Search results for 'Analogical Learning' (try it on Scholar)

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  1. Theodore Bach (2012). Analogical Cognition: Applications in Epistemology and the Philosophy of Mind and Language. Philosophy Compass 7 (5):348-360.score: 45.0
    Analogical cognition refers to the ability to detect, process, and learn from relational similarities. The study of analogical and similarity cognition is widely considered one of the ‘success stories’ of cognitive science, exhibiting convergence across many disciplines on foundational questions. Given the centrality of analogy to mind and knowledge, it would benefit philosophers investigating topics in epistemology and the philosophies of mind and language to become familiar with empirical models of analogical cognition. The goal of this essay (...)
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  2. Theodore Bach, Philosophical Discovery Through the Activity of Comparison.score: 33.0
    I argue that at least one of the reasons that philosophy is difficult is because it requires students to master “relational categories”, which contrast with “object” or “entity” categories. An object category is one whose members are united on the basis of perceptual and/ or salient properties, and a relational category is one whose members are united on the basis of a relational property. Empirical evidence shows that relational categories are more difficult to grasp than object categories. If learning (...)
     
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  3. Theodore Bach (2011). Structure-Mapping: Directions From Simulation to Theory. Philosophical Psychology 24 (1):23-51.score: 30.0
    The theory of mind debate has reached a “hybrid consensus” concerning the status of theory-theory and simulation-theory. Extant hybrid models either specify co-dependency and implementation relations, or distribute mentalizing tasks according to folk-psychological categories. By relying on a non-developmental framework these models fail to capture the central connection between simulation and theory. I propose a “dynamic” hybrid that is informed by recent work on the nature of similarity cognition. I claim that Gentner’s model of structure-mapping allows us to understand simulation (...)
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  4. Stephen Downes (2010). Learning Networks and Connective Knowledge. In Harrison Hao Yang & Steve Chi-Yin Yuen (eds.), Collective Intelligence and E-Learning 2.0: Implications of Web-Based Communities and Networking. IGI Global.score: 21.0
    The purpose of this chapter is to outline some of the thinking behind new e-learning technology, including e-portfolios and personal learning environments. Part of this thinking is centered around the theory of connectivism, which asserts that knowledge - and therefore the learning of knowledge - is distributive, that is, not located in any given place (and therefore not 'transferred' or 'transacted' per se) but rather consists of the network of connections formed from experience and interactions with a (...)
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  5. Mark Colyvan & Lev R. Ginzburg, Analogical Thinking in Ecology.score: 21.0
    We consider several ways in which a good understanding of modern techniques and principles in physics can elucidate ecology. We focus on analogical reasoning between these two branches of science. This style of reasoning requires an understanding of both sciences and an appreciation of the similarities and points of contact between the two. In the current ecological literature on the relationship between ecology and physics, there has been some misunderstanding about the nature of modern physics and its methods. Physics (...)
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  6. Adrian Ratkic (forthcoming). Images of Reflection: On the Meanings of the Word Reflection in Different Learning Contexts. AI and Society.score: 21.0
    Reflection is today a watchword in many learning contexts. Experience is said to be transformed to knowledge when we reflect on it, university students are expected to acquire the ability to reflect critically, and we want practitioners to be reflective practitioners in order to improve their professional practice. If we consider what people mean when they talk about reflection in practice, we will discover that they often mean different things. Moreover, their conceptions of reflection are guided by images rather (...)
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  7. Peter F. Dominey (1997). Reducing Problem Complexity by Analogical Transfer. Behavioral and Brain Sciences 20 (1):71-72.score: 21.0
    Analogical transfer in sequence learning is presented as an example of how the type-2 problem of learning an unbounded number of isomorphic sequences is reduced to the type-1 problem of learning a small finite set of sequences. The commentary illustrates how the difficult problem of appropriate analogical filter creation and selection is addressed while avoiding the trap of strong nativism, and it provides theoretical and experimental evidence for the existence of dissociable mechanisms for type-1 (...) and type-2 recoding. (shrink)
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  8. Arthur S. Reber (1993). Implicit Learning and Tacit Knowledge: An Essay on the Cognitive Unconscious. Oxford University Press.score: 18.0
    In this new volume in the Oxford Psychology Series, the author presents a highly readable account of the cognitive unconscious, focusing in particular on the problem of implicit learning. Implicit learning is defined as the acquisition of knowledge that takes place independently of the conscious attempts to learn and largely in the absence of explicit knowledge about what was acquired. One of the core assumptions of this argument is that implicit learning is a fundamental, "root" process, one (...)
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  9. Christopher Winch (1998). The Philosophy of Human Learning. Routledge.score: 18.0
    Christopher Winch launches a vigorous Wittgensteinian attack on both the "romantic" Rousseauian and the "scientific" cognitivist traditions in learning theory. These two schools, he argues, are more closely related than is commonly realized.
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  10. Knud Illeris (ed.) (2009). Contemporary Theories of Learning: Learning Theorists -- In Their Own Words. Routledge.score: 18.0
    In this definitive collection of today's most influential learning theorists, sixteen world-renowned experts present their understanding of what learning is and ...
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  11. Richard Edwards, Gert Biesta & Mary Thorpe (eds.) (2009). Rethinking Contexts for Learning and Teaching. Routledge.score: 18.0
    It specifically addressesWhat constitutes a context for learning?How do we engage the full resources of learners for learning?What are the relationships between ...
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  12. Michael Cholbi (2007). Intentional Learning as a Model for Philosophical Pedagogy. Teaching Philosophy 30 (1):35-58.score: 18.0
    The achievement of intentional learning is a powerful paradigm for the objectives and methods of the teaching of philosophy. This paradigm sees the objectives and methods of such teaching as based not simply on the mastery of content, but as rooted in attempts to shape the various affective and cognitive factors that influence students’ learning efforts. The goal of such pedagogy is to foster an intentional learning orientation, one characterized by self-awareness, active monitoring of the learning (...)
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  13. B. van Oers (ed.) (2008). The Transformation of Learning: Advances in Cultural-Historical Activity Theory. Cambridge University Press.score: 18.0
    Learning is a changing phenomenon, depending on the advances in theory and research. This book presents a relatively new approach to learning, based on meaningful human activities in cultural practices and in collaboration with others. It draws extensively from the ideas of Lev Vygotsky and his recent followers. The book presents ideas that elaborate this learning theory and also gives recent developments and applications of this approach in a variety of educational situations in and outside of school. (...)
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  14. Christopher D. Viger (2005). Learning to Think: A Response to the Language of Thought Argument for Innateness. Mind and Language 20 (3):313-25.score: 18.0
    Jerry Fodor's argument for an innate language of thought continues to be a hurdle for researchers arguing that natural languages provide us with richer conceptual systems than our innate cognitive resources. I argue that because the logical/formal terms of natural languages are given a usetheory of meaning, unlike predicates, logical/formal terms might be learned without a mediating internal representation. In that case, our innate representational system might have less logical structure than a natural language, making it possible that we augment (...)
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  15. Kenneth Reisman (2007). Is Culture Inherited Through Social Learning? Biological Theory 2 (3):300-306.score: 18.0
    In this article I challenge the widely held assumption that human culture is inherited by means of social learning. First, I address the distinction between “social” learning and “individual” learning. I argue that most cultural ideas are not acquired by one form of learning or the other, but from a hybrid of both. Second, I discuss how individual learning can interact with niche construction. I argue that these processes collectively provide a non-social route for learned (...)
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  16. Kevin Connolly, Dylan Bianchi, Craig French, Lana Kuhle & Andy MacGregor, Perceptual Learning and Cognitive Penetration (Network for Sensory Research/University of York Perceptual Learning Workshop, Question Two).score: 18.0
    This is an excerpt of a report that highlights and explores five questions that arose from the Network for Sensory Research workshop on perceptual learning and perceptual recognition at the University of York in March, 2012. This portion of the report explores the question: Can perceptual experience be modified by reason?
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  17. Dominic Scott (1995). Recollection and Experience: Plato's Theory of Learning and its Successors. Cambridge University Press.score: 18.0
    Questions about learning and discovery have fascinated philosophers from Plato onwards. Does the mind bring innate resources of its own to the process of learning or does it rely wholly upon experience? Plato was the first philosopher to give an innatist response to this question and in doing so was to provoke the other major philosophers of ancient Greece to give their own rival explanations of learning. This book is the first to examine these theories of (...) in relation to each other. It presents an entirely new interpretation of the theory of recollection which also changes the way we understand the development of ancient philosophy after Plato. The final section of the book compares ancient theories of learning with the seventeenth-century debate about innate ideas, and finds that the relation between the two periods is far more interesting and complete than is usually supposed. (shrink)
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  18. Kevin Connolly, Dylan Bianchi, Craig French, Lana Kuhle & Andy MacGregor, Report on the Network for Sensory Research/University of York Perceptual Learning Workshop.score: 18.0
    This report highlights and explores five questions that arose from the Network for Sensory Research workshop on perceptual learning and perceptual recognition at the University of York on March 19th and 20th, 2012: 1. What is perceptual learning? 2. Can perceptual experience be modified by reason? 3. How does perceptual learning alter perceptual phenomenology? 4. How does perceptual learning alter the contents of perception? 5. How is perceptual learning coordinated with action?
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  19. Kevin Connolly, John Donaldson, David M. Gray, Emily McWilliams, Sofia Ortiz-Hinojosa & David Suarez, Cognitive Penetration? (Network for Sensory Research Toronto Workshop on Perceptual Learning: Question Four).score: 18.0
    This is an excerpt from a report that highlights and explores five questions which arose from the workshop on perceptual learning and perceptual recognition at the University of Toronto, Mississauga on May 10th and 11th, 2012. This excerpt explores the question: What counts as cognitive penetration?
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  20. Nicholas Maxwell (2003). Two Great Problems of Learning. Teaching in Higher Education, 8 (January):129-134.score: 18.0
    Two great problems of learning confront humanity: learning about the universe, and learning how to live wisely. The first problem was solved with the creation of modern science, but the second problem has not been solved. This combination puts humanity into a situation of unprecedented danger. In order to solve the second problem we need to learn from our solution to the first problem. This requires that we bring about a revolution in the overall aims and methods (...)
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  21. Kevin Connolly, John Donaldson, David M. Gray, Emily McWilliams, Sofia Ortiz-Hinojosa & David Suarez, Report on the Network for Sensory Research Toronto Workshop on Perceptual Learning.score: 18.0
    This report highlights and explores five questions which arose from the workshop on perceptual learning and perceptual recognition at the University of Toronto, Mississauga on May 10th and 11th, 2012: 1. How should we demarcate perceptual learning from perceptual development? 2. What are the origins of multimodal associations? 3. Does our representation of time provide an amodal framework for multi-sensory integration? 4. What counts as cognitive penetration? 5. How can philosophers and psychologists most fruitfully collaborate?
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  22. Kevin Connolly, Dylan Bianchi, Craig French, Lana Kuhle & Andy MacGregor, Perceptual Learning and Perceptual Phenomenology (Network for Sensory Research/University of York Perceptual Learning Workshop, Question Three).score: 18.0
    This is an excerpt of a report that highlights and explores five questions that arose from the Network for Sensory Research workshop on perceptual learning and perceptual recognition at the University of York in March, 2012. This portion of the report explores the question: How does perceptual learning alter perceptual phenomenology?
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  23. Kevin Connolly, Dylan Bianchi, Craig French, Lana Kuhle & Andy MacGregor, Perceptual Learning (Network for Sensory Research/University of York Perceptual Learning Workshop, Question One).score: 18.0
    This is an excerpt of a report that highlights and explores five questions that arose from the Network for Sensory Research workshop on perceptual learning and perceptual recognition at the University of York in March, 2012. This portion of the report explores the question: What is perceptual learning?
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  24. Nina Gierasimczuk (2009). Bridging Learning Theory and Dynamic Epistemic Logic. Synthese 169 (2):371-384.score: 18.0
    This paper discusses the possibility of modelling inductive inference (Gold 1967) in dynamic epistemic logic (see e.g. van Ditmarsch et al. 2007). The general purpose is to propose a semantic basis for designing a modal logic for learning in the limit. First, we analyze a variety of epistemological notions involved in identification in the limit and match it with traditional epistemic and doxastic logic approaches. Then, we provide a comparison of learning by erasing (Lange et al. 1996) and (...)
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  25. Kevin Connolly, Dylan Bianchi, Craig French, Lana Kuhle & Andy MacGregor, Perceptual Learning and Perceptual Content (Network for Sensory Research/University of York Perceptual Learning Workshop, Question Four).score: 18.0
    This is an excerpt of a report that highlights and explores five questions that arose from the Network for Sensory Research workshop on perceptual learning and perceptual recognition at the University of York in March, 2012. This portion of the report explores the question: How does perceptual learning alter the contents of perception?
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  26. Kevin Connolly, Dylan Bianchi, Craig French, Lana Kuhle & Andy MacGregor, Perceptual Learning and Action (Network for Sensory Research/University of York Perceptual Learning Workshop, Question Five).score: 18.0
    This is an excerpt of a report that highlights and explores five questions that arose from the Network for Sensory Research workshop on perceptual learning and perceptual recognition at the University of York in March, 2012. This portion of the report explores the question: How is perceptual learning coordinated with action?
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  27. Robert M. French (2002). Implicit Learning and Consciousness: An Empirical, Philosophical, and Computational Consensus in the Making. Psychology Press.score: 18.0
    Implicit Learning and Consciousness challenges conventional wisdom and presents the most up-to-date studies to define, quantify and test the predictions of the main models of implicit learning. The chapters include a variety of research from computer modeling, experimental psychology and neural imaging to the clinical data resulting from work with amnesics. The result is a topical book that provides an overview of the debate on implicit learning, and the various philosophical, psychological and neurological frameworks in which it (...)
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  28. Alison Gopnik & Laura Schulz (eds.) (2007). Causal Learning: Psychology, Philosophy, and Computation. Oxford University Press.score: 18.0
    Understanding causal structure is a central task of human cognition. Causal learning underpins the development of our concepts and categories, our intuitive theories, and our capacities for planning, imagination and inference. During the last few years, there has been an interdisciplinary revolution in our understanding of learning and reasoning: Researchers in philosophy, psychology, and computation have discovered new mechanisms for learning the causal structure of the world. This new work provides a rigorous, formal basis for theory theories (...)
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  29. Chris Thornton (1997). Brave Mobots Use Representation: Emergence of Representation in Fight-or-Flight Learning. Minds and Machines 7 (4):475-494.score: 18.0
    The paper uses ideas from Machine Learning, Artificial Intelligence and Genetic Algorithms to provide a model of the development of a fight-or-flight response in a simulated agent. The modelled development process involves (simulated) processes of evolution, learning and representation development. The main value of the model is that it provides an illustration of how simple learning processes may lead to the formation of structures which can be given a representational interpretation. It also shows how these may form (...)
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  30. Kate Ashcroft (1994). Managing Teaching and Learning in Further and Higher Education. Falmer Press.score: 18.0
    This handbook covers ways of managing the teaching, learning and assessment process to improve students' learning.
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  31. Kevin Connolly, John Donaldson, David M. Gray, Emily McWilliams, Sofia Ortiz-Hinojosa & David Suarez, Multi-Sensory Integration and Time (Network for Sensory Research Toronto Workshop on Perceptual Learning: Question Three).score: 18.0
    This is an excerpt from a report that highlights and explores five questions which arose from the workshop on perceptual learning and perceptual recognition at the University of Toronto, Mississauga on May 10th and 11th, 2012. This excerpt explores the question: Does our representation of time provide and amodal framework for multi-sensory integration?
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  32. Robert Keith Shaw (2010). The Violence in Learning. Analysis and Metaphysics 9:76-100.score: 18.0
    This paper argues that learning is inherently violent. It examines the way in which Heidegger uses – and refrains from using – the concept in his account of Dasein. Heidegger explicitly discussed “learning” in 1951 and he used of the word in several contexts. Although he confines his use of “learning” to the ontic side of the ontic-ontological divide, there are aspects of what he says that open the door to an ontological analogue of the ontic (...). In this discussion it emerges that what precludes “learning” behaving as does “willing”, “waiting” and “thanking”, is something that derives from the relatedness of Dasein. The paper finally examines violence within the disclosure of truth. The approach to the investigation is experimental and is to some extent modeled on Heidegger‟s own later enquires. (shrink)
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  33. Kevin Connolly, John Donaldson, David M. Gray, Emily McWilliams, Sofia Ortiz-Hinojosa & David Suarez, Perceptual Learning and Development (Network for Sensory Research Toronto Workshop on Perceptual Learning: Question One).score: 18.0
    This is an excerpt from a report that highlights and explores five questions which arose from the workshop on perceptual learning and perceptual recognition at the University of Toronto, Mississauga on May 10th and 11th, 2012. This excerpt explores the question: How should we demarcate perceptual learning from perceptual development?
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  34. Kevin Connolly, John Donaldson, David M. Gray, Emily McWilliams, Sofia Ortiz-Hinojosa & David Suarez, Multimodal Associations (Network for Sensory Research Toronto Workshop on Perceptual Learning: Question Two).score: 18.0
    This is an excerpt from a report that highlights and explores five questions which arose from the workshop on perceptual learning and perceptual recognition at the University of Toronto, Mississauga on May 10th and 11th, 2012. This excerpt explores the question: What are the origins of multimodal associations?
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  35. Kevin Connolly, John Donaldson, David M. Gray, Emily McWilliams, Sofia Ortiz-Hinojosa & David Suarez, Philosophy/Psychology Collaboration (Network for Sensory Research Toronto Workshop on Perceptual Learning: Question Five).score: 18.0
    This is an excerpt from a report that highlights and explores five questions which arose from the workshop on perceptual learning and perceptual recognition at the University of Toronto, Mississauga on May 10th and 11th, 2012. This excerpt explores the question: How can philosophers and psychologists most fruitfully collaborate?
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  36. Sunbin Song, Howard Jr, James H. & Darlene V. Howard (2007). Implicit Probabilistic Sequence Learning is Independent of Explicit Awareness. Learning and Memory 14 (1-6):167-176.score: 18.0
  37. Muriel Vandenberghe, Nicolas Schmidt, Patrick Fery & Axel Cleeremans (2006). Can Amnesic Patients Learn Without Awareness? New Evidence Comparing Deterministic and Probabilistic Sequence Learning. Neuropsychologia 44 (10):1629-1641.score: 18.0
    Can associative learning take place without awareness? We explore this issue in a sequence learning paradigm with amnesic and control participants, who were simply asked to react to one of four possible stimuli on each trial. Unknown to them, successive stimuli occurred in a sequence. We manipulated the extent to which stimuli followed the sequence in a deterministic manner (noiseless condition) or only probabilistically so (noisy condition). Through this paradigm, we aimed at addressing two central issues: first, we (...)
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  38. David Guez (2009). A Bio-Logical Theory of Animal Learning. Biological Theory 4 (2):148-158.score: 18.0
    This article provides the foundation for a new predictive theory of animal learning that is based upon a simple logical model. The knowledge of experimental subjects at a given time is described using logical equations. These logical equations are then used to predict a subject’s response when presented with a known or a previously unknown situation. This new theory suc- cessfully anticipates phenomena that existing theories predict, as well as phenomena that they cannot. It provides a theoretical account for (...)
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  39. Gregory M. Nixon (2013). Scientism, Philosophy and Brain-Based Learning. Northwest Journal of Teacher Education 11 (2):113-144.score: 18.0
    Since educators are always looking for ways to improve their practice, and since empirical science is now accepted in our worldview as the final arbiter of truth, it is no surprise they have been lured toward cognitive neuroscience in hopes that discovering how the brain learns will provide a nutshell explanation for student learning in general. I argue that identifying the person with the brain is scientism (not science), that the brain is not the person, and that it is (...)
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  40. Robert F. Hadley & M. B. Hayward (1997). Strong Semantic Systematicity From Hebbian Connectionist Learning. Minds and Machines 7 (1):1-55.score: 18.0
    Fodor's and Pylyshyn's stand on systematicity in thought and language has been debated and criticized. Van Gelder and Niklasson, among others, have argued that Fodor and Pylyshyn offer no precise definition of systematicity. However, our concern here is with a learning based formulation of that concept. In particular, Hadley has proposed that a network exhibits strong semantic systematicity when, as a result of training, it can assign appropriate meaning representations to novel sentences (both simple and embedded) which contain words (...)
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  41. Helena M. Purkis & Ottmar V. Lipp (2001). Does Affective Learning Exist in the Absence of Contingency Awareness? Learning and Motivation 32 (1):84-99.score: 18.0
  42. Mark D. Johnston (1996). The Evangelical Rhetoric of Ramon Llull: Lay Learning and Piety in the Christian West Around 1300. Oxford University Press.score: 18.0
    Ramon Llull (1232-1316), born on Majorca, was one of the most remarkable lay intellectuals of the thirteenth century. He devoted much of his life to promoting missions among unbelievers, the reform of Western Christian society, and personal spiritual perfection. He wrote over 200 philosophical and theological works in Catalan, Latin, and Arabic. Many of these expound on his "Great Universal Art of Finding Truth," an idiosyncratic dialectical system that he thought capable of proving Catholic beliefs to non-believers. This study offers (...)
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  43. Mats Bergman (forthcoming). Fields of Rhetoric: Inquiry, Communication, and Learning. Educational Philosophy and Theory.score: 18.0
    This article examines the disciplinary status and experiential underpinnings of C. S. Peirce's philosophical rhetoric. The first part explores the relationship between grammar and rhetoric in the context of Peirce's theory of signs. Next, a possible tension in Peirce's conception of the scope and function of rhetoric is identified, and a resolution is proposed. The field of rhetorical research is then provisionally characterised as spanning philosophical studies of communication, learning, and methods of inquiry. Rather than being a secondary application (...)
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  44. James Blackmon, David Byrd, Robert C. Cummins, Pierre Poirier & Martin Roth (2005). Atomistic Learning in Non-Modular Systems. Philosophical Psychology 18 (3):313-325.score: 18.0
    We argue that atomistic learning?learning that requires training only on a novel item to be learned?is problematic for networks in which every weight is available for change in every learning situation. This is potentially significant because atomistic learning appears to be commonplace in humans and most non-human animals. We briefly review various proposed fixes, concluding that the most promising strategy to date involves training on pseudo-patterns along with novel items, a form of learning that is (...)
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  45. David William Jardine (2008). Back to the Basics of Teaching and Learning: Thinking the World Together. Routledge.score: 18.0
    This book is about an ecological-interpretive image of "the basics" in teaching and learning. The authors offer a generous, rigorous, difficult, and pleasurable image of what this term might mean in the living work of teachers and learners. In this book, Jardine, Clifford, and Friesen: *sketch out some of the key ideas in the traditional, taken-for-granted meaning of "the basics"; *explain how the interpretive-hermeneutic version of "the basics" operates on different fundamental assumptions; *show how this difference leads, of necessity, (...)
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  46. Stephen Petersen (2004). Functions, Creatures, Learning, Emotion. Hudlicka and Canamero.score: 18.0
    I propose a conceptual framework for emotions according to which they are best understood as the feedback mechanism a creature possesses in virtue of its function to learn. More specifically, emotions can be neatly modeled as a measure of harmony in a certain kind of constraint satisfaction problem. This measure can be used as error for weight adjustment (learning) in an unsupervised connectionist network.
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  47. Ramona Ilea & Susan Hawthorne (2011). Beyond Service Learning. Teaching Philosophy 34 (3):219-240.score: 18.0
    In this essay, we describe a form of civic engagement for ethics classes in which students identify a community problem and devise a project to address that need. Like traditional service learning, our civic engagement project improves critical thinking and expressive philosophical skills. It is especially effective in meeting pedagogical goals of engaging and expanding student agency and independence while connecting class materials with individual students’ interests. The project can be adapted to a variety of ethics classes and institutional (...)
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  48. Vincian Gaillard, Muriel Vandenberghe, Arnaud Destrebecqz & Axel Cleeremans (2006). First and Third-Person Approaches in Implicit Learning Research. Consciousness and Cognition 15 (4):709-722.score: 18.0
    How do we find out whether someone is conscious of some information or not? A simple answer is “We just ask them”! However, things are not so simple. Here, we review recent developments in the use of subjective and objective methods in implicit learning research and discuss the highly complex methodological problems that their use raises in the domain.
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  49. Markus F. Peschl (2007). Triple-Loop Learning as Foundation for Profound Change, Individual Cultivation, and Radical Innovation. Construction Processes Beyond Scientific and Rational Knowledge. Constructivist Foundations 2 (2/3):136-145.score: 18.0
    Purpose: Ernst von Glasersfeld’s question concerning the relationship between scientific/ rational knowledge and the domain of wisdom and how these forms of knowledge come about is the starting point. This article aims at developing an epistemological as well as methodological framework that is capable of explaining how profound change can be brought about in various contexts, such as in individual cultivation, in organizations, in processes of radical innovation, etc. This framework is based on the triple-loop learning strategy and the (...)
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  50. Eamon P. Fulcher & Marianne Hammerl (2001). When All is Considered: Evaluative Learning Does Not Require Contingency Awareness. Consciousness and Cognition 10 (4):567-573.score: 18.0
    We argue that the effects of evaluative learning may occur (a) without conscious perception of the affective stimuli, (b) without awareness of the stimulus contingencies, and (c) without any awareness that learning has occurred at all. Whether the three experiments reported in our target article provide conclusive evidence for either or any of these assertions is discussed in the commentaries of De Houwer and Field. We respond with the argument that when considered alongside other studies carried out over (...)
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  51. Randall C. O.’Reilly, Rajan Bhattacharyya, Michael D. Howard & Nicholas Ketz (forthcoming). Complementary Learning Systems. Cognitive Science.score: 18.0
    This paper reviews the fate of the central ideas behind the complementary learning systems (CLS) framework as originally articulated in McClelland, McNaughton, and O’Reilly (1995). This framework explains why the brain requires two differentially specialized learning and memory systems, and it nicely specifies their central properties (i.e., the hippocampus as a sparse, pattern-separated system for rapidly learning episodic memories, and the neocortex as a distributed, overlapping system for gradually integrating across episodes to extract latent semantic structure). We (...)
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  52. Andy Clark (1994). Representational Trajectories in Connectionist Learning. Minds and Machines 4 (3):317-32.score: 18.0
    The paper considers the problems involved in getting neural networks to learn about highly structured task domains. A central problem concerns the tendency of networks to learn only a set of shallow (non-generalizable) representations for the task, i.e., to miss the deep organizing features of the domain. Various solutions are examined, including task specific network configuration and incremental learning. The latter strategy is the more attractive, since it holds out the promise of a task-independent solution to the problem. Once (...)
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  53. Brent Gregory, Sue Gregory, Bogdanovych A., Jacobson Michael, Newstead Anne & Simeon Simoff and Many Others (2011). How Are Australian Higher Education Institutions Contributing to Innovative Teaching and Learning Through Virtual Worlds? In Gregory Sue (ed.), Proceedings of Ascilite 2011 (Australian Society of Computers in Tertiary Education). Ascilite.score: 18.0
    Over the past decade, teaching and learning in virtual worlds has been at the forefront of many higher education institutions around the world. The DEHub Virtual Worlds Working Group (VWWG) consisting of Australian and New Zealand higher education academics was formed in 2009. These educators are investigating the role that virtual worlds play in the future of education and actively changing the direction of their own teaching practice and curricula. 47 academics reporting on 28 Australian higher education institutions present (...)
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  54. James Liszka (forthcoming). Charles Peirce's Rhetoric and the Pedagogy of Active Learning. Educational Philosophy and Theory.score: 18.0
    Although John Dewey has had the most profound effect on education, less is known about the philosophy of education of the original founder of pragmatism, Charles Peirce. Using Peirce's theory of formal rhetoric, I try to show that Peirce's philosophy of education, when fully understood, is aligned with Dewey's pedagogy of experiential learning, and can provide a justification for the promotion of active learning in the classroom. Peirce's rhetoric, as one part of his logical or semiotic theory, argues (...)
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  55. John E. C. MacBeath & Lejf Moos (eds.) (2004). Democratic Learning: The Challenge to School Effectiveness. Routledgefalmer.score: 18.0
    The time has come to challenge many of the age-old assumptions about schools and school learning. In this timely book, leading thinkers from around the world offer a different vision of what schools are for. They suggest new ways of thinking about citizenship, lifelong learning, and the role of schools in democratic societies. They question many of the tenets of school effectiveness studies which have been so influential in shaping policy, but are essentially backward looking and premised on (...)
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  56. Chase E. Thiel, Shane Connelly, Lauren Harkrider, Lynn D. Devenport, Zhanna Bagdasarov, James F. Johnson & Michael D. Mumford (2013). Case-Based Knowledge and Ethics Education: Improving Learning and Transfer Through Emotionally Rich Cases. Science and Engineering Ethics 19 (1):265-286.score: 18.0
    Case-based instruction is a stable feature of ethics education, however, little is known about the attributes of the cases that make them effective. Emotions are an inherent part of ethical decision-making and one source of information actively stored in case-based knowledge, making them an attribute of cases that likely facilitates case-based learning. Emotions also make cases more realistic, an essential component for effective case-based instruction. The purpose of this study was to investigate the influence of emotional case content, and (...)
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  57. Paul T. Gibbs (2004). Trusting in the University: The Contribution of Temporality and Trust to a Praxis of Higher Learning. Kluwer Academic Publishers.score: 18.0
    The world changes and we are encouraged to change with it, but is all change good? This book asks us to stop and consider whether the higher education we are providing, and engaging in, for ourselves and our societies is what we ought to have, or what commercial interests want us to have. In claiming that there is a place for a higher education of learning, such as the university, amongst our array of tertiary options the book attempts to (...)
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  58. Daniel Yurovsky, Chen Yu & Linda B. Smith (2013). Competitive Processes in Cross‐Situational Word Learning. Cognitive Science 37 (4).score: 18.0
    Cross-situational word learning, like any statistical learning problem, involves tracking the regularities in the environment. However, the information that learners pick up from these regularities is dependent on their learning mechanism. This article investigates the role of one type of mechanism in statistical word learning: competition. Competitive mechanisms would allow learners to find the signal in noisy input and would help to explain the speed with which learners succeed in statistical learning tasks. Because cross-situational word (...)
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  59. Terry Hyland (2011). Mindfulness and Learning: Celebrating the Affective Dimension of Education. Springer Verlag.score: 18.0
    The result is a one-dimensional, economistic and bleakly utilitarian conception of the educational task.In Mindfulness and Learning: Celebrating the Affective Dimension of Education, Terry Hyland advances the thesis that education stands in ...
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  60. Ramsey Affifi (forthcoming). Learning Plants: Semiosis Between the Parts and the Whole. Biosemiotics:1-13.score: 18.0
    In this article, I explore plant semiosis with a focus on plant learning. I distinguish between the scales and levels of learning conceivable in phytosemiosis, and identify organism-scale learning as the distinguishing question for plant semiosis. Since organism-scale learning depends on organism-scale semiosis, I critically review the arguments regarding whole-plant functional cycles. I conclude that they have largely relied on Uexküllian biases that have prevented an adequate interpretation of modern plant neurobiology. Through an examination of trophic (...)
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  61. Alex B. Fine & T. Florian Jaeger (2013). Evidence for Implicit Learning in Syntactic Comprehension. Cognitive Science 37 (3):578-591.score: 18.0
    This study provides evidence for implicit learning in syntactic comprehension. By reanalyzing data from a syntactic priming experiment (Thothathiri & Snedeker, 2008), we find that the error signal associated with a syntactic prime influences comprehenders' subsequent syntactic expectations. This follows directly from error-based implicit learning accounts of syntactic priming, but it is unexpected under accounts that consider syntactic priming a consequence of temporary increases in base-level activation. More generally, the results raise questions about the principles underlying the maintenance (...)
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  62. Martin L. Jönsson (forthcoming). Semantic Holism and Language Learning. Journal of Philosophical Logic:1-35.score: 18.0
    Holistic theories of meaning have, at least since Dummett’s Frege: The Philosophy of language, been assumed to be problematic from the perspective of the incremental nature of natural language learning. In this essay I argue that the general relationship between holism and language learning is in fact the opposite of that claimed by Dummett. It is only given a particular form of language learning, and a particular form of holism, that there is a problem at all; in (...)
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  63. Line Wittek (2013). The Activity of “Writing for Learning” in a Nursing Program. Outlines. Critical Practice Studies 14 (1):73 - 94.score: 18.0
    This article explores the activity of writing in higher education as a mediational means for student meaning making. From a dialogic perspective, writing is not about learning and applying formulas and making fixed kinds of texts, but about ways of working and ways of acting that brings writers, readers, resources and contexts into trajectories. The argument is that processes of writing enhance student meaning making and that these processes are formed by complex interaction. Contextual interpretation and use of mediational (...)
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  64. Hannah Anglin-Jaffe (2013). Signs of Resistance: Peer Learning of Sign Languages Within 'Oral' Schools for the Deaf. Studies in Philosophy and Education 32 (3):261-271.score: 18.0
    This article explores the role of the Deaf child as peer educator. In schools where sign languages were banned, Deaf children became the educators of their Deaf peers in a number of contexts worldwide. This paper analyses how this peer education of sign language worked in context by drawing on two examples from boarding schools for the deaf in Nicaragua and Thailand. The argument is advanced that these practices constituted a child-led oppositional pedagogy. A connection is drawn to Freire’s (1972) (...)
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  65. Francis Bacon (1851/2001). The Advancement of Learning. Modern Library.score: 18.0
    Francis Bacon, lawyer, statesman, and philosopher, remains one of the most effectual thinkers in European intellectual history. We can trace his influence from Kant in the 1700s to Darwin a century later. The Advancement of Learning , first published in 1605, contains an unprecedented and thorough systematization of the whole range of human knowledge. Bacon’s argument that the sciences should move away from divine philosophy and embrace empirical observation would forever change the way philosophers and natural scientists interpret their (...)
     
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  66. Lorenzo Carlucci & John Case (2013). On the Necessity of U-Shaped Learning. Topics in Cognitive Science 5 (1):56-88.score: 18.0
    A U-shaped curve in a cognitive-developmental trajectory refers to a three-step process: good performance followed by bad performance followed by good performance once again. U-shaped curves have been observed in a wide variety of cognitive-developmental and learning contexts. U-shaped learning seems to contradict the idea that learning is a monotonic, cumulative process and thus constitutes a challenge for competing theories of cognitive development and learning. U-shaped behavior in language learning (in particular in learning English (...)
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  67. Sean Fulop & Nick Chater (2013). Editors' Introduction: Why Formal Learning Theory Matters for Cognitive Science. Topics in Cognitive Science 5 (1):3-12.score: 18.0
    This article reviews a number of different areas in the foundations of formal learning theory. After outlining the general framework for formal models of learning, the Bayesian approach to learning is summarized. This leads to a discussion of Solomonoff's Universal Prior Distribution for Bayesian learning. Gold's model of identification in the limit is also outlined. We next discuss a number of aspects of learning theory raised in contributed papers, related to both computational and representational complexity. (...)
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  68. Bryan R. Gibson, Timothy T. Rogers & Xiaojin Zhu (2013). Human Semi-Supervised Learning. Topics in Cognitive Science 5 (1):132-172.score: 18.0
    Most empirical work in human categorization has studied learning in either fully supervised or fully unsupervised scenarios. Most real-world learning scenarios, however, are semi-supervised: Learners receive a great deal of unlabeled information from the world, coupled with occasional experiences in which items are directly labeled by a knowledgeable source. A large body of work in machine learning has investigated how learning can exploit both labeled and unlabeled data provided to a learner. Using equivalences between models found (...)
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  69. Anne S. Hsu, Nick Chater & Paul Vitányi (2013). Language Learning From Positive Evidence, Reconsidered: A Simplicity-Based Approach. Topics in Cognitive Science 5 (1):35-55.score: 18.0
    Children learn their native language by exposure to their linguistic and communicative environment, but apparently without requiring that their mistakes be corrected. Such learning from “positive evidence” has been viewed as raising “logical” problems for language acquisition. In particular, without correction, how is the child to recover from conjecturing an over-general grammar, which will be consistent with any sentence that the child hears? There have been many proposals concerning how this “logical problem” can be dissolved. In this study, we (...)
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  70. Luis Jimenez (2003). Intention, Attention, and Consciousness in Probabilistic Sequence Learning. In Luis Jimenez (ed.), Attention and Implicit Learning. John Benjamins.score: 18.0
  71. George Kachergis, Chen Yu & Richard M. Shiffrin (2013). Actively Learning Object Names Across Ambiguous Situations. Topics in Cognitive Science 5 (1):200-213.score: 18.0
    Previous research shows that people can use the co-occurrence of words and objects in ambiguous situations (i.e., containing multiple words and objects) to learn word meanings during a brief passive training period (Yu & Smith, 2007). However, learners in the world are not completely passive but can affect how their environment is structured by moving their heads, eyes, and even objects. These actions can indicate attention to a language teacher, who may then be more likely to name the attended objects. (...)
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  72. Paul Oskar Kristeller (1974). Medieval Aspects of Renaissance Learning. Durham, N.C.,Duke University Press.score: 18.0
    The scholar and his public in the late Middle Ages and the Renaissance.--Thomism and the Italian thought of the Renaissance.--The contribution of religious orders to Renaissance thought and learning.--Bibliography (p. [115]-120).
     
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  73. T. Lambert (2003). Visual Orienting, Learning and Conscious Awareness. In Luis Jimenez (ed.), Attention and Implicit Learning. John Benjamins.score: 18.0
  74. David R. Shanks (2003). Attention and Awareness in 'Implicit' Sequence Learning. In L. Jiminez (ed.), Attention and Implicit Learning. John Benjamins.score: 18.0
  75. Mark Stein (2004). Theories of Experiential Learning and the Unconscious. In Laurence J. Gould, Lionel F. Stapley & Mark Stein (eds.), Experiential Learning in Organizations: Applications of the Tavistock Group Relations Approach: Contributions in Honour of Eric J. Miller.score: 18.0
     
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  76. Erik D. Thiessen & Philip I. Pavlik (2013). iMinerva: A Mathematical Model of Distributional Statistical Learning. Cognitive Science 37 (2):310-343.score: 18.0
    Statistical learning refers to the ability to identify structure in the input based on its statistical properties. For many linguistic structures, the relevant statistical features are distributional: They are related to the frequency and variability of exemplars in the input. These distributional regularities have been suggested to play a role in many different aspects of language learning, including phonetic categories, using phonemic distinctions in word learning, and discovering non-adjacent relations. On the surface, these different aspects share few (...)
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  77. John A. Tucker (2013). Skepticism and the Neo-Confucian Canon: Itō Jinsai's Philosophical Critique of the Great Learning. Dao: A Journal of Comparative Philosophy 12 (1):11-39.score: 18.0
    This study examines Itō Jinsai’s 伊藤仁斎 (1627–1705) criticisms of the Great Learning (C: Daxue 大學 J: Daigaku). Three primary sources are considered: Jinsai’s Shigi sakumon 私擬策問 (Personal Essays, 1668); the Daigaku teihon 大學定本 (The Definitive Text of the Great Learning, manuscript 1685); and his essay, “Daigaku wa Kōshi no isho ni arazaru no ben” 大學非孔氏之遺書辨 (The Great Learning is not a Writing Confucius Transmitted, 1705), appended to his Gomō jigi 語孟字義. The study suggests that Jinsai’s critical inclinations (...)
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  78. Yanping Liu, Erik D. Reichle & Ding-Guo Gao (2013). Using Reinforcement Learning to Examine Dynamic Attention Allocation During Reading. Cognitive Science 37 (4).score: 16.0
    A fundamental question in reading research concerns whether attention is allocated strictly serially, supporting lexical processing of one word at a time, or in parallel, supporting concurrent lexical processing of two or more words (Reichle, Liversedge, Pollatsek, & Rayner, 2009). The origins of this debate are reviewed. We then report three simulations to address this question using artificial reading agents (Liu & Reichle, 2010; Reichle & Laurent, 2006) that learn to dynamically allocate attention to 1–4 words to “read” as efficiently (...)
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  79. Mike Fleetham (2006). Multiple Intelligences in Practice: Enhancing Self-Esteem and Learning in the Classroom. Network Continuum Education.score: 15.0
    This accessible guide gives a clear introduction to MI and provides concrete examples of how you can use it in your teaching.
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  80. John N. Williams (2005). Learning Without Awareness. Studies in Second Language Acquisition. Special Issue 27 (2):269-304.score: 15.0
  81. Axel Cleeremans & Luis Jimenez (2002). Implicit Learning and Consciousness: A Graded, Dynamic Perspective. In Robert M. French & Axel Cleeremans (eds.), Implicit Learning and Consciousness: An Empirical. Psychology Press.score: 15.0
    While the study of implicit learning is nothing new, the field as a whole has come to embody — over the last decade or so — ongoing questioning about three of the most fundamental debates in the cognitive sciences: The nature of consciousness, the nature of mental representation (in particular the difficult issue of abstraction), and the role of experience in shaping the cognitive system. Our main goal in this chapter is to offer a framework that attempts to integrate (...)
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  82. Bettina Davou (2002). Unconscious Processes Influencing Learning. Psychodynamic Practice 8 (3):277-294.score: 15.0
  83. Patricia S. Churchland (1978). Fodor on Language Learning. Synthese 38 (May):149-59.score: 15.0
  84. John Emery Murdoch & Edith Dudley Sylla (eds.) (1975). The Cultural Context of Medieval Learning: Proceedings of the First International Colloquium on Philosophy, Science, and Theology in the Middle Ages--September 1973. D. Reidel Pub. Co..score: 15.0
    JOHN E. MURDOCH AND EDITH DUDLEY SYLLA INTRODUCTION Conferences and colloquia are held and their results often published, but very rarely is any account ...
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  85. Myles Bogner, Uma Ramamurthy & Stan Franklin (2000). Consciousness and Conceptual Learning in a Socially Situated Agent. In Kerstin Dauthenhahn (ed.), Human Cognition and Social Agent Technology. Amsterdam: John Benjamins Publishing Company.score: 15.0
  86. Axel Cleeremans & L. JimC)nez (1998). Implicit Sequence Learning: The Truth is in the Details. In Michael A. Stadler & Peter A. Frensch (eds.), Handbook of Implicit Learning. Newbury Park, CA: Sage.score: 15.0
    Over the past decade, sequence learning has gradually become a central paradigm through which to study implicit learning. In this chapter, we start by briefly summarizing the results obtained with different variants of the sequence learning paradigm. We distinguish three subparadigms in terms of whether the stimulus material is generated either by following a fixed and repeating sequence (e.g., Nissen & Bullemer, 1987), by relying on a complex set of rules from which one can produce several alternative (...)
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  87. Luis Jimenez (ed.) (2003). Attention and Implicit Learning. John Benjamins.score: 15.0
  88. D. W. Hamlyn (1983). Perception, Learning, and the Self: Essays in the Philosophy of Psychology. Routledge & K. Paul.score: 15.0
    INTRODUCTION If there is one underlying implication in the following essays it is the inadequacy of the information-processing model for cognitive ...
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  89. Elisabeth Norman, Mark C. Price & Simon C. Duff (2006). Fringe Consciousness in Sequence Learning: The Influence of Individual Differences. Consciousness and Cognition 15 (4):723-760.score: 15.0
  90. James R. Schmidt, Matthew J. C. Crump, Jim Cheesman & Derek Besner (2007). Contingency Learning Without Awareness: Evidence for Implicit Control. Consciousness and Cognition 16 (2):421-435.score: 15.0
  91. Flavio T. P. Oliveira & David Goodman (2004). Conscious and Effortful or Effortless and Automatic: A Practice/Performance Paradox in Motor Learning. Perceptual and Motor Skills 99 (1):315-324.score: 15.0
  92. Edwin M. Robertson, Alvaro Pascual-Leone & Daniel Z. Press (2004). Awareness Modifies the Skill-Learning Benefits of Sleep. Current Biology 14 (3):208-212.score: 15.0
  93. Daniel B. Willingham, Joanna Salidis & John D. E. Gabrieli (2002). Direct Comparison of Neural Systems Mediating Conscious and Unconscious Skill Learning. Journal of Neurophysiology 88 (3):1451-1460.score: 15.0
  94. Thomas Schmidt (2006). Learning Under Anesthesia: Checking the Light in the Fridge? Commentary on Deeprose and Andrade (2006). Consciousness and Cognition 15 (1):24-27.score: 15.0
  95. Jon Williamson, The Philosophy of Science and its Relation to Machine Learning.score: 15.0
    In this chapter I discuss connections between machine learning and the philosophy of science. First I consider the relationship between the two disciplines. There is a clear analogy between hypothesis choice in science and model selection in machine learning. While this analogy has been invoked to argue that the two disciplines are essentially doing the same thing and should merge, I maintain that the disciplines are distinct but related and that there is a dynamic interaction operating between the (...)
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  96. Anthony Randal McIntosh, M. Natasha Rajah & Nancy J. Lobaugh (2003). Functional Connectivity of the Medial Temporal Lobe Relates to Learning and Awareness. Journal of Neuroscience 23 (16):6520-6528.score: 15.0
  97. Peter M. Milner (1999). The Autonomous Brain: A Neural Theory of Attention and Learning. L. Erlbaum Associates.score: 15.0
    The thesis of this bk is that the brain is innately constructed to initiate behaviors likely to promote the survival of the species & to sensitize sensory systems to stimuli required for those behaviors. Intended for behavioral & brain scientists.
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  98. S. Russell (1991). Inductive Learning by Machines. Philosophical Studies 64 (October):37-64.score: 15.0
  99. Carol Slater (1994). Discrimination Without Indication: Why Dretske Can't Lean on Learning. Mind and Language 9 (2):163-80.score: 15.0
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  100. Paul R. Thagard (1990). Philosophy and Machine Learning. Canadian Journal of Philosophy 20 (2):261-76.score: 15.0
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