Evaluating a Doctoral Program in College and University Teaching: A Single Case Study

Evaluating a Doctoral Program in College and University Teaching: A Single Case Study

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Date: August 2006
Creator: Kraus, Janine Stillwell
Description: This study assessed alumni of the College and University Teaching Program at the University of North Texas and how they perceived the training they received. Three hundred sixty alumni holding a college and university teaching degree were surveyed. One hundred forty-two usable questionnaires were returned. A response rate of 39.4 % was achieved. A survey instrument was used to gather alumni perceptions of learning experiences, academics, and professional benefits as a result of earning a doctorate in the major of college and university teaching at the University of North Texas. Alumni were asked their perceptions on the following: 1) the quality of graduate professional education in college and university teaching degree program, 2) whether they thought the goals and objectives of the program were met, and 3) their recommendations regarding the college and university teaching degree program. It is the overall opinion of the alumni that the quality of the graduate education in college and university teaching degree program was high. The majority of alumni indicated that the program should be reinstated and continued and if the program was still available they would recommend it to others.
Contributing Partner: UNT Libraries
Multi-Agent Architecture for Internet Information Extraction and Visualization

Multi-Agent Architecture for Internet Information Extraction and Visualization

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Date: August 2000
Creator: Gollapally, Devender R.
Description: The World Wide Web is one of the largest sources of information; more and more applications are being developed daily to make use of this information. This thesis presents a multi-agent architecture that deals with some of the issues related to Internet data extraction. The primary issue addresses the reliable, efficient and quick extraction of data through the use of HTTP performance monitoring agents. A second issue focuses on how to make use of available data to take decisions and alert the user when there is change in data; this is done with the help of user agents that are equipped with a Defeasible reasoning interpreter. An additional issue is the visualization of extracted data; this is done with the aid of VRML visualization agents. The cited issues are discussed using stock portfolio management as an example application.
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The Cluster Hypothesis: A visual/statistical analysis

The Cluster Hypothesis: A visual/statistical analysis

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Date: May 2000
Creator: Sullivan, Terry
Description: By allowing judgments based on a small number of exemplar documents to be applied to a larger number of unexamined documents, clustered presentation of search results represents an intuitively attractive possibility for reducing the cognitive resource demands on human users of information retrieval systems. However, clustered presentation of search results is sensible only to the extent that naturally occurring similarity relationships among documents correspond to topically coherent clusters. The Cluster Hypothesis posits just such a systematic relationship between document similarity and topical relevance. To date, experimental validation of the Cluster Hypothesis has proved problematic, with collection-specific results both supporting and failing to support this fundamental theoretical postulate. The present study consists of two computational information visualization experiments, representing a two-tiered test of the Cluster Hypothesis under adverse conditions. Both experiments rely on multidimensionally scaled representations of interdocument similarity matrices. Experiment 1 is a term-reduction condition, in which descriptive titles are extracted from Associated Press news stories drawn from the TREC information retrieval test collection. The clustering behavior of these titles is compared to the behavior of the corresponding full text via statistical analysis of the visual characteristics of a two-dimensional similarity map. Experiment 2 is a dimensionality reduction condition, in ...
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The Value of Everything: Ranking and Association with Encyclopedic Knowledge

The Value of Everything: Ranking and Association with Encyclopedic Knowledge

Date: December 2009
Creator: Coursey, Kino High
Description: This dissertation describes WikiRank, an unsupervised method of assigning relative values to elements of a broad coverage encyclopedic information source in order to identify those entries that may be relevant to a given piece of text. The valuation given to an entry is based not on textual similarity but instead on the links that associate entries, and an estimation of the expected frequency of visitation that would be given to each entry based on those associations in context. This estimation of relative frequency of visitation is embodied in modifications to the random walk interpretation of the PageRank algorithm. WikiRank is an effective algorithm to support natural language processing applications. It is shown to exceed the performance of previous machine learning algorithms for the task of automatic topic identification, providing results comparable to that of human annotators. Second, WikiRank is found useful for the task of recognizing text-based paraphrases on a semantic level, by comparing the distribution of attention generated by two pieces of text using the encyclopedic resource as a common reference. Finally, WikiRank is shown to have the ability to use its base of encyclopedic knowledge to recognize terms from different ontologies as describing the same thing, and thus ...
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Usability of a Keyphrase Browsing Tool Based on a Semantic Cloud Model

Usability of a Keyphrase Browsing Tool Based on a Semantic Cloud Model

Date: August 2006
Creator: Johnston, Onaje Omotola
Description: The goal of this research was to facilitate the scrutiny and utilization of Web search engine retrieval results. I used a graphical keyphrase browsing interface to visualize the conceptual information space of the results, presenting document characteristics that make document relevance determinations easier.
Contributing Partner: UNT Libraries
Accessing Information on the World Wide Web: Predicting Usage Based on Involvement

Accessing Information on the World Wide Web: Predicting Usage Based on Involvement

Date: May 2003
Creator: Langford, James David
Description: Advice for Web designers often includes an admonition to use short, scannable, bullet-pointed text, reflecting the common belief that browsing the Web most often involves scanning rather than reading. Literature from several disciplines focuses on the myriad combinations of factors related to online reading but studies of the users' interests and motivations appear to offer a more promising avenue for understanding how users utilize information on Web pages. This study utilized the modified Personal Involvement Inventory (PII), a ten-item instrument used primarily in the marketing and advertising fields, to measure interest and motivation toward a topic presented on the Web. Two sites were constructed from Reader's Digest Association, Inc. online articles and a program written to track students' use of the site. Behavior was measured by the initial choice of short versus longer versions of the main page, the number of pages visited and the amount of time spent on the site. Data were gathered from students at a small, private university in the southwest part of the United States to answer six hypotheses which posited that subjects with higher involvement in a topic presented on the Web and a more positive attitude toward the Web would tend to select ...
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A multi-dimensional entropy model of jazz improvisation for music information retrieval.

A multi-dimensional entropy model of jazz improvisation for music information retrieval.

Date: December 2005
Creator: Simon, Scott J.
Description: Jazz improvisation provides a case context for examining information in music; entropy provides a means for representing music for retrieval. Entropy measures are shown to distinguish between different improvisations on the same theme, thus demonstrating their potential for representing jazz information for analysis and retrieval. The calculated entropy measures are calibrated against human representation by means of a case study of an advanced jazz improvisation course, in which synonyms for "entropy" are frequently used by the instructor. The data sets are examined for insights in music information retrieval, music information behavior, and music representation.
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Measuring the accuracy of four attributes of sound for conveying changes in a large data set.

Measuring the accuracy of four attributes of sound for conveying changes in a large data set.

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Date: May 2003
Creator: Holmes, Jason
Description: Human auditory perception is suited to receiving and interpreting information from the environment but this knowledge has not been used extensively in designing computer-based information exploration tools. It is not known which aspects of sound are useful for accurately conveying information in an auditory display. An auditory display was created using PD, a graphical programming language used primarily to manipulate digital sound. The interface for the auditory display was a blank window. When the cursor is moved around in this window, the sound generated would changed based on the underlying data value at any given point. An experiment was conducted to determine which attribute of sound most accurately represents data values in an auditory display. The four attributes of sound tested were frequency-sine waveform, frequency-sawtooth waveform, loudness and tempo. 24 subjects were given the task of finding the highest data point using sound alone using each of the four sound treatments. Three dependent variables were measured: distance accuracy, numeric accuracy, and time on task. Repeated measures ANOVA procedures conducted on these variables did not rise to the level of statistical significance (α=.05). None of the sound treatments was more accurate than the other as representing the underlying data values. 52% ...
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Relevance Thresholds: A Conjunctive/Disjunctive Model of End-User Cognition as an Evaluative Process

Relevance Thresholds: A Conjunctive/Disjunctive Model of End-User Cognition as an Evaluative Process

Date: December 2000
Creator: Greisdorf, Howard F.
Description: This investigation identifies end-user cognitive heuristics that facilitate judgment and evaluation during information retrieval (IR) system interactions. The study extends previous research surrounding relevance as a key construct for representing the value end-users ascribe to items retrieved from IR systems and the perceived effectiveness of such systems. The Lens Model of user cognition serves as the foundation for design and interpretation of the study; earlier research in problem solving, decision making, and attitude formation also contribute to the model and analysis. A self reporting instrument collected evaluative responses from 32 end-users related to 1432 retrieved items in relation to five characteristics of each item: topical, pertinence, utility, systematic, and motivational levels of relevance. The nominal nature of the data collected led to non-parametric statistical analyses that indicated that end-user evaluation of retrieved items to resolve an information problem at hand is most likely a multi-stage process. That process appears to be a cognitive progression from topic to meaning (pertinence) to functionality (use). Each step in end-user evaluative processing engages a cognitive hierarchy of heuristics that includes consideration (of appropriate cues), differentiation (the positive or negative aspects of those cues considered), and aggregation (the combination of differentiated cue aspects needed to ...
Contributing Partner: UNT Libraries
Perceived features and similarity of images: An investigation into their relationships and a test of Tversky's contrast model.

Perceived features and similarity of images: An investigation into their relationships and a test of Tversky's contrast model.

Date: May 2005
Creator: Rorissa, Abebe
Description: The creation, storage, manipulation, and transmission of images have become less costly and more efficient. Consequently, the numbers of images and their users are growing rapidly. This poses challenges to those who organize and provide access to them. One of these challenges is similarity matching. Most current content-based image retrieval (CBIR) systems which can extract only low-level visual features such as color, shape, and texture, use similarity measures based on geometric models of similarity. However, most human similarity judgment data violate the metric axioms of these models. Tversky's (1977) contrast model, which defines similarity as a feature contrast task and equates the degree of similarity of two stimuli to a linear combination of their common and distinctive features, explains human similarity judgments much better than the geometric models. This study tested the contrast model as a conceptual framework to investigate the nature of the relationships between features and similarity of images as perceived by human judges. Data were collected from 150 participants who performed two tasks: an image description and a similarity judgment task. Qualitative methods (content analysis) and quantitative (correlational) methods were used to seek answers to four research questions related to the relationships between common and distinctive features ...
Contributing Partner: UNT Libraries
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