Context: It is beyond doubt that RC has received a great deal of attention in educational studies and learning theory. But overall, the current situation seems to be rather ambivalent in view of the blurring of the various strands in constructivist discourses and the different ways of distinguishing and foregrounding constructivist positions. Correspondingly, there is a wide range of claims, from the claim that (radical) constructivism represents a mainstream endeavor to attributions of its being outdated, self-refuting or irrelevant. (...) Purpose: The paper seeks to sound out the ambivalent situation of (radical) constructivism between “all” and “nothing” by examples of attributions of meaning to constructivist positions in academic everyday life and by challenging both prevalent criticisms of systemic-constructivist pedagogy and widespread broad classifications in learning theory. Method: The article critically reflects on (1) one-sentence “destructions” of constructivist positions, (2) Pongratz’s criticism of systemic-constructivist pedagogy, and (3) the threefold classification of the world of learning, i.e., behaviorism, cognitivism, and constructivism. Results: Both the current criticism of constructivism as a mainstream endeavor and evolutionary suggestions provided by the threefold classification are criticized. Although some constructivist concepts and distinctions are widely accepted today, often these achievements are not recognized as being rooted in constructivist discourses. Implications: As far as mainstreaming constructivism might be related to power politics, selling the “real thing,” and joining the ranks of truth-oriented Isms, it would not appear to be a desirable endeavor for those who rely on viability, circular foundations, relativist philosophy, and relationalist approaches. Nevertheless, clarifications of power relations and the interplay between constructivist analyses of politics and the politics of constructivism might contribute to overcoming the diffuse popularity of constructivist thought towards a better understanding of constructivist contributions to solution oriented, meaningful ways of dealing with urgent problems. (shrink)

Alfred North Whitehead, although probably known best for his collaborative work with Bertrand Russell on the Principia Mathematica, also developed an original theory of learning and instruction which has much to offer for our times. His theory will be discussed in this paper. In order to do so, two criteria are first developed which in their combination give rise to five categories: radical behaviorism, cognitivism, and radical constructivism, with the intermediary categories of moderate behaviorism and moderate constructivism. (...) A great number of educational researchers are ascribed to one of these five categories. After discussing the shortcomings of the three major philosophical proponents of these three major educational approaches (Hume, Kant, and Berkeley), the basic assumptions of Whitehead’s philosophy of organism are presented, and his assumptions concerning learning and teaching are discussed in view of it. Finally, it is shown that Whitehead’s organismic philosophy is able to offer a frame for integrating Behaviorism, Cognitivism, and Constructivism, thereby solving a long standing scandal of education. (shrink)

The general process view of learning, which guided research into learning for the first half of this century, has come under attack in recent years from several quarters. One form of criticism has come from proponents of the so-called biological boundaries approach to learning. These theorists have presented a variety of data showing that supposedly general laws of learning may in fact be limited in their applicability to different species and learning tasks, and they argue (...) that the limitations are drawn by the nature of each species' adaptation to the particular requirements of its natural environment. The biological boundaries approach has served an important critical function in the move away from general process learning theory, but it is limited in its ability to provide an alternative to the general process approach. In particular, the biological boundaries approach lacks generality, it is in some respects subservient to the general process tradition, and its ecological content is in too many cases limited toex post factoadaptive explanations of learning skills. A contrasting, ecological approach to learning, which can provide a true alternative to general process theory, is presented. The ecological approach begins by providing an ecological task description for naturally occurring instances of learning; this step answers the question:Whatdoes this animal learn to do? The next step is an analysis of the means by which learning occurs in the course of development, answering the question:Howdoes the animal learn to do this? On the basis of such analyses, local principles of adaptation are formulated to account for the learning abilities of individual species. More global principles are sought by generalization among these local principles and may form the basis for a general ecological theory of learning. (shrink)

In this paper it is argued that certain stimulus-response learning models which are adequate to represent finite automata (acceptors) are not adequate to represent noninitial state input-output automata (transducers). This circumstance suggests the question whether or not the behavior of animals if satisfactorily modelled by automata is predictive. It is argued in partial answer that there are automata which can be explained in the sense that their transition and output functions can be described (roughly, Hempel-type covering law explanation) while (...) their behaviors are in principle not predictable short of possession of their complete histories or of information concerning present internal states by indirect observation. (shrink)

Theories of Early Childhood Education continues to provide a comprehensive overview of the various theoretical perspectives in early childhood education from developmental psychology to critical studies, Piaget to Freire. This revised and updated edition includes additional chapters on Michael Alexander Halliday's view of language learning and the attachment theory work of John Bowlby and Mary Ainsworth. Each author questions assumptions underpinning the use of theory in early childhood education and explores the implications of these questions for policy (...) and practice. Theories reported in this book are a timely reminder of the importance of the relationship between theory and practice necessary for teacher candidates, teacher educators, and early childhood teachers. Students will learn the fundamentals while in-service teachers and professionals will learn the theory behind field observations for their certification exams. (shrink)

Research in sport pedagogy and its applied recommendations are still characterized by a contrast between the different learning theories from psychology. Traditional theories and their corresponding approaches to the specific case of teaching and learning “how to play [team sports like soccer]” are subject to compatibilities and incompatibilities. We discuss how behaviorism as an approach to teaching the game shows more incompatibilities with the nature of tactical actions when compared to constructivism. As coaches strive to teach the game (...) and make their players and team perform, we argue that teaching the game requires teaching approaches that will help develop their way to play without taking away their autonomy and adaptiveness. The teaching-learning-training process for playing the game should then be conducted to harmonize the characteristics of the contents, the context, and the individual at hand. We provide two illustrated examples and portray how the recommended approaches fit key contents of the game that are observed in the tactical behavior. We finally argue that the coherent design of games provides minimal conditions to teaching approaches, and that such a design should be a priority when elaborating the learning activities along the player development process. As a conclusion, the interactionist theory is the one that best serves the teaching of the game and the development of tactical behavior. We therefore defend that its principles can help coaches tailor their own strategy to teach the game with the many tools. (shrink)

This paper examines the relationship among behaviorism, constructivism and Socratic pedagogy. Specifically, it asks if a Socratic educator can be a constructivist or a behaviorist. In the first part of the paper, each learning theory, as it relates to the Socratic project, is explained. In the last section, the question of whether or not a Socratic teacher can subscribe to a constructivist or a behaviorist learning theory is addressed. The paper concludes by stating that while Socratic (...) pedagogy shares some similarities with each learning theory, ultimately it is fundamentally incompatible with both. (shrink)

This paper examines the relationship among behaviorism, constructivism and Socratic pedagogy. Specifically, it asks if a Socratic educator can be a constructivist or a behaviorist. In the first part of the paper, each learning theory, as it relates to the Socratic project, is explained. In the last section, the question of whether or not a Socratic teacher can subscribe to a constructivist or a behaviorist learning theory is addressed. The paper concludes by stating that while Socratic (...) pedagogy shares some similarities with each learning theory, ultimately it is fundamentally incompatible with both. (shrink)

Some of Quine’s critics charge that he arrives at a behavioristic account of linguistic meaning by starting from inappropriately behavioristic assumptions (Kripke 1982, 14; Searle 1987, 123). Quine has even written that this account of linguistic meaning is a consequence of his behaviorism (Quine 1992, 37). I take it that the above charges amount to the assertion that Quine assumes the denial of one or more of the following claims: (1) Language-users associate mental ideas with their linguistic expressions. (...) (2) A language-user can have a private theory of linguistic meaning which guides his or her use of language. (3) Language learning relies on innate mechanisms. Call an antecedent denial of one or more of these claims illicit behaviorism. In this paper I show that Quine is prepared to grant, if only for the sake of argument, all three of the above claims. I argue that his claim that there is nothing in linguistic meaning beyond what is to be gleaned from overt behavior in observable circumstances is unscathed by these allowances (Quine 1992, 38). And I show that the behaviorism which Quine does assume should be viewed as a largely uncontroversial aspect of his evidential empiricism. I conclude that if one sets out to dismiss Quine’s arguments for internal-meaning skepticism, this dismissal should not be motivated by the charge that his conclusions rely on the illicitly behavioristic assumptions that some have suggested that they do. (shrink)

The continuing and expanding successes of behavior therapy in the treatment of psychological problems raise important questions about their scientific and philosophical bases. In this paper I examine the claims of Edward Erwin that behaviorism cannot provide an adequate philosophical basis for behavior therapy, contemporary learning theories which exclude cognitive factors as causes of behavior cannot provide an adequate empirical basis for behavior therapy; and learning theories have played only a heuristic role in the development of behavior therapy. (...) And I argue that Erwin's claims rest on two doubtful logical empiricist assumptions about scientific theory and explanation. Using different assumptions, I argue that some of the regularities involving cognitions which seem to govern behavior therapy techniques are analogical extensions of operant learning principles. On this basis I suggest some modifications of Erwin's claim about the philosophical foundations of behavior therapy. (shrink)

We try not just to reconcile but to “integrate” Cognitivism and Behaviorism by a theory of different forms of purposiveness in behavior and mind. This also implies a criticism of the Dual System theory and a claim on the strong interaction and integration of Sist1 (automatic) and Sist2 (deliberative), based on reasons, preferences, and decisions. We present a theory of different kinds of teleology. Mere “functions” of the behavior: finalism not represented in the mind of the agent, (...) not “regulating” the behavior. Two kinds of teleological mental representations: true “Goals” in control-theory, cybernetic view, with “goal-driven” behavior (intentional action); vs. Expectations in Anticipatory Classifiers: a reactive but anticipatory device, explaining the “instrumental” (finalistic) nature of Skinner’s reinforcement learning. We present different kinds of Goals and goal processing and on this ground the theory of what “intentions” are. On such basis, we can discuss Kathy Wilkes’s hint about the necessarily linguistic formulation of “intentions”; with the hypothesis that her intuition is not correct for any kind on “intention” which may be represented in sensory-motor format, but correct for “volition” and our will-strength for socially influencing ourselves. (shrink)

We owe most scientific knowledge to methods of inquiry that are never formally analyzed. The analysis of behavior does not call for hypothetico-deductive methods. Statistics, taught in lieu of scientific method, is incompatible with major features of much laboratory research. Squeezing significance out of ambiguous data discourages the more promising step of scrapping the experiment and starting again. As a consequence, psychologists have taken flight from the laboratory. They have fled to Real People and the human interest of “real life,” (...) to Mathematical Models and the elegance of symbolic treatments, to the Inner Man and the explanatory preoccupation with inferred internal mechanisms, and to Laymanship and its appeal to “common sense.” An experimental analysis provides an alternative to these divertissements.The “theories” to which objection is raised here are not the basic assumptions essential to any scientific activity or statements that are not yet facts, but rather explanations which appeal to events taking place somewhere else, at some other level of observation, described in different terms, and measured, if at all, in different dimensions. Three types of learning theories satisfy this definition: physiological theories attempting to reduce behavior to events in the nervous system; mentalistic theories appealing to inferred inner events; and theories of the Conceptual Nervous System offered as explanatory models of behavior. It would be foolhardy to deny the achievements of such theories in the history of science. The question of whether they are necessary, however, has other implications.Experimental material in three areas illustrates the function of theory more concretely. Alternatives to behavior ratios, excitatory potentials, and so on demonstrate the utility of rate or probability of response as the basic datum in learning. Functional relations between behavior and environmental variables provide an account of why learning occurs. Activities such as preferring, choosing, discriminating, and matching can be dealt with solely in terms of behavior, without referring to processes in another dimensional system. The experiments are not offered as demonstrating that theories are not necessary but to suggest an alternative. Theory is possible in another sense. Beyond the collection of uniform relationships lies the need for a formal representation of the data reduced to a minimal number of terms. A theoretical construction may yield greater generality than any assemblage of facts; such a construction will not refer to another dimensional system. (shrink)

The alternative offered by Professor Stemmer to cognitivist theories of the process whereby general terms acquire their meaning is criticised in its turn on the grounds that it presents an oversimplified view of the complex processes involved in the acquisition of word meanings.

Context: The advent of a general artificial intelligence mechanism that learns like humans do would represent the realization of an old and major dream of science. It could be achieved by an artifact able to develop its own cognitive structures following constructivist principles. However, there is a large distance between the descriptions of the intelligence made by constructivist theories and the mechanisms that currently exist. Problem: The constructivist conception of intelligence is very powerful for explaining how cognitive development takes place. (...) However, until now, no computational model has successfully demonstrated the underlying mechanisms necessary to realize it. In other words, the artificial intelligence (AI) community has not been able to give rise to a system that convincingly implements the principles of intelligence as postulated by constructivism, and that is also capable of dealing with complex environments. Results: This paper presents the constructivist anticipatory learning mechanism (CALM), an agent learning mechanism based on the constructivist approach of AI. It is designed to deal dynamically and interactively with environments that are at the same time partially deterministic and partially observable. CALM can model the regularities experienced in the interaction with the environment, on the sensorimotor level as well, as by constructing abstract or high-level representational concepts. The created model provides the knowledge necessary to generate the agent behavior. The paper also presents the coupled agent environment system (CAES) meta-architecture, which defines a conception of an autonomous agent, situated in the environment, embodied and intrinsically motivated. Implications: The paper can be seen as a step towards a computational implementation of constructivist principles, on the one hand suggesting a further perspective of this refreshing movement on the AI field (which is still too steeped in a behaviorist influence and dominated by probabilistic models and narrow applied approaches), and on the other hand bringing some abstract descriptions of the cognitive process into a more concrete dimension, in the form of algorithms. Constructivist content: The connection of this paper with constructivism is the proposal of a computational and formally described mechanism that implements important aspects of the subjective process of knowledge construction based on key ideas proposed by constructivist theories. (shrink)

This essay argues that Freud’s case of Little Hans, while complicated by Hans’ father’s dual role in the analysis and in the Oedipal drama itself, provides valuable insight into the nature of psychoanalytic evidence and argument. The case provides direct, if sometimes ambiguous, evidence concerning primal phantasies and infantile sexuality--issues of universality, the role of experience, and the nature of phantasy are explored. Four strands of Freud’s analysis of Little Hans’ horse phobia are also explored. While the toxicological theory (...) of anxiety is problematical and was subsequently abandoned by Freud himself, the other strands have great explanatory power and offer advantages over behaviorist and other alternative accounts. A kind of theoretical rigor in the concepts employed is argued to be among those advantages. The inevitably theory-laden character of observation is emphasized throughout, and it is argued that psychoanalysis provides a far more powerful theory than certain critiques would allow. (shrink)

La vision par ordinateur est un des domaines de l’intelligence artificielle qui connaît les succès les plus fulgurants. Depuis une vingtaine d’années, les machines n’ont cessé de progresser dans leur capacité à extraire des informations à partir d’images et à identifier des objets. Mais faut-il en conclure que ces machines sont littéralement des machines voyantes, ou ne s’agit-il que d’une façon imagée de décrire des capacités de détection? Le présent article se propose de fournir les bases d’une réponse raisonnée à (...) cette question. Nous examinons successivement trois types de conditions d’attribution de la vision, et soutenons que le critère fonctionnaliste, en termes de représentations internes de stimuli visuels exploitables à diverses fins, doit être préféré aux critères behavioriste ou phénoménologique. Ce critère fonctionnaliste est ensuite appliqué à une des technologies les plus utilisées dans le domaine de la vision par ordinateur, celle des réseaux de neurones et plus particulièrement des réseaux convolutifs. Nous soutenons alors que de tels réseaux sont bien capables de voir, précisément dans la mesure où ils sont entraînés pour produire des représentations à partir de données visuelles. Ces représentations ont des traits spécifiques associés à un entraînement réussi : elles sont hiérarchiques, versatiles et robustes. De telles propriétés ont un intérêt théorique au-delà de leur domaine d’origine : nous suggérons pour finir qu’elles pourraient être utilisées pour spécifier la nature de la fonction de représentation et résoudre certains des problèmes classiques auxquels font face les théories téléosémantiques de la représentation comme celle de Dretske. (shrink)

In contemporary Science, Technology and Society studies, Bruno Latour’s Actor Network Theory is often used to study how social change arises from interaction between people and technologies. Though Latour’s approach is rich in the sense of enabling scholars to appreciate the complexity of many relevant technological, environmental, and social factors in their studies, the approach is poor from an ethical point of view: the doings of things and people are couched in one and the same behaviorist vocabulary without giving (...) due recognition to the ethical relevance of human intelligence, sympathy and reflection in making responsible choices. This article argues that two other naturalist projects, the non-teleological virtue ethics of Charles Darwin and the pragmatist instrumentalism of John Dewey can enrich ANT-based STS studies, both, in a descriptive and in a normative sense. (shrink)

Formal learning theory is the mathematical embodiment of a normative epistemology. It deals with the question of how an agent should use observations about her environment to arrive at correct and informative conclusions. Philosophers such as Putnam, Glymour and Kelly have developed learning theory as a normative framework for scientific reasoning and inductive inference.

This paper places formal learning theory in a broader philosophical context and provides a glimpse of what the philosophy of induction looks like from a learning-theoretic point of view. Formal learning theory is compared with other standard approaches to the philosophy of induction. Thereafter, we present some results and examples indicating its unique character and philosophical interest, with special attention to its unified perspective on inductive uncertainty and uncomputability.

In this paper, we explore the possibility that machine learning approaches to naturallanguage processing being developed in engineering-oriented computational linguistics may be able to provide specific scientific insights into the nature of human language. We argue that, in principle, machine learning results could inform basic debates about language, in one area at least, and that in practice, existing results may offer initial tentative support for this prospect. Further, results from computational learning theory can inform arguments carried (...) on within linguistic theory as well. (shrink)

In this paper, we explore the possibility that machine learning approaches to naturallanguage processing being developed in engineering-oriented computational linguistics may be able to provide specific scientific insights into the nature of human language. We argue that, in principle, machine learning results could inform basic debates about language, in one area at least, and that in practice, existing results may offer initial tentative support for this prospect. Further, results from computational learning theory can inform arguments carried (...) on within linguistic theory as well. (shrink)

An important question for a naturalized philosophical psychology is what constitutes moral agency (MA). The two prominent scientific theories to which such a philosophical approach might appeal, those of cognitive developmental theory (CDT) and social learning theory (SLT), currently face an investigative dilemma: The better theories of the acquisition of beliefs and the performance of action based on them, the SLTs, seem to be irrelevant to the phenomenon of MA and the theories that seem to be relevant, (...) the CDTs, are unsatisfactory in their accounts of acquisition and action. In this paper I take up the cause of SLT accounts of MA. Critics of SLT accounts of MA can be interpreted as arguing that they are irrelevant to MA because they lack one or more of five functional criteria that require MA to be integral morally motivated cognitive agency. I argue that SLT accounts of MA, and specifically Bandura's social cognitive theory, (SCT), when applied to issues of MA, meet these criteria. Assuming the merits of SLT explanations of both the acquisition of beliefs and the performance of actions based on them, I conclude that SLTs generally, and specifically Bandura's SCT, are promising candidates for explaining MA. If so, they merit the attention of naturalistic philosophical psychologists. (shrink)

This paper discusses the possibility of modelling inductive inference (Gold 1967) in dynamic epistemic logic (see e.g. van Ditmarsch et al. 2007). The general purpose is to propose a semantic basis for designing a modal logic for learning in the limit. First, we analyze a variety of epistemological notions involved in identification in the limit and match it with traditional epistemic and doxastic logic approaches. Then, we provide a comparison of learning by erasing (Lange et al. 1996) and (...) iterated epistemic update (Baltag and Moss 2004) as analyzed in dynamic epistemic logic. We show that finite identification can be modelled in dynamic epistemic logic, and that the elimination process of learning by erasing can be seen as iterated belief-revision modelled in dynamic doxastic logic. Finally, we propose viewing hypothesis spaces as temporal frames and discuss possible advantages of that perspective. (shrink)

Computational learning theory explores the limits of learnability. Studying language acquisition from this perspective involves identifying classes of languages that are learnable from the available data, within the limits of time and computational resources available to the learner. Different models of learning can yield radically different learnability results, where these depend on the assumptions of the model about the nature of the learning process, and the data, time, and resources that learners have access to. To the (...) extent that such assumptions accurately reflect human language learning, a model that invokes them can offer important insights into the formal properties of natural languages, and the way in which their representations might be efficiently acquired. In this chapter we consider several computational learning models that have been applied to the language learning task. Some of these have yielded results that suggest that the class of natural languages cannot be efficiently learned from the primary linguistic data (PLD) available to children, through.. (shrink)

Artificial intelligence research connected with learning theory ("deep learning," “machine learning,” analysis of the quality of learning, etc.) has existed for many years; however, there have been few investigations in that area conducted from a robust philosophical methodological basis.

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.

Statistical Learning Theory (e.g., Hastie et al., 2001; Vapnik, 1998, 2000, 2006) is the basic theory behind contemporary machine learning and data-mining. We suggest that the theory provides an excellent framework for philosophical thinking about inductive inference.

Go beyond reading about early learning theories and see what they look like in action in modern programs and teacher practices. With classroom vignettes and colorful photographs, this book makes the works of Jean Piaget, Erik Erikson, Lev Vygotsky, Abraham Maslow, John Dewey, Howard Gardner, and Louise Derman-Sparks visible, accessible, and easier to understand. Each theory is defined-through engaging stories and rich visuals-in relation to cognitive, social-emotional, and physical developmental domains. Use this book to build a stronger comprehension (...) of the foundations of early learning theories and become more reflective and intentional in your work with young children. (shrink)

In this article, we provide a tutorial overview of some aspects of statistical learning theory, which also goes by other names such as statistical pattern recognition, nonparametric classification and estimation, and supervised learning. We focus on the problem of two-class pattern classification for various reasons. This problem is rich enough to capture many of the interesting aspects that are present in the cases of more than two classes and in the problem of estimation, and many of the (...) results can be extended to these cases. Focusing on two-class pattern classification simplifies our discussion, and yet it is directly applicable to a wide range of practical settings. (shrink)

then essentially characterized the hypotheses that mechanical scientists can successfully decide in the limit in terms of arithmetic complexity. These ideas were developed still further by Peter Kugel [4]. In this paper, I extend this approach to obtain characterizations of identification in the limit, identification with bounded mind-changes, and identification in the short run, both for computers and for ideal agents with unbounded computational abilities. The characterization of identification with n mind-changes entails, as a corollary, an exact arithmetic characterization of (...) Putnam's n-trial predicates, which closes a gap of a factor of two in Putnam's original characterization [12]. (shrink)

We compare Karl Popper’s ideas concerning the falsifiability of a theory with similar notions from the part of statistical learning theory known as VC-theory . Popper’s notion of the dimension of a theory is contrasted with the apparently very similar VC-dimension. Having located some divergences, we discuss how best to view Popper’s work from the perspective of statistical learning theory, either as a precursor or as aiming to capture a different learning activity.