Results for 'Learning theory'

995 found
Order:
  1. Pragmatism : A Learning Theory for the Future.Bente Elkjaer - 2009 - In Knud Illeris (ed.), Contemporary Theories of Learning: Learning Theorists -- In Their Own Words. London: Routledge. pp. 74-89.
    A theory of learning for the future advocates the teaching of a preparedness to respond in a creative way to difference and otherness. This includes an ability to act imaginatively in situations of uncertainties. John Dewey’s pragmatism holds the key to such a learning theory his view of the continuous meetings of individuals and environments as experimental and playful. That pragmatism has not yet been acknowledged as a relevant learning theory for the future may (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  2. How to Learn From Theory-Dependent Evidence; or Commutativity and Holism: A Solution for Conditionalizers.J. Dmitri Gallow - 2014 - British Journal for the Philosophy of Science 65 (3):493-519.
    Weisberg ([2009]) provides an argument that neither conditionalization nor Jeffrey conditionalization is capable of accommodating the holist’s claim that beliefs acquired directly from experience can suffer undercutting defeat. I diagnose this failure as stemming from the fact that neither conditionalization nor Jeffrey conditionalization give any advice about how to rationally respond to theory-dependent evidence, and I propose a novel updating procedure that does tell us how to respond to evidence like this. This holistic updating rule yields conditionalization as a (...)
    Download  
     
    Export citation  
     
    Bookmark   9 citations  
  3. Adaptive Intelligent Tutoring System for Learning Computer Theory.Mohammed A. Al-Nakhal & Samy S. Abu Naser - 2017 - European Academic Research 4 (10).
    In this paper, we present an intelligent tutoring system developed to help students in learning Computer Theory. The Intelligent tutoring system was built using ITSB authoring tool. The system helps students to learn finite automata, pushdown automata, Turing machines and examines the relationship between these automata and formal languages, deterministic and nondeterministic machines, regular expressions, context free grammars, undecidability, and complexity. During the process the intelligent tutoring system gives assistance and feedback of many types in an intelligent manner (...)
    Download  
     
    Export citation  
     
    Bookmark   12 citations  
  4. A Unified Account of General Learning Mechanisms and Theory‐of‐Mind Development.Theodore Bach - 2014 - Mind and Language 29 (3):351-381.
    Modularity theorists have challenged that there are, or could be, general learning mechanisms that explain theory-of-mind development. In response, supporters of the ‘scientific theory-theory’ account of theory-of-mind development have appealed to children's use of auxiliary hypotheses and probabilistic causal modeling. This article argues that these general learning mechanisms are not sufficient to meet the modularist's challenge. The article then explores an alternative domain-general learning mechanism by proposing that children grasp the concept belief through (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  5. A Bio-Logical Theory of Animal Learning.David Guez - 2009 - Biological Theory 4 (2):148-158.
    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 (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  6. A Theory Explains Deep Learning.Kenneth Kijun Lee & Chase Kihwan Lee - manuscript
    This is our journal for developing Deduction Theory and studying Deep Learning and Artificial intelligence. Deduction Theory is a Theory of Deducing World’s Relativity by Information Coupling and Asymmetry. We focus on information processing, see intelligence as an information structure that relatively close object-oriented, probability-oriented, unsupervised learning, relativity information processing and massive automated information processing. We see deep learning and machine learning as an attempt to make all types of information processing relatively close (...)
    Download  
     
    Export citation  
     
    Bookmark  
  7. Dewey's Theory of Inquiry and Experiential Learning.Field Richard W. - manuscript
    A discussion of John Dewey's theory of inquiry and what it does and does not imply concerning good educational practice.
    Download  
     
    Export citation  
     
    Bookmark  
  8. Semantic Information G Theory and Logical Bayesian Inference for Machine Learning.Chenguang Lu - 2019 - Information 10 (8):261.
    An important problem with machine learning is that when label number n>2, it is very difficult to construct and optimize a group of learning functions, and we wish that optimized learning functions are still useful when prior distribution P(x) (where x is an instance) is changed. To resolve this problem, the semantic information G theory, Logical Bayesian Inference (LBI), and a group of Channel Matching (CM) algorithms together form a systematic solution. MultilabelMultilabel A semantic channel in (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  9.  86
    Lessons From Learning the Craft of Theory-Driven Research.Michael A. Dover - 2010 - Proceedings of the American Sociological Association 2010.
    This article presents a case study of the structure and logic of the author’s dissertation, with a focus on theoretical content. Designed for use in proposal writing seminars or research methods courses, the article stresses the value of identifying the originating, specifying and subsidiary research questions; clarifying the subject and object of the research; situating research within a particular research tradition, and using a competing theories approach. The article stresses the need to identify conceptual problems and empirical problems and their (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  10.  76
    What Can the Capabilities Approach Learn From an Ubuntu Ethic? A Relational Approach to Development Theory.Nimi Hoffmann & Thaddeus Metz - 2017 - World Development 97 (September):153–164.
    Over the last two decades, the capabilities approach has become an increasingly influential theory of development. It conceptualises human wellbeing in terms of an individual's ability to achieve functionings we have reason to value. In contrast, the African ethic of ubuntu views human flourishing as the propensity to pursue relations of fellowship with others, such that relationships have fundamental value. These two theoretical perspectives seem to be in tension with each other; while the capabilities approach focuses on individuals as (...)
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark   7 citations  
  11. Distributed Learning: Educating and Assessing Extended Cognitive Systems.Richard Heersmink & Simon Knight - 2018 - Philosophical Psychology 31 (6):969-990.
    Extended and distributed cognition theories argue that human cognitive systems sometimes include non-biological objects. On these views, the physical supervenience base of cognitive systems is thus not the biological brain or even the embodied organism, but an organism-plus-artifacts. In this paper, we provide a novel account of the implications of these views for learning, education, and assessment. We start by conceptualising how we learn to assemble extended cognitive systems by internalising cultural norms and practices. Having a better grip on (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  12. William James' Theory of Universals: Approach to Learning.Mark Maller - 2012 - Linguistic and Philosophical Investigations 11:62-73.
    xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx.
    Download  
     
    Export citation  
     
    Bookmark  
  13. Learning in Lithic Landscapes: A Reconsideration of the Hominid “Toolmaking” Niche.Peter Hiscock - 2014 - Biological Theory 9 (1):27-41.
    This article reconsiders the early hominid ‘‘lithic niche’’ by examining the social implications of stone artifact making. I reject the idea that making tools for use is an adequate explanation of the elaborate artifact forms of the Lower Palaeolithic, or a sufficient cause for long-term trends in hominid technology. I then advance an alternative mechanism founded on the claim that competency in making stone artifacts requires extended learning, and that excellence in artifact making is attained only by highly skilled (...)
    Download  
     
    Export citation  
     
    Bookmark   22 citations  
  14. A Statistical Learning Approach to a Problem of Induction.Kino Zhao - manuscript
    At its strongest, Hume's problem of induction denies the existence of any well justified assumptionless inductive inference rule. At the weakest, it challenges our ability to articulate and apply good inductive inference rules. This paper examines an analysis that is closer to the latter camp. It reviews one answer to this problem drawn from the VC theorem in statistical learning theory and argues for its inadequacy. In particular, I show that it cannot be computed, in general, whether we (...)
    Download  
     
    Export citation  
     
    Bookmark  
  15.  38
    The Learning-Consciousness Connection.Jonathan Birch, Simona Ginsburg & Eva Jablonka - 2021 - Biology and Philosophy 36 (5):1-14.
    This is a response to the nine commentaries on our target article “Unlimited Associative Learning: A primer and some predictions”. Our responses are organized by theme rather than by author. We present a minimal functional architecture for Unlimited Associative Learning that aims to tie to together the list of capacities presented in the target article. We explain why we discount higher-order thought theories of consciousness. We respond to the criticism that we have overplayed the importance of learning (...)
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark   1 citation  
  16. Learning Networks and Connective Knowledge.Stephen Downes - 2010 - 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.
    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 (...)
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark   2 citations  
  17. Learning Concepts: A Learning-Theoretic Solution to the Complex-First Paradox.Nina Laura Poth & Peter Brössel - 2020 - Philosophy of Science 87 (1):135-151.
    Children acquire complex concepts like DOG earlier than simple concepts like BROWN, even though our best neuroscientific theories suggest that learning the former is harder than learning the latter and, thus, should take more time (Werning 2010). This is the Complex- First Paradox. We present a novel solution to the Complex-First Paradox. Our solution builds on a generalization of Xu and Tenenbaum’s (2007) Bayesian model of word learning. By focusing on a rational theory of concept (...), we show that it is easier to infer the meaning of complex concepts than that of simple concepts. (shrink)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  18. Learning From Failure: Shame and Emotion Regulation in Virtue as Skill.Matt Stichter - 2020 - Ethical Theory and Moral Practice 23 (2):341-354.
    On an account of virtue as skill, virtues are acquired in the ways that skills are acquired. In this paper I focus on one implication of that account that is deserving of greater attention, which is that becoming more skillful requires learning from one’s failures, but that turns out to be especially challenging when dealing with moral failures. In skill acquisition, skills are improved by deliberate practice, where you strive to correct past mistakes and learn how to overcome your (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  19. Logical Ignorance and Logical Learning.Richard Pettigrew - 2021 - Synthese 198 (10):9991-10020.
    According to certain normative theories in epistemology, rationality requires us to be logically omniscient. Yet this prescription clashes with our ordinary judgments of rationality. How should we resolve this tension? In this paper, I focus particularly on the logical omniscience requirement in Bayesian epistemology. Building on a key insight by Hacking :311–325, 1967), I develop a version of Bayesianism that permits logical ignorance. This includes: an account of the synchronic norms that govern a logically ignorant individual at any given time; (...)
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  20. Adaptive ITS for Learning Computer Theory.Mohamed Nakhal & Bastami Bashhar - 2017 - European Academic Research 4 (10):8770-8782.
    In this paper, we present an intelligent tutoring system developed to help students in learning Computer Theory. The Intelligent tutoring system was built using ITSB authoring tool. The system helps students to learn finite automata, pushdown automata, Turing machines and examines the relationship between these automata and formal languages, deterministic and nondeterministic machines, regular expressions, context free grammars, undecidability, and complexity. During the process the intelligent tutoring system gives assistance and feedback of many types in an intelligent manner (...)
    Download  
     
    Export citation  
     
    Bookmark  
  21. Learning to See.Boyd Millar - 2020 - Mind and Language 35 (5):601-620.
    The reports of individuals who have had their vision restored after a long period of blindness suggest that, immediately after regaining their vision, such individuals are not able to recognize shapes by vision alone. It is often assumed that the empirical literature on sight restoration tells us something important about the relationship between visual and tactile representations of shape. However, I maintain that, immediately after having their sight restored, at least some newly sighted individuals undergo visual experiences that instantiate basic (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  22. Information, Learning and Falsification.David Balduzzi - 2011
    There are (at least) three approaches to quantifying information. The first, algorithmic information or Kolmogorov complexity, takes events as strings and, given a universal Turing machine, quantifies the information content of a string as the length of the shortest program producing it [1]. The second, Shannon information, takes events as belonging to ensembles and quantifies the information resulting from observing the given event in terms of the number of alternate events that have been ruled out [2]. The third, statistical (...) theory, has introduced measures of capacity that control (in part) the expected risk of classifiers [3]. These capacities quantify the expectations regarding future data that learning algorithms embed into classifiers. Solomonoff and Hutter have applied algorithmic information to prove remarkable results on universal induction. Shannon information provides the mathematical foundation for communication and coding theory. However, both approaches have shortcomings. Algorithmic information is not computable, severely limiting its practical usefulness. Shannon information refers to ensembles rather than actual events: it makes no sense to compute the Shannon information of a single string – or rather, there are many answers to this question depending on how a related ensemble is constructed. Although there are asymptotic results linking algorithmic and Shannon information, it is unsatisfying that there is such a large gap – a difference in kind – between the two measures. This note describes a new method of quantifying information, effective information, that links algorithmic information to Shannon information, and also links both to capacities arising in statistical learning theory [4, 5]. After introducing the measure, we show that it provides a non-universal analog of Kolmogorov complexity. We then apply it to derive basic capacities in statistical learning theory: empirical VC-entropy and empirical Rademacher complexity. A nice byproduct of our approach is an interpretation of the explanatory power of a learning algorithm in terms of the number of hypotheses it falsifies [6], counted in two different ways for the two capacities. We also discuss how effective information relates to information gain, Shannon and mutual information. (shrink)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  23. Teaching & Learning Guide For: Duality and Ontology.Baptiste Le Bihan & James Read - 2018 - Philosophy Compass 13 (12):e12555.
    Dualities are a pervasive phenomenon in contemporary physics, in which two physical theories are empirically equivalent, yet prima facie make different ontological claims about the world (potentially very different claims—differing in e.g. the number and radius of dimensions of the universe). Dualities thus present a particular instantiation of the well-known notion of underdetermination of theory by evidence. Many different philosophical proposals have been made for how such putative underdetermination might be resolved—this continues to be a programme of active research.
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  24. Tic-Tac-Toe Learning Using Artificial Neural Networks.Mohaned Abu Dalffa, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (2):9-19.
    Throughout this research, imposing the training of an Artificial Neural Network (ANN) to play tic-tac-toe bored game, by training the ANN to play the tic-tac-toe logic using the set of mathematical combination of the sequences that could be played by the system and using both the Gradient Descent Algorithm explicitly and the Elimination theory rules implicitly. And so on the system should be able to produce imunate amalgamations to solve every state within the game course to make better of (...)
    Download  
     
    Export citation  
     
    Bookmark   25 citations  
  25.  94
    Learning by Doing: Assessment of Apprentices Performances Across Partner Institutions in Metro Manila.L. F. Cada Jr - 2020 - Research Review International Journal of Multidisciplinary 5 (08):114-122.
    Apprenticeship is one way of learning by doing. The Student Apprenticeship Program (SAP) or Apprenticeship as referred to in this study is a curricular program of the Institute of Accounts, Business and Finance (IABF) of the Far Eastern University - Manila. It aims to enhance the preparation of the students for actual employment after college graduation. A study was conducted on the sixty-nine (69) Business Administration interns of a private university in Manila during the first semester of academic year (...)
    Download  
     
    Export citation  
     
    Bookmark  
  26. Learning as Hypothesis Testing: Learning Conditional and Probabilistic Information.Jonathan Vandenburgh - manuscript
    Complex constraints like conditionals ('If A, then B') and probabilistic constraints ('The probability that A is p') pose problems for Bayesian theories of learning. Since these propositions do not express constraints on outcomes, agents cannot simply conditionalize on the new information. Furthermore, a natural extension of conditionalization, relative information minimization, leads to many counterintuitive predictions, evidenced by the sundowners problem and the Judy Benjamin problem. Building on the notion of a `paradigm shift' and empirical research in psychology and economics, (...)
    Download  
     
    Export citation  
     
    Bookmark  
  27. How to Learn the Natural Numbers: Inductive Inference and the Acquisition of Number Concepts.Eric Margolis & Stephen Laurence - 2008 - Cognition 106 (2):924-939.
    Theories of number concepts often suppose that the natural numbers are acquired as children learn to count and as they draw an induction based on their interpretation of the first few count words. In a bold critique of this general approach, Rips, Asmuth, Bloomfield [Rips, L., Asmuth, J. & Bloomfield, A.. Giving the boot to the bootstrap: How not to learn the natural numbers. Cognition, 101, B51–B60.] argue that such an inductive inference is consistent with a representational system that clearly (...)
    Download  
     
    Export citation  
     
    Bookmark   15 citations  
  28. Fair Machine Learning Under Partial Compliance.Jessica Dai, Sina Fazelpour & Zachary Lipton - 2021 - In Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society. pp. 55–65.
    Typically, fair machine learning research focuses on a single decision maker and assumes that the underlying population is stationary. However, many of the critical domains motivating this work are characterized by competitive marketplaces with many decision makers. Realistically, we might expect only a subset of them to adopt any non-compulsory fairness-conscious policy, a situation that political philosophers call partial compliance. This possibility raises important questions: how does partial compliance and the consequent strategic behavior of decision subjects affect the allocation (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  29. Teaching & Learning Guide For: Basic Needs in Normative Contexts.Thomas Pölzler - 2021 - Philosophy Compass 16 (5):e12732.
    From the day on which humans are born they need things. Some of these needs seem “basic,” such as our needs for food, water or shelter. Everybody has these needs. We cannot escape them. We also cannot escape the serious harm that arises when these needs remain unsatisfied. It is thus no wonder that in thinking about what we ought to do some researchers have suggested to first and foremost focus on people's basic needs. Such need‐based theories must answer three (...)
    Download  
     
    Export citation  
     
    Bookmark  
  30. Building Machines That Learn and Think About Morality.Christopher Burr & Geoff Keeling - 2018 - In Proceedings of the Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour (AISB 2018). Society for the Study of Artificial Intelligence and Simulation of Behaviour.
    Lake et al. propose three criteria which, they argue, will bring artificial intelligence (AI) systems closer to human cognitive abilities. In this paper, we explore the application of these criteria to a particular domain of human cognition: our capacity for moral reasoning. In doing so, we explore a set of considerations relevant to the development of AI moral decision-making. Our main focus is on the relation between dual-process accounts of moral reasoning and model-free/model-based forms of machine learning. We also (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  31. What Can Philosophers Learn From Psychopathy?Heidi L. Maibom - 2018 - European Journal of Analytic Philosophy 14 (1):63-78.
    Many spectacular claims about psychopaths are circulated. This contribution aims at providing the reader with the more complex reality of the phenomenon (or phenomena), and to point to issues of particular interest to philosophers working in moral psychology and moral theory. I first discuss the current evidence regarding psychopaths’ deficient empathy and decision-making skills. I then explore what difference it makes to our thinking whether we regard their deficit dimensionally (as involving abilities that are on or off) and whether (...)
    Download  
     
    Export citation  
     
    Bookmark   11 citations  
  32.  73
    Game Technologies to Assist Learning of Communication Skills in Dialogic Settings for Persons with Aphasia.Ylva Backman, Viktor Gardelli & Peter Parnes - 2021 - International Journal of Emerging Technologies in Learning 16 (3):190-205.
    Persons with aphasia suffer from a loss of communication ability as a consequence of a brain injury. A small strand of research indicates effec- tiveness of dialogic interventions for communication development for persons with aphasia, but a vast amount of research studies shows its effectiveness for other target groups. In this paper, we describe the main parts of the hitherto technological development of an application named Dialogica that is (i) aimed at facilitating increased communicative participation in dialogic settings for persons (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  33. Aesthetic Concepts, Perceptual Learning, and Linguistic Enculturation: Considerations From Wittgenstein, Language, and Music.Adam M. Croom - 2012 - Integrative Psychological and Behavioral Science 46:90-117.
    Aesthetic non-cognitivists deny that aesthetic statements express genuinely aesthetic beliefs and instead hold that they work primarily to express something non-cognitive, such as attitudes of approval or disapproval, or desire. Non-cognitivists deny that aesthetic statements express aesthetic beliefs because they deny that there are aesthetic features in the world for aesthetic beliefs to represent. Their assumption, shared by scientists and theorists of mind alike, was that language-users possess cognitive mechanisms with which to objectively grasp abstract rules fixed independently of human (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  34. Distance Learning: Empathy and Culture in Junot Diaz’s “Wildwood”. [REVIEW]Rebecca Garden - 2013 - Journal of Medical Humanities 34 (4):439-450.
    This essay discusses critical approaches to culture, difference, and empathy in health care education through a reading of Junot Diaz’s “Wildwood” chapter from the 2007 novel The Brief Wondrous Life of Oscar Wao. I begin with an analysis of the way that Diaz’s narrative invites readers to imagine and explore the experiences of others with subtlety and complexity. My reading of “Wildwood” illuminates its double-edged injunction to try to imagine another’s perspective while recognizing the limits to—or even the impossibility of—that (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  35. A Theory of the Epigenesis of Neuronal Networks by Selective Stabilization of Synapses.Jean Pierre Changeux, Philippe Courrège & Antoine Danchin - 1973 - Proceedings of the National Academy of Sciences Usa 70 (10):2974-8.
    A formalism is introduced to represent the connective organization of an evolving neuronal network and the effects of environment on this organization by stabilization or degeneration of labile synapses associated with functioning. Learning, or the acquisition of an associative property, is related to a characteristic variability of the connective organization: the interaction of the environment with the genetic program is printed as a particular pattern of such organization through neuronal functioning. An application of the theory to the development (...)
    Download  
     
    Export citation  
     
    Bookmark   14 citations  
  36. A Theory of Predictive Dissonance: Predictive Processing Presents a New Take on Cognitive Dissonance.Roope Oskari Kaaronen - 2018 - Frontiers in Psychology 9.
    This article is a comparative study between predictive processing (PP, or predictive coding) and cognitive dissonance (CD) theory. The theory of CD, one of the most influential and extensively studied theories in social psychology, is shown to be highly compatible with recent developments in PP. This is particularly evident in the notion that both theories deal with strategies to reduce perceived error signals. However, reasons exist to update the theory of CD to one of “predictive dissonance.” First, (...)
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  37.  82
    The Explanation Game: A Formal Framework for Interpretable Machine Learning.David S. Watson & Luciano Floridi - 2020 - Synthese 198 (10):1–⁠32.
    We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to (...)
    Download  
     
    Export citation  
     
    Bookmark   11 citations  
  38. Théories à processus duaux et théories de l’éducation : Le cas de l’enseignement de la pensée critique et de la logique.Guillaume Beaulac & Serge Robert - 2011 - Les ateliers de l'éthique/The Ethics Forum 6 (1):63-77.
    Many theories about the teaching of logic and critical thinking take for granted that theoretical learning, the learning of formal rules for example, and its practical application are sufficient to master the tools taught and to take the habit of using them. However, this way of teaching is not efficient, a conclusion supported by much work in cognitive science. Approaching cognition evolutionarily with dual-process theories allows for an explanation of these insufficiencies and offers clues on how we could (...)
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark   2 citations  
  39. Can Motto-Goals Outperform Learning and Performance Goals? Influence of Goal Setting on Performance and Affect in a Complex Problem Solving Task.Miriam Sophia Rohe, Joachim Funke, Maja Storch & Julia Weber - 2016 - Journal of Dynamic Decision Making 2 (1):1-15.
    In this paper, we bring together research on complex problem solving with that on motivational psychology about goal setting. Complex problems require motivational effort because of their inherent difficulties. Goal Setting Theory has shown with simple tasks that high, specific performance goals lead to better performance outcome than do-your-best goals. However, in complex tasks, learning goals have proven more effective than performance goals. Based on the Zurich Resource Model, so-called motto-goals should activate a person’s resources through positive affect. (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  40.  62
    Learning to Appreciate the Gray Areas: A Critical Notice of Anil Gupta’s “Conscious Experience”. [REVIEW]Eric Hochstein - 2020 - Canadian Journal of Philosophy 50:801-813.
    Anil Gupta’s Conscious Experience: A Logical Inquiry provides an impressive and novel account of rational justification based on conscious experience which is used as a foundation for a new theory of empiricism. In this critical notice, I argue that Gupta’s project is fascinating, but is often hampered by a lack of sufficient philosophical justification and clarity regarding some essential features of his project, as well as a lack of engagement with relevant scientific domains that would directly bear on it, (...)
    Download  
     
    Export citation  
     
    Bookmark  
  41. Evolutionary Theory and the Epistemology of Science.Kevin McCain & Brad Weslake - 2013 - In Kostas Kampourakis (ed.), The Philosophy of Biology: A Companion for Educators. Springer. pp. 101-119.
    Evolutionary theory is a paradigmatic example of a well-supported scientific theory. In this chapter we consider a number of objections to evolutionary theory, and show how responding to these objections reveals aspects of the way in which scientific theories are supported by evidence. Teaching these objections can therefore serve two pedagogical aims: students can learn the right way to respond to some popular arguments against evolutionary theory, and they can learn some basic features of the structure (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  42. Wisdom of the Crowds Vs. Groupthink: Learning in Groups and in Isolation.Conor Mayo-Wilson, Kevin Zollman & David Danks - 2013 - International Journal of Game Theory 42 (3):695-723.
    We evaluate the asymptotic performance of boundedly-rational strategies in multi-armed bandit problems, where performance is measured in terms of the tendency (in the limit) to play optimal actions in either (i) isolation or (ii) networks of other learners. We show that, for many strategies commonly employed in economics, psychology, and machine learning, performance in isolation and performance in networks are essentially unrelated. Our results suggest that the appropriateness of various, common boundedly-rational strategies depends crucially upon the social context (if (...)
    Download  
     
    Export citation  
     
    Bookmark   11 citations  
  43. Paradoxical Education: Learning to Unlearn What We Think We Have Learned.Zachary Isrow - 2021 - World Journal of Education and Humanities 3 (3):57-65.
    There is no shortage of pedagogical theories from the tradition formal methods of instruction to the free-play methods of unschooling. A sharp shift in education and instruction models took place with the introduction of critical pedagogy. The focus was no longer on the authority of the teacher and the submissive, passive approach taken by the learner, but rather on the engagement between the two. Still, even when critical pedagogy is utilized in a formal model of education something is missing from (...)
    Download  
     
    Export citation  
     
    Bookmark  
  44. Diagnosis of Blood Cells Using Deep Learning.Ahmed J. Khalil & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (2):69-84.
    In computer science, Artificial Intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Deep Learning is a new field of research. One of the branches of Artificial Intelligence Science deals with the creation of theories and algorithms (...)
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  45. Self-Locating Belief and Updating on Learning.Darren Bradley - 2020 - Mind 129 (514):579-584.
    Self-locating beliefs cause a problem for conditionalization. Miriam Schoenfield offers a solution: that on learning E, agents should update on the fact that they learned E. However, Schoenfield is not explicit about whether the fact that they learned E is self-locating. I will argue that if the fact that they learned E is self-locating then the original problem has not been addressed, and if the fact that they learned E is not self-locating then the theory generates implausible verdicts (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  46.  87
    The Use and Misuse of Counterfactuals in Ethical Machine Learning.Atoosa Kasirzadeh & Andrew Smart - 2021 - In ACM Conference on Fairness, Accountability, and Transparency (FAccT 21).
    The use of counterfactuals for considerations of algorithmic fairness and explainability is gaining prominence within the machine learning community and industry. This paper argues for more caution with the use of counterfactuals when the facts to be considered are social categories such as race or gender. We review a broad body of papers from philosophy and social sciences on social ontology and the semantics of counterfactuals, and we conclude that the counterfactual approach in machine learning fairness and social (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  47. The Social Trackways Theory of the Evolution of Human Cognition.Kim Shaw-Williams - 2014 - Biological Theory 9 (1):1-11.
    Only our lineage has ever used trackways reading to find unseen and unheard targets. All other terrestrial animals, including our great ape cousins, use scent trails and airborne odors. Because trackways as natural signs have very different properties, they possess an information-rich narrative structure. There is good evidence we began to exploit conspecific trackways in our deep past, at first purely associatively, for safety and orienteering when foraging in vast featureless wetlands. Since our own old trackways were recognizable they were (...)
    Download  
     
    Export citation  
     
    Bookmark   11 citations  
  48. Basic Beliefs and the Perceptual Learning Problem: A Substantial Challenge for Moderate Foundationalism.Bram M. K. Vaassen - 2016 - Episteme 13 (1):133-149.
    In recent epistemology many philosophers have adhered to a moderate foundationalism according to which some beliefs do not depend on other beliefs for their justification. Reliance on such ‘basic beliefs’ pervades both internalist and externalist theories of justification. In this article I argue that the phenomenon of perceptual learning – the fact that certain ‘expert’ observers are able to form more justified basic beliefs than novice observers – constitutes a challenge for moderate foundationalists. In order to accommodate perceptual (...) cases, the moderate foundationalist will have to characterize the ‘expertise’ of the expert observer in such a way that it cannot be had by novice observers and that it bestows justification on expert basic beliefs independently of any other justification had by the expert. I will argue that the accounts of expert basic beliefs currently present in the literature fail to meet this challenge, as they either result in a too liberal ascription of justification or fail to draw a clear distinction between expert basic beliefs and other spontaneously formed beliefs. Nevertheless, some guidelines for a future solution will be provided. (shrink)
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  49.  41
    Can the World Learn Wisdom?Nicholas Maxwell - 2021 - In Theory of Knowledge; The Ultimate Guide. London, UK: pp. 93-97.
    The crisis of our times is science without wisdom. It is the outcome of an astonishingly successful tradition of scientific and technological research pursued within the context of an academic inquiry that is profoundly and damagingly irrational, in a structural way, when judged from the standpoint of helping humanity make progress towards a wise, enlightened world. This damaging irrationality of academia goes back to the 18th century Enlightenment. The philosophes of the French Enlightenment, in implementing the profound idea that we (...)
    Download  
     
    Export citation  
     
    Bookmark  
  50. From Blended Learning to Learning Onlife : ICTs, Time and Access in Higher Education.Anders Norberg - unknown
    Information and Communication Technologies, ICTs, has now for decades being increasingly taken into use for higher education, enabling distance learning, e-learning and online learning, mainly in parallel to mainstream educational practise. The concept Blended learning aims at the integration of ICTs with these existing educational practices. The term is frequently used, but there is no agreed-upon definition. The general aim of this dissertation is to identify new possible perspectives on ICTs and access to higher education, for (...)
    Download  
     
    Export citation  
     
    Bookmark  
1 — 50 / 995