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  1. Language and thought: The view from LLMs.Daniel Rothschild - forthcoming - In David Sosa & Ernie Lepore (eds.), Oxford Studies in Philosophy of Language Volume 3.
  2. Pain and Pleasure.Murat Aydede - 2024 - In Andrea Scarantino (ed.), : The Routledge Comprehensive Guide Volume II: Theories of Specific Emotions and Major Theoretical Challenges. Routledge.
    This is a piece written for interdisciplinary audiences and contains very little philosophy. It looks into whether, or in what sense, pains and pleasures are emotions.
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  3. Functional Information: a Graded Taxonomy of Difference Makers.Nir Fresco, Simona Ginsburg & Eva Jablonka - 2020 - Review of Philosophy and Psychology 11 (3):547-567.
    There are many different notions of information in logic, epistemology, psychology, biology and cognitive science, which are employed differently in each discipline, often with little overlap. Since our interest here is in biological processes and organisms, we develop a taxonomy of functional information that extends the standard cue/signal distinction (in animal communication theory). Three general, main claims are advanced here. (1) This new taxonomy can be useful in describing learning and communication. (2) It avoids some problems that the natural/non-natural information (...)
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  4. A Psychological Approach to Causal Understanding and the Temporal Asymmetry.Elena Popa - 2020 - Review of Philosophy and Psychology 11 (4):977-994.
    This article provides a conceptual account of causal understanding by connecting current psychological research on time and causality with philosophical debates on the causal asymmetry. I argue that causal relations are viewed as asymmetric because they are understood in temporal terms. I investigate evidence from causal learning and reasoning in both children and adults: causal perception, the temporal priority principle, and the use of temporal cues for causal inference. While this account does not suffice for correct inferences of causal structure, (...)
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  5. Embedding the assessment of emotion in the learning process with AI-driven technologies.Rossitza Kaltenborn - 2019 - In Petrov Vesselin & Katie Andersen (eds.), Traditional Learning Theories, Process Philosophy and AI.
    This paper examines the possibility of an objective evaluation of emotions occurring within the learning process and methods for embedding such an evaluation in advanced learning systems. The main conceptual understandings of emotion in learning and teaching are systematized, with an emphasis on the process philosophy approach. Different models of emotion are considered and the possible generalization of Whitehead’s approach to the role of emotion in education is examined. Special attention is given to significant developments in artificial intelligence in identifying (...)
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  6. 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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  7. Excavating the origins of the learning pyramid myths.Kåre Letrud & Sigbjørn Hernes - 2018 - Cogent 1 (5).
    The family of cognitive models sometimes referred to as the “Learning Pyramid” enjoys a considerable level of authority within several areas of educational studies, despite that nobody knows how they originated or whether they were supported by any empirical evidence. This article investigates the early history of these models. Through comprehensive searches in digital libraries, we have found that versions of the Learning Pyramids have been part of educational debates and practices for more than 160 years. These findings demonstrate that (...)
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  8. Neonatal imitation in context: Sensorimotor development in the perinatal period.Nazim Keven & Kathleen A. Akins - 2017 - Behavioral and Brain Sciences 40:e381.
    Over 35 years ago, Meltzoff and Moore (1977) published their famous article ‘Imitation of facial and manual gestures by human neonates’. Their central conclusion, that neonates can imitate, was and continues to be controversial. Here we focus on an often neglected aspect of this debate, namely on neonatal spontaneous behaviors themselves. We present a case study of a paradigmatic orofacial ‘gesture’, namely tongue protrusion and retraction (TP/R). Against the background of new research on mammalian aerodigestive development, we ask: How does (...)
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  9. Advice seeking network structures and the learning organization.Jarle Aarstad, Marcus Selart & Sigurd Troye - 2011 - Problems and Perspectives in Management 9 (2):44-51.
    Organizational learning can be described as a transfer of individuals’ cognitive mental models to shared mental models. Employees, seeking the same colleagues for advice, are structurally equivalent, and the aim of the paper is to study if the concept can act as a conduit for organizational learning. It is argued that the mimicking of colleagues’ advice seeking structures will induce structural equivalence and transfer the accuracy of individuals’ cognitive mental models to shared mental models. Taking a dyadic level of analysis (...)
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  10. Introduction: Machine learning as philosophy of science.Kevin B. Korb - 2004 - Minds and Machines 14 (4):433-440.
    I consider three aspects in which machine learning and philosophy of science can illuminate each other: methodology, inductive simplicity and theoretical terms. I examine the relations between the two subjects and conclude by claiming these relations to be very close.
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  11. Science as systems learning: Some reflections on the cognitive and communicational aspects of science.Hugo F. Alrøe - 2000 - Cybernetics and Human Knowing 7 (4):57-78.
    This paper undertakes a theoretical investigation of the 'learning' aspect of science as opposed to the 'knowledge' aspect. The practical background of the paper is in agricultural systems research – an area of science that can be characterised as 'systemic' because it is involved in the development of its own subject area, agriculture. And the practical purpose of the theoretical investigation is to contribute to a more adequate understanding of science in such areas, which can form a basis for developing (...)
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  12. Review of James J. O'Donnell, *Avatars of the Word*. [REVIEW]G. Nixon - 1999 - Journal of Consciousness Studies 6 (6-7):120-122.
    J. J. OʼDonnell is one those scholars whose learning is assumed rather than displayed. As a result, his brief approach to the long-terms effects of the computer revolution onreading and higher education feels like a bracing, sophisticated exchange of ideas. Like conversation, O'Donnellʼs thesis is not terribly unified or orderly. He often makessidetracks from his focus on high technology and literacy into explaining such interestingthings as how we choose our cultural ancestry instead of merely evolving out of it, the errors (...)
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  13. The hierarchies of knowledge and the mathematics of discovery.Clark Glymour - 1991 - Minds and Machines 1 (1):75-95.
    Rather than attempting to characterize a relation of confirmation between evidence and theory, epistemology might better consider which methods of forming conjectures from evidence, or of altering beliefs in the light of evidence, are most reliable for getting to the truth. A logical framework for such a study was constructed in the early 1960s by E. Mark Gold and Hilary Putnam. This essay describes some of the results that have been obtained in that framework and their significance for philosophy of (...)
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  14. Formal Learning Theory and the Philosophy of Science.Kevin T. Kelly - 1988 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1988:413 - 423.
    Formal learning theory is an approach to the study of inductive inference that has been developed by computer scientists. In this paper, I discuss the relevance of formal learning theory to such standard topics in the philosophy of science as underdetermination, realism, scientific progress, methodology, bounded rationality, the problem of induction, the logic of discovery, the theory of knowledge, the philosophy of artificial intelligence, and the philosophy of psychology.
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  15. Behavioristic, evidentialist, and learning models of statistical testing.Deborah G. Mayo - 1985 - Philosophy of Science 52 (4):493-516.
    While orthodox (Neyman-Pearson) statistical tests enjoy widespread use in science, the philosophical controversy over their appropriateness for obtaining scientific knowledge remains unresolved. I shall suggest an explanation and a resolution of this controversy. The source of the controversy, I argue, is that orthodox tests are typically interpreted as rules for making optimal decisions as to how to behave--where optimality is measured by the frequency of errors the test would commit in a long series of trials. Most philosophers of statistics, however, (...)
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  16. Effect of the spatial relationship between cue, reward, and response in simple discrimination learning.J. V. Murphy & R. E. Miller - 1958 - Journal of Experimental Psychology 56 (1):26.
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  17. Dr.Polit.s pretending to be Dr.Ped - in a structurally corrupted Norwegian Ed-Sci (2016).Kai Soerfjord - manuscript
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  18. Didactic-reflexive Form Errors, full initial MANUSCRIPT, May 2017.Kai Soerfjord - manuscript