Results for 'learning'

983 found
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  1. 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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  2. 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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  3. Learning Matters: The Role of Learning in Concept Acquisition.Eric Margolis & Stephen Laurence - 2011 - Mind and Language 26 (5):507-539.
    In LOT 2: The Language of Thought Revisited, Jerry Fodor argues that concept learning of any kind—even for complex concepts—is simply impossible. In order to avoid the conclusion that all concepts, primitive and complex, are innate, he argues that concept acquisition depends on purely noncognitive biological processes. In this paper, we show (1) that Fodor fails to establish that concept learning is impossible, (2) that his own biological account of concept acquisition is unworkable, and (3) that there are (...)
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  4. Perceptual Learning Explains Two Candidates for Cognitive Penetration.Valtteri Arstila - 2016 - Erkenntnis 81 (6):1151-1172.
    The cognitive penetrability of perceptual experiences has been a long-standing topic of disagreement among philosophers and psychologists. Although the notion of cognitive penetrability itself has also been under dispute, the debate has mainly focused on the cases in which cognitive states allegedly penetrate perceptual experiences. This paper concerns the plausibility of two prominent cases. The first one originates from Susanna Siegel’s claim that perceptual experiences can represent natural kind properties. If this is true, then the concepts we possess change the (...)
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  5. Deep learning and synthetic media.Raphaël Millière - 2022 - Synthese 200 (3):1-27.
    Deep learning algorithms are rapidly changing the way in which audiovisual media can be produced. Synthetic audiovisual media generated with deep learning—often subsumed colloquially under the label “deepfakes”—have a number of impressive characteristics; they are increasingly trivial to produce, and can be indistinguishable from real sounds and images recorded with a sensor. Much attention has been dedicated to ethical concerns raised by this technological development. Here, I focus instead on a set of issues related to the notion of (...)
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  6. Perceptual learning.Zoe Jenkin - 2023 - Philosophy Compass 18 (6):e12932.
    Perception provides us with access to the external world, but that access is shaped by our own experiential histories. Through perceptual learning, we can enhance our capacities for perceptual discrimination, categorization, and attention to salient properties. We can also encode harmful biases and stereotypes. This article reviews interdisciplinary research on perceptual learning, with an emphasis on the implications for our rational and normative theorizing. Perceptual learning raises the possibility that our inquiries into topics such as epistemic justification, (...)
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  7. 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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  8. Perceptual learning and reasons‐responsiveness.Zoe Jenkin - 2022 - Noûs 57 (2):481-508.
    Perceptual experiences are not immediately responsive to reasons. You see a stick submerged in a glass of water as bent no matter how much you know about light refraction. Due to this isolation from reasons, perception is traditionally considered outside the scope of epistemic evaluability as justified or unjustified. Is perception really as independent from reasons as visual illusions make it out to be? I argue no, drawing on psychological evidence from perceptual learning. The flexibility of perceptual learning (...)
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  9. 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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  10.  79
    Meta-learning Contributes to Cultivation of Wisdom in Moral Domains: Implications of Recent Artificial Intelligence Research and Educational Considerations.Hyemin Han - forthcoming - International Journal of Ethics Education.
    Meta-learning is learning to learn, which includes the development of capacities to transfer what people learned in one specific domain to other domains. It facilitates finetuning learning parameters and setting priors for effective and optimal learning in novel contexts and situations. Recent advances in research on artificial intelligence have reported meta-learning is essential in improving and optimizing the performance of trained models across different domains. In this paper, I suggest that meta-learning plays fundamental roles (...)
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  11. 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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  12. Learning Places: Building Dwelling Thinking Online.David Kolb - 2000 - Journal of Philosophy of Education 34 (1):121-133.
    Lack of information is hardly our problem. Information comes at us in waves, sloshing out of the magazine rack, lapping at our computer monitors. It repeats and repeats on all-day news shows. It comes neatly packaged as sound bites, or little nuggets ready for trivia games. We have plenty of information, but it is not often the information we need. Even if it is, we need to learn how to deal with it. It is not just the amount, but the (...)
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  13. Learning Motivation and Utilization of Virtual Media in Learning Mathematics.Almighty Tabuena & Jupeth Pentang - 2021 - Asia-Africa Journal of Recent Scientific Research 1 (1):65-75.
    This study aims to describe the learning motivation of students using virtual media when they are learning mathematics in grade 5. The research design applied in this research is classroom action research. The research is conducted in two phases which involve planning, action and observation and reflection. The results of the study revealed that intrinsic motivation to learn is most prevalent in the form of fun to learn mathematics with virtual media. Other forms of intrinsic motivation include curiosity, (...)
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  14. 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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  15. (1 other version)Machine Learning and Irresponsible Inference: Morally Assessing the Training Data for Image Recognition Systems.Owen C. 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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  16. Constraints in Organizational Learning, Cognitive Load and Its Effect on Employee Behavior.Sidharta Chatterjee - 2013 - IUP Journal of Knowledge Management 11 (4):7-19.
    Traditionally, learning organizations face certain constraints related to both exogenous and endogenous factors. This paper models three well-established constraints that employees face while being part of their organizations. One is an explicit constraint on their natural behavior, and two implicit constraints on their endeavor to acquire new knowledge and perform new actions. The implicit constraints, which are elaborated, are related to their relative performance in acquiring new knowledge and by their consecutive actions based on the new knowledge gained. Therefore, (...)
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  17. Learning Incommensurate Concepts.Hayley Clatterbuck & Hunter Gentry - forthcoming - Synthese.
    A central task of developmental psychology and philosophy of science is to show how humans learn radically new concepts. Famously, Fodor has argued that such learning is impossible if concepts have definitional structure and all learning is hypothesis testing. We present several learning processes that can generate novel concepts. They yield transformations of the fundamental feature space, generating new similarity structures which can underlie conceptual change. This framework provides a tractable, empiricist-friendly account that unifies and shores up (...)
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  18. Learning to Discriminate: The Perfect Proxy Problem in Artificially Intelligent Criminal Sentencing.Benjamin Davies & Thomas Douglas - 2022 - In Jesper Ryberg & Julian V. Roberts (eds.), Sentencing and Artificial Intelligence. Oxford: OUP.
    It is often thought that traditional recidivism prediction tools used in criminal sentencing, though biased in many ways, can straightforwardly avoid one particularly pernicious type of bias: direct racial discrimination. They can avoid this by excluding race from the list of variables employed to predict recidivism. A similar approach could be taken to the design of newer, machine learning-based (ML) tools for predicting recidivism: information about race could be withheld from the ML tool during its training phase, ensuring that (...)
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  19. 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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  20. 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 learning, (...)
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  21. 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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  22. Modular Learning Efficiency: Learner’s Attitude and Performance Towards Self-Learning Modules.April Clarice C. Bacomo, Lucy P. Daculap, Mary Grace O. Ocampo, Crystalyn D. Paguia, Jupeth Pentang & Ronalyn M. Bautista - 2022 - IOER International Multidisciplinary Research Journal 4 (2):60-72.
    Learner’s attitude towards modular distance learning catches uncertainties as a world crisis occurs up to this point. As self-learning modules (SLMs) become a supplemental means of learning in new normal education, this study investigated efficiency towards the learners’ attitude and performance. Specifically, the study described the learners’ profile and their attitude and performance towards SLMs. It also ascertained the relationship between the learner’s profile with their attitude and performance, as well as the relationship between attitude and performance (...)
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  23. Understanding from Machine Learning Models.Emily Sullivan - 2022 - British Journal for the Philosophy of Science 73 (1):109-133.
    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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  24. (1 other version)Learning as Differentiation of Experiential Schemas.Jan Halák - 2019 - In Jim Parry & Pete Allison (eds.), Experiential Learning and Outdoor Education: Traditions of practice and philosophical perspectives. Routledge. pp. 52-70.
    The goal of this chapter is to provide an interpretation of experiential learning that fully detaches itself from the epistemological presuppositions of empiricist and intellectualist accounts of learning. I first introduce the concept of schema as understood by Kant and I explain how it is related to the problems implied by the empiricist and intellectualist frameworks. I then interpret David Kolb’s theory of learning that is based on the concept of learning cycle and represents an attempt (...)
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  25. Learning from Conditionals.Benjamin Eva, Stephan Hartmann & Soroush Rafiee Rad - 2020 - Mind 129 (514):461-508.
    In this article, we address a major outstanding question of probabilistic Bayesian epistemology: how should a rational Bayesian agent update their beliefs upon learning an indicative conditional? A number of authors have recently contended that this question is fundamentally underdetermined by Bayesian norms, and hence that there is no single update procedure that rational agents are obliged to follow upon learning an indicative conditional. Here we resist this trend and argue that a core set of widely accepted Bayesian (...)
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  26. Networked Learning and Three Promises of Phenomenology.Lucy Osler - forthcoming - In Phenomenology in Action for Researching Networked Learning Experiences.
    In this chapter, I consider three ‘promises’ of bringing phenomenology into dialogue with networked learning. First, a ‘conceptual promise’, which draws attention to conceptual resources in phenomenology that can inspire and inform how we understand, conceive of, and uncover experiences of participants in networked learning activities and environments. Second, a ‘methodological promise’, which outlines a variety of ways that phenomenological methodologies and concepts can be put to use in empirical research in networked learning. And third, a ‘critical (...)
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  27. Machine Learning-Based Diabetes Prediction: Feature Analysis and Model Assessment.Fares Wael Al-Gharabawi & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (9):10-17.
    This study employs machine learning to predict diabetes using a Kaggle dataset with 13 features. Our three-layer model achieves an accuracy of 98.73% and an average error of 0.01%. Feature analysis identifies Age, Gender, Polyuria, Polydipsia, Visual blurring, sudden weight loss, partial paresis, delayed healing, irritability, Muscle stiffness, Alopecia, Genital thrush, Weakness, and Obesity as influential predictors. These findings have clinical significance for early diabetes risk assessment. While our research addresses gaps in the field, further work is needed to (...)
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  28. 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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  29. Learning to Imagine.Amy Kind - 2022 - British Journal of Aesthetics 62 (1):33-48.
    Underlying much current work in philosophy of imagination is the assumption that imagination is a skill. This assumption seems to entail not only that facility with imagining will vary from one person to another, but also that people can improve their own imaginative capacities and learn to be better imaginers. This paper takes up this issue. After showing why this is properly understood as a philosophical question, I discuss what it means to say that one imagining is better than another (...)
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  30. Learning and Business Incubation Processes and Their Impact on Improving the Performance of Business Incubators.Shehada Y. Rania, El Talla A. Suliman, J. Shobaki Mazen & Samy S. Abu-Naser - 2020 - International Journal of Academic Multidisciplinary Research (IJAMR) 4 (5):120-142.
    This study aimed to identify the learning and business incubation processes and their impact on developing the performance of business incubators in Gaza Strip, and the study relied on the descriptive analytical approach, and the study population consisted of all employees working in business incubators in Gaza Strip in addition to experts and consultants in incubators where their total number reached (62) individuals, and the researchers used the questionnaire as a main tool to collect data through the comprehensive survey (...)
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  31. 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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  32. 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 (...)
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  33. Amidst the Online Learning Modality: The Social Support and Its Relationship to the Anxiety of Senior High School Students.Jastine Joy Basilio, Twinkle Pangilinan, Jeremiah Joy Kalong & Jhoselle Tus - 2022 - Psychology Abd Education: A Multidisciplinary Journal 1 (1):1-6.
    Senior high school is known to be part of the newly implemented K-12 program in the Philippines' educational system. Hence, this program added two years to the academic learning program of students, which mainly focuses on different theoretical and vocational strands that aim to prepare and fully furnish the students for education and employment in the future. Due to adjustments to new online learning amidst the pandemic, students begin to experience various challenges, primarily social support and mental well-being. (...)
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  34. 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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  35. Learning from errors in digital patient communication: Professionals’ enactment of negative knowledge and digital ignorance in the workplace.Rikke Jensen, Charlotte Jonasson, Martin Gartmeier & Jaana Parviainen - 2023 - Journal of Workplace Learning 35 (5).
    Purpose. The purpose of this study is to investigate how professionals learn from varying experiences with errors in health-care digitalization and develop and use negative knowledge and digital ignorance in efforts to improve digitalized health care. Design/methodology/approach. A two-year qualitative field study was conducted in the context of a public health-care organization working with digital patient communication. The data consisted of participant observation, semistructured interviews and document data. Inductive coding and a theoretically informed generation of themes were applied. Findings. The (...)
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  36. Learning Strategies, Motivation, and Its Relationship to the Online Learning Environment Among College Students.Ana Mhey M. Tabinas, Jemimah Abigail R. Panuncio, Dianah Marie T. Salvo, Rebecca A. Oliquino, Shaena Bernadette D. Villar & Jhoselle Tus - 2023 - Psychology and Education: A Multidisciplinary Journal 11 (2):622-628.
    Online education has become an essential component of education. Thus, several factors, such as the student’s learning strategy and motivation, generally contribute to their academic success. This study investigates the relationship between learning strategies, motivation, and online learning environment among 150 first-year college students. Employing correlational design, the statistical findings of the study reveal that the r coefficient of 0.59 indicates a moderate positive correlation between the variables. The p-value of 0.00, which is less than 0.05, leads (...)
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  37. 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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  38. Deep Learning as Method-Learning: Pragmatic Understanding, Epistemic Strategies and Design-Rules.Phillip H. Kieval & Oscar Westerblad - manuscript
    We claim that scientists working with deep learning (DL) models exhibit a form of pragmatic understanding that is not reducible to or dependent on explanation. This pragmatic understanding comprises a set of learned methodological principles that underlie DL model design-choices and secure their reliability. We illustrate this action-oriented pragmatic understanding with a case study of AlphaFold2, highlighting the interplay between background knowledge of a problem and methodological choices involving techniques for constraining how a model learns from data. Building successful (...)
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  39. Machine Learning, Misinformation, and Citizen Science.Adrian K. Yee - 2023 - European Journal for Philosophy of Science 13 (56):1-24.
    Current methods of operationalizing concepts of misinformation in machine learning are often problematic given idiosyncrasies in their success conditions compared to other models employed in the natural and social sciences. The intrinsic value-ladenness of misinformation and the dynamic relationship between citizens' and social scientists' concepts of misinformation jointly suggest that both the construct legitimacy and the construct validity of these models needs to be assessed via more democratic criteria than has previously been recognized.
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  40. Machine learning in bail decisions and judges’ trustworthiness.Alexis Morin-Martel - 2023 - AI and Society:1-12.
    The use of AI algorithms in criminal trials has been the subject of very lively ethical and legal debates recently. While there are concerns over the lack of accuracy and the harmful biases that certain algorithms display, new algorithms seem more promising and might lead to more accurate legal decisions. Algorithms seem especially relevant for bail decisions, because such decisions involve statistical data to which human reasoners struggle to give adequate weight. While getting the right legal outcome is a strong (...)
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  41. 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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  42. Learning in the social being system.Zoe Jenkin & Lori Markson - 2024 - Behavioral and Brain Sciences 47:e132.
    We argue that the core social being system is unlike other core systems in that it participates in frequent, widespread learning. As a result, the social being system is less constant throughout the lifespan and less informationally encapsulated than other core systems. This learning supports the development of the precursors of bias, but also provides avenues for preempting it.
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  43. Learning and Selection Processes.Marc Artiga - 2010 - Theoria 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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  44. Learning from experience and conditionalization.Peter Brössel - 2023 - Philosophical Studies 180 (9):2797-2823.
    Bayesianism can be characterized as the following twofold position: (i) rational credences obey the probability calculus; (ii) rational learning, i.e., the updating of credences, is regulated by some form of conditionalization. While the formal aspect of various forms of conditionalization has been explored in detail, the philosophical application to learning from experience is still deeply problematic. Some philosophers have proposed to revise the epistemology of perception; others have provided new formal accounts of conditionalization that are more in line (...)
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  45. Learning to be Reliable: Confucius' Analects.Karyn L. Lai - 2018 - In Karyn L. Lai, Rick Benitez & Hyun Jin Kim (eds.), Cultivating a Good Life in Early Chinese and Ancient Greek Philosophy: Perspectives and Reverberations. Bloomsbury. pp. 193-207.
    In the Lunyu, Confucius remarks on the implausibility—or impossibility—of a life lacking in xin 信, reliability (2.22). In existing discussions of Confucian philosophy, this aspect of life is often eclipsed by greater emphasis on Confucian values such as ren 仁 (benevolence), li 禮 (propriety) and yi 義 (rightness). My discussion addresses this imbalance by focusing on reliability, extending current debates in two ways. First, it proposes that the common translation of xin as denoting coherence between a person’s words and deeds (...)
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  46. 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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  47. Constructivist Learning Amid the COVID-19 Pandemic: Investigating Students’ Perceptions of Biology Self-Learning Modules.Aaron Funa & Frederick Talaue - 2021 - International Journal of Learning, Teaching and Educational Research 20 (3):250-264.
    Modes of teaching and learning have had to rapidly shift amid the COVID-19 pandemic. As an emergency response, students from Philippine public schools were provided learning modules based on a minimized list of essential learning competencies in Biology. Using a cross-sectional survey method, we investigated students’ perceptions of the Biology self-learning modules (BSLM) that were designed in print and digitized formats according to a constructivist learning approach. Senior high school STEM students from grades 11 (n (...)
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  48. Learning to Act.Jan Bransen - 2016 - Symposion: Theoretical and Applied Inquiries in Philosophy and Social Sciences 3 (1):11-35.
    In this paper I argue that to understand minded agency – the capacity we typically find instantiated in instances of human behaviour that could sensibly be questioned by asking “What did you do?” – one needs to understand childhood, i.e. the trajectory of learning to act. I discuss two different types of trajectory, both of which seem to take place during childhood and both of which might be considered crucial to learning to act: a growth of bodily control (...)
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  49. E-Learning Strategies in Developing Research Performance Efficiency: Higher Education Institutions.Samia A. M. Abdalmenem, Samer M. Arqawi, Youssef M. Abu Amuna, Samy S. Abu Naser & Mazen J. Al Shobaki - 2019 - International Journal of Academic Pedagogical Research (IJAPR) 3 (9):8-19.
    The study aimed to identify E- Learning strategies and their relation to the efficiency of research performance in foreign and Palestinian universities (University of Ottawa, Munster, Suez Canal, Al-Azhar, Islamic, Al-Aqsa). The analytical descriptive approach was used for this purpose, and relying on the questionnaire as a main tool for data collection. The study society is from the senior management, where the number of senior management in the universities in question is 206. The random stratified sample was selected and (...)
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  50. Learning How to Represent: An Associationist Account.Nancy Salay - 2019 - Journal of Mind and Behavior 40 (2):121-14.
    The paper develops a positive account of the representational capacity of cognitive systems: simple, associationist learning mechanisms and an architecture that supports bootstrapping are sufficient conditions for symbol tool use. In terms of the debates within the philosophy of mind, this paper offers a plausibility account of representation externalism, an alternative to the reductive, computational/representational models of intentionality that still play a leading role in the field. Although the central theme here is representation, methodologically this view complements embodied, enactivist (...)
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