Natural categories seem to be comprised of clustered stimuli that contain a myriad of correlated features; birds, for example, tend to fly, have wings, lay eggs, and make nests. Nonetheless, the evidence that people use these correlations during intentional category learning is overwhelmingly negative (Murphy, 2002). People do, however, show evidence of correlational sensitivity during other types of category learning tasks (e.g., feature prediction). The usual explanation is that intentional category learning tasks promote rule use, which discards the correlated feature information; whereas, other types of category learning tasks promote exemplar storage, which preserves correlated feature information. However, all of the intentional category learning tasks employed to examine correlational sensitivity to date have only used deterministic mappings of stimuli to categories (i.e., each stimulus belongs to only one category). The current thesis is concerned primarily with the effects introducing the probabilistic assignment of stimuli to categories on the acquisition of different types of correlational knowledge. If correlational knowledge depends on whether or not people selectively attend to the correlation then probabilistic reinforcement, which is predicted to increase attention shifting (Kruschke & Johansen, 1999), should lead to increased correlational sensitivity. The first paper of this thesis confirms that selective attention provides a way to explain the presence or absence of correlational knowledge in different tasks. However, selective attention models have been unable to account for tasks in which people use the correlation between a non-relevant cue and regions of the category space to switch between the application of multiple rules. This phenomenon, known as knowledge partitioning, is explored in the second paper of this thesis. This thesis also extends the empirical implications of the first two papers to existing research (see included paper 3) and also provides recommendations of how utilize this conceptualization of knowledge for practitioners in the applied setting (see included paper 4). Finally, in addition to increasing attention shifting, probabilistic feedback is also assumed to result in an attenuation of learning over time (Kruschke & Johansen, 1999); the fifth paper in this thesis provides empirical confirmation that people attenuate learning in response to unavoidable error.

This thesis engages with epistemology???s value problem. That is, is knowledge epistemically preferable to true belief? If so, how is that the case? The issue under discussion is whether epistemic justification can account for a value discrepancy between true belief and knowledge. First of all, the contours of the justificatory landscape are presented???in particular, the division between externalist and internalist styles. The thesis then considers whether solely truth-directed justification (which includes externalism) can possibly account for a value unique to knowledge. The preliminary conclusion is that solely truth-directed justification cannot solve the value problem. A discussion of internalism then ensues. The discussion does not focus explicitly on which benefits internalism may offer in terms of value; instead, the focus is on whether internalism qua internalism can solve the value problem. It is concluded that, if internalism is the sole provider of the value of knowledge (above that of true belief), then epistemology must forgo the belief that knowledge is preferable to a Gettiered belief. I do not accept such a concession; therefore, I reject the thesis that internalism exclusively solves the value problem. Throughout the thesis, the importance of externalism to epistemology becomes apparent. This feature invites a reconsideration of the value of externalism (in particular, of reliabilism). The thesis closes by reconsidering the value of reliabilism and concludes that the value problem can be solved, but only by an appeal to externalist justification.

Thesis (M.A.)--Georgia State University, 2006. / Title from title screen. Andrea Scarantino, Tim O'Keefe, George Rainbolt, committee members. Electronic text (38 p.) : digital, PDF file. Description based on contents viewed Apr. 18, 2007. Includes bibliographical references (p. 38).

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 427-434).

This study examined the effects of life experience information on the prediction of domain knowledge. Specifically, it was hypothesized that individuals with a higher level of experience within a domain would have a higher level of domain knowledge, and that attribution of experience (e.g., educational experience, extracurricular experience, etc) would influence the type of domain knowledge assessment on which an individual was most successful (e.g., open-ended scenarios vs. multiple-choice questions). In order to test these hypotheses, participants completed a biodata measure, various ability and non-ability measures, and a set of domain knowledge tests. Hypotheses were evaluated in the context of regressions and structural equation modeling. Results showed that biodata had significant predictive validity for domain knowledge.

Thesis (Ph. D.)--University of Chicago, Committee on Social Thought, June 2001. / Includes bibliographical references. Also available on the Internet.

Texte remanié de : Habilitationsschrift : Philosophie, Pädagogik und Publizistik : Ruhr-Universität Bochum : 2004. / Bibliogr. p. [525]-556.

Thesis (M.A.)--Memorial University of Newfoundland, 2000. / Bibliography: leaves 123-124.

Thèse : Théologie : Helsinki : 1978. / Bibliogr. pp. 195-204.

Thesis (M.A.)--University of Hong Kong.