2 resultados para Relational

em DigitalCommons@The Texas Medical Center


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People often use tools to search for information. In order to improve the quality of an information search, it is important to understand how internal information, which is stored in user’s mind, and external information, represented by the interface of tools interact with each other. How information is distributed between internal and external representations significantly affects information search performance. However, few studies have examined the relationship between types of interface and types of search task in the context of information search. For a distributed information search task, how data are distributed, represented, and formatted significantly affects the user search performance in terms of response time and accuracy. Guided by UFuRT (User, Function, Representation, Task), a human-centered process, I propose a search model, task taxonomy. The model defines its relationship with other existing information models. The taxonomy clarifies the legitimate operations for each type of search task of relation data. Based on the model and taxonomy, I have also developed prototypes of interface for the search tasks of relational data. These prototypes were used for experiments. The experiments described in this study are of a within-subject design with a sample of 24 participants recruited from the graduate schools located in the Texas Medical Center. Participants performed one-dimensional nominal search tasks over nominal, ordinal, and ratio displays, and searched one-dimensional nominal, ordinal, interval, and ratio tasks over table and graph displays. Participants also performed the same task and display combination for twodimensional searches. Distributed cognition theory has been adopted as a theoretical framework for analyzing and predicting the search performance of relational data. It has been shown that the representation dimensions and data scales, as well as the search task types, are main factors in determining search efficiency and effectiveness. In particular, the more external representations used, the better search task performance, and the results suggest the ideal search performance occurs when the question type and corresponding data scale representation match. The implications of the study lie in contributing to the effective design of search interface for relational data, especially laboratory results, which are often used in healthcare activities.

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Three rhesus monkeys (Macaca mulatta) and four pigeons (Columba livia) were trained in a visual serial probe recognition (SPR) task. A list of visual stimuli (slides) was presented sequentially to the subjects. Following the list and after a delay interval, a probe stimulus was presented that could be either from the list (Same) or not from the list (Different). The monkeys readily acquired a variable list length SPR task, while pigeons showed acquisition only under constant list length condition. However, monkeys memorized the responses to the probes (absolute strategy) when overtrained with the same lists and probes, while pigeons compared the probe to the list in memory (relational strategy). Performance of the pigeon on 4-items constant list length was disrupted when blocks of trials of different list lengths were imbedded between the 4-items blocks. Serial position curves for recognition at variable probe delays showed better relative performance on the last items of the list at short delays (0-0.5 seconds) and better relative performance on the initial items of the list at long delays (6-10 seconds for the pigeons and 20-30 seconds for the monkeys and a human adolescent). The serial position curves also showed reliable primacy and recency effects at intermediate probe delays. The monkeys showed evidence of using a relational strategy in the variable probe delay task. The results are the first demonstration of relational serial probe recognition performance in an avian and suggest similar underlying dynamic recognition memory mechanisms in primates and avians. ^