupational characteristics, and instructional context.  Data analysis was conducted using SPSS. To answer the research questions means, standard deviations, frequencies, percents, correlations, and t-tests were implemented.  This study found the majority of faculty workload is spent on teaching and the majority of program and faculty evaluation is based on research.  The study suggests that more research is needed to develop a better picture of CIS faculty in terms of workloads

An Email Attachment is Worth a Thousand Words, or Is It?

There is an extensive body of research on Social Network Analysis (SNA) based on the email archive. The network used in the analysis is generally extracted either by capturing the email communication in From, To, Cc and Bcc email header fields or by the entities contained in the email message. In the latter case, the entities could be, for instance, the bag of words, url's, names, phones, etc. It could also include the textual content of attachments, for instance Microsoft Word documents, excel spreadsheets, or Adobe pdfs. The nodes in this network represent users and entities. The edges represent communication between users and relations to the entities. We suggest taking a different approach to the network extraction and use attachments shared between users as the edges. The motivation for this is two-fold. First, attachments represent the "intimacy" manifestation of the relation's strength. Second, the statistical analysis of private email archives that we collected and Enron email corpus shows that the attachments contribute in average around 80-90% to the archive's disk-space usage, which means that most of the data is presently ignored in the SNA of email archives. Consequently, we hypothesize that this approach might provide more insight into the social structure of the email archive. We extract the communication and shared attachments networks from Enron email corpus. We further analyze degree, betweenness, closeness, and eigenvector centrality measures in both networks and review the differences and what can be learned from them. We use nearest neighbor algorithm to generate similarity groups for five Enron employees. The groups are consistent with Enron's organizational chart, which validates our approach.Comment: 12 pages, 4 figures, 7 tables, IML'17, Liverpool, U

Using ePortfolios to Support Student Writers

This session explores how the use of eportfolios can support students’ writing development. An eportfolio initiative director, writing center director, composition professor, and literature professor discuss the use of eportfolios in various contexts

Counterion Condensation on Spheres in the Salt-free Limit

A highly-charged spherical colloid in a salt-free environment exerts such a powerful attraction on its counterions that a certain fraction condenses onto the surface of a particle. The degree of condensation depends on the curvature of the surface. So, for instance, condensation is triggered on a highly-charged sphere only if the radius exceeds a certain critical radius \collrad^{*}. \collrad^{*} is expected to be a simple function of the volume fraction of particles. To test these predictions, we prepare spherical particles which contain a covalently-bound ionic liquid, which is engineered to dissociate efficiently in a low-dielectric medium. By varying the proportion of ionic liquid to monomer we synthesise nonpolar dispersions of highly-charged spheres which contain essentially no free co-ions. The only ions in the system are counterions generated by the dissociation of surface-bound groups. We study the electrophoretic mobility of this salt-free system as a function of the colloid volume fraction, the particle radius, and the bare charge density and find evidence for extensive counterion condensation. At low electric fields, we observe excellent agreement with Poisson-Boltzmann predictions for counterion condensation on spheres. At high electric fields however, where ion advection is dominant, the electrophoretic mobility is enhanced significantly which we attribute to hydrodynamic stripping of the condensed layer of counterions from the surface of the particle.Comment: 13 pages, 9 figures and two table

Optimizing Observational Strategy for Future Fgas Constraints

The Planck cluster catalog is expected to contain of order a thousand galaxy clusters, both newly discovered and previously known, detected through the Sunyaev-Zeldovich effect over the redshift range 0 < z < 1. Follow-up X-ray observations of a dynamically relaxed sub-sample of newly discovered Planck clusters will improve constraints on the dark energy equation-of-state found through measurement of the cluster gas mass fraction fgas. In view of follow-up campaigns with XMM-Newton and Chandra, we determine the optimal redshift distribution of a cluster sample to most tightly constrain the dark energy equation of state. The distribution is non-trivial even for the standard w0-wa parameterization. We then determine how much the combination of expected data from the Planck satellite and fgas data will be able to constrain the dark energy equation-of-state. Our analysis employs a Markov Chain Monte Carlo method as well as a Fisher Matrix analysis. We find that these upcoming data will be able to improve the figure-of-merit by at least a factor two.Comment: 11 pages, 8 figure

Perceptions of Mainland Chinese Students Toward Obtaining Higher Education in the United States

Since 1978, when the first group of 50 mainland Chinese students came to the United States for education, increasing numbers of mainland Chinese students have come to the United States to get a degree (Lampton, Madancy & Williams, 1986). In 2009, China surpassed India, becoming the largest source country of international students in the United States, and since then, China has the most international students seeking education in the United States (Open Doors Data, 2015). The purpose of this Q methodology study is to explore personal perspectives of mainland Chinese students on the value of getting a degree in the United States. Data analysis grouped similar viewpoints. Based on data from ten mainland Chinese students, we categorized three different groups of mainland Chinese students: job and education group, education group, and migration group

Power to the people: a beginner’s tutorial to power analysis using jamovi

Authors have highlighted for decades that sample size justification through power analysis is the exception rather than the rule. Even when authors do report a power analysis, there is often no justification for the smallest effect size of interest, or they do not provide enough information for the analysis to be reproducible. We argue one potential reason for these omissions is the lack of a truly accessible introduction to the key concepts and decisions behind power analysis. In this tutorial targeted at complete beginners, we demonstrate a priori and sensitivity power analysis using jamovi for two independent samples and two dependent samples. Respectively, these power analyses allow you to ask the questions: “How many participants do I need to detect a given effect size?”, and “What effect sizes can I detect with a given sample size?”. We emphasise how power analysis is most effective as a reflective process during the planning phase of research to balance your inferential goals with your resources. By the end of the tutorial, you will be able to understand the fundamental concepts behind power analysis and extend them to more advanced statistical models

Cosmic Microwave Background Polarization

Cosmic microwave background (CMB) anisotropy is our richest source of cosmological information; the standard cosmological model was largely established thanks to study of the temperature anisotropies. By the end of the decade, the Planck satellite will close this important chapter and move us deeper into the new frontier of polarization measurements. Numerous ground--based and balloon--borne experiments are already forging into this new territory. Besides providing new and independent information on the primordial density perturbations and cosmological parameters, polarization measurements offer the potential to detect primordial gravity waves, constrain dark energy and measure the neutrino mass scale. A vigorous experimental program is underway worldwide and heading towards a new satellite mission dedicated to CMB polarization.Comment: Review given at TAUP 2005; References added; Additional reference