Results for 'learning'

998 found
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  1. Perceptual Learning and the Contents of Perception.Kevin Connolly - 2014 - Erkenntnis 79 (6):1407-1418.
    Suppose you have recently gained a disposition for recognizing a high-level kind property, like the property of being a wren. Wrens might look different to you now. According to the Phenomenal Contrast Argument, such cases of perceptual learning show that the contents of perception can include high-level kind properties such as the property of being a wren. I detail an alternative explanation for the different look of the wren: a shift in one’s attentional pattern onto other low-level properties. Philosophers (...)
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  2. Machines Learning Values.Steve Petersen - 2020 - In S. Matthew Liao (ed.), Ethics of Artificial Intelligence. New York, USA: Oxford University Press.
    Whether it would take one decade or several centuries, many agree that it is possible to create a *superintelligence*---an artificial intelligence with a godlike ability to achieve its goals. And many who have reflected carefully on this fact agree that our best hope for a "friendly" superintelligence is to design it to *learn* values like ours, since our values are too complex to program or hardwire explicitly. But the value learning approach to AI safety faces three particularly philosophical puzzles: (...)
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  3. Perceptual Learning, the Mere Exposure Effect and Aesthetic Antirealism.Bence Nanay - 2017 - Leonardo 50:58-63.
    It has been argued that some recent experimental findings about the mere exposure effect can be used to argue for aesthetic antirealism: the view that there is no fact of the matter about aesthetic value. The aim of this paper is to assess this argument and point out that this strategy, as it stands, does not work. But we may still be able to use experimental findings about the mere exposure effect in order to engage with the aesthetic realism/antirealism debate. (...)
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  4. Learning Organizations and Their Role in Achieving Organizational Excellence in the Palestinian Universities.Mazen J. Al Shobaki, Samy S. Abu Naser, Youssef M. Abu Amuna & Amal A. Al Hila - 2017 - International Journal of Digital Publication Technology 1 (2):40-85.
    The research aims to identify the learning organizations and their role in achieving organizational excellence in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) workers from the Palestinian universities was selected and the recovery (...)
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  5. 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 (...)
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  6. Bayesian Learning Models of Pain: A Call to Action.Abby Tabor & Christopher Burr - 2019 - Current Opinion in Behavioral Sciences 26:54-61.
    Learning is fundamentally about action, enabling the successful navigation of a changing and uncertain environment. The experience of pain is central to this process, indicating the need for a change in action so as to mitigate potential threat to bodily integrity. This review considers the application of Bayesian models of learning in pain that inherently accommodate uncertainty and action, which, we shall propose are essential in understanding learning in both acute and persistent cases of pain.
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  7.  58
    Perceptual Learning, Categorical Perception, and Cognitive Permeation.Daniel Burnston - forthcoming - Dialectica.
    Proponents of cognitive penetration often argue for the thesis on the basis of combined intuitions about categorical perception and perceptual learning. The claim is that beliefs penetrate perceptions in the course of learning to perceive categories. I argue that this “diachronic” penetration thesis is false. In order to substantiate a robust notion of penetration, the beliefs that enable learning must describe the particular ability that subjects learn. However, they cannot do so, since in order to help with (...)
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  8. Learning Computer Networks Using Intelligent Tutoring System.Mones M. Al-Hanjori, Mohammed Z. Shaath & Samy S. Abu Naser - 2017 - International Journal of Advanced Research and Development 2 (1).
    Intelligent Tutoring Systems (ITS) has a wide influence on the exchange rate, education, health, training, and educational programs. In this paper we describe an intelligent tutoring system that helps student study computer networks. The current ITS provides intelligent presentation of educational content appropriate for students, such as the degree of knowledge, the desired level of detail, assessment, student level, and familiarity with the subject. Our Intelligent tutoring system was developed using ITSB authoring tool for building ITS. A preliminary evaluation of (...)
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  9. 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 (...)
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  10. Machine Learning and Irresponsible Inference: Morally Assessing the Training Data for Image Recognition Systems.Owen King - 2019 - In Matteo Vincenzo D'Alfonso & Don Berkich (eds.), On the Cognitive, Ethical, and Scientific Dimensions of Artificial Intelligence. Springer Verlag. pp. 265-282.
    Just as humans can draw conclusions responsibly or irresponsibly, so too can computers. Machine learning systems that have been trained on data sets that include irresponsible judgments are likely to yield irresponsible predictions as outputs. In this paper I focus on a particular kind of inference a computer system might make: identification of the intentions with which a person acted on the basis of photographic evidence. Such inferences are liable to be morally objectionable, because of a way in which (...)
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  11.  35
    Clinical Applications of Machine Learning Algorithms: Beyond the Black Box.David S. Watson, Jenny Krutzinna, Ian N. Bruce, Christopher E. M. Griffiths, Iain B. McInnes, Michael R. Barnes & Luciano Floridi - 2019 - British Medical Journal 364:I886.
    Machine learning algorithms may radically improve our ability to diagnose and treat disease. For moral, legal, and scientific reasons, it is essential that doctors and patients be able to understand and explain the predictions of these models. Scalable, customisable, and ethical solutions can be achieved by working together with relevant stakeholders, including patients, data scientists, and policy makers.
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  12. 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 (...)
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  13. Perceptual Learning (Network for Sensory Research/University of York Perceptual Learning Workshop, Question One).Kevin Connolly, Dylan Bianchi, Craig French, Lana Kuhle & Andy MacGregor - manuscript
    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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  14. Learning and Value Change.J. Dmitri Gallow - 2019 - Philosophers' Imprint 19:1--22.
    Accuracy-first accounts of rational learning attempt to vindicate the intuitive idea that, while rationally-formed belief need not be true, it is nevertheless likely to be true. To this end, they attempt to show that the Bayesian's rational learning norms are a consequence of the rational pursuit of accuracy. Existing accounts fall short of this goal, for they presuppose evidential norms which are not and cannot be vindicated in terms of the single-minded pursuit of accuracy. I propose an alternative (...)
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  15. Understanding From Machine Learning Models.Emily Sullivan - forthcoming - British Journal for the Philosophy of Science:axz035.
    Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal models provide understanding (...)
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  16. Learning, Evolvability and Exploratory Behaviour: Extending the Evolutionary Reach of Learning.Rachael L. Brown - 2013 - Biology and Philosophy 28 (6):933-955.
    Traditional accounts of the role of learning in evolution have concentrated upon its capacity as a source of fitness to individuals. In this paper I use a case study from invasive species biology—the role of conditioned taste aversion in mitigating the impact of cane toads on the native species of Northern Australia—to highlight a role for learning beyond this—as a source of evolvability to populations. This has two benefits. First, it highlights an otherwise under-appreciated role for learning (...)
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  17. Lemon Classification Using Deep Learning.Jawad Yousif AlZamily & Samy Salim Abu Naser - 2020 - International Journal of Academic Pedagogical Research (IJAPR) 3 (12):16-20.
    Abstract : Background: Vegetable agriculture is very important to human continued existence and remains a key driver of many economies worldwide, especially in underdeveloped and developing economies. Objectives: There is an increasing demand for food and cash crops, due to the increasing in world population and the challenges enforced by climate modifications, there is an urgent need to increase plant production while reducing costs. Methods: In this paper, Lemon classification approach is presented with a dataset that contains approximately 2,000 images (...)
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  18. 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 (...)
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  19. Learning Places: Building Dwelling Thinking Online.D. Kolb - 2000 - Journal of Philosophy of Education 34 (1):121–133.
    What would it take to design a real place online where real learning would happen?
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  20. Cognitive Penetration, Perceptual Learning and Neural Plasticity.Ariel S. Cecchi - 2014 - Dialectica 68 (1):63-95.
    Cognitive penetration of perception, broadly understood, is the influence that the cognitive system has on a perceptual system. The paper shows a form of cognitive penetration in the visual system which I call ‘architectural’. Architectural cognitive penetration is the process whereby the behaviour or the structure of the perceptual system is influenced by the cognitive system, which consequently may have an impact on the content of the perceptual experience. I scrutinize a study in perceptual learning that provides empirical evidence (...)
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  21. Learning and Selection Processes.Marc Artiga - 2010 - Theoria : An International Journal for Theory, History and Fundations of Science 25 (2):197-209.
    In this paper I defend a teleological explanation of normativity, i. e., I argue that what an organism is supposed to do is determined by its etiological function. In particular, I present a teleological account of the normativity that arises in learning processes, and I defend it from some objections.
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  22. Learning, Institutions, and Economic Performance.C. Mantzavinos - 2004 - Perspectives on Politics 2:75-84.
    In this article, we provide a broad overview of the interplay among cognition, belief systems, and institutions, and how they affect economic performance. We argue that a deeper understanding of institutions’ emergence, their working properties, and their effect on economic and political outcomes should begin from an analysis of cognitive processes. We explore the nature of individual and collective learning, stressing that the issue is not whether agents are perfectly or boundedly rational, but rather how human beings actually reason (...)
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  23. 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 a (...)
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  24. Learning to Love the Reviewer.Quan-Hoang Vuong - 2017 - European Science Editing 43 (4):83-83.
    Learning to love the reviewer -/- Issue: 43(4) November 2017. Viewpoint Page 83 -/- Quan Hoang Vuong Western University Hanoi, Centre for Interdisciplinary Social Research, Hanoi, Vietnam.
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  25. Enkrasia or Evidentialism? Learning to Love Mismatch.Maria Lasonen-Aarnio - 2020 - Philosophical Studies 177 (3):597-632.
    I formulate a resilient paradox about epistemic rationality, discuss and reject various solutions, and sketch a way out. The paradox exemplifies a tension between a wide range of views of epistemic justification, on the one hand, and enkratic requirements on rationality, on the other. According to the enkratic requirements, certain mismatched doxastic states are irrational, such as believing p, while believing that it is irrational for one to believe p. I focus on an evidentialist view of justification on which a (...)
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  26. The Cicada Catcher: Learning for Life.Karyn L. Lai - 2019 - In Karyn L. Lai & Wai-wai Chiu (eds.), Skill and Mastery Philosophical Stories from the Zhuangzi. UK: Rowman and Littlefield International. pp. 143 - 162.
    The cicada catcher focuses as much on technique as he does on outcomes. In response to Confucius’ question, he articulates in detail the learning he has undertaken to develop techniques at each level of competence. This chapter explains the connection between the cicada catcher’s development of technique and his orientation toward outcomes. It uses details in this story to contribute to recent discussions in epistemology on the cultivation of technique.
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  27.  31
    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 (...)
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  28. The Archimedean Trap: Why Traditional Reinforcement Learning Will Probably Not Yield AGI.Samuel Allen Alexander - 2020 - Journal of Artificial General Intelligence 11 (1):70-85.
    After generalizing the Archimedean property of real numbers in such a way as to make it adaptable to non-numeric structures, we demonstrate that the real numbers cannot be used to accurately measure non-Archimedean structures. We argue that, since an agent with Artificial General Intelligence (AGI) should have no problem engaging in tasks that inherently involve non-Archimedean rewards, and since traditional reinforcement learning rewards are real numbers, therefore traditional reinforcement learning probably will not lead to AGI. We indicate two (...)
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  29.  34
    Can We Learn From Hidden Mistakes? Self-Fulfilling Prophecy and Responsible Neuroprognostic Innovation.Mayli Mertens, Owen C. King, Michel J. A. M. van Putten & Marianne Boenink - forthcoming - Journal of Medical Ethics.
    A self-fulfilling prophecy (SFP) in neuroprognostication occurs when a patient in coma is predicted to have a poor outcome, and life-sustaining treatment is withdrawn on the basis of that prediction, thus directly bringing about a poor outcome (viz. death) for that patient. In contrast to the predominant emphasis in the bioethics literature, we look beyond the moral issues raised by the possibility that an erroneous prediction might lead to the death of a patient who otherwise would have lived. Instead, we (...)
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  30. Learning Not to Be Naïve: A Comment on the Exchange Between Perrine/Wykstra and Draper.Lara Buchak - 2014 - In Trent Dougherty & Justin McBrayer (eds.), Skeptical Theism: New Essays. Oxford University Press.
    Does postulating skeptical theism undermine the claim that evil strongly confirms atheism over theism? According to Perrine and Wykstra, it does undermine the claim, because evil is no more likely on atheism than on skeptical theism. According to Draper, it does not undermine the claim, because evil is much more likely on atheism than on theism in general. I show that the probability facts alone do not resolve their disagreement, which ultimately rests on which updating procedure – conditionalizing or updating (...)
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  31. 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 special (...)
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  32. Potato Classification Using Deep Learning.Abeer A. Elsharif, Ibtesam M. Dheir, Alaa Soliman Abu Mettleq & Samy S. Abu-Naser - 2020 - International Journal of Academic Pedagogical Research (IJAPR) 3 (12):1-8.
    Abstract: Potatoes are edible tubers, available worldwide and all year long. They are relatively cheap to grow, rich in nutrients, and they can make a delicious treat. The humble potato has fallen in popularity in recent years, due to the interest in low-carb foods. However, the fiber, vitamins, minerals, and phytochemicals it provides can help ward off disease and benefit human health. They are an important staple food in many countries around the world. There are an estimated 200 varieties of (...)
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  33. Type of Tomato Classification Using Deep Learning.Mahmoud A. Alajrami & Samy S. Abu-Naser - 2020 - International Journal of Academic Pedagogical Research (IJAPR) 3 (12):21-25.
    Abstract: Tomatoes are part of the major crops in food security. Tomatoes are plants grown in temperate and hot regions of South American origin from Peru, and then spread to most countries of the world. Tomatoes contain a lot of vitamin C and mineral salts, and are recommended for people with constipation, diabetes and patients with heart and body diseases. Studies and scientific studies have proven the importance of eating tomato juice in reducing the activity of platelets in diabetics, which (...)
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  34. 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; (...)
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  35. Learning to Communicate: The Emergence of Signaling in Spatialized Arrays of Neural Nets.Patrick Grim, Trina Kokalis & Paul St Denis - 2003 - Adaptive Behavior 10:45-70.
    We work with a large spatialized array of individuals in an environment of drifting food sources and predators. The behavior of each individual is generated by its simple neural net; individuals are capable of making one of two sounds and are capable of responding to sounds from their immediate neighbors by opening their mouths or hiding. An individual whose mouth is open in the presence of food is “fed” and gains points; an individual who fails to hide when a predator (...)
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  36. Learning and Teaching in Uncertain Times: A Nietzschean Approach in Professional Higher Education.Henriëtta Joosten - 2013 - Journal of Philosophy of Education 47 (4):548-563.
    Today professionals have to deal with more uncertainties in their field than before. We live in complex and rapidly changing environments. The British philosopher Ronald Barnett adds the term ‘supercomplexity’ to highlight the fact that ‘we can no longer be sure how even to describe the world that faces us’ (Barnett, 2004). Uncertainty is, nevertheless, not a highly appreciated notion. An obvious response to uncertainty is to reduce it—or even better, to wipe it away. The assumption of this approach is (...)
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  37. 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 (...)
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  38. Pictures, Experiential Learning and Phenomenology.Matthew Crippen - 2015 - In András Benedek & Nyiri Kristof (eds.), Saying by Showing, Showing by Saying – Pictures, Parables, Paradoxes. Peter Lang. pp. 83-90.
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  39. Sensory Substitution and Perceptual Learning.Kevin Connolly - forthcoming - In Fiona Macpherson (ed.), Sensory Substitution and Augmentation. Oxford University Press.
    When a user integrates a sensory substitution device into her life, the process involves perceptual learning, that is, ‘relatively long-lasting changes to an organism’s perceptual system that improve its ability to respond to its environment’ (Goldstone 1998: 585). In this paper, I explore ways in which the extensive literature on perceptual learning can be applied to help improve sensory substitution devices. I then use these findings to answer a philosophical question. Much of the philosophical debate surrounding sensory substitution (...)
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  40. 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 we (...)
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  41. Student Privacy in Learning Analytics: An Information Ethics Perspective.Alan Rubel & Kyle M. L. Jones - 2016 - The Information Society 32 (2):143-159.
    In recent years, educational institutions have started using the tools of commercial data analytics in higher education. By gathering information about students as they navigate campus information systems, learning analytics “uses analytic techniques to help target instructional, curricular, and support resources” to examine student learning behaviors and change students’ learning environments. As a result, the information educators and educational institutions have at their disposal is no longer demarcated by course content and assessments, and old boundaries between information (...)
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  42.  82
    Learning From the Confucians: Learning From the Past.Karyn L. Lai - 2008 - Journal of Chinese Philosophy 35 (1):97-119.
    A distinguishing characteristic of Confucianism is its emphasis on learning (xue), is a key element in moral self cultivation. This paper discusses why learning from the experiences of those in the past is important in Confucian learning.
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  43. 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 (...)
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  44. Can Humanity Learn to Become Civilized? The Crisis of Science Without Civilization.Nicholas Maxwell - 2000 - Journal of Applied Philosophy 17 (1):29-44.
    Two great problems of learning confront humanity: learning about the nature of the universe and our place in it, and learning how to become civilized. The first problem was solved, in essence, in the 17th century, with the creation of modern science. But the second problem has not yet been solved. Solving the first problem without also solving the second puts us in a situation of great danger. All our current global problems have arisen as a result. (...)
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  45. How Digital Natives Learn and Thrive in the Digital Age: Evidence From an Emerging Economy.Trung Tran, Manh-Toan Ho, Thanh-Hang Pham, Minh-Hoang Nguyen, Khanh-Linh P. Nguyen, Thu-Trang Vuong, Thanh-Huyen T. Nguyen, Thanh-Dung Nguyen, Thi-Linh Nguyen, Quy Khuc, Viet-Phuong La & Quan-Hoang Vuong - 2020 - Sustainability 12 (9):3819.
    As a generation of ‘digital natives,’ secondary students who were born from 2002 to 2010 have various approaches to acquiring digital knowledge. Digital literacy and resilience are crucial for them to navigate the digital world as much as the real world; however, these remain under-researched subjects, especially in developing countries. In Vietnam, the education system has put considerable effort into teaching students these skills to promote quality education as part of the United Nations-defined Sustainable Development Goal 4 (SDG4). This issue (...)
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  46. 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 (...)
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  47. The Epistemic Significance of Perceptual Learning.Elijah Chudnoff - 2018 - Inquiry: An Interdisciplinary Journal of Philosophy 61 (5-6):520-542.
    First impressions suggest the following contrast between perception and memory: perception generates new beliefs and reasons, justification, or evidence for those beliefs; memory preserves old beliefs and reasons, justification, or evidence for those beliefs. In this paper, I argue that reflection on perceptual learning gives us reason to adopt an alternative picture on which perception plays both generative and preservative epistemic roles.
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  48. Mobile Learning: Essays on Philosophy, Psychology and Education.Kristóf Nyíri (ed.) - 2003 - Passagen Verlag.
    The changing conditions for the accumulation and transmission of knowledge in the age of multimedia networks make it inevitable that old philosophical problems become formulated in a new light. Above all, the problem of the unity of knowledge is once again a topical issue. The situation-dependent acquisition of knowledge that is made possible by mobile learning transcends the boundaries of traditional disciplines, linking the domains of text, diagram, and picture. Database integration and multimedia search become central problems in the (...)
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  49. 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 results (...)
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  50. 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 be due to (...)
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