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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Many scientific claims being made today are not based on established scientific principles. They are a result of motivating factors that include media, political influences, legal and social issues, economic pursuits, the experimental procedure itself, peer review, and, central to this thesis, the lack of science education of the public. Intelligent Design, a much discussed potential theory of biological origins is one of these claims. Intelligent Design offers an array of scientific and probabilistic arguments supporting the concept that an intelligent agency better accounts for certain aspects of the natural world. The response and reaction to this theory within the science, political, education and religious communities has been increasingly expressive. Some believe that Intelligent Design is a threat to Darwinian evolution, some argue that teaching ID as an evolutionary theory is "only fair." And all believe the stakes are high--to the victor goes the privilege of teaching their theory as biology in the public school classroom. This study of Intelligent Design is not an extensive quantitative review of primary materials in the scientific debate, or qualitative reviews of sweeping breadth of religious-based theories. Rather, a quantitative content analysis with selected primary sources was conducted to acquire data to discover which arguments constitutes effective presentation of Intelligent Design, to whom they are presented, and which arguments are promulgated and which are not. The study analyses what rhetorical devices (such as use of selective word choices and framing techniques) are utilized, whether consciously or unconsciously, in the presentation of these arguments. / Master of Science

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published_or_final_version / Housing Management / Master / Master of Housing Management

The need to give educators the ability to enter a particular teaching strategy of their choice into an Intelligent Tutoring System (ITS) and have the ITS respond appropriately to each student has been stated by many researchers. For example, an educator could tell the ITS to keep students within a certain help level ratio (how much help they request), or to introduce a new topic in a particular manner and the ITS simply carries this out at each learning point of interest. Educators could then try new strategies, ones that unaided are impossible to try out in class (such as keeping a student within a help-seeking range) or difficult within an ITS (as the ITS would have to be specially programmed in that way). Current ITSs provide adaptivity to the student at the domain level but not necessarily at the pedagogical level. While a variety of pedagogical strategies have been implemented (e.g. apprenticeship, socratic, practice), there is no system that offers parts or all of these strategies with the ability to choose between them dynamically. In this project, we designed a new framework for an ITS to include multiple, potentially adaptable pedagogical strategies. This was done by breaking up the pedagogical module into separate components. The Pedagogical Strategy Set (PSS) contains all the strategies, written as constraints. The Pedagogical Student Model (PSM) keeps track of which pedagogical strategies were used by each student. Within the ITS, there is still a smaller, separate pedagogical module to deal with domain-specific strategies. The Pedagogical Control Centre (PCC) contains the logic of when and how to use the pedagogical strategies. It gathers its information from the other modules and uses decision logic to trigger strategies. We implemented and evaluated this framework within the context of SQL-Tutor and found that the framework could be used to enter pedagogical strategies, which in turn compared favourably to the original SQL-Tutor. This proof of concept opens up the possibility of the logic and algorithms that could be implemented (e.g. in the PCC) in future ITSs. The PSS is a separate module, written in a different language, independent of ITSs. This could lead to sharing of pedagogical strategies between tutors. Furthermore, students learn differently to each other; this framework allows them to do so.

Les systèmes tuteurs intelligents sont considérés comme un remarquable concentré de technologies qui permettent un processus d'apprentissage. Ces systèmes sont capables de jouer le rôle d'assistants voire même de tuteur humain. Afin d'y arriver, ces systèmes ont besoin de maintenir et d'utiliser une représentation interne de l'environnement. Ainsi, ils peuvent tenir compte des évènements passés et présents ainsi que de certains aspects socioculturels. Parallèlement à l'évolution dynamique de l'environnement, un agent STI doit évoluer en modifiant ses structures et en ajoutant de nouveaux phénomènes. Cette importante capacité d'adaptation est observée dans le cas de tuteurs humains. Les humains sont capables de gérer toutes ces complexités à l'aide de l'attention et du mécanisme de conscience (Baars B. J., 1983, 1988), et (Sloman, A and Chrisley, R., 2003). Toutefois, reconstruire et implémenter des capacités humaines dans un agent artificiel est loin des possibilités actuelles de la connaissance de même que des machines les plus sophistiquées. Pour réaliser un comportement humanoïde dans une machine, ou simplement pour mieux comprendre l'adaptabilité et la souplesse humaine, nous avons à développer un mécanisme d'apprentissage proche de celui de l'homme. Ce présent travail décrit quelques concepts d'apprentissage fondamentaux implémentés dans un agent cognitif autonome, nommé CTS (Conscious Tutoring System) développé dans le GDAC (Dubois, D., 2007). Nous proposons un modèle qui étend un apprentissage conscient et inconscient afin d'accroître l'autonomie de l'agent dans un environnement changeant ainsi que d'améliorer sa finesse. ______________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : Apprentissage, Conscience, Agent cognitif, Codelet.

The concept of knowledge management has become a critical issue in both academic and practical area. Organizations invest huge resources in knowledge management work in order to maintain long term competitive advantage. Therefore, how to use information technology to support knowledge management in an efficient way is a critical success factor in organizations adopting knowledge management. However, the running effect of knowledge management system does not achieve organizations¡¦ expectancy. The main reason is that knowledge management system is designed for unstable form of knowledge; developing information system in a structural way can not process this abstract knowledge effectively. For the reason, this research applies intelligent agent technique in developing knowledge management system, hoping to make use of intelligent agents¡¦ autonomy, communication ability, adaptability and mobility to raise the efficiency of knowledge management. This research analysis the general knowledge management works in order to find out the general knowledge management requirements. And then, this research also checks which requirements are suitable for intelligent agent to process. After integrating these requirements, this research proposes a complete intelligent agent based knowledge management system framework and a detail definition of each intelligent agent, and a set of message communication protocols between these intelligent agents.

Thesis (Ph.D.)--Drexel University, 2009. / Includes abstract and vita. Includes bibliographical references (leaves 105-114).

Thesis (Ph.D.)--University of Nebraska-Lincoln, 2007. / Title from title screen (site viewed Aug. 2, 2007). PDF text: xviii, 388 p. : ill. UMI publication number: AAT 3258404. Includes bibliographical references. Also available in microfilm and microfiche formats.