242,223 research outputs found

    Analytic frameworks for assessing dialogic argumentation in online learning environments

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    Over the last decade, researchers have developed sophisticated online learning environments to support students engaging in argumentation. This review first considers the range of functionalities incorporated within these online environments. The review then presents five categories of analytic frameworks focusing on (1) formal argumentation structure, (2) normative quality, (3) nature and function of contributions within the dialog, (4) epistemic nature of reasoning, and (5) patterns and trajectories of participant interaction. Example analytic frameworks from each category are presented in detail rich enough to illustrate their nature and structure. This rich detail is intended to facilitate researchers’ identification of possible frameworks to draw upon in developing or adopting analytic methods for their own work. Each framework is applied to a shared segment of student dialog to facilitate this illustration and comparison process. Synthetic discussions of each category consider the frameworks in light of the underlying theoretical perspectives on argumentation, pedagogical goals, and online environmental structures. Ultimately the review underscores the diversity of perspectives represented in this research, the importance of clearly specifying theoretical and environmental commitments throughout the process of developing or adopting an analytic framework, and the role of analytic frameworks in the future development of online learning environments for argumentation

    The Pragmatic Turn in Explainable Artificial Intelligence (XAI)

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    In this paper I argue that the search for explainable models and interpretable decisions in AI must be reformulated in terms of the broader project of offering a pragmatic and naturalistic account of understanding in AI. Intuitively, the purpose of providing an explanation of a model or a decision is to make it understandable to its stakeholders. But without a previous grasp of what it means to say that an agent understands a model or a decision, the explanatory strategies will lack a well-defined goal. Aside from providing a clearer objective for XAI, focusing on understanding also allows us to relax the factivity condition on explanation, which is impossible to fulfill in many machine learning models, and to focus instead on the pragmatic conditions that determine the best fit between a model and the methods and devices deployed to understand it. After an examination of the different types of understanding discussed in the philosophical and psychological literature, I conclude that interpretative or approximation models not only provide the best way to achieve the objectual understanding of a machine learning model, but are also a necessary condition to achieve post hoc interpretability. This conclusion is partly based on the shortcomings of the purely functionalist approach to post hoc interpretability that seems to be predominant in most recent literature

    Assessing relevance

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    This paper advances an approach to relevance grounded on patterns of material inference called argumentation schemes, which can account for the reconstruction and the evaluation of relevance relations. In order to account for relevance in different types of dialogical contexts, pursuing also non-cognitive goals, and measuring the scalar strength of relevance, communicative acts are conceived as dialogue moves, whose coherence with the previous ones or the context is represented as the conclusion of steps of material inferences. Such inferences are described using argumentation schemes and are evaluated by considering 1) their defeasibility, and 2) the acceptability of the implicit premises on which they are based. The assessment of both the relevance of an utterance and the strength thereof depends on the evaluation of three interrelated factors: 1) number of inferential steps required; 2) the types of argumentation schemes involved; and 3) the implicit premises required

    How Belief-Credence Dualism Explains Away Pragmatic Encroachment

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    Belief-credence dualism is the view that we have both beliefs and credences and neither attitude is reducible to the other. Pragmatic encroachment is the view that practical stakes can affect the epistemic rationality of states like knowledge or justified belief. In this paper, I argue that dualism offers a unique explanation of pragmatic encroachment cases. First, I explain pragmatic encroachment and what motivates it. Then, I explain dualism and outline a particular argument for dualism. Finally, I show how dualism can explain the intuitions that underlie pragmatic encroachment. My basic proposal is that in high-stakes cases, it is not that one cannot rationally believe that p; instead, one ought not to rely on one's belief that p. One should rather rely on one's credence in p. I conclude that we need not commit ourselves to pragmatic encroachment in order to explain the intuitiveness of the cases that motivate it

    Scientific Argumentation as a Foundation for the Design of Inquiry-Based Science Instruction

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    Despite the attention that inquiry has received in science education research and policy, a coherent means for implementing inquiry in the classroom has been missing [1]. In recent research, scientific argumentation has received increasing attention for its role in science and in science education [2]. In this article, we propose that organizing a unit of instruction around building a scientific argument can bring inquiry practices together in the classroom in a coherent way. We outline a framework for argumentation, focusing on arguments that are central to science—arguments for the best explanation. We then use this framework as the basis for a set of design principles for developing a sequence of inquiry-based learning activities that support students in the construction of a scientific argument. We show that careful analysis of the argument that students are expected to build provides designers with a foundation for selecting resources and designing supports for scientific inquiry. Furthermore, we show that creating multiple opportunities for students to critique and refine their explanations through evidence-based argumentation fosters opportunities for critical thinking, while building science knowledge and knowledge of the nature of science

    Causal mapping as a teaching tool for reflecting on causation in human evolution (advance online)

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    Character and theory of mind: an integrative approach

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    Traditionally, theories of mindreading have focused on the representation of beliefs and desires. However, decades of social psychology and social neuroscience have shown that, in addition to reasoning about beliefs and desires, human beings also use representations of character traits to predict and interpret behavior. While a few recent accounts have attempted to accommodate these findings, they have not succeeded in explaining the relation between trait attribution and belief-desire reasoning. On my account, character-trait attribution is part of a hierarchical system for action prediction, and serves to inform hypotheses about agents’ beliefs and desires, which are in turn used to predict and interpret behavior

    Argumentation in school science : Breaking the tradition of authoritative exposition through a pedagogy that promotes discussion and reasoning

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    The value of argumentation in science education has become internationally recognised and has been the subject of many research studies in recent years. Successful introduction of argumentation activities in learning contexts involves extending teaching goals beyond the understanding of facts and concepts, to include an emphasis on cognitive and metacognitive processes, epistemic criteria and reasoning. The authors focus on the difficulties inherent in shifting a tradition of teaching from one dominated by authoritative exposition to one that is more dialogic, involving small-group discussion based on tasks that stimulate argumentation. The paper builds on previous research on enhancing the quality of argument in school science, to focus on how argumentation activities have been designed, with appropriate strategies, resources and modelling, for pedagogical purposes. The paper analyses design frameworks, their contexts and lesson plans, to evaluate their potential for enhancing reasoning through foregrounding the processes of argumentation. Examples of classroom dialogue where teachers adopt the frameworks/plans are analysed to show how argumentation processes are scaffolded. The analysis shows that several layers of interpretation are needed and these layers need to be aligned for successful implementation. The analysis serves to highlight the potential and limitations of the design frameworks

    Explaining Explanation

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    It is not a particularly hard thing to want or seek explanations. In fact, explanations seem to be a large and natural part of our cognitive lives. Children ask why and how questions very early in development and seem genuinely to want some sort of answer, despite our often being poorly equipped to provide them at the appropriate level of sophistication and detail. We seek and receive explanations in every sphere of our adult lives, whether it be to understand why a friendship has foundered, why a car will not start, or why ice expands when it freezes. Moreover, correctly or incorrectly, most of the time we think we know when we have or have not received a good explanation. There is a sense both that a given, successful explanation satisfies a cognitive need, and that a questionable or dubious explanation does not. There are also compelling intuitions about what make good explanations in terms of their form, that is, a sense of when they are structured correctly
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