234 resultados para Praise
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"Composed for the Worcester Triennial Musical Festival, 1902."
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Appended: Remarks on the Essays on the principles of morality and natural religion, in a letter to a minister of the Church of Scotland: by the Revrend Mr. Jonathan Edwards ... (A criticism of Lord Kames' Essays ... p. [183]-190.)
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Appended: Remarks on the Essays on the principles of morality and natural religion, in a letter to a minister of the Church of Scotland: by the Reverend Mr. Jonathan Edwards ... (A criticism of Lord Kames' Essays ... p. [183]-190.)
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Mode of access: Internet.
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Wright I, 1767.
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Mode of access: Internet.
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Albert Kahn, architect. Building completed 1924. Named James Burrill Angell Hall. Sometimes called Literary College. Interior ceiling decorations: Di Lorenzo Studios, N.Y. Upper right hand corner torn off. On image in lower right corner: No 1.
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Mode of access: Internet.
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This study extends previous media equation research, which showed that the effects of flattery from a computer can produce the same general effects as flattery from humans. Specifically, the study explored the potential moderating effect of experience on the impact of flattery from a computer. One hundred and fifty-eight students from the University of Queensland voluntarily participated in the study. Participants interacted with a computer and were exposed to one of three kinds of feedback: praise (sincere praise), flattery (insincere praise), or control (generic feedback). Questionnaire measures assessing participants' affective state. attitudes and opinions were taken. Participants of high experience, but not low experience, displayed a media equation pattern of results, reacting to flattery from a computer in a manner congruent with peoples' reactions to flattery from other humans. High experience participants tended to believe that the computer spoke the truth, experienced more positive affect as a result of flattery, and judged the computer's performance more favourably. These findings are interpreted in light of previous research and the implications for software design in fields such as entertainment and education are considered. (C) 2004 Elsevier Ltd. All rights reserved.
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In an audio cueing system, a teacher is presented with randomly spaced auditory signals via tape recorder or intercom. The teacher is instructed to praise a child who is on-task each time the cue is presented. In this study, a baseline was obtained on the teacher's praise rate and the children's on-task behaviour in a Grade 5 class of 37 students. Children were then divided into high, medium and low on-task groups. Followinq baseline, the teacher's praise rate and the children's on-task behaviour were observed under the following successively implemented conditions: (l) Audio Cueing 1: Audio cueing at a rate of 30 cues per hour was introduced into the classroom and remained in effect during subsequent conditions. A group of consistently low on-task children were delineated. (2) Audio Cueing Plus 'focus praise package': Instructions to direct two-thirds o£ the praise to children identified by the experimenter (consistently low on-task children), feedback and experimenter praise for meeting or surpassing the criterion distribution of praise ('focus praise package') were introduced. (3) Audio Cueing 2: The 'focus praise package' was removed. (4) Audio Cueing Plus 'increase praise package': Instructions to increase the rate of praise, feedback and experimenter praise for improved praise rates ('increase praise package') were introduced. The primary aims of the study were to determine the distribution of praise among hi~h, medium and low on-task children when audio cueinq was first introduced and to investigate the effect of the 'focus praise package' on the distribution of teacher praise. The teacher distributed her praise evenly among the hiqh, medium and low on-task groups during audio cueing 1. The effect of the 'focus praise package' was to increase the percentage of praise received by the consistently low on-task children. Other findings tended to suggest that audio cueing increased the teacher's praise rate. However, the teacher's praise rate unexpectedly decreased to a level considerably below the cued rate during audio cueing 2. The 'increase praise package' appeared to increase the teacher's praise rate above the audio cueing 2 level. The effect of an increased praise rate and two distributions of praise on on-task behaviour were considered. Significant increases in on-task behaviour were found in audio cueing 1 for the low on-task group, in the audio cueing plus 'focus praise package' condition for the entire class and the consistently low on-task group and in audio cueing 2 for the medium on-task group. Except for the high on-task children who did not change, the effects of the experimental manipulations on on-task behaviour were e quivocal. However, there were some indications that directing 67% of the praise to the consistently low on-task children was more effective for increasing this group's on-task behaviour than distributing praise equally among on-task groups.
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This article marks the decline of the historical study of the Library meet the increase in studies on technology-driven globalization and the predominance of technicality in the discipline, but it is essential to return to that historical knowledge if the Library want instituted as a fully scientific field of knowledge. Emphasized in the beginning of the Library from orality to the written record preserved by the archives and libraries and its close relation to the development of the science of history. It also establishes the link between documents librarians and historians to understand the past and present society.
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The growth of social networking platforms has drawn a lot of attentions to the need for social computing. Social computing utilises human insights for computational tasks as well as design of systems that support social behaviours and interactions. One of the key aspects of social computing is the ability to attribute responsibility such as blame or praise to social events. This ability helps an intelligent entity account and understand other intelligent entities’ social behaviours, and enriches both the social functionalities and cognitive aspects of intelligent agents. In this paper, we present an approach with a model for blame and praise detection in text. We build our model based on various theories of blame and include in our model features used by humans determining judgment such as moral agent causality, foreknowledge, intentionality and coercion. An annotated corpus has been created for the task of blame and praise detection from text. The experimental results show that while our model gives similar results compared to supervised classifiers on classifying text as blame, praise or others, it outperforms supervised classifiers on more finer-grained classification of determining the direction of blame and praise, i.e., self-blame, blame-others, self-praise or praise-others, despite not using labelled training data.