Factors Affecting Peer Tutoring Programs in Higher Education As Perceived by Administrators

This study examined a) institutional factors that administrators see as facilitating peer tutoring programs and b) institutional factors that administrators see as forming barriers to peer tutoring programs. In addition, a comparison was made of administrators\u27 perceptions based on the following institutional demographic factors: department affiliation, enrollment, highest degree awarded, and Carnegie classification. The data were collected through an electronic survey instrument, Administrative and Faculty Factors that Contribute to the Institutionalization of Peer Tutoring in Higher Education, developed specifically for this study and based on the work of Dr. Anthony Pina (2005, 2008a, 2008b), who studied the institutionalization of distance learning programs and factors that institutionalize programs in higher education; and Dr. Vincent Tinto (1997, 2006-7), an expert on both retention and peer tutoring, who identified a gap in the literature on policies and practices in higher education which enable peer tutoring programs to endure and become institutionalized and in so doing, enable schools to be more successful in increasing student GPAs and retaining students. The sample included 192 administrators and faculty, who were members of Region II in the National Association of Student Personnel Administrators (NASPA), with an interest in and knowledge about academic tutoring programs, and who were involved in their supervision, evaluation, and delivery of services. Most of the respondents (87 percent) were administrators from public institutions, who oversaw peer tutoring programs but were not involved in the day-to-day operations. Results of the study revealed that centralization -- having one department oversee the implementation, supervision, and assessment of peer tutoring; and collaboration -- having regular meetings between Student Affairs and Academic Affairs to plan and access the program, are key to the success of peer tutoring. In addition, the results of this study presented new research on peer tutoring and provided guidance that may be used by administrators and faculty to a) evaluate existing peer tutoring programs to determine strengths, weaknesses, and areas for improvement; b) establish priorities in developing new peer tutoring programs; and c) develop strategies that will lead to the improvement and institutionalization of peer tutoring. The institutionalization factors identified in this study provided a model that may be used as a basis for cooperation between those who oversee the supervision, evaluation, and assessment of peer tutoring (administrators) and those who oversee the day-to-day operations of peer tutoring (faculty)

Research in the effective implementation of guidance computers with large scale arrays Interim report

Functional logic character implementation in breadboard design of NASA modular compute

Density-matrix functional theory of the Hubbard model: An exact numerical study

A density functional theory for many-body lattice models is considered in which the single-particle density matrix is the basic variable. Eigenvalue equations are derived for solving Levy's constrained search of the interaction energy functional W, which is expressed as the sum of Hartree-Fock energy and the correlation energy E_C. Exact results are obtained for E_C of the Hubbard model on various periodic lattices. The functional dependence of E_C is analyzed by varying the number of sites, band filling and lattice structure. The infinite one-dimensional chain and one-, two-, or three-dimensional finite clusters with periodic boundary conditions are considered. The properties of E_C are discussed in the limits of weak and strong electronic correlations, as well as in the crossover region. Using an appropriate scaling we observe a pseudo-universal behavior which suggests that the correlation energy of extended systems could be obtained quite accurately from finite cluster calculations. Finally, the behavior of E_C for repulsive (U>0) and attractive (U<0) interactions are contrasted.Comment: Phys. Rev. B (1999), in pres

Evidence for Excimer Photoexcitations in an Ordered {\pi}-Conjugated Polymer Film

We report pressure-dependent transient picosecond and continuous-wave photomodulation studies of disordered and ordered films of 2-methoxy-5-(2-ethylhexyloxy) poly(para-phenylenevinylene). Photoinduced absorption (PA) bands in the disordered film exhibit very weak pressure dependence and are assigned to intrachain excitons and polarons. In contrast, the ordered film exhibits two additional transient PA bands in the midinfrared that blueshift dramatically with pressure. Based on high-order configuration interaction calculations we ascribe the PA bands in the ordered film to excimers. Our work brings insight to the exciton binding energy in ordered films versus disordered films and solutions. The reduced exciton binding energy in ordered films is due to new energy states appearing below the continuum band threshold of the single strand.Comment: 5.5 pages, 5 figure

Interaction energy functional for lattice density functional theory: Applications to one-, two- and three-dimensional Hubbard models

The Hubbard model is investigated in the framework of lattice density functional theory (LDFT). The single-particle density matrix $\gamma_{ij}$ with respect the lattice sites is considered as the basic variable of the many-body problem. A new approximation to the interaction-energy functional $W[\gamma]$ is proposed which is based on its scaling properties and which recovers exactly the limit of strong electron correlations at half-band filling. In this way, a more accurate description of $W$ is obtained throughout the domain of representability of $\gamma_{ij}$, including the crossover from weak to strong correlations. As examples of applications results are given for the ground-state energy, charge-excitation gap, and charge susceptibility of the Hubbard model in one-, two-, and three-dimensional lattices. The performance of the method is demonstrated by comparison with available exact solutions, with numerical calculations, and with LDFT using a simpler dimer ansatz for $W$. Goals and limitations of the different approximations are discussed.Comment: 25 pages and 8 figures, submitted to Phys. Rev.

Providing awareness, explanation and control of personalized filtering in a social networking site

Social networking sites (SNSs) have applied personalized filtering to deal with overwhelmingly irrelevant social data. However, due to the focus of accuracy, the personalized filtering often leads to “the filter bubble” problem where the users can only receive information that matches their pre-stated preferences but fail to be exposed to new topics. Moreover, these SNSs are black boxes, providing no transparency for the user about how the filtering mechanism decides what is to be shown in the activity stream. As a result, the user’s usage experience and trust in the system can decline. This paper presents an interactive method to visualize the personalized filtering in SNSs. The proposed visualization helps to create awareness, explanation, and control of personalized filtering to alleviate the “filter bubble” problem and increase the users’ trust in the system. Three user evaluations are presented. The results show that users have a good understanding about the filter bubble visualization, and the visualization can increase users’ awareness of the filter bubble, understandability of the filtering mechanism and to a feeling of control over the data stream they are seeing. The intuitiveness of the design is overall good, but a context sensitive help is also preferred. Moreover, the visualization can provide users with better usage experience and increase users’ trust in the system

Data Portraits and Intermediary Topics: Encouraging Exploration of Politically Diverse Profiles

In micro-blogging platforms, people connect and interact with others. However, due to cognitive biases, they tend to interact with like-minded people and read agreeable information only. Many efforts to make people connect with those who think differently have not worked well. In this paper, we hypothesize, first, that previous approaches have not worked because they have been direct -- they have tried to explicitly connect people with those having opposing views on sensitive issues. Second, that neither recommendation or presentation of information by themselves are enough to encourage behavioral change. We propose a platform that mixes a recommender algorithm and a visualization-based user interface to explore recommendations. It recommends politically diverse profiles in terms of distance of latent topics, and displays those recommendations in a visual representation of each user's personal content. We performed an "in the wild" evaluation of this platform, and found that people explored more recommendations when using a biased algorithm instead of ours. In line with our hypothesis, we also found that the mixture of our recommender algorithm and our user interface, allowed politically interested users to exhibit an unbiased exploration of the recommended profiles. Finally, our results contribute insights in two aspects: first, which individual differences are important when designing platforms aimed at behavioral change; and second, which algorithms and user interfaces should be mixed to help users avoid cognitive mechanisms that lead to biased behavior.Comment: 12 pages, 7 figures. To be presented at ACM Intelligent User Interfaces 201

Using an Electronic Monitoring System to Link Offspring Provisioning and Foraging Behavior of a Wild Passerine

Although the costs of parental care are at the foundations of optimal-parental-investment theory, our understanding of the nature of the underlying costs is limited by the difficulty of measuring variation in foraging effort. We simultaneously measured parental provisioning and foraging behavior in a free-living population of Zebra Finches (Taeniopygia guttata) using an electronic monitoring system. We fitted 145 adults with a passive transponder tag and remotely recorded their visits to nest boxes and feeders continuously over a 2-month period. After validating the accuracy of this monitoring system, we studied how provisioning and foraging activities varied through time (day and breeding cycle) and influenced the benefits (food received by the offspring) and costs (interclutch interval) of parental care. The provisioning rates of wild Zebra Finches were surprisingly low, with an average of only one visit per hour throughout the day. This was significantly lower than those reported for this model species in captivity and for most other passerines in the wild. Nest visitation rate only partially explained the amount of food received by the young, with parental foraging activity, including the minimum distance covered on foraging trips, being better predictors. Parents that sustained higher foraging activity and covered more distance during the first breeding attempt took longer to renest. These results demonstrate that in some species matching foraging activity with offspring provisioning may provide a better estimate of the true investment that individuals commit to a reproductive attempt

My friends, editors, algorithms, and I: Examining audience attitudes to news selection

Prompted by the ongoing development of content personalization by social networks and mainstream news brands, and recent debates about balancing algorithmic and editorial selection, this study explores what audiences think about news selection mechanisms and why. Analysing data from a 26-country survey (N=53,314), we report the extent to which audiences believe story selection by editors and story selection by algorithms are good ways to get news online and, using multi-level models, explore the relationships that exist between individuals’ characteristics and those beliefs. The results show that, collectively, audiences believe algorithmic selection guided by a user’s past consumption behaviour is a better way to get news than editorial curation. There are, however, significant variations in these beliefs at the individual level. Age, trust in news, concerns about privacy, mobile news access, paying for news, and six other variables had effects. Our results are partly in line with current general theory on algorithmic appreciation, but diverge in our findings on the relative appreciation of algorithms and experts, and in how the appreciation of algorithms can differ according to the data that drive them. We believe this divergence is partly due to our study’s focus on news, showing algorithmic appreciation has context-specific characteristics