<p> The web has become more than a supplementary information resource but a valuable and pervasive tool for nearly all aspects of daily life including social and community participation, health promotion, creative pursuits, education, and employment opportunity. However, the web is not yet easily accessible to all people, particularly those with cognitive disabilities who encounter many challenges with access and use of the web including limited accessibility of online content and difficulty with content comprehension. Furthermore, little is documented about how individuals with cognitive disabilities who currently use the web are overcoming or being inhibited by these challenges. Much of what is documented is anecdotal or generalized as broad technical guidance rather than providing methods to empower individual end users. This research explores which websites people with cognitive disabilities use and do not use and what challenges and successes they encounter with those websites. We developed the SimpleWebAnywhere tool to address the above research needs and serve as a technology probe to determine how content simplification affects web use by people with cognitive disabilities. We explored personalizable content transformation techniques, including advertisement removal, content extraction, and text to speech, to make webpages easier to use and comprehend. We found that many people with cognitive disabilities frequently access the web for long periods of time despite popular opinion to the contrary. Web access is preferred via mobile platforms, such as smartphones and tablet computers. Users had a strong preference for entertainment content largely comprised of images, videos, and games but did not necessarily have difficulty using or understanding long, complex textual content. An intercommunity approach of combining existing open source software to provide personalized content manipulations was found to be an effective method to improve web accessibility for people with cognitive disabilities.</p>

<p> This dissertation presents a Bayesian generative modeling approach for complex dynamical systems for emotion-interaction patterns within multivariate data collected in social psychology studies. While dynamical models have been used by social psychologists to study complex psychological and behavior patterns in recent years, most of these studies have been limited by using regression methods to fit the model parameters from noisy observations. These regression methods mostly rely on the estimates of the derivatives from the noisy observation, thus easily result in overfitting and fail to predict future outcomes. A Bayesian generative model solves the problem by integrating the prior knowledge of where the data comes from with the observed data through posterior distributions. It allows the development of theoretical ideas and mathematical models to be independent of the inference concerns. Besides, Bayesian generative statistical modeling allows evaluation of the model based on its predictive power instead of the model residual error reduction in regression methods to prevent overfitting in social psychology data analysis. </p><p> In the proposed Bayesian generative modeling approach, this dissertation uses the State Space Model (SSM) to model the dynamics of emotion interactions. Specifically, it tests the approach in a class of psychological models aimed at explaining the emotional dynamics of interacting couples in committed relationships. The latent states of the SSM are composed of continuous real numbers that represent the level of the true emotional states of both partners. One can obtain the latent states at all subsequent time points by evolving a differential equation (typically a coupled linear oscillator (CLO)) forward in time with some known initial state at the starting time. The multivariate observed states include self-reported emotional experiences and physiological measurements of both partners during the interactions. To test whether well-being factors, such as body weight, can help to predict emotion-interaction patterns, We construct functions that determine the prior distributions of the CLO parameters of individual couples based on existing emotion theories. Besides, we allow a single latent state to generate multivariate observations and learn the group-shared coefficients that specify the relationship between the latent states and the multivariate observations. </p><p> Furthermore, we model the nonlinearity of the emotional interaction by allowing smooth changes (drift) in the model parameters. By restricting the stochasticity to the parameter level, the proposed approach models the dynamics in longer periods of social interactions assuming that the interaction dynamics slowly and smoothly vary over time. The proposed approach achieves this by applying Gaussian Process (GP) priors with smooth covariance functions to the CLO parameters. Also, we propose to model the emotion regulation patterns as clusters of the dynamical parameters. To infer the parameters of the proposed Bayesian generative model from noisy experimental data, we develop a Gibbs sampler to learn the parameters of the patterns using a set of training couples. </p><p> To evaluate the fitted model, we develop a multi-level cross-validation procedure for learning the group-shared parameters and distributions from training data and testing the learned models on held-out testing data. During testing, we use the learned shared model parameters to fit the individual CLO parameters to the first 80% of the time points of the testing data by Monte Carlo sampling and then predict the states of the last 20% of the time points. By evaluating models with cross-validation, one can estimate whether complex models are overfitted to noisy observations and fail to generalize to unseen data. I test our approach on both synthetic data that was generated by the generative model and real data that was collected in multiple social psychology experiments. The proposed approach has the potential to model other complex behavior since the generative model is not restricted to the forms of the underlying dynamics.</p>

<p>The purpose of this dissertation is to provide a rationale and framework for a systemic praxis for Marriage and Family Therapists (MFTs) that can be utilized to increase possibilities for therapeutic change. In a time in which &ldquo;common factors&rdquo; are valued and MFTs generally consider themselves eclectic or integrative, there is a need for therapists to learn to cultivate a systemic praxis that allows them to effectively &ldquo;juggle&rdquo; all of the elements of and responsibilities inherent in the therapeutic situation. Drawing from cybernetics, systemic theory, and radical constructivism, I develop a systemic praxis for therapists which incorporates systemic ways of perceiving and engaging, improvisation, and Recursive Frame Analysis (Keeney, 1990). I develop a theory regarding the nature, impact, and utilization of what I call &ldquo;systemic sensing&rdquo; and ways of engaging that go beyond adherence to various aspects of therapy models. Systemic Sensing constitutes ways of seeing, hearing, sensing, and intuiting that therapists can utilize to co-create, with their clients, opportunities for therapeutic transformation. </p><p> In this dissertation, I extend Ray Ison&rsquo;s (2010) framework for systemic practice to the practice of marriage and family therapy. Ison (2010) provided a metaphor of the systems practitioner as a juggler. MFTs can improve their practice by learning to juggle Maturana&rsquo;s (2002, 2008) notions of languaging and emotioning, Bateson&rsquo;s (1972; 1979) notion of distinguishing, and Ison&rsquo;s (2010) notion of naming; the practice of and responsibilities inherent in systemic sensing; and the tailoring and contextualizing of the practice of therapy to individual clients and moments in time. </p><p> What is needed in the field of marriage and family therapy is a way of envisioning and practicing therapy that increases possibilities for change. I call for a reformation that will shift the emphasis in marriage and family therapy from model-based training into more holistic, flexible, and systemic interpersonal practices that are based on inspiring therapeutic change and healing. </p>

<p> According to the U.S. Department of Education, the 2012-2013 national high school completion rate for Latino (75%), African American (73%), American Indian (70%), and limited English proficient (63%) students increased slightly compared to the 2011 national graduation data. While the national trend shows a one percentage point gain in the overall high school graduation rate across all subgroups, the numbers for African Americans, Latinos and other ethnic groups far trail that of their White (87%) and Asian (89%) peers. It is also far more likely that ethnic groups trailing in high school completion rates live in economically disadvantaged communities that are plagued with the disparate effects of poverty, such as single-family households, poor nutrition, and community safety concerns. As a result, there has been an increase in local and national conversations about how to best amend inequitable educational outcomes for these groups of students.</p><p> The conceptual framework for this study is oriented around systems thinking, race, empowerment theory, and community schools and partnerships. More specifically, this study sought to explore systems thinking and opportunities that schools can explore to eradicate the current negative racialized outcomes for African American, Latino, other ethnic minorities, and socially disadvantaged students. The one-year study took place at Roses in Concrete Community School, a newly designed charter school located in Oakland, California.</p><p> Findings suggest that during its first year implementation, the school&rsquo;s leadership team and staff focused primarily on supporting students and families by (a) establishing a foundation of responding to basic needs, (b) partnering with community organizations, universities, and activists to provide additional school and community supports, (c) analyzing the system that produces the current outcomes with the intention of not reproducing inequities, and (d) empowering students and families to have a voice and increase their sense of agency.</p>

<p> News organizations, non-profits, and even government agencies use information graphics to advertise and communicate their messages. Data visualizations are used heavily in these graphics, but they also often incorporate unusual design elements to help catch viewers&rsquo; eyes. In the struggle to rise to the top of the crowd, the data visualizations in infographics are often embellished with additions and modifications to the raw chart. The general consensus is that these embellishments can make charts less effective at communicating information, but most of them have never been tested to see if this is true. This work examines the factors in bar, pie, and donut charts that affect our perception of the charts.</p><p> I approach this in two different ways, both using a series of surveys on Mechanical Turk. The work on pie charts examines the individual contribution of arc-length, angle, and area variables so that embellishments may be evaluated based on their use of visual variables. The bar chart work examines some of the most common embellishments designers make to bar charts. This approach allows the isolated study of embellishments to determine which hinder or contribute the most to our perception of charts. I conclude with concrete recommendations based on the findings of the studies. My results show that conventional wisdom about how these charts are perceived is not always correct, and some types of embellishments are harmful while others have virtually no effect.</p>

<p> Many users of smart mobile devices (SMDs) are unaware that personally identifiable information (PII) is being sent from mobile applications to digital corporations for processing and use by third-parties. The severity of the PII disclosed includes location tracking, health status, friends lists, or detailed financial transactions, which increasingly involve SMDs. A total of 407 participants recruited from the eLancing ecosystem were randomly assigned to a scenario-based experimental survey to determine the extent that level-of-effort (LOE) moderated the privacy calculus. The privacy calculus is subjective based on an individual&rsquo;s own perceived privacy risks and perceived benefits; however, it is also subject to a level of engagement by an individual in the amount of effort the individual is willing to apply to the problem. Actively open-minded thinking (AOT) was used as a proxy for LOE. It has been shown that, independent of cognitive ability, AOT plays an important role in predicting the degree to which individuals reason rationally, independent of immediate experience, mood, or affect, and is a measure of good thinking. Partial least squares structural equation modeling was conducted, and results show that users LOE moderates the privacy calculus. Participants that use high-effort processing perceived risks to be much higher when trusting beliefs are low and perceive benefits to be lower when perceived risks are high. In the context of health data compared to location data, high-effort respondents perceive benefits to be lower than low-level processors when perceived risk is high but much higher than low-effort respondents when the perceived risks are low. In addition, this study provided a replication of prior findings that privacy concern has a third-order conceptualization using measures adapted for use with the Enhanced-APCO macro-model within the context of location-based and health-based mobile applications that have theoretical and practical application in the field of information privacy.</p><p>

Thesis (Ph.D.)--Indiana University, Dept. of Computer Science, 2009. / Title from PDF t.p. (viewed on Feb. 10, 2010). Source: Dissertation Abstracts International, Volume: 70-05, Section: B, page: 3009. Adviser: David B. Leake.

Thesis (Ph.D.)--Indiana University, Computer Science and Cognitive Science, 2007. / Title from PDF t.p. (viewed Nov. 11, 2008). Source: Dissertation Abstracts International, Volume: 68-09, Section: B, page: 6350. Advisers: Robert L. Goldstone; Michael Gasser.

Thesis (Ph. D.)--Westfälische Wilhelms-Universität zu Münster, 1974. / Vita. Includes bibliographical references (p. 327-338).

Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.