The emergence of new trends sometimes carries the risk that established, well-proven concepts rooted in other disciplines are not properly integrated into new approaches. As Learning Analytics seems to be evolving into a highly multidisciplinary field, we would like to demonstrate the importance of embedding classic theories and concepts into a Learning Analytics, system-data-driven setting. Our results confirm that classical factors that are operationalized with the help of system-generated data outperform more recent survey-based models. Therefore, we want to stress the point that system-generated data should not be left behind in the quickly evolving field of Learning Analytics.

Magister Educationis (Adult Learning and Global Change) - MEd(AL) / Conceptualised within Habermasian critical theory, the conceptual framework includes concepts such as domination, emancipation and emancipatory education, and frames RPL as emancipation. Recognition of prior learning is promoted by the South African government as an instrument for access and redress. This research paper focuses on an investigation into the benefits of the implementation of RPL policies and practices in the policing sector. Findings reveal that the participants in the study who are employed in the policing sector enjoyed a wide range of emancipatory benefits, including access to formal academic programmes. Furthermore, these programmes enabled historically disadvantaged staff to gain formal qualifications which in turn provided access to higher salaries and promotions. Explaining the latter as redress, I argue that RPL is a form of emancipation that has liberated disadvantaged staff from apartheid discrimination and domination.

Shattered assumptions theory posits that each individual has a core set of assumptions about the world and the self, often termed the assumptive world which includes: the world is a benevolent place, the world is meaningful, and the self is worthy. Experiencing a traumatic event is believed to lead individuals to question these assumptions in light of the new contradictory information that causes the assumptive world to shatter, leaving the individual to rebuild a more negative perception of the world and themselves. This rebuilding of a fragile new set of core beliefs is believed to be a cause of posttraumatic stress disorder (PTSD) symptoms. Although shattered assumptions theory has been widely accepted in the field of trauma psychology, the shattering of the assumptive world has not been empirically supported due to measurement issues and poor research designs. The current study implemented a prospective design to assess a new measure of the individual’s assumptive world when there is an intervening trauma. In a college sample (N = 336), individuals who experienced a traumatic event over the course of the semester (n = 40) evidenced decreases in optimism in their assumptive worlds, in comparison to individuals who did not experience a traumatic event. The results suggest there is a limited shattering of the assumptive world for those who experienced a traumatic event. Applications, limitations and future directions are discussed.

A major problem associated with Bayesian estimation is selecting the prior distribution. The more recent literature on the selection of the prior is reviewed. Very little of a general nature on the selection of the prior is formed in the literature except for non-informative priors. This class of priors is seen to have limited usefulness. A method of selecting an informative prior is generalized in this thesis to include estimation of several parameters using a multivariate prior distribution. The concepts required for quantifying prior information is based on intuitive principles. In this way, it can be understood and controlled by the decision maker (i.e., those responsible for the consequences) rather than analysts. The information required is: (1) prior point estimates of the parameters being estimated and (2) an expression of the desired influence of the prior relative to the present data in determining the parameter estimates (e.g., item (2) implies twice as much influence as the data). These concepts (point estimates and influence) may be used equally with subjective or quantitative prior information.

Indiana University-Purdue University Indianapolis (IUPUI) / Cluster randomization is frequently used in clinical trials for convenience of inter ventional implementation and for reducing the risk of contamination. The opera tional convenience of cluster randomized trials, however, is gained at the expense of reduced analytical power. Compared to individually randomized studies, cluster randomized trials often have a much-reduced power. In this dissertation, I consider ways of enhancing analytical power with historical trial data. Specifically, I introduce a hierarchical Bayesian model that is designed to incorporate available information from previous trials of the same or similar interventions. Operationally, the amount of information gained from the previous trials is determined by a Kullback-Leibler divergence measure that quantifies the similarity, or lack thereof, between the histor ical and current trial data. More weight is given to the historical data if they more closely resemble the current trial data. Along this line, I examine the Type I error rates and analytical power associated with the proposed method, in comparison with the existing methods without utilizing the ancillary historical information. Similarly, to design a cluster randomized trial, one could estimate the power by simulating trial data and comparing them with the historical data from the published studies. Data analytical and power simulation methods are developed for more general situations of cluster randomized trials, with multiple arms and multiple types of data following the exponential family of distributions. An R package is developed for practical use of the methods in data analysis and trial design.

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Establishing relationships between a learner's prior knowledge and any new concepts he or she will be expected to learn is an important instructional activity. Learning objects are often devoid of such activities in an attempt to maintain their conciseness and reusability in a variety of instructional contexts. The purpose of this study was to examine the efficacy of using questioning as a prior knowledge activation strategy in learning objects. Previous research on the use prior knowledge activation strategies supports their effectiveness in helping to improve learner retention. Approaches such as questioning, advance organizers, and group discussions are examples of techniques used in previous studies. Participants enrolled in a Navy engineering curriculum were randomly assigned to two groups (experimental and comparison). The experimental group was exposed to a prior knowledge activation component at the start of session I, while the comparison group received no treatment. Participants in both groups were tested at three different times during the course of the study- the pretest, at the start of session 1, posttest I, at the conclusion of session1, and posttest II, during session 2. The findings indicate that the prior knowledge activation strategy did not result in statistically significant differences between the levels of retention gained by the experimental and comparison groups. Due to administrative constraints experienced during the course of the study, statistical power was not achieved due to an insufficiently sized sample. Potential limitations and implications for future research directions are described.

In the dynamic global environment of today, understanding how travelers acquire information is important for marketing management decisions (Srinivasan 1990; Wilkie and Dickson 1985). For destination marketing managers, understanding information search behavior of travelers is crucial for designing effective marketing communication campaigns because information search represents the primary stage at which marketing can provide information and influence travelers' vacation decisions. Therefore, conceptual and empirical examinations of tourist information search behavior have a long tradition in tourism marketing literature (Etzel and Wahlers, 1985; Fodness and Murray, 1997, 1998, 1999; Perdue, 1985; Schul and Crompton, 1983; Snepenger and Snepenger 1993; Woodside and Ronkainen, 1980). Even though several studies examined travelers information search behavior and the factors that are likely to affect it, they all examined travelers' prior product knowledge as a uni-dimensional construct, most often referred to as destination familiarity or previous trip experiences (Woodside and Ronkainen, 1980). However, consumer behavior literature suggests that the prior product knowledge is not a uni-dimensional construct (Alba and Hutchinson). Alba and Hutchinson (1987) propose that prior product knowledge has two major components, familiarity and expertise, and cannot be measured by a single indicator. In addition, in tourism, little research has been done on the factors that are likely to influence travelers' prior product knowledge and, therefore, their information search behavior. The purpose of this study is to examine travelers' information search behavior by studying the effects of travelers' familiarity and expertise on their information search behavior and identifying the factors that are likely to influence travelers' familiarity and expertise and their information search behavior. A travelers' information search behavior model and a measurement instrument to assess the constructs of the model were designed for the use of this study. The model proposed that the type of information search (internal and/or external) that is likely to be utilized will be influenced by travelers' familiarity and expertise. In addition, travelers' involvement, learning, prior visits and cost of information search are proposed to influence travelers' familiarity and their information search behavior. Even though a very complex travelers' information search behavior model was proposed, only the effects of travelers' prior product knowledge (familiarity and expertise) on travelers' information search behavior were empirically tested due to the complex nature of the model. First the proposed measurement scales were pretested on 224 consumers. After making sure that proposed measures of each construct were valid and reliable, a survey of 470 consumers of travel/tourism services who reside in Virginia was conducted. Structural Equation Modeling (i.e., LISREL) analysis was performed to test the fit of the model. Results of the study confirmed that travelers' prior product knowledge has two components, familiarity and expertise, and expertise is a function of familiarity. Both familiarity and expertise affect travelers' information search behavior. While the effect of familiarity on internal search is positive and on external search is negative, the effect of expertise on internal search is negative and on external search is positive. The study identified a U-shaped relationship between travelers' prior product knowledge and external information search. At early stages of learning (low familiarity), travelers are likely to rely on external information sources to make their vacation decisions. As their prior product knowledge (familiarity) increases they tend to make their vacation decisions based on what is in their memory, therefore, reliance on external information sources decreases. However, as they learn more (become experts), they realize that they need more detailed information to make their vacation decisions. As a result, they start searching for additional external information to make their vacation decisions. / Ph. D.

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