cognitive psychology history research paper

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The Place of Development in the History of Psychology and Cognitive Science

In this article, I analyze how the relationship of developmental psychology with general psychology and cognitive science has unfolded. This historical analysis will provide a background for a critical examination of the present state of the art. I shall argue that the study of human mind is inherently connected with the study of its development. From the beginning of psychology as a discipline, general psychology and developmental psychology have followed parallel and relatively separated paths. This separation between adult and child studies has also persisted with the emergence of cognitive science. The reason is due essentially to methodological problems that have involved not only research methods but also the very object of inquiry. At present, things have evolved in many ways. Psychology and cognitive science have enlarged their scope to include change process and the interaction between mind and environment. On the other hand, the possibility of using experimental methods to study infancy has allowed us to realize the complexity of young humans. These facts have paved the way for new possibilities of convergence, which are eliciting interesting results, despite a number of ongoing problems related to methods.

Introduction

In this paper, I intend to analyze how the relationship of developmental psychology to general psychology and cognitive science has unfolded. This historical analysis will provide a background for a critical examination of the present state of the art.

Psychology emerged as a scientific discipline with the founding of Wundt’s Laboratory in Leipzig at the end of the nineteenth century (1879) 1 . Wundt’s method, both experimental and introspective, was directed to the study of an adult’s mind and behavior. It is less well-known that only 10 years later, James Baldwin, who had attended Wundt’s seminars in Germany, founded a laboratory of experimental psychology in Toronto in which experiments devoted to the study of mental development were performed. If the occasion that aroused Baldwin’s interest was the birth of his first daughter, actually, “that interest in the problems of genesis–origin, development, evolution–became prominent; the interest which was to show itself in all the subsequent years” ( Baldwin, 1930 ). Baldwin’s work was a source of inspiration for Piaget, certainly one of the most prominent figures in developmental psychology ( Morgan and Harris, 2015 ).

From the origins of psychology as a discipline, general psychology and developmental psychology have followed parallel and relatively separate paths. Two questions are particularly relevant to explain this fact.

From a theoretical point of view, developmental psychology has all along been greatly influenced by biology and evolutionary theory. The founders of developmental psychology have widely analyzed the relation between ontogenesis and phylogenesis ( Baldwin, 1895 ; Piaget, 1928 ). This analysis resulted in accepting the challenge of explaining development in a broad sense. In his autobiography, Baldwin affirms that already in the 10 years that he spent in Princeton between 1893 and 1903, where he founded another laboratory of experimental psychology, “the new interest in genetic psychology and general biology had become absorbing, and the meagerness of the results of the psychological laboratories (apart from direct work on sensation and movement) was becoming evident everywhere.” Thus, developmental psychology has followed an approach that in general psychology appeared much later 2 .

A second question regards method. Developmental researchers, while manifesting their attachment to experimental procedures, have been confronted with their insufficiency in the study of development. Both for deontological and practical reasons, many aspects of development, in particular in infants and young children, can hardly be investigated experimentally. Thus, a great number of studies in developmental psychology make use of observational methods based on different techniques such as ethnographic methods or parent reports, and the reliability of these methods has been questioned.

This relative separation between studies of adults and children has also persisted with the emergence of cognitive science. Actually, the primary aim of cognitive science, at least at the outset, was to model what we could call an adult static mind. Given a certain output, for instance an action, the task of the psychologist was to reconstruct the inference processes that were at the origin of this same action.

At the beginning of the twenty-first century, psychology and cognitive science have enlarged their scope to include change processes and the interaction between mind and environment, including other minds. Developmental psychology, for its part, has developed nonverbal methods such as looking measures and choice measures that also make it possible to carry out experiments with infants. These facts have paved the way for new possibilities of convergence, which are eliciting interesting results, despite a number of ongoing problems related to methods.

Psychology, Cognitive Science and Artificial Intelligence

The beginning of cognitive science.

According to the American psychologist George Miller, cognitive science was born on September 11, 1956, the second day of the Second Symposium on Information Theory held at MIT. That day began with a paper read by Allen Newell and Herbert Simon on the state of art of the Logic Theory Machine: a proof on computer of theorem 2.01 of Whitehead and Russell’s Principia Mathematica . That very same day ended with the first version of Chomsky’s The Structures of Syntax . Miller left the symposium convinced that experimental psychology, theoretical linguistics, and computer simulation of cognitive processes could become parts of a wider whole and that the future of research would be found in the elaboration of this composite whole (reported in Bruner, 1983a ). It is Miller who in 1960, together with Eugene Galanter and Karl Pribram, authored a text that may be considered the manifesto of cognitive science and that proclaimed the encompassing of cognitive psychology within the more general framework of information processing ( Miller et al., 1960 ). The assumption was that newly born information science could provide a unifying framework for the study of cognitive systems ( Schank and Abelson, 1977 ).

From a theoretical point of view, the core of this project is the concept of representation. Intentional mental states, such as beliefs and perceptions, are defined as relations to mental representations. The semantic properties of mental representations explain intentionality ( Pitt, 2017 ). Representations can be computed and thus constitute the basis for some forms of logic systems. According to the Cognitive Science Committee (1978) , which drew up a research project for the Sloan Foundation, all those disciplines, which belong to cognitive science, share the common goal of investigating the representational and computational capacities of the mind and the structural and functional realization of these capacities in the brain.

This point of view constitutes the foundation for what has been called functionalism in the philosophy of mind, i.e., the hypothesis that what defines the mind are those features that are independent of its natural realization. The classic functionalist stance is expressed by Pylyshyn in his book on computation and cognition ( Pylyshyn, 1984 ). He maintains that a clear distinction must be made between the functional architecture of the cognitive system and the rules and representations that the system employs.

Functionalism has been greatly discussed and criticized from the beginning ( Block, 1978 ; Dreyfus, 1979 ). Harnad (1990) identified what has been defined as the symbol grounding problem : “How can the semantic interpretation of a formal symbol system be made intrinsic to the system?”

The most exhaustive and most deeply argued critique of functionalism was advanced by Searle, who developed his arguments over time, publishing a number of essays which have given rise to heated debate ( Searle, 1980 , 1990 , 1992 ). The position taken up by functionalism is that the relationship between the brain and its products, that is to say conscious processes, is mediated by an intermediate level of unconscious rules. This intermediate level is, for functionalists, the level of the program. It is postulated that the rules are computational and that, consequently, the aim of research in cognitive science is to reconstruct these rules. Searle’s objection is that there are only two types of natural phenomena, the brain and the mental states that the brain brings into being and that humans experience. The brain produces mental states due to its specific biological characteristics. When we postulate the existence of unconscious rules, according to Searle, we invent a construct whose aim is to highlight a function, which we believe is especially significant. Such a function is not intrinsic and has no causal power. This argument is particularly interesting because it is founded on the impassable biological nature of the mind. Neither logic nor mathematical or statistical procedures may replace brain as a biological organ.

From another perspective, some scholars have emphasized that functionalism leads to a new form of behaviorism. Putnam (1988) claimed that reducing mental processes exclusively to their functional descriptions is tantamount to describe such processes in behavioristic terms 3 . In psychology, one of the most polemical critics of functionalism as a dangerous vehicle toward a new form of anti-mentalism, which would render vain all the battles waged by cognitivists against classic behaviorism, was a developmental psychologist, Bruner (1990) . The centrality of computability as the criterion for the construction of models in cognitive science leads naturally, in Bruner’s opinion, to abandoning “meaning making,” which was the central concern of the “Cognitive Revolution.”

Thus, at least at the outset, cognitive science was devoted to constructing computational models of human inference processes and of the knowledge that is used in performing these inferences. This definition of the object of cognitive science has led at first to designing and implementing problem-solving systems, where the complexity was located in the inference mechanisms, supposed to be the same for all problems ( Newell and Simon, 1972 ). Later, systems were implemented where reasoning was associated with specific and articulated knowledge representation ( Levesque and Brachman, 1985 ).

Notably, the aspect that was absent from this view of cognitive science was learning. This lack, according to Gentner (2010) , could be partly explained as a reaction to behaviorism, which was completely centered on learning. In fact, there were also philosophical reasons. Chomsky and Fodor, who were among the most influential members of the cognitive science community, were highly critical of the concept of learning. In their view, learning as a general mechanism does not exist, and Fodor even went so far as to state explicitly that no theory of development exists either ( Fodor, 1985 ).

Thus, cognitive science was born essentially as a reaction to behaviorism and took its legitimacy from the use of methodologies developed within artificial intelligence. These methodologies were supposed to make explicit how mental representations produced human activity in specific domains. However, this approach had a price: it separated the mind from its biological basis and from the context in which human activity takes place. There was no place for development, interaction, and variation due to biological or social causes 4 . This theoretical choice explains Bruner’s disillusion. For Bruner, cognitive science had fallen back into the behaviorism against which it originated, and no interesting relation could be established with developmental psychology. Developmental psychology is founded on the premise that a human being develops in interaction with the physical world and the society of other humans.

Cognitive Science in the Twenty-First Century

Cognitive science has changed considerably from its beginning. An obvious novelty concerns the increased importance assumed by learning with the emergence of connectionism ( Hinton, 1989 ).

When connectionist models were introduced, there was much debate regarding the relation of neural networks with the functioning of the human brain and their ability to address higher forms of thought ( Fodor and Pylyshyn, 1988 ; Quinlan, 1991 ; Chalmers, 1993 ). Later, philosophical discussion was replaced by empirical considerations. Networks are an efficient computational tool in some domains and are often used jointly with symbolic computations ( Wermter and Sun, 2000 ). Moreover, in recent advancements of artificial Intelligence, neural networks have been largely replaced by a variety of techniques of statistical learning ( Forbus, 2010 ).

More interesting for my purpose is the changes that the general philosophy of cognitive science has undergone due to the problems that have emerged with classic symbolic models. At its origin, the core of cognitive science was the relation between psychology and artificial intelligence. In the original project, this marriage was to be fruitful for both disciplines. Artificial intelligence expected from psychology the analysis of high-level mental mechanisms that, once simulated on a computer, could improve the efficiency of artificial systems. With computer simulation, psychology was to acquire a method to validate its models. However, this marriage, which for a while has been very productive and has generated many interesting ideas, ultimately failed. Artificial intelligence has evolved computing techniques that produce efficient systems without asking anymore if these techniques replicate human mental processes more or less faithfully. In psychology, the constraint to produce computational models has again restricted its scope ( Airenti and Colombetti, 1991 ).

Thus, the results of cognitive science of the twentieth century have led to a shift in cognitive science that has emerged with this century. Some researchers have proclaimed that the theoretical hypothesis that minds functionalities can be modeled disregarding the fact that they operate on the external world through the body could no longer be accepted. This new approach implies accounting for the biology of the mind/body unity and the interaction with the external world, both physical and social. One source of inspiration for this new turn came from Varela et al. (1991) , who proposed the concept of the embodied mind . Actually, the concept of embodiment includes many rather disparate inspirations, from Merleau-Ponty and phenomenology to Buddhism. I do not analyze these questions here. What interests me is the mere assumption that cognition is grounded in the world.

This new turn corresponds to the major importance assumed by robotics. It might be exaggerated to say that the role played by artificial intelligence in the past is now assumed by robotics. However, it is clear that the aim of constructing artificial actors that interact with the world and/or with humans has again established a link between the study of humans and the production of artificial systems. With respect to the past, the focus is no longer on the symbolic function of the mind, but on the mind embedded into a physical device that interacts with the external world. This evolution is linked to the enlarged scope of present robotics that goes well beyond traditional tasks such as farm automation. The ambition is to construct robots that may cooperate with humans in a multiplicity of tasks, including, for instance, assisting aged or disabled people or interacting with autistic children. Social robotics has then evolved toward biologically inspired systems, based on the notions of self-organization and embodiment ( Pfeifer et al., 2007 ). This new development has led to question once again psychologists about those characteristics that make humans what they are. If robots must be able to interact with humans, they should show those same characteristics ( Kahn et al., 2007 ). Can robots be endowed with intentionality, emotions, and possibly empathy?

Here, again a functionalist position appears. For some authors, the fact that the robot’s internal mechanisms are grounded in physical interactions with the external environment means that they truly have the potentiality of intrinsic intentionality ( Zlatev, 2001 ). This means, for them, that a mind is embodied in a robot. To the question of whether robots can have emotions, Arbib and Fellous (2004) answer that a better knowledge of biological systems will allow us in the future to single out “brain operating principles” independent of the physical medium in which they are implemented. This new form of functionalism is currently contrasted with an approach that considers that mental states and emotions are not intrinsic but can only be attributed to robots by humans ( Ziemke et al., 2015 ). Robots’ embodiment does not overcome the objection that was addressed to traditional artificial intelligence, namely that mental states and emotions can only be produced by a biological brain ( Ziemke, 2008 ). This latter position maintains that the relevant question for human-robot interaction is not that robots must be intentional beings, but that they must be perceived as such by humans ( Airenti, 2015 ; Wiese et al., 2017 ).

In conclusion, we can say that cognitive science was born as a way to renew psychology through a privileged connection with artificial intelligence. In the present state of research, it is social robotics that is attempting to establish a connection with biological sciences, psychology, and neuroscience, in order to build into robots those functionalities that should allow them to successfully interact with the external physical and social world. However, the main fundamental philosophical problems remain unchanged. One could still argue, as Searle did, that human mentality is an emergent feature of biological brains and no logical, mathematical or statistical procedure can produce it.

Present Questions for Cognitive Science

The question that we may raise today is this: what is cognitive science for? The relation that psychology has established with the sciences of the artificial has hidden the fact that a number of phenomena, which are essential for explaining the functioning of the human mind, have been largely ignored. This failure in explanation, which has concerned, for instance, the managing of mental states and emotions, and many complex communicative phenomena, is fundamentally linked to the fact that the mind is constantly in interaction with the physical and social world in a process of development. The primitive idea of cognitive science was to go beyond traditional psychology to enrich the study of mind with the contributions of other disciplines that also investigated human mind, such as linguistics, philosophy, and anthropology. This approach, which concerns the definition of the field of cognitive science, has been quite early reinterpreted as a problem of formalism. The question posed has been: how could psychology produce scientific models of human thought? Hence, the importance assumed by computer modeling as a means of replacing more traditional logical, mathematical, and statistical models. However, this theoretical choice has generated a major ambiguity, because computer models that are founded on logical, mathematical, or statistical formalisms have been seen as possibly equivalent to the mind. Once the fallacy of this equivalence appears—because no artificial model may replace the causal power of the human brain—we are left with some formal models with very limited psychological significance. What has been lost is the richness that cognitive science was supposed to acquire by connecting different disciplines. In particular, for many years, this approach has prevented general psychology from connecting with developmental psychology, a field of studies that, since Baldwin, had already posed the problem of the construction of the human mind as the result of biological development and social interaction.

The Study of Development

Biology and development in the debate between piaget and chomsky.

Studying development necessarily implies considering the fact that humans are biological systems that are certainly particularly complex but also share many characteristics with other living beings. Thus, in the field of developmental psychology, many questions have emerged concerning the link between development and evolution, the relation between genetic endowment and the influence on acquisition of environment (a concept that includes physical environment, parenting, social rules, etc.), and the nature of learning.

For Piaget, who came to developmental psychology from natural sciences, development had to be seen in the light of the theories of evolution. Intelligence, for him, is a particular case of biological adaptation, and knowledge is not a state but a process. Through action, children explore space and objects in the external world, and in this way, for instance, they learn the properties of the objects and their relations. These ideas, which sound rather contemporary to us, were considered as problematic in the past and prevented the establishment of a relationship between the study of development and the study of cognition in general. It is only in this century that development has been integrated into evolution studies via the so-called evo-devo approach and that these ideas have given rise to an interest in psychology ( Burman, 2013 ).

Actually, some aspects of Piaget’s perspective were problematic. Piaget supported his theory using what was considered a Lamarckian vision of evolution that assumed the inheritance of acquired characteristics. He had a well-known debate at the end of his life (1975) with Noam Chomsky on language acquisition, and outstanding biologists who also participated to the debate contested the validity of his use of the concept of phenocopy ( Piattelli-Palmarini, 1979/1980 ). In fact, on this point, Piaget had been influenced by Baldwin, who proposed what is known as Baldwin’s effect ( Simpson, 1953 ). This effect manifests in three stages: (1) Individual organisms interact with the environment in such a way as to produce nonhereditary adaptations; (2) genetic factors producing similar traits occur in the population; and (3) these factors increase in frequency under natural selection (taken from Waddington, 1953 ). Later, Piaget revised his own theory and updated Baldwin’s effect under the influence of Waddington ( Burman, 2013 ). Recently, epigenetic theories have emerged in biology, and the importance of development is generally accepted. On the developmental side, it has been proposed that Piaget’s theory might be replaced as a metatheory for cognitive development by evolutionary psychology ( Bjorklund, 2018 ).

The debate between Chomsky and Piaget is interesting because it is a clear example of the impossibility of dialogue between one of the fathers of cognitive science and the scholar who, at that moment, personified developmental psychology. Piaget was unable to justify his position that grammar rules could also be accounted for by sensorimotor schemata, and Chomsky appeared to have won the debate. At the same time, Chomsky presented the emergence of syntactic rules in the child’s mind, excluding in principle any possible form of learning. However, in hindsight, we know how the task of establishing abstract principles of universal grammar proved to be arduous, underwent many substantial changes and is not yet realized.

Another controversial aspect of Piaget’s position was his adherence to the recapitulation theory, i.e., the idea originally proposed by Haeckel, that ontogeny recapitulates phylogeny. It is this principle that motivated Piaget’s study of development as a way of contributing to the study of the evolution of human thought ( Koops, 2015 ). However, this position has as its consequence the idea that primitive populations would exist wherein we might find adult thought processes that in modern civilizations are typical of young children.

What is striking in this debate is that the specific biological model that Piaget adopted was not the only point of disagreement. What was questioned was in general the relevance of development for the study of a basic human ability such as language. Certainly, in the work of the first figures of developmental psychology, we find a baffling mix of very interesting ideas regarding the place of humans as biological entities in evolution and a difficulty in taking into account the complexities of actual biological theories and of social aspects such as cultural variation. At the same time, these scholars were confronted with objections from cognitive scientists who did not admit the relevance of investigating development for the study of the human mind.

The Interactionist Perspective

Piaget’s perspective was, in a sense, paradoxical. This perspective considered children’s development as the product of their action on the environment, but at the same time postulated a rather rigid succession of stages that led to adult thought and excluded the importance of the social aspects of this environment in the first years. In fact, infants and young children were considered closed in their egocentrism and unable to take advantage of their interactions with adults and peers.

These aspects have been criticized within developmental psychology, where a cultural turn, fathered by Vygotsky (1962/1986) and mainly interpreted in the United States by Bruner (1990) , has arisen. For both these authors, biological factors are considered an endowment of potentialities that develop in a society of co-specifics and are submitted to variability and to cultural variation.

Bruner was, at the outset, an enthusiastic supporter of cognitive science and in particular of the mentalist theory of language proposed by Chomsky ( Bruner, 1983b ). Later, however, the primacy that Chomsky assigns to syntax turned out to be unsatisfactory to Bruner, according to whom language is fundamentally a communicative device. The problem of language acquisition is thus redefined as the development of a communicative capacity that appears in the prelinguistic stage. This position was the result of Bruner’s work on preverbal communication carried out at the Center for Cognitive Studies at Harvard University starting in 1966.

For Bruner, language requires the maturation of cognitive structures, which underlie intentional action in general. His debt to Piaget with regard to the importance of action is evident. Language is “a specialized and conventionalized extension of cooperative action” ( Bruner, 1975 ). In this, he rejoins the communication theories proposed within the philosophy of language by Austin (1962) and Grice (1989) .

Bruner’s studies are part of a revolution in developmental studies in which more careful scrutiny and more sophisticated experimentation led to the discovery that children begin to engage in rather complex cognitive activity very early on. Prior to these studies, many of the aspects relating to infant cognition were not taken into consideration. The prejudice that saw human development as the slow acquisition of rationality prevented researchers from seeking elements of complexity in the cognition of a new-born.

In brief, since its origin, developmental psychology has undergone an important change. At the outset, the idea was that what characterized human cognition was adult rational thought, and studying development meant understanding the stages that led to this achievement. Later, the goal became understanding the development of the different faculties that characterize cognition starting from birth. This goal has also opened the door to comparative studies.

The Problems of Method

Developmental psychologists have always struggled with problems of method.

Piaget frequently discussed his observations of his three children. Studies on language acquisition have often benefited from researchers’ observations of their own children (see, for instance, Stern and Stern, 1928 ). These procedures, which have been considered as barely scientific by other psychologists, have provided useful inspiration for further research. Note that Darwin’s observations of his children were a fundamental source for his work on emotions ( Darwin, 1872/1965 ).

Ethical reasons forbid experiments, which may perturb children. Moreover, conceiving experiments that have ecological validity is even more difficult to do with young children than with adults. Hence, the necessity of using different methods in order to produce data that cannot be collected using classic experimental procedures. Without using observational methods, for instance, it is not possible to assess the spontaneous appearance of a given phenomenon ( Airenti, 2016 ). Furthermore, some behaviors may appear only in specific situations and would go unnoticed if they were not observed by caregivers who may see children at different moments of the day and in different situations. Thus, developmental psychologists have used different methodologies, classic experiments but also fieldwork, ethological observation, and parent reports.

A fundamental advancement was the development of techniques permitting to assess infants’ and young children’s abilities in experiments. A key element was the elaboration of the habituation paradigm ( Fantz, 1964 ; Bornstein, 1985 ). After repeated exposure to a stimulus, infants’ looking time decreases due to habituation and increases when a novel stimulus is presented. Habituation allows us to understand if infants discriminate among different stimuli.

In particular for language studies, nonnutritive sucking ( Siqueland and De Lucia, 1969 ) has been used. This is an experimental method based on operant conditioning allowing one to test infants’ discrimination of and preference for different stimuli. This technique has been used to show, for instance, that infants already acquire in the mother’s womb the ability to recognize and prefer the prosody of a language and of familiar voices ( DeCasper and Fifer, 1980 ).

Currently, the most utilized technique with infants is preferential looking or reaching. In this technique, two stimuli are presented together and what is measured is the infant’s preference. Specific types of this technique are used to claim surprise, anticipation, and preferences for novel or familiar stimuli and to evaluate preference over and above novelty or familiarity ( Hamlin, 2014 ) 5 .

Another technique presently used to investigate infant cognitive development is EEG recordings, even if creating infant-friendly laboratory environments, age-appropriate stimuli, and infant- friendly paradigms requires special care ( Hoehl and Wahl, 2012 ).

The development of these experimental techniques has vastly enlarged the scope of infant studies. In particular, a new research trend has emerged aimed at discovering what has been called the core knowledge ( Spelke, 2000 ; Spelke and Kinzler, 2007 ). The idea is that at the basis of human cognition, there is a set of competencies, such as representing objects, action, number and space, which are already present in infants and which underlie and constrain later acquisitions. Researchers have also been working on other possible basic competencies such as social cognition ( Baillargeon et al., 2016 ) and morality ( Wynn and Bloom, 2014 ).

In the literature, debate continues surrounding the replicability and robustness of findings obtained within these experimental paradigms, in particular with respect to infants’ and toddlers’ implicit false belief and morality ( Hamlin, 2014 ; Tafreshi et al., 2014 ; Baillargeon et al., 2018 ; Sabbagh and Paulus, 2018 ).

This debate also involves the relation between development and evolution. For Tafreshi and colleagues, for instance, the idea of core knowledge would involve a consideration of high-level cognitive capacities as biologically predetermined instead of constructed in interaction with the environment. This is not the perspective of those who consider that development does exist in the social environment but is constrained by a number of basic competencies ( Hamlin, 2014 ). An important element of this perspective is comparing human and animal capacities. In fact, research has shown that such basic competencies also exist in some form in animals. For instance, numerous studies have shown that adult nonhuman primates have the core systems of object, number, agent representations, etc. ( Spelke and Kinzler, 2007 ).

These preoccupations have also informed work by Tomasello and the Leipzig group. “All we can claim to have done so far–writes Tomasello–is to establish some comparative facts–organized by some theoretical speculations–that hopefully get us started in the right direction toward an evolutionary informed account of the ontogeny of uniquely human psychology” ( Tomasello, 2018 ). Comparing experimental work on great apes and young children has led him to formulate the hypothesis that the factors marking the difference between these two groups are different aspects of social cognition. Nonhuman primates have some basic capacities in these areas. In humans, the evolved capacity for shared intentionality transforms them in the species-unique human cognition and sociality ( Tomasello and Herrmann, 2010 ).

Tomasello’s work has also aroused criticism. In this case, the criticism is because his research, both with young children and primates, uses experimental methods and is carried out in a laboratory. Fieldwork primatologists have claimed that primates in captivity, tested by someone of another species, cannot display the abilities that their conspecifics display in their natural environment ( Boesch, 2007 ; De Waal et al., 2008 ). Tomasello answered this criticism by maintaining that the fact of being raised in a human environment enhances primates’ capacities ( Tomasello et al., 1993 ; Tomasello and Call, 2008 ).

In conclusion, in developmental psychology, a multiplicity of methods has been applied, and the debate over their respective validity and correct application continues. However, what is not in question is that development is a complex and multifaceted phenomenon that must be analyzed as such and from different points of view.

A paradigmatic case in the present research is the study of the theory of mind. Discovering how subjects represent their own mind and other minds was proposed in 1978 by Premack and Woodruff as a problem of research on primates, and in a short time, it has become one of the main topics in developmental research ( Premack and Woodruff, 1978 ). It is currently being studied in groups of different ages, from infants to the elderly, both in typical and clinical subjects and using different methodologies, from classic experiments to clinical observation. Moreover, a number of studies investigate individual and cross-cultural variation and its role in human-robots interactions. Philosophers have contributed to the definition of this phenomenon, and neuroscientists are working to discover its neural basis.

Computational Models of Development

Some researchers have pursued the goal of constructing computational models of cognitive development using different computational approaches (for a review, see Mareschal, 2010 ). However, as the author of this review remarks, all the models have explored cognition “as an isolated phenomenon”, i.e., they did not consider the physical and social context in which development unfolds.

Karmiloff-Smith, a developmental psychologist who proposed the most interesting theory about developmental change as an alternative to Piaget’s, considered that a number of features of her RR ( representational redescription ) model happened to map onto features of connectionist models ( Karmiloff-Smith, 1992 ; for a review of these models, see Plunkett et al., 1997 ). However, she also remarks that connectionist models have modeled tasks, while development is not simply task-specific learning, as it involves deriving and using previously acquired knowledge 6 .

One result of the dissatisfaction with the results deriving from the relation between cognitive psychology and artificial intelligence and the concomitant increase in interest in embodied cognition has been the growth of developmental robotics ( Lungarella et al., 2003 ). The aim of this field is to produce baby robots endowed with sensorimotor and cognitive abilities inspired by child psychology and to model developmental changes ( Cangelosi and Schlesinger, 2018 ). This approach has led to the comparison of results in experiments with robots and children. This is a promising field, even if it does not overcome the problems described above regarding the specificity of tasks that does not allow to account for infants’ ability to utilize previously differently acquired knowledge in the performance of a given task.

In conclusion, some approaches within cognitive science have acknowledged the usefulness of studying children in order to understand the mechanisms of development. Especially in the case of developmental robotics, this has allowed for studying the interaction of different capacities such as sensorimotor abilities, perception, and language. At the same time, the computational constraints do not allow for overcoming task specificity.

Concluding Remarks

I have argued that since their beginning, general psychology and developmental psychology have followed parallel paths that have only occasionally converged. The reason is due essentially to methodological problems that have involved not only research methods but also the very object of inquiry.

Psychology was founded with the ambition of becoming a science performed in laboratories and based on experimental work. However, as early as in 1934, Vygotsky had already deplored the attempt to achieve scientific standards by limiting the importance of general issues. “As long as we lack a generally accepted system incorporating all available psychological knowledge, any important factual discovery inevitably leads to the creation of a new theory to fit the newly observed facts” ( Vygotsky, 1962/1986 , p. 13).

The birth of cognitive science has taken important steps toward constructing links with other disciplines and also other ways to study cognition. However, this opening was soon transformed in the search for a unifying methodology, namely computer modeling, as a guarantee of scientific results. Many interesting ideas have been generated. However, after four decades of work in this direction, it has become impossible to ignore that too many important aspects of the human mind and activity have been eluded.

The relative isolation of developmental psychology came from the prejudice, also shared by eminent developmental psychologists like Piaget, that what characterizes human cognition are adult cognitive abilities.

However, from the start, developmental psychology was not limited to investiganting the specificity of children’s cognition. It devoted attention to what makes development possible, including biological endowment and cultural transmission; whether an infant should be considered a blank slate or if one can define some pre-existent basic abilities; what makes humans different from animals and nonhuman primates; and how specific human abilities such as language have evolved.

At present, a rapprochement between adult and child studies is made possible by different factors. The possibility of using experimental methods to study infancy has allowed us to realize the complexity of young humans. Moreover, development is increasingly being considered as a phenomenon not only characterizing childhood but also present over the life span, including both the acquisition and the decay of mental abilities ( Bialystok and Craik, 2006 ). Studying the human mind means studying how the human mind changes in interaction with the external environment all life long. In this sense, the study of human mind is inherently connected with the study of its development.

An important question of method emerges here. We have observed that over the years, developmental psychologists have sought to construct methods that can be reliable and at the same time can adequately address the topics under discussion here. The achievement of finding ways to carry out experiments with infants and nonhuman primates has been an important advancement in this perspective. This advancement has garnered both praise and criticism. To be reliable, experiments with infants require very rigorous procedures. Frequently, a detailed analysis of procedures is necessary to explain divergent results. However, it can be noted that reproducibility is an open problem for psychological science in general ( Open Science Collaboration, 2015 ). For nonhuman primates, the ecological validity of laboratory experiments has been questioned. More generally, it has been shown that in the field of developmental psychology, experimental studies do not completely replace other methodologies, but rather should coexist with them.

The human mind is complex, and all the methods that have been proposed in different disciplines may be useful in advancing our knowledge of it. The explanation of this complexity was the main goal underlying the proposal of cognitive science and is the perspective we must pursue in the future.

On this ground, the paths of psychology and developmental psychology may reconverge.

Author Contributions

The author confirms being the sole contributor of this work and has approved it for publication.

Conflict of Interest Statement

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The reviewer MT declared a shared affiliation, with no collaboration, with the author to the handling editor at time of review.

1 The very earliest date was 1875 and that same year William James’ laboratory at Harvard in the United States was established ( Harper, 1950 ).

2 William James was influenced by Darwin and this appears in particular in his conceiving the mind as a function and not as a thing ( Bredo, 1998 ). However, his book The Principles of Psychology , first published in 1890 and later revised several times, ignored child development. In the chapter devoted to methods and snares in psychology, he adds to introspective observation and experimental method the comparative method. “So it has come to pass that instincts of animals are ransacked to throw light on our own; and that the reasoning faculties of bees and ants, the minds of savages, infants, madmen, idiots, the deaf and blind, criminals, and eccentrics, are invoked in support of this or that special theory about some part of our own mental life” ( James, 1983 , p. 193). If he admits that “information grows and results emerge”, he also cautions that “there are great sources of error in the comparative method” and that “comparative observation, to be definite, must usually be made to test some pre-existing hypothesis” ( James, 1983 ).

3 Putnam was actually the first to employ the term functionalism , and his aim in doing so was anti-reductionist. In his 1975 work he used the comparison with a computer program to show that psychological properties do not have a physical and chemical nature, even though they are realized by physical and chemical properties ( Putnam, 1975 ).

4 , Hewitt (1991) highlights the difficulties inherent in constructing artificial systems, which, like social systems, are founded on concepts such as commitment, cooperation, conflict, negotiation, and so forth.

5 Gaze and eye-tracking techniques are normally used in psychological research with adults ( Mele and Federici, 2012 ) but it is in developmental studies that they have had a dramatic impact on the possibilities of inquiry.

6 A different approach that has given origin to formal models and simulations is the paradigm that views the developmental process as a change within a complex dynamic system. Cognition in this perspective is embodied in the processes of perception and action ( Smith and Thelen, 2003 ).

• Airenti G. (2015). The cognitive bases of anthropomorphism: from relatedness to empathy . Int. J. Soc. Robot. 7 , 117–127. 10.1007/s12369-014-0263-x [ CrossRef ] [ Google Scholar ]
• Airenti G. (2016). Playing with expectations: a contextual view of humor development . Front. Psychol. 7 :1392. 10.3389/fpsyg.2016.01392 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Airenti G., Colombetti M. (1991). “ Artificial intelligence and the representation problem ” in Proceedings of the first world conference on the fundamentals of artificial intelligence. (Paris: Angkor; ), 17–28. [ Google Scholar ]
• Arbib M. A., Fellous J.-M. (2004). Emotions: from brain to robot . Trends Cogn. Sci. 8 , 554–561. 10.1016/j.tics.2004.10.004, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Austin J. A. (1962). How to do things with words. (Oxford: Oxford University Press; ). [ Google Scholar ]
• Baillargeon R., Buttelmann D., Southgate V. (2018). Invited commentary: interpreting failed replications of early-false belief findings: methodological and theoretical considerations . Cogn. Dev. 46 , 112–124. 10.1016/j.cogdev.2018.06.001 [ CrossRef ] [ Google Scholar ]
• Baillargeon R., Scott R. M., Bian L. (2016). Psychological reasoning in infancy . Annu. Rev. Psychol. 67 , 159–186. 10.1146/annurev-psych-010213-115033, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Baldwin J. M. (1895). Mental development in the child and the race. (New York, NY: Macmillan; ). [ Google Scholar ]
• Baldwin J. M. (1930). “ Autobiography of James Mark Baldwin ” in History of psychology in autobiography. ed. Murchison C., Vol. 1 (Worchester, MA: Clark University Press; ), 1–30. [ Google Scholar ]
• Bialystok E., Craik F. I. M. (2006). Lifespan cognition: Mechanisms of change. (New York: Oxford University Press; ). [ Google Scholar ]
• Bjorklund D. F. (2018). A metatheory for cognitive development (or “Piaget is dead” revisited) . Child Dev. 89 , 2288–2302. 10.1111/cdev.13019, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Block N. (1978). Troubles with functionalism. Minnesota studies in the philosophy of science. Vol. 9 (Minneapolis: University of Minnesota Press; ), 261–325. [ Google Scholar ]
• Boesch C. (2007). What makes us human (Homo sapiens)? The challenge of cognitive cross-species comparison . J. Comp. Psychol. 121 , 227–240. 10.1037/0735-7036.121.3.227, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bornstein M. H. (1985). “ Habituation of attention as a measure of visual information processing in human infants: summary, systematization, and synthesis ” in Measurement of audition and vision during the first year of postnatal life: A methodological overview. eds. Gottlieb G., Krasnegor N. A. (Norwood, NJ: Ablex; ), 253–300. [ Google Scholar ]
• Bredo E. (1998). The Darwinian center to the vision of William James. Paper presented at the Annual Meeting of the American Educational Research Association . (SanDiego, CA, April 13–17, 1998).
• Bruner J. S. (1975). The ontogenesis of speech acts . J. Child Lang. 2 , 1–19. [ Google Scholar ]
• Bruner J. S. (1983a). In search of mind: Essays in autobiography. (New York, NY: Harper and Row; ). [ Google Scholar ]
• Bruner J. S. (1983b). Child's talk: Learning to use language. (New York: Norton; ). [ Google Scholar ]
• Bruner J. S. (1990). Acts of meaning. (Cambridge, MA: Harvard University Press; ). [ Google Scholar ]
• Burman J. T. (2013). Updating the Baldwin effect. The biological levels behind Piaget’s new theory . New Ideas Psychol. 31 , 363–373. 10.1016/j.newideapsych.2012.07.003 [ CrossRef ] [ Google Scholar ]
• Cangelosi A., Schlesinger M. (2018). From babies to robots: the contribution of developmental robotics to developmental psychology . Child Dev. Perspect. 12 , 183–188. 10.1111/cdep.12282 [ CrossRef ] [ Google Scholar ]
• Chalmers D. (1993). Why Fodor and Pylyshyn were wrong: the simplest refutation . Philos. Psychol. 6 , 305–319. 10.1080/09515089308573094 [ CrossRef ] [ Google Scholar ]
• Cognitive Science Committee (1978). Report of the State of the Art, Ms.
• Darwin C. (1872/1965). The expression of emotions in man and animals. (Chicago: University of Chicago Press; ). [ Google Scholar ]
• De Waal F. B., Boesch C., Horner V., Whiten A. (2008). Comparing social skills of children and apes . Science 319 :569. 10.1126/science.319.5863.569c, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• DeCasper A. J., Fifer W. P. (1980). Of human bonding: newborns prefer their mothers’ voices . Science 208 , 1174–1176. 10.1126/science.7375928, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Dreyfus H. (1979). What computers can’t do: A critique of artificial reason. (New York, NY: Harper & Row; ). [ Google Scholar ]
• Fantz R. L. (1964). Visual experience in infants: decreased attention to familiar patterns relative to novel ones . Science 146 , 668–670. 10.1126/science.146.3644.668, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Fodor J. A. (1985). Fodor’s guide to mental representation: the intelligent auntie’s vademecum . Mind 94 , 76–100. [ Google Scholar ]
• Fodor J., Pylyshyn Z. (1988). Connectionism and cognitive architecture: a critical analysis . Cognition 28 , 3–71. 10.1016/0010-0277(88)90031-5, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Forbus K. D. (2010). AI and cognitive science: the past and next 30 years . Top. Cogn. Sci. 2 , 345–356. 10.1111/j.1756-8765.2010.01083.x, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Gentner D. (2010). Psychology in cognitive science: 1978–2038 . Top. Cogn. Sci. 2 , 328–344. 10.1111/j.1756-8765.2010.01103.x, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Grice H. P. (1989). Studies in the way of words. (Cambridge, MA: Harvard University Press; ). [ Google Scholar ]
• Hamlin J. K. (2014). The conceptual and empirical case for social evaluation in infancy. Commentary on Tafreshi, Thompson, and Racine . Hum. Dev. 57 , 250–258. 10.1159/000365120 [ CrossRef ] [ Google Scholar ]
• Harnad S. (1990). The symbol grounding problem . Physica D 42 , 335–346. 10.1016/0167-2789(90)90087-6 [ CrossRef ] [ Google Scholar ]
• Harper R. S. (1950). The first psychological laboratory . Isis 41 , 158–161. 10.1086/349141 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hewitt C. (1991). Open information systems semantics for distributed artificial intelligence . Artif. Intell. 47 , 79–106. 10.1016/0004-3702(91)90051-K [ CrossRef ] [ Google Scholar ]
• Hinton G. E. (1989). Connectionist learning procedures . Artif. Intell. 40 , 185–234. 10.1016/0004-3702(89)90049-0 [ CrossRef ] [ Google Scholar ]
• Hoehl S., Wahl S. (2012). Recording infant ERP data for cognitive research . Dev. Neuropsychol. 37 , 187–209. 10.1080/87565641.2011.627958, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• James W. (1983). The principles of psychology. (Cambridge, Mass: Harvard University Press; ). [ Google Scholar ]
• Kahn P. H., Jr., Ishiguro H., Friedman B., Kanda T., Freier N. G., Severson R. L., et al. (2007). What is a human? Toward psychological benchmarks in the field of human-robot interaction . Inter. Stud. 8 , 363–390. 10.1075/is.8.3.04kah [ CrossRef ] [ Google Scholar ]
• Karmiloff-Smith A. (1992). Beyond modularity. (Cambridge, Mass: The MIT Press; ). [ Google Scholar ]
• Koops W. (2015). No developmental psychology without recapitulation theory . Eur. J. Dev. Psychol. 12 , 630–639. 10.1080/17405629.2015.1078234 [ CrossRef ] [ Google Scholar ]
• Levesque H., Brachman R. (1985). “ A fundamental tradeoff in knowledge representation and reasoning (revised version) ” in Readings in knowledge representation. eds. Brachman R., Levesque H. J. (Burlington, MA: Morgan Kaufmann; ), 41–70. [ Google Scholar ]
• Lungarella M., Metta G., Pfeifer R., Sandini G. (2003). Developmental robotics: a survey . Con. Sci. 15 , 151–190. 10.1080/09540090310001655110 [ CrossRef ] [ Google Scholar ]
• Mareschal D. (2010). Computational perspectives on cognitive development . WIREs Cognit. Sci. 1 , 696–708. 10.1002/wcs.67, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Mele M. L., Federici S. (2012). Gaze and eye-tracking solutions for psychological research . Cogn. Proc. 13 , S261–S265. 10.1007/s10339-012-0499-z [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Miller G. A., Galanter E., Pribram K. (1960). Plans and structure of behavior. (New York, NY: Holt, Rinehart and Winston; ). [ Google Scholar ]
• Morgan T. J. H., Harris P. L. (2015). James Mark Baldwin and contemporary theories of culture and evolution . Eur. J. Dev. Psychol. 12 , 666–677. 10.1080/17405629.2015.1074068 [ CrossRef ] [ Google Scholar ]
• Newell A., Simon H. A. (1972). Human problem solving. (Englewood Cliffs, N.J: Prentice-Hall; ). [ Google Scholar ]
• Open Science Collaboration (2015). Estimating the reproducibility of psychological science . Science 349 :aac4716. 10.1126/science.1253751, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Pfeifer R., Lungarella M., Iida F. (2007). Self-organization, embodiment, and biologically inspired robotics . Science 318 , 1088–1093. 10.1126/science.1145803, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Piaget J. (1928). Logique génétique et sociologie . Revue Philosophique de la France et de l’Étranger 53 , 167–205. [ Google Scholar ]
• Piattelli-Palmarini M. (1979/1980). Language and learning: The debate between Jean Piaget and Noam Chomsky. (London: Routledge and Kegan Paul; ). [ Google Scholar ]
• Pitt D. (2017). “ Mental representation ” in The Stanford Encyclopedia of philosophy. ed. Zalta E. N. https://plato.stanford.edu/archives/spr2017/entries/mental-representation
• Plunkett K., Karmiloff-Smith A., Bates E., Elman J. L., Johnson M. H. (1997). Connectionism and developmental psychology . J. Child Psychol. Psychiatry 38 , 53–80. 10.1111/j.1469-7610.1997.tb01505.x, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Premack D., Woodruff G. (1978). Does the chimpanzee have a theory of mind? Behav. Brain Sci. 4 , 515–526. [ Google Scholar ]
• Putnam H. (1975). Mind, language and reality. (Cambridge: Cambridge University Press; ). [ Google Scholar ]
• Putnam H. (1988). Representation and reality. (Cambridge, MA: MIT Press; ). [ Google Scholar ]
• Pylyshyn Z. W. (1984). Computation and cognition. (Cambridge, MA: The MIT Press/Bradford; ). [ Google Scholar ]
• Quinlan P. T. (1991). Connectionism and psychology: A psychological perspective on new connectionist research. (Hemel Hempstead: Harvester Wheatsheaf; ). [ Google Scholar ]
• Sabbagh M. A., Paulus M. (2018). Editorial. Replication studies of implicit false belief with infants and toddlers . Cogn. Dev. 46 , 1–3. 10.1016/j.cogdev.2018.07.003 [ CrossRef ] [ Google Scholar ]
• Schank R. C., Abelson R. P. (1977). Scripts, plans, goals and understanding. (Hillsdale, N.J: Lawrence Erlbaum; ). [ Google Scholar ]
• Searle J. R. (1980). Minds, brains and programs . Behav. Brain Sci. 3 , 417–424. 10.1017/S0140525X00005756 [ CrossRef ] [ Google Scholar ]
• Searle J. R. (1990). Consciousness, explanatory inversion, and cognitive science . Behav. Brain Sci. 13 , 585–596. 10.1017/S0140525X00080304 [ CrossRef ] [ Google Scholar ]
• Searle J. R. (1992). The rediscovery of the mind. (Cambridge, MA: The MIT Press; ). [ Google Scholar ]
• Simpson G. G. (1953). The Baldwin effect . Evolution 7 , 110–117. 10.1111/j.1558-5646.1953.tb00069.x [ CrossRef ] [ Google Scholar ]
• Siqueland E. R., De Lucia C. A. (1969). Visual reinforcement of non-nutritive sucking in human infants . Science 165 , 1144–1146. 10.1126/science.165.3898.1144, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Smith L. B., Thelen E. (2003). Development as a dynamic system . Trends Cogn. Sci. 7 , 343–348. 10.1016/S1364-6613(03)00156-6, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Spelke E. S. (2000). Core knowledge . Am. Psychol. 55 , 1233–1243. 10.1037/0003-066X.55.11.1233, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Spelke E. S., Kinzler K. D. (2007). Core knowledge . Dev. Sci. 10 , 89–96. 10.1111/j.1467-7687.2007.00569.x, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Stern C., Stern W. (1928). Die Kindersprache [The speech of children. (4th Ed.)]. (Oxford, England: Barth; ). [ Google Scholar ]
• Tafreshi D., Thompson J. J., Racine T. P. (2014). An analysis of the conceptual foundations of the infant preferential looking paradigm . Hum. Dev. 57 , 222–240. 10.1159/000363487 [ CrossRef ] [ Google Scholar ]
• Tomasello M. (2018). Great apes and human development: a personal history . Child Dev. Perspect. 12 , 189–193. 10.1111/cdep.12281 [ CrossRef ] [ Google Scholar ]
• Tomasello M., Call J. (2008). Assessing the validity of ape-human comparisons: a reply to Boesch (2007) . J. Comp. Psychol. 122 , 449–452. 10.1037/0735-7036.122.4.449, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Tomasello M., Herrmann E. (2010). Ape and human cognition: what’s the difference? Curr. Dir. Psychol. Sci. 19 , 3–8. 10.1177/0963721409359300 [ CrossRef ] [ Google Scholar ]
• Tomasello M., Savage-Rumbaugh S., Kruger A. (1993). Imitative learning of actions on objects by children, chimpanzees and enculturated chimpanzees . Child Dev. 64 , 1688–1705. 10.2307/1131463, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Varela F. D., Rosch E., Thompson E. (1991). The embodied mind: Cognitive science and human experience. (Cambridge, MA: MIT Press; ). [ Google Scholar ]
• Vygotsky L. (1962/1986). Thought and language. (Cambridge, MA: The MIT Press; ). [ Google Scholar ]
• Waddington C. H. (1953). The ‘Baldwin effect,’ ‘genetic assimilation’ and ‘homeostasis’ . Evolution 7 , 386–387. [ Google Scholar ]
• Wermter S., Sun R. (eds.) (2000). Hybrid neural symbolic integration. (Berlin: Springer Verlag; ). [ Google Scholar ]
• Wiese E., Metta G., Wykowska A. (2017). Robots as intentional agents: using neuroscientific methods to make robots appear more social . Front. Psychol. 8 :1663. 10.3389/fpsyg.2017.01663 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Wynn K., Bloom P. (2014). “ The moral baby ” in The handbook of moral development. 2nd Edn. eds. Killen M., Smetana J. G. (New York: Psychology Press; ), 435–453. [ Google Scholar ]
• Ziemke T. (2008). On the role of emotion in biological and robotic autonomy . BioSystems 91 , 401–408. 10.1016/j.biosystems.2007.05.015, PMID: [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ziemke T., Thill S., Vernon D. (2015). “ Embodiment is a double-edged sword in human-robot interaction: ascribed vs. intrinsic intentionality ” in Proceedings of the workshop on cognition: A bridge between robotics and interaction , 9–10.
• Zlatev J. (2001). The epigenesis of meaning in human beings, and possibly robots . Minds Mach. 11 , 155–195. 10.1023/A:1011218919464 [ CrossRef ] [ Google Scholar ]

IResearchNet

Cognitive Psychology

History of cognitive psychology.

The history of cognitive psychology can be parsed into four periods: philosophical, early experimental, the cognitive revolution, and modern cognitive psychology.

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Get 10% off with 24start discount code, philosophical period.

Ancient Egyptian hieroglyphics suggest that thoughtful people were concerned with processes such as thought, memory, and most of all the “ka”, or soul, Great energy was directed toward preserving the soul but also some theorized that knowledge was localized in the heart. Greek philosophers were obsessed with knowledge and cognitive matters and current models of cognition often have some ties to ancient Greece. Aristotle’s views on the locus of knowledge were similar to the Egyptians. However, Plato postulated that the brain was the true locus of knowledge. Renaissance scholars considered thinking, logic, and the nature of the soul and, al­though divergent views were expressed, the locus of the knowledge and rationality was thought to be in the brain.

During the eighteenth century, philosophic debate over the source of knowledge took place between the empiricist and the nativist. A British empiricist believed knowledge came from experience. However, the nativist believed knowledge was innate and based on structural characteristics and properties inherent in the brain. Modern cognitive psychologists continue to argue these matters, although usually with scientific data.

The philosophic period provided a context for un­derstanding the mind and its processes. In addition, these early thinkers identified some major theoretical issues that would later be studied empirically using scientific research methods.

Early Experimental Period

Cognition has been studied scientifically since the end of the nineteenth century. In 1879, the philosophical aspects of mental processes gave way to empirical ob­servations when Wundt founded the first psychological laboratory in Germany in 1879. Psychology began to break away from philosophy and form a discipline based on objective science rather than on speculation, logic, and conjecture. Many forces propelled the break with moral philosophy, but certainly the development of new methods that allowed for the examination of mental events changed the way cognition was studied. Intro­spection, or looking within, was one such method that allowed the observer to examine consciousness and the structure of mental representation by breaking down an experience into sensations and images. By detecting patterns within introspective reports, the mind’s con­tents were presumed to be revealed.

Theories of knowledge representation became di­vided between introspectionists who studied observable sensations, and act psychologists, led by Brentano, who studied the activities of the mind. Brentano considered internal representations meaningless to psychology and chose to study mental acts of comparing, judging, and feeling physical objects.

By the beginning of the twentieth century American psychology was beginning to take a distinctive form with a wide range of topics under investigation. Lead­ing this expanded experimental psychology was Wil­liam James, the first president of the American Psycho­logical Association. His ideas on philosophy, religion, and psychology shaped the intellectual history of these topics throughout the twentieth century. No less im­portant were his thoughts about attention and memory, and his distinction of a dichotomy memory store—pri­mary and secondary memory—led directly to experi­ments in the 1960s on that topic. Clearly, James’s ideas were important in shaping modern cognitive psychol­ogy.

During this time, American psychologists became in­terested in educational matters and were greatly influ­enced by the objective nature of act psychology. Psy­chologists such as Thorndike were concerned with the effects of reward and punishment on learning and less concerned with consciousness. The introspective tech­nique, in which a subject asks himself what sensations he might experience, for example, were considered by American psychologists as being sterile and leading to inconsistent results. There was, argued many, a need for a purely objective and scientific psychology in which mental processes, such as memory, sensations, and learning, could be reliably measured. Behaviorism, led by John Watson, was predicated on the idea that overt behavior could be objectively observed, offered an at­tractive scientific approach to psychology, and was an appropriate foil to the rapidly developing interest in psy­choanalysis.

Despite interest in overt behavior, cognitive process were not totally neglected. During the early 1900s Donders and Cattell were conducting perception experiments on imageless thought using brief visual displays to examine the time required for mental operations to take place and using reaction time data as dependent measures.

In several laboratories in America interesting re­search was being done on memory, attention, percep­tion, language, concept formation, and problem solving that was the preformal stage of cognitive psychology. In addition to these efforts within psychology, several forces outside of traditional experimental psychology helped shape cognitive psychology. Among these forces are the considerable influence of the Swiss psychologist, Jean Piaget, whose central idea was that there are dis­tinctive cognitive stages through which children de­velop. In Russia, the brilliant young savant, Lev Vygotsky, suggested a model of development psychology in which learning precedes development. Another impor­tant influence was the work of Frederic Bartlett, from England, who investigated memory from a naturalistic viewpoint and was particularly concerned with the re­membering of stories. From recall of stories, Bartlett hypothesized that memory is largely determined by schemata, or the way knowledge is organized and rep­resented in the brain. Even some animal studies were beginning to embrace cognitive themes. In 1932, Tolman, a well-known behavioral psychologist, observed that rats learned a cognitive map of their environment while learning to run a maze.

Although cognition was not the dominant school of psychological thought in America during this time, some experimental psychologists demonstrated that scientific methodology could be used in the study of men­tal events. The techniques, subject matter, procedures, and even the interpretations used by these researchers anticipated the emergence of a cognitive discipline.

Concepts such as sensation, thinking, and mental imagery were anathema under the behaviorist’s influ­ence, as they were considered subjective. Internal states were considered intervening variables and not neces­sary to understand human behavior. Psychology had been concentrated on observable behaviors and human subjects were largely replaced with rats and pigeons.

Gestalt psychology offered an alternative way to study sensory perception to the problematic method of introspection that diffused the research on cognition. Concurrently the behaviorists attempted to create a purely objective psychology by successfully attacking the cognitive psychologists and Gestaltists as well.

Cognitive Revolution

Cognitive psychology began to take form as a new way of understanding the science of the mind during the late 1950s. These formative events were spurred on by research discoveries in memory, learning, and attention as well as ideas outside of the mainstay of experimental psychology, such as communication theory , develop­mental psychology, social psychology, linguistics, and computer science, which gave cognitive psychologists additional breadth to deal with the complexity of hu­man information processing and thinking.

The reemergence of cognitive psychology during this period is commonly referred to as the Cognitive Revo­lution, emerging in 1956 with a conference on com­munication theory at Massachusetts Institute of Tech­nology (MIT) (Solso, 1998) in which seminal papers were presented by Noam Chomsky, Jerome Bruner, Al­len Newell and Herbert Simon, and George Miller. The coalescence of cognitive psychology during this period was probably not due to a single group of people (and certainly no precise date of a movement is possible) but was a reflection of a larger Zeitgeist in which psychol­ogists appreciated the complexity of the thinking hu­man. At the same time, cognitive psychologists rejected the traditional, simplistic theories of the mind, but in many cases held on to the scientific methodology as had developed in the early part of the twentieth century. The paradigm that offered a pertinent methodol­ogy and embraced a sufficiently wide latitude of intel­lectual topics was cognitive psychology, which enjoyed widespread acceptance and growth.

Research in verbal learning and semantic organi­zation led to the development of testable models of memory and cognition, providing another empirical base for the study of mental processes. George A. Miller made a distinction between short-term and long-term memory and his influential paper The Magic Number Seven, Plus or Minus Two (Miller, 1956) addressed the limited capacity of short-term memory and introduced the concept of chunking—the idea that the limits of short-term memory could be extended by grouping in­formation into larger units of information. In 1958, Pe­terson and Peterson in America and John Brown in England found a rapid loss or decay of memory after the study of nonsense syllables after a few seconds when verbal rehearsal was absent, thus promoting the idea of a separate stage of short-term memory. In 1960, Sperling showed that a very transitory memory (or in­formation storage system) held information for a very brief period of time. This discovery further advanced the notion that humans were complex information-processing creatures who processed incoming infor­mation through a series of stages. That simple idea was a perfect model for researchers and theorists interested in memory, and several models appeared about this time by Atkinson and Shiffrin, Waugh and Norman, and later by Craik and Tulving.

Prior to this period, information theory was intro­duced by Shannon and Weaver, who used box diagrams to describe how information is communicated and transformed along a series of stages. Donald Broadbent, a psychologist at Cambridge, began applying Shannon and Weaver’s ideas to selective attention processes and introduced the concept of information flow to psychol­ogy and used box diagrams to describe cognitive pro­cesses. Broadbent’s information flow referred to the se­ries of operations that analyze, transform, or change mental events such as memory encoding, forgetting, thinking, concept formation, etc. As such, Broadbent provided “a language to talk about what happened in­side a man which was not a mentalistic introspective language” (Cohen, 1986, p. 23).

Elsewhere, technological advances in computer sci­ence called for reexamination of basic postulates of cognition. In 1955, Simon and Newell developed a computer capable of solving a mathematical proof. Cogni­tive psychologists were excited that machines could simulate human thought and computers could possibly be operating according to the same rules and proce­dures as the human mind. Furthermore, since com­puters were seen as intelligent, it required us to analyze our own intelligence so that the intelligence of a ma­chine could be determined. As a result the hypothetical Turing test was devised to determine if observers could discriminate the output of a computer from that of hu­man responses.

Meanwhile, the behaviorists came under attack from Chomsky, a linguist from MIT, who developed a method of analyzing the structure of language. Chomsky ar­gued that language was too complicated to learn and produce via behavioral principles of reinforcement and postulated the existence of a cognitive structure of an innate language acquisition device.

Another influence that aided cognitive psychology’s foothold was World War II. Financial support in areas of military interest became readily available during the war. Because of the military’s interest in developing and using new technology, research in vigilance, cre­ativity, and human factors was encouraged. One out­come was a seminal report in 1954 by Tanner and Swets on signal detection demonstrating that cognitive processes can have a mediating effect on sensory thresholds. Another outcome of the war was that many soldiers suffered from brain injuries. A vast amount of clinical data in perception, memory, and language was a by-product of these victims’ afflictions.

In the 1950s, interest turned to attention, memory, pattern recognition, images, semantic organization, language processes, thinking, and even consciousness (the most dogmatically eschewed concept), as well as other cognitive topics once considered outside the boundary of experimental psychology. Behaviorism and its dogma failed to account for the richness and diver­sity of human experience. Behaviorists could not ac­count for the results found by Piaget’s and Chomsky’s developmental studies. And information theory and computer science gave psychologists new ways to con­ceptualize and discuss cognition.

Modern Cognitive Psychology

By the 1960s, cognitive psychology had experienced a renaissance. Cognitive Psychology, which systematized the new science, was written by Ulric Neisser and was published in America (1967). Neisser’s book was cen­tral to the solidification of cognitive psychology as it gave a label to the field and defined the topical areas. Neisser used the computer metaphor for selecting, stor­ing. Recovering, combining, outputting, and manipu­lating information. And in 1966 Hilgard and Bower in­troduced a chapter in their Theories of Learning (New York) that developed the idea of using computer pro­grams to serve as models on theories of cognition.

The 1970s saw the emergence of professional jour­nals devoted to cognitive psychology such as Cognitive Psychology, Cognition, Memory & Cognition, and a series of symposia volumes, including the Loyola Symposium on Cognition edited by Solso and the Carnegie-Mellon series edited by Chase and others, based on the Car­negie Symposium on Cognition. In the 1970s and 1980s cognitive laboratories were beginning to be built, symposia and conferences appeared at national and re­gional meetings, courses in cognitive psychology and related topics were being added to curricula, grants were awarded to people investigating memory, lan­guage processing, attention, and like topics, new text­books were written on the theme of cognition, and uni­versities recruited professors of cognitive psychology to replace those of traditional experimental psychology. In the 1980s and 1990s serious efforts were made to find corresponding neural components that were linked to cognitive constructs. Thus, the cerebral location for a word, like hammer, as a noun, might be far different than the location for the same word if the word were used as a verb. Furthermore, influential memory the­ories (such as Tulving’s semantic and episodic memory theory) were manifest in cerebral localization experi­ments using brain imaging technology. The science of human cognition is still undergoing transformation due to major changes in computer technology and brain science. As a result cognitive psychology has converged with computer science and neuroscience to create a new discipline called cognitive science.

Finally, with the advent of new ways to see the brain (e.g. functional magnetic resonance imaging [fMRI], positron emission tomography [PET], electroencepha­logram [EEG]) cognitive psychologists have expanded their operations to neuroscience, which promises to empirically display the parts of the brain involved in cognition that were hypothesized by twentieth-century psychologists.

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What Is Cognitive Psychology?

The Science of How We Think

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Steven Gans, MD is board-certified in psychiatry and is an active supervisor, teacher, and mentor at Massachusetts General Hospital.

Topics in Cognitive Psychology

• Current Research
• Cognitive Approach in Practice

Careers in Cognitive Psychology

How cognitive psychology differs from other branches of psychology, frequently asked questions.

Cognitive psychology involves the study of internal mental processes—all of the workings inside your brain, including perception, thinking, memory, attention, language, problem-solving, and learning.

Cognitive psychology--the study of how people think and process information--helps researchers understand the human brain. It also allows psychologists to help people deal with psychological difficulties.

This article discusses what cognitive psychology is, the history of this field, and current directions for research. It also covers some of the practical applications for cognitive psychology research and related career options you might consider.

Findings from cognitive psychology help us understand how people think, including how they acquire and store memories. By knowing more about how these processes work, psychologists can develop new ways of helping people with cognitive problems.

Cognitive psychologists explore a wide variety of topics related to thinking processes. Some of these include: 

• Attention --our ability to process information in the environment while tuning out irrelevant details
• Choice-based behavior --actions driven by a choice among other possibilities
• Decision-making
• Information processing
• Language acquisition --how we learn to read, write, and express ourselves
• Problem-solving
• Speech perception -how we process what others are saying
• Visual perception --how we see the physical world around us

History of Cognitive Psychology

Although it is a relatively young branch of psychology , it has quickly grown to become one of the most popular subfields. Cognitive psychology grew into prominence between the 1950s and 1970s.

Prior to this time, behaviorism was the dominant perspective in psychology. This theory holds that we learn all our behaviors from interacting with our environment. It focuses strictly on observable behavior, not thought and emotion. Then, researchers became more interested in the internal processes that affect behavior instead of just the behavior itself. 

This shift is often referred to as the cognitive revolution in psychology. During this time, a great deal of research on topics including memory, attention, and language acquisition began to emerge. 

In 1967, the psychologist Ulric Neisser introduced the term cognitive psychology, which he defined as the study of the processes behind the perception, transformation, storage, and recovery of information.

Cognitive psychology became more prominent after the 1950s as a result of the cognitive revolution.

Current Research in Cognitive Psychology

The field of cognitive psychology is both broad and diverse. It touches on many aspects of daily life. There are numerous practical applications for this research, such as providing help coping with memory disorders, making better decisions , recovering from brain injury, treating learning disorders, and structuring educational curricula to enhance learning.

Current research on cognitive psychology helps play a role in how professionals approach the treatment of mental illness, traumatic brain injury, and degenerative brain diseases.

Thanks to the work of cognitive psychologists, we can better pinpoint ways to measure human intellectual abilities, develop new strategies to combat memory problems, and decode the workings of the human brain—all of which ultimately have a powerful impact on how we treat cognitive disorders.

The field of cognitive psychology is a rapidly growing area that continues to add to our understanding of the many influences that mental processes have on our health and daily lives.

From understanding how cognitive processes change as a child develops to looking at how the brain transforms sensory inputs into perceptions, cognitive psychology has helped us gain a deeper and richer understanding of the many mental events that contribute to our daily existence and overall well-being.

The Cognitive Approach in Practice

In addition to adding to our understanding of how the human mind works, the field of cognitive psychology has also had an impact on approaches to mental health. Before the 1970s, many mental health treatments were focused more on psychoanalytic , behavioral , and humanistic approaches.

The so-called "cognitive revolution" put a greater emphasis on understanding the way people process information and how thinking patterns might contribute to psychological distress. Thanks to research in this area, new approaches to treatment were developed to help treat depression, anxiety, phobias, and other psychological disorders .

Cognitive behavioral therapy and rational emotive behavior therapy are two methods in which clients and therapists focus on the underlying cognitions, or thoughts, that contribute to psychological distress.

What Is Cognitive Behavioral Therapy?

Cognitive behavioral therapy (CBT) is an approach that helps clients identify irrational beliefs and other cognitive distortions that are in conflict with reality and then aid them in replacing such thoughts with more realistic, healthy beliefs.

If you are experiencing symptoms of a psychological disorder that would benefit from the use of cognitive approaches, you might see a psychologist who has specific training in these cognitive treatment methods.

These professionals frequently go by titles other than cognitive psychologists, such as psychiatrists, clinical psychologists , or counseling psychologists , but many of the strategies they use are rooted in the cognitive tradition.

Many cognitive psychologists specialize in research with universities or government agencies. Others take a clinical focus and work directly with people who are experiencing challenges related to mental processes. They work in hospitals, mental health clinics, and private practices.

Research psychologists in this area often concentrate on a particular topic, such as memory. Others work directly on health concerns related to cognition, such as degenerative brain disorders and brain injuries.

Treatments rooted in cognitive research focus on helping people replace negative thought patterns with more positive, realistic ones. With the help of cognitive psychologists, people are often able to find ways to cope and even overcome such difficulties.

Reasons to Consult a Cognitive Psychologist

• Alzheimer's disease, dementia, or memory loss
• Brain trauma treatment
• Cognitive therapy for a mental health condition
• Interventions for learning disabilities
• Perceptual or sensory issues
• Therapy for a speech or language disorder

Whereas behavioral and some other realms of psychology focus on actions--which are external and observable--cognitive psychology is instead concerned with the thought processes behind the behavior. Cognitive psychologists see the mind as if it were a computer, taking in and processing information, and seek to understand the various factors involved.

A Word From Verywell

Cognitive psychology plays an important role in understanding the processes of memory, attention, and learning. It can also provide insights into cognitive conditions that may affect how people function.

Being diagnosed with a brain or cognitive health problem can be daunting, but it is important to remember that you are not alone. Together with a healthcare provider, you can come up with an effective treatment plan to help address brain health and cognitive problems.

Your treatment may involve consulting with a cognitive psychologist who has a background in the specific area of concern that you are facing, or you may be referred to another mental health professional that has training and experience with your particular condition.

Ulric Neisser is considered the founder of cognitive psychology. He was the first to introduce the term and to define the field of cognitive psychology. His primary interests were in the areas of perception and memory, but he suggested that all aspects of human thought and behavior were relevant to the study of cognition.

A cognitive map refers to a mental representation of an environment. Such maps can be formed through observation as well as through trial and error. These cognitive maps allow people to orient themselves in their environment.

While they share some similarities, there are some important differences between cognitive neuroscience and cognitive psychology. While cognitive psychology focuses on thinking processes, cognitive neuroscience is focused on finding connections between thinking and specific brain activity. Cognitive neuroscience also looks at the underlying biology that influences how information is processed.

Cognitive psychology is a form of experimental psychology. Cognitive psychologists use experimental methods to study the internal mental processes that play a role in behavior.

Sternberg RJ, Sternberg K. Cognitive Psychology . Wadsworth/Cengage Learning. 

Krapfl JE. Behaviorism and society . Behav Anal. 2016;39(1):123-9. doi:10.1007/s40614-016-0063-8

Cutting JE. Ulric Neisser (1928-2012) . Am Psychol . 2012;67(6):492. doi:10.1037/a0029351

Ruggiero GM, Spada MM, Caselli G, Sassaroli S. A historical and theoretical review of cognitive behavioral therapies: from structural self-knowledge to functional processes .  J Ration Emot Cogn Behav Ther . 2018;36(4):378-403. doi:10.1007/s10942-018-0292-8

Parvin P. Ulric Neisser, cognitive psychology pioneer, dies . Emory News Center.

APA Dictionary of Psychology. Cognitive map . American Psychological Association.

Forstmann BU, Wagenmakers EJ, Eichele T, Brown S, Serences JT. Reciprocal relations between cognitive neuroscience and formal cognitive models: opposites attract? . Trends Cogn Sci . 2011;15(6):272-279. doi:10.1016/j.tics.2011.04.002

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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9 Cognitive Psychology

Mary whiton calkins (1863–1930).

Mary W. Calkins was a prominent psychologist in America during the late 19th and early 20th centuries, who contributed extensively to experimental research and psychological literature.

Furumoto (1980) describes Calkins growing up in a large, warm family, which arranged that she has a good education. Calkin completed her undergraduate degree in classics and philosophy at Smith College in 1885. In 1887, she began teaching in the Greek Department at Wellesley College, an undergraduate women’s college. In 1890, the college introduced a psychology curriculum within the Philosophy Department, and the administration offered Calkins a teaching position due to her interest in philosophy and skill as a teacher. Since Calkins had had no formal education in psychology, she left to study psychology for one year before taking the position. Calkins was adamant about studying at a school with a psychological laboratory and decided to pursue study at Harvard University with psychologist William James and philosopher Josiah Royce. James and Royce were supportive of Calkins’ plan to study under their direction. Since Harvard did not allow women to enroll as students, Calkins was permitted to attend James’ and Royce’s seminars as a guest. During that same academic year, she also undertook experimental training with Edmund Sanford in the psychological laboratory at Clark University. In 1891, she returned to Wellesley as Instructor of Psychology, created an experimental psychology course, and helped to establish one of the first psychological laboratories in the United States at the college. The following year, Calkins returned to Harvard to further her education in psychology under the direction of Hugo Münsterberg. Once again, she was permitted to study as a guest but not as a student of the university. When Calkins completed the requirements of a doctoral degree in 1895, Münsterberg advocated on behalf of her Ph.D. candidacy, stating that she was the strongest student in the laboratory. Harvard refused to award her the degree, and in 1902, Calkins and three other women were offered the Radcliffe doctorate, which was created for women who completed the requirements of a Ph.D. at Harvard. Calkins turned down the Radcliffe degree based on the conviction that women should receive the same designation as their male counterparts. In 1895, Calkins returned to Wellesley again, this time as an Associate Professor of Psychology and Philosophy, and was appointed as a full professor three years later (Furumoto , 1980).

Further, Furumoto (1980) states how between 1892 and 1894, Calkins published a series of papers on association and memory from Münsterberg’s laboratory. She also published her research on dreams from her time with Edmund Sanford, and her work at the Wellesley laboratory. Following her completion of graduate studies, she published several more papers from her time in Münsterberg ’s laboratory and on studies coming out of Wellesley. In 1901, Calkins published her first textbook, An Introduction to Psychology , which became widely used for undergraduate courses in psychology. She also wrote A First Book in Psychology , first published in 1910, in addition to a number of philosophical works. In 1903, Calkins’ distinction in the field of psychology was first formally recognized when she was ranked 12th on a list of the 50 most influential American psychologists. In 1905, she was again recognized when she became the first woman to be elected president of the American Psychological Association. She went on to serve as the president of the American Philosophical Association and was also granted honorary membership in the British Psychological Association after presenting at an annual meeting in 1927. Calkins also received honorary degrees from both Columbia University and Smith College, who both offered her a position on their faculties, however, she did not assume either position in order to stay close to home and care for her parents.

One of Calkins’ most influential contributions to psychology was the invention of the paired-associate method. Although Calkins did not use the term “paired-associate”, she is considered the first person to use the method in her experimental studies on association, which were published in 1894 and 1896 (Madigan & O’Hara, 1992). In these studies, participants were presented with lists of paired items containing a “cue item,” which was either the name of a colour or a random combination of 3 letters, and a “response item,” which was a 2 or 3-digit number (e.g., blue-245). Calkins tested the participants’ memory of response items when presented with the cue items, and investigated various factors that might influence their recall, including primacy, recency, and fluency effects. Additionally, she conducted studies using both visual and auditory presentation of items. Her primary findings were that frequency was the most prominent factor influencing recall, and that recency effects were stronger for auditory presentation and for immediate (rather than delayed) recall. This demonstrates Calkins’ superior skills as a researcher and her significant influence in the area of memory and learning.

Another major contribution of Calkins’ was her theory of self-psychology, which first appeared in the literature in 1900 and was the topic of her APA presidential address in 1906 (Strunk, 1972). The goal of this theory was to create a unified theoretical framework for psychology that satisfied both structuralist and functionalist ideologies while placing the conscious self as the primary concern of the discipline. Calkins believed that the elements of consciousness, as well as the relationship between the self, its environment, and the adaptiveness of that relationship, should be included, however, psychology should ultimately be a study of the self, consciousness, and internal processes (e.g., memory, perception, emotions, etc.). Although self-psychology did not become one of the leading schools of thought, it provides another example of Calkins’ excellence as a leading figure in American psychology.

Furumoto, L. (1980). Mary Whiton Calkins (1863-1930). Psychology of Women Quarterly, 5 , 55–68. https://doi.org/10.1111/j.1471-6402.1980.tb01033.x

Madigan, S., & O’Hara, R. (1992). Short-term memory at the turn of the century: Mary Whiton Calkins’s memory research. American Psychologist, 47 , 170–174. https://doi.org/10.1037/0003-066x.47.2.170

Strunk, O. (1972). The self-psychology of Mary Whiton Calkins. Journal of the History of the Behavioral Sciences, 8 , 196–203. doi:10.1002/1520-6696(197204)8:2<196::aid-jhbs2300080205>3.0.co;2-l

Contributors

• Nicole Smith
• Kundan Ahluwalia

Thomas Verner Moore (1877–1969)

Dom Thomas Verner Moore was an American priest, psychiatrist, experimental psychologist, and, in his later years, a Carthusian monk.

Moore received his Ph.D. in psychology from Catholic University in 1903 and subsequently travelled to Leipzig to study under Wilhelm Wundt in 1904 (Noll et al., 2017). During this time, Moore also met and worked with psychologist and statistician Charles Spearman, which contributed to Moore’s interest and prominence in the application of statistical methods, namely factor analysis (Noll et al., 2017). Moore returned to the United States at the University of California, where he completed the research that he had started while at Leipzig, and published this work in the paper, “The Process of Abstraction” in 1910 (Stafford, 1970). That same year, Moore returned to Catholic University as an instructor until 1913, when he travelled to Munich to study medicine. Due to the start of WWI, however, Moore came back to the United States and completed his medical degree at John Hopkins University in 1915.

Stafford (1970) states that after returning to Catholic University, Moore implemented the university’s first course on clinical psychology and established a clinic for treating children with nervous and mental diseases, which he ran from 1916 to 1918. In 1918, he went to Europe with the American Expeditionary Forces to serve as a captain in the neuropsychiatric division of the medical corps. After the war ended, Moore took over as the head of the psychology department at Catholic University, a position which he held for the remainder of his academic career. During his career, he established a school of arts and crafts for children with mental deficiencies and transferred his clinic to the campus of Catholic University, where it became a charter member of the American Association of Psychiatric Clinics for Children. Moreover, he served on a committee that investigated the potential uses of factor analysis in personality psychology, whose work yielded the development of the “principal components” analysis method (Holzinger, 1936). Moore’s most renowned works are Dynamic Psychology , published in 1924, and The Nature and Treatment of Mental Disorders , published in 1943. Further, Moore’s work focused on imagery and memory. In some of his more famous experiments, Moore found that response time was faster for language tasks than imagery tasks, and that recollection of objects was better than the recollection of words, with these findings being supported by recent work in cognitive psychology (Surprenant & Neath, 1997).

While Moore’s prominence in psychology did not go unnoticed, Surprenant & Neath (1997) bring attention to  one significant work of his which gained relatively little attention and failed to achieve recognition as an influential text in the history of psychology. This work was Moore’s Cognitive Psychology , published in 1939, which was the first use of the term “cognitive psychology”. There are a couple of reasons why Moore’s text was unsuccessful in obtaining this recognition. Firstly, two highly influential texts were published around the same time, which overshadowed Moore’s publication. Also, Moore’s emphasis on consciousness, as well as his overall contention that the experimental subject plays an active, rather than a passive role in interpreting stimuli was not consistent with the trends in psychology at the time. However, this work went largely unnoticed, and these ideas only became popularized when Ulrich Neisser published Cognitive Pyschology in 1967. However, Suprenant and Neath argue that although Neisser’s text had a progressive tone, Moore’s text better reflected modern trends in cognitive psychology, as he included sections on the biological bases of perception and case studies of neurological impairment to infer the functioning of non-impaired cognitive processes. Furthermore, Moore’s Cognitive Psychology included emphases on consciousness, faculty psychology, and philosophy, and anticipated the renewed interest in these topics seen toward the end of the 20th century. Despite the components of Moore’s text which prevented its success, there were elements which expressed the trends of 1930s experimental psychology, including an emphasis on statistical methods, and a comprehensive discussion of relevant subject matter. Recent reviews of Moore’s Cognitive Psychology suggest that there are sections worth reading for various purposes (e.g., historical purposes, philosophical considerations). However, given the magnitude of incorrect information, it should not be taken as a foundation for the study of cognitive psychology. Nevertheless, it still reflects remarkable proficiency in scientific analysis and theorizing, and had it been produced 20 years later, may have been met with a different reception from the psychological community.

Overall, Moore was a highly skilled experimental psychologist and psychiatrist who impacted the field of psychology in many important ways.

Holzinger, A. J. (1936). Recent research on unitary mental traits.  Character & Personality; A Quarterly for Psychodiagnostic & Allied Studies .

Noll, R., DeYoung, C. G., & Kendler, K. S. (2017). Thomas Verner Moore. American Journal of Psychiatry, 174 , 729–730.

Surprenant, A. M., & Neath, I. (1997). T. V. Moore’s (1939) Cognitive Psychology. Psychonomic Bulletin & Review, 4 , 342-349.

Stafford, J. W. (1970). Thomas Verner Moore: 1877-1969. The American Journal of Psychology, 83 , 286–288.

• M. Grant Leger

Revisiting the History of Psychology Copyright © by Ali Hashemi and Amber Morrison. All Rights Reserved.

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CONCEPTUAL ANALYSIS article

The place of development in the history of psychology and cognitive science.

• Department of Psychology, Center for Logic, Language, and Cognition, University of Torino, Turin, Italy

In this article, I analyze how the relationship of developmental psychology with general psychology and cognitive science has unfolded. This historical analysis will provide a background for a critical examination of the present state of the art. I shall argue that the study of human mind is inherently connected with the study of its development. From the beginning of psychology as a discipline, general psychology and developmental psychology have followed parallel and relatively separated paths. This separation between adult and child studies has also persisted with the emergence of cognitive science. The reason is due essentially to methodological problems that have involved not only research methods but also the very object of inquiry. At present, things have evolved in many ways. Psychology and cognitive science have enlarged their scope to include change process and the interaction between mind and environment. On the other hand, the possibility of using experimental methods to study infancy has allowed us to realize the complexity of young humans. These facts have paved the way for new possibilities of convergence, which are eliciting interesting results, despite a number of ongoing problems related to methods.

Introduction

In this paper, I intend to analyze how the relationship of developmental psychology to general psychology and cognitive science has unfolded. This historical analysis will provide a background for a critical examination of the present state of the art.

Psychology emerged as a scientific discipline with the founding of Wundt’s Laboratory in Leipzig at the end of the nineteenth century (1879) 1 . Wundt’s method, both experimental and introspective, was directed to the study of an adult’s mind and behavior. It is less well-known that only 10 years later, James Baldwin, who had attended Wundt’s seminars in Germany, founded a laboratory of experimental psychology in Toronto in which experiments devoted to the study of mental development were performed. If the occasion that aroused Baldwin’s interest was the birth of his first daughter, actually, “that interest in the problems of genesis–origin, development, evolution–became prominent; the interest which was to show itself in all the subsequent years” ( Baldwin, 1930 ). Baldwin’s work was a source of inspiration for Piaget, certainly one of the most prominent figures in developmental psychology ( Morgan and Harris, 2015 ).

From the origins of psychology as a discipline, general psychology and developmental psychology have followed parallel and relatively separate paths. Two questions are particularly relevant to explain this fact.

From a theoretical point of view, developmental psychology has all along been greatly influenced by biology and evolutionary theory. The founders of developmental psychology have widely analyzed the relation between ontogenesis and phylogenesis ( Baldwin, 1895 ; Piaget, 1928 ). This analysis resulted in accepting the challenge of explaining development in a broad sense. In his autobiography, Baldwin affirms that already in the 10 years that he spent in Princeton between 1893 and 1903, where he founded another laboratory of experimental psychology, “the new interest in genetic psychology and general biology had become absorbing, and the meagerness of the results of the psychological laboratories (apart from direct work on sensation and movement) was becoming evident everywhere.” Thus, developmental psychology has followed an approach that in general psychology appeared much later 2 .

A second question regards method. Developmental researchers, while manifesting their attachment to experimental procedures, have been confronted with their insufficiency in the study of development. Both for deontological and practical reasons, many aspects of development, in particular in infants and young children, can hardly be investigated experimentally. Thus, a great number of studies in developmental psychology make use of observational methods based on different techniques such as ethnographic methods or parent reports, and the reliability of these methods has been questioned.

This relative separation between studies of adults and children has also persisted with the emergence of cognitive science. Actually, the primary aim of cognitive science, at least at the outset, was to model what we could call an adult static mind. Given a certain output, for instance an action, the task of the psychologist was to reconstruct the inference processes that were at the origin of this same action.

At the beginning of the twenty-first century, psychology and cognitive science have enlarged their scope to include change processes and the interaction between mind and environment, including other minds. Developmental psychology, for its part, has developed nonverbal methods such as looking measures and choice measures that also make it possible to carry out experiments with infants. These facts have paved the way for new possibilities of convergence, which are eliciting interesting results, despite a number of ongoing problems related to methods.

Psychology, Cognitive Science and Artificial Intelligence

The beginning of cognitive science.

According to the American psychologist George Miller, cognitive science was born on September 11, 1956, the second day of the Second Symposium on Information Theory held at MIT. That day began with a paper read by Allen Newell and Herbert Simon on the state of art of the Logic Theory Machine: a proof on computer of theorem 2.01 of Whitehead and Russell’s Principia Mathematica . That very same day ended with the first version of Chomsky’s The Structures of Syntax . Miller left the symposium convinced that experimental psychology, theoretical linguistics, and computer simulation of cognitive processes could become parts of a wider whole and that the future of research would be found in the elaboration of this composite whole (reported in Bruner, 1983a ). It is Miller who in 1960, together with Eugene Galanter and Karl Pribram, authored a text that may be considered the manifesto of cognitive science and that proclaimed the encompassing of cognitive psychology within the more general framework of information processing ( Miller et al., 1960 ). The assumption was that newly born information science could provide a unifying framework for the study of cognitive systems ( Schank and Abelson, 1977 ).

From a theoretical point of view, the core of this project is the concept of representation. Intentional mental states, such as beliefs and perceptions, are defined as relations to mental representations. The semantic properties of mental representations explain intentionality ( Pitt, 2017 ). Representations can be computed and thus constitute the basis for some forms of logic systems. According to the Cognitive Science Committee (1978) , which drew up a research project for the Sloan Foundation, all those disciplines, which belong to cognitive science, share the common goal of investigating the representational and computational capacities of the mind and the structural and functional realization of these capacities in the brain.

This point of view constitutes the foundation for what has been called functionalism in the philosophy of mind, i.e., the hypothesis that what defines the mind are those features that are independent of its natural realization. The classic functionalist stance is expressed by Pylyshyn in his book on computation and cognition ( Pylyshyn, 1984 ). He maintains that a clear distinction must be made between the functional architecture of the cognitive system and the rules and representations that the system employs.

Functionalism has been greatly discussed and criticized from the beginning ( Block, 1978 ; Dreyfus, 1979 ). Harnad (1990) identified what has been defined as the symbol grounding problem : “How can the semantic interpretation of a formal symbol system be made intrinsic to the system?”

The most exhaustive and most deeply argued critique of functionalism was advanced by Searle, who developed his arguments over time, publishing a number of essays which have given rise to heated debate ( Searle, 1980 , 1990 , 1992 ). The position taken up by functionalism is that the relationship between the brain and its products, that is to say conscious processes, is mediated by an intermediate level of unconscious rules. This intermediate level is, for functionalists, the level of the program. It is postulated that the rules are computational and that, consequently, the aim of research in cognitive science is to reconstruct these rules. Searle’s objection is that there are only two types of natural phenomena, the brain and the mental states that the brain brings into being and that humans experience. The brain produces mental states due to its specific biological characteristics. When we postulate the existence of unconscious rules, according to Searle, we invent a construct whose aim is to highlight a function, which we believe is especially significant. Such a function is not intrinsic and has no causal power. This argument is particularly interesting because it is founded on the impassable biological nature of the mind. Neither logic nor mathematical or statistical procedures may replace brain as a biological organ.

From another perspective, some scholars have emphasized that functionalism leads to a new form of behaviorism. Putnam (1988) claimed that reducing mental processes exclusively to their functional descriptions is tantamount to describe such processes in behavioristic terms 3 . In psychology, one of the most polemical critics of functionalism as a dangerous vehicle toward a new form of anti-mentalism, which would render vain all the battles waged by cognitivists against classic behaviorism, was a developmental psychologist, Bruner (1990) . The centrality of computability as the criterion for the construction of models in cognitive science leads naturally, in Bruner’s opinion, to abandoning “meaning making,” which was the central concern of the “Cognitive Revolution.”

Thus, at least at the outset, cognitive science was devoted to constructing computational models of human inference processes and of the knowledge that is used in performing these inferences. This definition of the object of cognitive science has led at first to designing and implementing problem-solving systems, where the complexity was located in the inference mechanisms, supposed to be the same for all problems ( Newell and Simon, 1972 ). Later, systems were implemented where reasoning was associated with specific and articulated knowledge representation ( Levesque and Brachman, 1985 ).

Notably, the aspect that was absent from this view of cognitive science was learning. This lack, according to Gentner (2010) , could be partly explained as a reaction to behaviorism, which was completely centered on learning. In fact, there were also philosophical reasons. Chomsky and Fodor, who were among the most influential members of the cognitive science community, were highly critical of the concept of learning. In their view, learning as a general mechanism does not exist, and Fodor even went so far as to state explicitly that no theory of development exists either ( Fodor, 1985 ).

Thus, cognitive science was born essentially as a reaction to behaviorism and took its legitimacy from the use of methodologies developed within artificial intelligence. These methodologies were supposed to make explicit how mental representations produced human activity in specific domains. However, this approach had a price: it separated the mind from its biological basis and from the context in which human activity takes place. There was no place for development, interaction, and variation due to biological or social causes 4 . This theoretical choice explains Bruner’s disillusion. For Bruner, cognitive science had fallen back into the behaviorism against which it originated, and no interesting relation could be established with developmental psychology. Developmental psychology is founded on the premise that a human being develops in interaction with the physical world and the society of other humans.

Cognitive Science in the Twenty-First Century

Cognitive science has changed considerably from its beginning. An obvious novelty concerns the increased importance assumed by learning with the emergence of connectionism ( Hinton, 1989 ).

When connectionist models were introduced, there was much debate regarding the relation of neural networks with the functioning of the human brain and their ability to address higher forms of thought ( Fodor and Pylyshyn, 1988 ; Quinlan, 1991 ; Chalmers, 1993 ). Later, philosophical discussion was replaced by empirical considerations. Networks are an efficient computational tool in some domains and are often used jointly with symbolic computations ( Wermter and Sun, 2000 ). Moreover, in recent advancements of artificial Intelligence, neural networks have been largely replaced by a variety of techniques of statistical learning ( Forbus, 2010 ).

More interesting for my purpose is the changes that the general philosophy of cognitive science has undergone due to the problems that have emerged with classic symbolic models. At its origin, the core of cognitive science was the relation between psychology and artificial intelligence. In the original project, this marriage was to be fruitful for both disciplines. Artificial intelligence expected from psychology the analysis of high-level mental mechanisms that, once simulated on a computer, could improve the efficiency of artificial systems. With computer simulation, psychology was to acquire a method to validate its models. However, this marriage, which for a while has been very productive and has generated many interesting ideas, ultimately failed. Artificial intelligence has evolved computing techniques that produce efficient systems without asking anymore if these techniques replicate human mental processes more or less faithfully. In psychology, the constraint to produce computational models has again restricted its scope ( Airenti and Colombetti, 1991 ).

Thus, the results of cognitive science of the twentieth century have led to a shift in cognitive science that has emerged with this century. Some researchers have proclaimed that the theoretical hypothesis that minds functionalities can be modeled disregarding the fact that they operate on the external world through the body could no longer be accepted. This new approach implies accounting for the biology of the mind/body unity and the interaction with the external world, both physical and social. One source of inspiration for this new turn came from Varela et al. (1991) , who proposed the concept of the embodied mind . Actually, the concept of embodiment includes many rather disparate inspirations, from Merleau-Ponty and phenomenology to Buddhism. I do not analyze these questions here. What interests me is the mere assumption that cognition is grounded in the world.

This new turn corresponds to the major importance assumed by robotics. It might be exaggerated to say that the role played by artificial intelligence in the past is now assumed by robotics. However, it is clear that the aim of constructing artificial actors that interact with the world and/or with humans has again established a link between the study of humans and the production of artificial systems. With respect to the past, the focus is no longer on the symbolic function of the mind, but on the mind embedded into a physical device that interacts with the external world. This evolution is linked to the enlarged scope of present robotics that goes well beyond traditional tasks such as farm automation. The ambition is to construct robots that may cooperate with humans in a multiplicity of tasks, including, for instance, assisting aged or disabled people or interacting with autistic children. Social robotics has then evolved toward biologically inspired systems, based on the notions of self-organization and embodiment ( Pfeifer et al., 2007 ). This new development has led to question once again psychologists about those characteristics that make humans what they are. If robots must be able to interact with humans, they should show those same characteristics ( Kahn et al., 2007 ). Can robots be endowed with intentionality, emotions, and possibly empathy?

Here, again a functionalist position appears. For some authors, the fact that the robot’s internal mechanisms are grounded in physical interactions with the external environment means that they truly have the potentiality of intrinsic intentionality ( Zlatev, 2001 ). This means, for them, that a mind is embodied in a robot. To the question of whether robots can have emotions, Arbib and Fellous (2004) answer that a better knowledge of biological systems will allow us in the future to single out “brain operating principles” independent of the physical medium in which they are implemented. This new form of functionalism is currently contrasted with an approach that considers that mental states and emotions are not intrinsic but can only be attributed to robots by humans ( Ziemke et al., 2015 ). Robots’ embodiment does not overcome the objection that was addressed to traditional artificial intelligence, namely that mental states and emotions can only be produced by a biological brain ( Ziemke, 2008 ). This latter position maintains that the relevant question for human-robot interaction is not that robots must be intentional beings, but that they must be perceived as such by humans ( Airenti, 2015 ; Wiese et al., 2017 ).

In conclusion, we can say that cognitive science was born as a way to renew psychology through a privileged connection with artificial intelligence. In the present state of research, it is social robotics that is attempting to establish a connection with biological sciences, psychology, and neuroscience, in order to build into robots those functionalities that should allow them to successfully interact with the external physical and social world. However, the main fundamental philosophical problems remain unchanged. One could still argue, as Searle did, that human mentality is an emergent feature of biological brains and no logical, mathematical or statistical procedure can produce it.

Present Questions for Cognitive Science

The question that we may raise today is this: what is cognitive science for? The relation that psychology has established with the sciences of the artificial has hidden the fact that a number of phenomena, which are essential for explaining the functioning of the human mind, have been largely ignored. This failure in explanation, which has concerned, for instance, the managing of mental states and emotions, and many complex communicative phenomena, is fundamentally linked to the fact that the mind is constantly in interaction with the physical and social world in a process of development. The primitive idea of cognitive science was to go beyond traditional psychology to enrich the study of mind with the contributions of other disciplines that also investigated human mind, such as linguistics, philosophy, and anthropology. This approach, which concerns the definition of the field of cognitive science, has been quite early reinterpreted as a problem of formalism. The question posed has been: how could psychology produce scientific models of human thought? Hence, the importance assumed by computer modeling as a means of replacing more traditional logical, mathematical, and statistical models. However, this theoretical choice has generated a major ambiguity, because computer models that are founded on logical, mathematical, or statistical formalisms have been seen as possibly equivalent to the mind. Once the fallacy of this equivalence appears—because no artificial model may replace the causal power of the human brain—we are left with some formal models with very limited psychological significance. What has been lost is the richness that cognitive science was supposed to acquire by connecting different disciplines. In particular, for many years, this approach has prevented general psychology from connecting with developmental psychology, a field of studies that, since Baldwin, had already posed the problem of the construction of the human mind as the result of biological development and social interaction.

The Study of Development

Biology and development in the debate between piaget and chomsky.

Studying development necessarily implies considering the fact that humans are biological systems that are certainly particularly complex but also share many characteristics with other living beings. Thus, in the field of developmental psychology, many questions have emerged concerning the link between development and evolution, the relation between genetic endowment and the influence on acquisition of environment (a concept that includes physical environment, parenting, social rules, etc.), and the nature of learning.

For Piaget, who came to developmental psychology from natural sciences, development had to be seen in the light of the theories of evolution. Intelligence, for him, is a particular case of biological adaptation, and knowledge is not a state but a process. Through action, children explore space and objects in the external world, and in this way, for instance, they learn the properties of the objects and their relations. These ideas, which sound rather contemporary to us, were considered as problematic in the past and prevented the establishment of a relationship between the study of development and the study of cognition in general. It is only in this century that development has been integrated into evolution studies via the so-called evo-devo approach and that these ideas have given rise to an interest in psychology ( Burman, 2013 ).

Actually, some aspects of Piaget’s perspective were problematic. Piaget supported his theory using what was considered a Lamarckian vision of evolution that assumed the inheritance of acquired characteristics. He had a well-known debate at the end of his life (1975) with Noam Chomsky on language acquisition, and outstanding biologists who also participated to the debate contested the validity of his use of the concept of phenocopy ( Piattelli-Palmarini, 1979/1980 ). In fact, on this point, Piaget had been influenced by Baldwin, who proposed what is known as Baldwin’s effect ( Simpson, 1953 ). This effect manifests in three stages: (1) Individual organisms interact with the environment in such a way as to produce nonhereditary adaptations; (2) genetic factors producing similar traits occur in the population; and (3) these factors increase in frequency under natural selection (taken from Waddington, 1953 ). Later, Piaget revised his own theory and updated Baldwin’s effect under the influence of Waddington ( Burman, 2013 ). Recently, epigenetic theories have emerged in biology, and the importance of development is generally accepted. On the developmental side, it has been proposed that Piaget’s theory might be replaced as a metatheory for cognitive development by evolutionary psychology ( Bjorklund, 2018 ).

The debate between Chomsky and Piaget is interesting because it is a clear example of the impossibility of dialogue between one of the fathers of cognitive science and the scholar who, at that moment, personified developmental psychology. Piaget was unable to justify his position that grammar rules could also be accounted for by sensorimotor schemata, and Chomsky appeared to have won the debate. At the same time, Chomsky presented the emergence of syntactic rules in the child’s mind, excluding in principle any possible form of learning. However, in hindsight, we know how the task of establishing abstract principles of universal grammar proved to be arduous, underwent many substantial changes and is not yet realized.

Another controversial aspect of Piaget’s position was his adherence to the recapitulation theory, i.e., the idea originally proposed by Haeckel, that ontogeny recapitulates phylogeny. It is this principle that motivated Piaget’s study of development as a way of contributing to the study of the evolution of human thought ( Koops, 2015 ). However, this position has as its consequence the idea that primitive populations would exist wherein we might find adult thought processes that in modern civilizations are typical of young children.

What is striking in this debate is that the specific biological model that Piaget adopted was not the only point of disagreement. What was questioned was in general the relevance of development for the study of a basic human ability such as language. Certainly, in the work of the first figures of developmental psychology, we find a baffling mix of very interesting ideas regarding the place of humans as biological entities in evolution and a difficulty in taking into account the complexities of actual biological theories and of social aspects such as cultural variation. At the same time, these scholars were confronted with objections from cognitive scientists who did not admit the relevance of investigating development for the study of the human mind.

The Interactionist Perspective

Piaget’s perspective was, in a sense, paradoxical. This perspective considered children’s development as the product of their action on the environment, but at the same time postulated a rather rigid succession of stages that led to adult thought and excluded the importance of the social aspects of this environment in the first years. In fact, infants and young children were considered closed in their egocentrism and unable to take advantage of their interactions with adults and peers.

These aspects have been criticized within developmental psychology, where a cultural turn, fathered by Vygotsky (1962/1986) and mainly interpreted in the United States by Bruner (1990) , has arisen. For both these authors, biological factors are considered an endowment of potentialities that develop in a society of co-specifics and are submitted to variability and to cultural variation.

Bruner was, at the outset, an enthusiastic supporter of cognitive science and in particular of the mentalist theory of language proposed by Chomsky ( Bruner, 1983b ). Later, however, the primacy that Chomsky assigns to syntax turned out to be unsatisfactory to Bruner, according to whom language is fundamentally a communicative device. The problem of language acquisition is thus redefined as the development of a communicative capacity that appears in the prelinguistic stage. This position was the result of Bruner’s work on preverbal communication carried out at the Center for Cognitive Studies at Harvard University starting in 1966.

For Bruner, language requires the maturation of cognitive structures, which underlie intentional action in general. His debt to Piaget with regard to the importance of action is evident. Language is “a specialized and conventionalized extension of cooperative action” ( Bruner, 1975 ). In this, he rejoins the communication theories proposed within the philosophy of language by Austin (1962) and Grice (1989) .

Bruner’s studies are part of a revolution in developmental studies in which more careful scrutiny and more sophisticated experimentation led to the discovery that children begin to engage in rather complex cognitive activity very early on. Prior to these studies, many of the aspects relating to infant cognition were not taken into consideration. The prejudice that saw human development as the slow acquisition of rationality prevented researchers from seeking elements of complexity in the cognition of a new-born.

In brief, since its origin, developmental psychology has undergone an important change. At the outset, the idea was that what characterized human cognition was adult rational thought, and studying development meant understanding the stages that led to this achievement. Later, the goal became understanding the development of the different faculties that characterize cognition starting from birth. This goal has also opened the door to comparative studies.

The Problems of Method

Developmental psychologists have always struggled with problems of method.

Piaget frequently discussed his observations of his three children. Studies on language acquisition have often benefited from researchers’ observations of their own children (see, for instance, Stern and Stern, 1928 ). These procedures, which have been considered as barely scientific by other psychologists, have provided useful inspiration for further research. Note that Darwin’s observations of his children were a fundamental source for his work on emotions ( Darwin, 1872/1965 ).

Ethical reasons forbid experiments, which may perturb children. Moreover, conceiving experiments that have ecological validity is even more difficult to do with young children than with adults. Hence, the necessity of using different methods in order to produce data that cannot be collected using classic experimental procedures. Without using observational methods, for instance, it is not possible to assess the spontaneous appearance of a given phenomenon ( Airenti, 2016 ). Furthermore, some behaviors may appear only in specific situations and would go unnoticed if they were not observed by caregivers who may see children at different moments of the day and in different situations. Thus, developmental psychologists have used different methodologies, classic experiments but also fieldwork, ethological observation, and parent reports.

A fundamental advancement was the development of techniques permitting to assess infants’ and young children’s abilities in experiments. A key element was the elaboration of the habituation paradigm ( Fantz, 1964 ; Bornstein, 1985 ). After repeated exposure to a stimulus, infants’ looking time decreases due to habituation and increases when a novel stimulus is presented. Habituation allows us to understand if infants discriminate among different stimuli.

In particular for language studies, nonnutritive sucking ( Siqueland and De Lucia, 1969 ) has been used. This is an experimental method based on operant conditioning allowing one to test infants’ discrimination of and preference for different stimuli. This technique has been used to show, for instance, that infants already acquire in the mother’s womb the ability to recognize and prefer the prosody of a language and of familiar voices ( DeCasper and Fifer, 1980 ).

Currently, the most utilized technique with infants is preferential looking or reaching. In this technique, two stimuli are presented together and what is measured is the infant’s preference. Specific types of this technique are used to claim surprise, anticipation, and preferences for novel or familiar stimuli and to evaluate preference over and above novelty or familiarity ( Hamlin, 2014 ) 5 .

Another technique presently used to investigate infant cognitive development is EEG recordings, even if creating infant-friendly laboratory environments, age-appropriate stimuli, and infant- friendly paradigms requires special care ( Hoehl and Wahl, 2012 ).

The development of these experimental techniques has vastly enlarged the scope of infant studies. In particular, a new research trend has emerged aimed at discovering what has been called the core knowledge ( Spelke, 2000 ; Spelke and Kinzler, 2007 ). The idea is that at the basis of human cognition, there is a set of competencies, such as representing objects, action, number and space, which are already present in infants and which underlie and constrain later acquisitions. Researchers have also been working on other possible basic competencies such as social cognition ( Baillargeon et al., 2016 ) and morality ( Wynn and Bloom, 2014 ).

In the literature, debate continues surrounding the replicability and robustness of findings obtained within these experimental paradigms, in particular with respect to infants’ and toddlers’ implicit false belief and morality ( Hamlin, 2014 ; Tafreshi et al., 2014 ; Baillargeon et al., 2018 ; Sabbagh and Paulus, 2018 ).

This debate also involves the relation between development and evolution. For Tafreshi and colleagues, for instance, the idea of core knowledge would involve a consideration of high-level cognitive capacities as biologically predetermined instead of constructed in interaction with the environment. This is not the perspective of those who consider that development does exist in the social environment but is constrained by a number of basic competencies ( Hamlin, 2014 ). An important element of this perspective is comparing human and animal capacities. In fact, research has shown that such basic competencies also exist in some form in animals. For instance, numerous studies have shown that adult nonhuman primates have the core systems of object, number, agent representations, etc. ( Spelke and Kinzler, 2007 ).

These preoccupations have also informed work by Tomasello and the Leipzig group. “All we can claim to have done so far–writes Tomasello–is to establish some comparative facts–organized by some theoretical speculations–that hopefully get us started in the right direction toward an evolutionary informed account of the ontogeny of uniquely human psychology” ( Tomasello, 2018 ). Comparing experimental work on great apes and young children has led him to formulate the hypothesis that the factors marking the difference between these two groups are different aspects of social cognition. Nonhuman primates have some basic capacities in these areas. In humans, the evolved capacity for shared intentionality transforms them in the species-unique human cognition and sociality ( Tomasello and Herrmann, 2010 ).

Tomasello’s work has also aroused criticism. In this case, the criticism is because his research, both with young children and primates, uses experimental methods and is carried out in a laboratory. Fieldwork primatologists have claimed that primates in captivity, tested by someone of another species, cannot display the abilities that their conspecifics display in their natural environment ( Boesch, 2007 ; De Waal et al., 2008 ). Tomasello answered this criticism by maintaining that the fact of being raised in a human environment enhances primates’ capacities ( Tomasello et al., 1993 ; Tomasello and Call, 2008 ).

In conclusion, in developmental psychology, a multiplicity of methods has been applied, and the debate over their respective validity and correct application continues. However, what is not in question is that development is a complex and multifaceted phenomenon that must be analyzed as such and from different points of view.

A paradigmatic case in the present research is the study of the theory of mind. Discovering how subjects represent their own mind and other minds was proposed in 1978 by Premack and Woodruff as a problem of research on primates, and in a short time, it has become one of the main topics in developmental research ( Premack and Woodruff, 1978 ). It is currently being studied in groups of different ages, from infants to the elderly, both in typical and clinical subjects and using different methodologies, from classic experiments to clinical observation. Moreover, a number of studies investigate individual and cross-cultural variation and its role in human-robots interactions. Philosophers have contributed to the definition of this phenomenon, and neuroscientists are working to discover its neural basis.

Computational Models of Development

Some researchers have pursued the goal of constructing computational models of cognitive development using different computational approaches (for a review, see Mareschal, 2010 ). However, as the author of this review remarks, all the models have explored cognition “as an isolated phenomenon”, i.e., they did not consider the physical and social context in which development unfolds.

Karmiloff-Smith, a developmental psychologist who proposed the most interesting theory about developmental change as an alternative to Piaget’s, considered that a number of features of her RR ( representational redescription ) model happened to map onto features of connectionist models ( Karmiloff-Smith, 1992 ; for a review of these models, see Plunkett et al., 1997 ). However, she also remarks that connectionist models have modeled tasks, while development is not simply task-specific learning, as it involves deriving and using previously acquired knowledge 6 .

One result of the dissatisfaction with the results deriving from the relation between cognitive psychology and artificial intelligence and the concomitant increase in interest in embodied cognition has been the growth of developmental robotics ( Lungarella et al., 2003 ). The aim of this field is to produce baby robots endowed with sensorimotor and cognitive abilities inspired by child psychology and to model developmental changes ( Cangelosi and Schlesinger, 2018 ). This approach has led to the comparison of results in experiments with robots and children. This is a promising field, even if it does not overcome the problems described above regarding the specificity of tasks that does not allow to account for infants’ ability to utilize previously differently acquired knowledge in the performance of a given task.

In conclusion, some approaches within cognitive science have acknowledged the usefulness of studying children in order to understand the mechanisms of development. Especially in the case of developmental robotics, this has allowed for studying the interaction of different capacities such as sensorimotor abilities, perception, and language. At the same time, the computational constraints do not allow for overcoming task specificity.

Concluding Remarks

I have argued that since their beginning, general psychology and developmental psychology have followed parallel paths that have only occasionally converged. The reason is due essentially to methodological problems that have involved not only research methods but also the very object of inquiry.

Psychology was founded with the ambition of becoming a science performed in laboratories and based on experimental work. However, as early as in 1934, Vygotsky had already deplored the attempt to achieve scientific standards by limiting the importance of general issues. “As long as we lack a generally accepted system incorporating all available psychological knowledge, any important factual discovery inevitably leads to the creation of a new theory to fit the newly observed facts” ( Vygotsky, 1962/1986 , p. 13).

The birth of cognitive science has taken important steps toward constructing links with other disciplines and also other ways to study cognition. However, this opening was soon transformed in the search for a unifying methodology, namely computer modeling, as a guarantee of scientific results. Many interesting ideas have been generated. However, after four decades of work in this direction, it has become impossible to ignore that too many important aspects of the human mind and activity have been eluded.

The relative isolation of developmental psychology came from the prejudice, also shared by eminent developmental psychologists like Piaget, that what characterizes human cognition are adult cognitive abilities.

However, from the start, developmental psychology was not limited to investiganting the specificity of children’s cognition. It devoted attention to what makes development possible, including biological endowment and cultural transmission; whether an infant should be considered a blank slate or if one can define some pre-existent basic abilities; what makes humans different from animals and nonhuman primates; and how specific human abilities such as language have evolved.

At present, a rapprochement between adult and child studies is made possible by different factors. The possibility of using experimental methods to study infancy has allowed us to realize the complexity of young humans. Moreover, development is increasingly being considered as a phenomenon not only characterizing childhood but also present over the life span, including both the acquisition and the decay of mental abilities ( Bialystok and Craik, 2006 ). Studying the human mind means studying how the human mind changes in interaction with the external environment all life long. In this sense, the study of human mind is inherently connected with the study of its development.

An important question of method emerges here. We have observed that over the years, developmental psychologists have sought to construct methods that can be reliable and at the same time can adequately address the topics under discussion here. The achievement of finding ways to carry out experiments with infants and nonhuman primates has been an important advancement in this perspective. This advancement has garnered both praise and criticism. To be reliable, experiments with infants require very rigorous procedures. Frequently, a detailed analysis of procedures is necessary to explain divergent results. However, it can be noted that reproducibility is an open problem for psychological science in general ( Open Science Collaboration, 2015 ). For nonhuman primates, the ecological validity of laboratory experiments has been questioned. More generally, it has been shown that in the field of developmental psychology, experimental studies do not completely replace other methodologies, but rather should coexist with them.

The human mind is complex, and all the methods that have been proposed in different disciplines may be useful in advancing our knowledge of it. The explanation of this complexity was the main goal underlying the proposal of cognitive science and is the perspective we must pursue in the future.

On this ground, the paths of psychology and developmental psychology may reconverge.

Author Contributions

The author confirms being the sole contributor of this work and has approved it for publication.

Conflict of Interest Statement

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The reviewer MT declared a shared affiliation, with no collaboration, with the author to the handling editor at time of review.

1. The very earliest date was 1875 and that same year William James’ laboratory at Harvard in the United States was established ( Harper, 1950 ).

2. William James was influenced by Darwin and this appears in particular in his conceiving the mind as a function and not as a thing ( Bredo, 1998 ). However, his book The Principles of Psychology , first published in 1890 and later revised several times, ignored child development. In the chapter devoted to methods and snares in psychology, he adds to introspective observation and experimental method the comparative method. “So it has come to pass that instincts of animals are ransacked to throw light on our own; and that the reasoning faculties of bees and ants, the minds of savages, infants, madmen, idiots, the deaf and blind, criminals, and eccentrics, are invoked in support of this or that special theory about some part of our own mental life” ( James, 1983 , p. 193). If he admits that “information grows and results emerge”, he also cautions that “there are great sources of error in the comparative method” and that “comparative observation, to be definite, must usually be made to test some pre-existing hypothesis” ( James, 1983 ).

3. Putnam was actually the first to employ the term functionalism , and his aim in doing so was anti-reductionist. In his 1975 work he used the comparison with a computer program to show that psychological properties do not have a physical and chemical nature, even though they are realized by physical and chemical properties ( Putnam, 1975 ).

4. Hewitt (1991) highlights the difficulties inherent in constructing artificial systems, which, like social systems, are founded on concepts such as commitment, cooperation, conflict, negotiation, and so forth.

5. Gaze and eye-tracking techniques are normally used in psychological research with adults ( Mele and Federici, 2012 ) but it is in developmental studies that they have had a dramatic impact on the possibilities of inquiry.

6. A different approach that has given origin to formal models and simulations is the paradigm that views the developmental process as a change within a complex dynamic system. Cognition in this perspective is embodied in the processes of perception and action ( Smith and Thelen, 2003 ).

Airenti, G. (2015). The cognitive bases of anthropomorphism: from relatedness to empathy. Int. J. Soc. Robot. 7, 117–127. doi: 10.1007/s12369-014-0263-x

CrossRef Full Text | Google Scholar

Airenti, G. (2016). Playing with expectations: a contextual view of humor development. Front. Psychol. 7:1392. doi: 10.3389/fpsyg.2016.01392

Airenti, G., and Colombetti, M. (1991). “Artificial intelligence and the representation problem” in Proceedings of the first world conference on the fundamentals of artificial intelligence. (Paris: Angkor), 17–28.

Google Scholar

Arbib, M. A., and Fellous, J.-M. (2004). Emotions: from brain to robot. Trends Cogn. Sci. 8, 554–561. doi: 10.1016/j.tics.2004.10.004

PubMed Abstract | CrossRef Full Text | Google Scholar

Austin, J. A. (1962). How to do things with words. (Oxford: Oxford University Press).

Baillargeon, R., Buttelmann, D., and Southgate, V. (2018). Invited commentary: interpreting failed replications of early-false belief findings: methodological and theoretical considerations. Cogn. Dev. 46, 112–124. doi: 10.1016/j.cogdev.2018.06.001

Baillargeon, R., Scott, R. M., and Bian, L. (2016). Psychological reasoning in infancy. Annu. Rev. Psychol. 67, 159–186. doi: 10.1146/annurev-psych-010213-115033

Baldwin, J. M. (1895). Mental development in the child and the race. (New York, NY: Macmillan).

Baldwin, J. M. (1930). “Autobiography of James Mark Baldwin” in History of psychology in autobiography. ed. C. Murchison, Vol. 1. (Worchester, MA: Clark University Press), 1–30.

Bialystok, E., and Craik, F. I. M. (2006). Lifespan cognition: Mechanisms of change. (New York: Oxford University Press).

Bjorklund, D. F. (2018). A metatheory for cognitive development (or “Piaget is dead” revisited). Child Dev. 89, 2288–2302. doi: 10.1111/cdev.13019

Block, N. (1978). Troubles with functionalism. Minnesota studies in the philosophy of science. Vol. 9. (Minneapolis: University of Minnesota Press), 261–325.

Boesch, C. (2007). What makes us human (Homo sapiens)? The challenge of cognitive cross-species comparison. J. Comp. Psychol. 121, 227–240. doi: 10.1037/0735-7036.121.3.227

Bornstein, M. H. (1985). “Habituation of attention as a measure of visual information processing in human infants: summary, systematization, and synthesis” in Measurement of audition and vision during the first year of postnatal life: A methodological overview. eds. G. Gottlieb, and N. A. Krasnegor (Norwood, NJ: Ablex), 253–300.

Bredo, E. (1998). The Darwinian center to the vision of William James. Paper presented at the Annual Meeting of the American Educational Research Association . (SanDiego, CA, April 13–17, 1998).

Bruner, J. S. (1975). The ontogenesis of speech acts. J. Child Lang. 2, 1–19.

Bruner, J. S. (1983a). In search of mind: Essays in autobiography. (New York, NY: Harper and Row).

Bruner, J. S. (1983b). Child's talk: Learning to use language. (New York: Norton).

Bruner, J. S. (1990). Acts of meaning. (Cambridge, MA: Harvard University Press).

Burman, J. T. (2013). Updating the Baldwin effect. The biological levels behind Piaget’s new theory. New Ideas Psychol. 31, 363–373. doi: 10.1016/j.newideapsych.2012.07.003

Cangelosi, A., and Schlesinger, M. (2018). From babies to robots: the contribution of developmental robotics to developmental psychology. Child Dev. Perspect. 12, 183–188. doi: 10.1111/cdep.12282

Chalmers, D. (1993). Why Fodor and Pylyshyn were wrong: the simplest refutation. Philos. Psychol. 6, 305–319. doi: 10.1080/09515089308573094

Cognitive Science Committee. (1978). Report of the State of the Art, Ms.

Darwin, C. (1872/1965). The expression of emotions in man and animals. (Chicago: University of Chicago Press).

De Waal, F. B., Boesch, C., Horner, V., and Whiten, A. (2008). Comparing social skills of children and apes. Science 319:569. doi: 10.1126/science.319.5863.569c

DeCasper, A. J., and Fifer, W. P. (1980). Of human bonding: newborns prefer their mothers’ voices. Science 208, 1174–1176. doi: 10.1126/science.7375928

Dreyfus, H. (1979). What computers can’t do: A critique of artificial reason. (New York, NY: Harper & Row).

Fantz, R. L. (1964). Visual experience in infants: decreased attention to familiar patterns relative to novel ones. Science 146, 668–670. doi: 10.1126/science.146.3644.668

Fodor, J. A. (1985). Fodor’s guide to mental representation: the intelligent auntie’s vademecum. Mind 94, 76–100.

Fodor, J., and Pylyshyn, Z. (1988). Connectionism and cognitive architecture: a critical analysis. Cognition 28, 3–71. doi: 10.1016/0010-0277(88)90031-5

Forbus, K. D. (2010). AI and cognitive science: the past and next 30 years. Top. Cogn. Sci. 2, 345–356. doi: 10.1111/j.1756-8765.2010.01083.x

Gentner, D. (2010). Psychology in cognitive science: 1978–2038. Top. Cogn. Sci. 2, 328–344. doi: 10.1111/j.1756-8765.2010.01103.x

Grice, H. P. (1989). Studies in the way of words. (Cambridge, MA: Harvard University Press).

Hamlin, J. K. (2014). The conceptual and empirical case for social evaluation in infancy. Commentary on Tafreshi, Thompson, and Racine. Hum. Dev. 57, 250–258. doi: 10.1159/000365120

Harnad, S. (1990). The symbol grounding problem. Physica D 42, 335–346. doi: 10.1016/0167-2789(90)90087-6

Harper, R. S. (1950). The first psychological laboratory. Isis 41, 158–161. doi: 10.1086/349141

Hewitt, C. (1991). Open information systems semantics for distributed artificial intelligence. Artif. Intell. 47, 79–106. doi: 10.1016/0004-3702(91)90051-K

Hinton, G. E. (1989). Connectionist learning procedures. Artif. Intell. 40, 185–234. doi: 10.1016/0004-3702(89)90049-0

Hoehl, S., and Wahl, S. (2012). Recording infant ERP data for cognitive research. Dev. Neuropsychol. 37, 187–209. doi: 10.1080/87565641.2011.627958

James, W. (1983). The principles of psychology. (Cambridge, Mass: Harvard University Press).

Kahn, P. H. Jr., Ishiguro, H., Friedman, B., Kanda, T., Freier, N. G., Severson, R. L., et al. (2007). What is a human? Toward psychological benchmarks in the field of human-robot interaction. Inter. Stud. 8, 363–390. doi: 10.1075/is.8.3.04kah

Karmiloff-Smith, A. (1992). Beyond modularity. (Cambridge, Mass: The MIT Press).

Koops, W. (2015). No developmental psychology without recapitulation theory. Eur. J. Dev. Psychol. 12, 630–639. doi: 10.1080/17405629.2015.1078234

Levesque, H., and Brachman, R. (1985). “A fundamental tradeoff in knowledge representation and reasoning (revised version)” in Readings in knowledge representation. eds. R. Brachman, and H. J. Levesque (Burlington, MA: Morgan Kaufmann), 41–70.

Lungarella, M., Metta, G., Pfeifer, R., and Sandini, G. (2003). Developmental robotics: a survey. Con. Sci. 15, 151–190. doi: 10.1080/09540090310001655110

Mareschal, D. (2010). Computational perspectives on cognitive development. WIREs Cognit. Sci. 1, 696–708. doi: 10.1002/wcs.67

Mele, M. L., and Federici, S. (2012). Gaze and eye-tracking solutions for psychological research. Cogn. Proc. 13, S261–S265. doi: 10.1007/s10339-012-0499-z

Miller, G. A., Galanter, E., and Pribram, K. (1960). Plans and structure of behavior. (New York, NY: Holt, Rinehart and Winston).

Morgan, T. J. H., and Harris, P. L. (2015). James Mark Baldwin and contemporary theories of culture and evolution. Eur. J. Dev. Psychol. 12, 666–677. doi: 10.1080/17405629.2015.1074068

Newell, A., and Simon, H. A. (1972). Human problem solving. (Englewood Cliffs, N.J: Prentice-Hall).

Open Science Collaboration (2015). Estimating the reproducibility of psychological science. Science 349:aac4716. doi: 10.1126/science.1253751

Pfeifer, R., Lungarella, M., and Iida, F. (2007). Self-organization, embodiment, and biologically inspired robotics. Science 318, 1088–1093. doi: 10.1126/science.1145803

Piaget, J. (1928). Logique génétique et sociologie. Revue Philosophique de la France et de l’Étranger 53, 167–205.

Piattelli-Palmarini, M. (1979/1980). Language and learning: The debate between Jean Piaget and Noam Chomsky. (London: Routledge and Kegan Paul).

Pitt, D. (2017). “Mental representation” in The Stanford Encyclopedia of philosophy. ed. E. N. Zalta. https://plato.stanford.edu/archives/spr2017/entries/mental-representation

Plunkett, K., Karmiloff-Smith, A., Bates, E., Elman, J. L., and Johnson, M. H. (1997). Connectionism and developmental psychology. J. Child Psychol. Psychiatry 38, 53–80. doi: 10.1111/j.1469-7610.1997.tb01505.x

Premack, D., and Woodruff, G. (1978). Does the chimpanzee have a theory of mind? Behav. Brain Sci. 4, 515–526.

Putnam, H. (1975). Mind, language and reality. (Cambridge: Cambridge University Press).

Putnam, H. (1988). Representation and reality. (Cambridge, MA: MIT Press).

Pylyshyn, Z. W. (1984). Computation and cognition. (Cambridge, MA: The MIT Press/Bradford).

Quinlan, P. T. (1991). Connectionism and psychology: A psychological perspective on new connectionist research. (Hemel Hempstead: Harvester Wheatsheaf).

Sabbagh, M. A., and Paulus, M. (2018). Editorial. Replication studies of implicit false belief with infants and toddlers. Cogn. Dev. 46, 1–3. doi: 10.1016/j.cogdev.2018.07.003

Schank, R. C., and Abelson, R. P. (1977). Scripts, plans, goals and understanding. (Hillsdale, N.J: Lawrence Erlbaum).

Searle, J. R. (1980). Minds, brains and programs. Behav. Brain Sci. 3, 417–424. doi: 10.1017/S0140525X00005756

Searle, J. R. (1990). Consciousness, explanatory inversion, and cognitive science. Behav. Brain Sci. 13, 585–596. doi: 10.1017/S0140525X00080304

Searle, J. R. (1992). The rediscovery of the mind. (Cambridge, MA: The MIT Press).

Simpson, G. G. (1953). The Baldwin effect. Evolution 7, 110–117. doi: 10.1111/j.1558-5646.1953.tb00069.x

Siqueland, E. R., and De Lucia, C. A. (1969). Visual reinforcement of non-nutritive sucking in human infants. Science 165, 1144–1146. doi: 10.1126/science.165.3898.1144

Smith, L. B., and Thelen, E. (2003). Development as a dynamic system. Trends Cogn. Sci. 7, 343–348. doi: 10.1016/S1364-6613(03)00156-6

Spelke, E. S. (2000). Core knowledge. Am. Psychol. 55, 1233–1243. doi: 10.1037/0003-066X.55.11.1233

Spelke, E. S., and Kinzler, K. D. (2007). Core knowledge. Dev. Sci. 10, 89–96. doi: 10.1111/j.1467-7687.2007.00569.x

Stern, C., and Stern, W. (1928). Die Kindersprache [The speech of children. (4th Ed.)]. (Oxford, England: Barth).

Tafreshi, D., Thompson, J. J., and Racine, T. P. (2014). An analysis of the conceptual foundations of the infant preferential looking paradigm. Hum. Dev. 57, 222–240. doi: 10.1159/000363487

Tomasello, M. (2018). Great apes and human development: a personal history. Child Dev. Perspect. 12, 189–193. doi: 10.1111/cdep.12281

Tomasello, M., and Call, J. (2008). Assessing the validity of ape-human comparisons: a reply to Boesch (2007). J. Comp. Psychol. 122, 449–452. doi: 10.1037/0735-7036.122.4.449

Tomasello, M., and Herrmann, E. (2010). Ape and human cognition: what’s the difference? Curr. Dir. Psychol. Sci. 19, 3–8. doi: 10.1177/0963721409359300

Tomasello, M., Savage-Rumbaugh, S., and Kruger, A. (1993). Imitative learning of actions on objects by children, chimpanzees and enculturated chimpanzees. Child Dev. 64, 1688–1705. doi: 10.2307/1131463

Varela, F. D., Rosch, E., and Thompson, E. (1991). The embodied mind: Cognitive science and human experience. (Cambridge, MA: MIT Press).

Vygotsky, L. (1962/1986). Thought and language. (Cambridge, MA: The MIT Press).

Waddington, C. H. (1953). The ‘Baldwin effect,’ ‘genetic assimilation’ and ‘homeostasis’. Evolution 7, 386–387.

S. Wermter, and R. Sun (eds.) (2000). Hybrid neural symbolic integration. (Berlin: Springer Verlag).

Wiese, E., Metta, G., and Wykowska, A. (2017). Robots as intentional agents: using neuroscientific methods to make robots appear more social. Front. Psychol. 8:1663. doi: 10.3389/fpsyg.2017.01663

Wynn, K., and Bloom, P. (2014). “The moral baby” in The handbook of moral development. 2nd Edn. eds. M. Killen, and J. G. Smetana (New York: Psychology Press), 435–453.

Ziemke, T. (2008). On the role of emotion in biological and robotic autonomy. BioSystems 91, 401–408. doi: 10.1016/j.biosystems.2007.05.015

Ziemke, T., Thill, S., and Vernon, D. (2015). “Embodiment is a double-edged sword in human-robot interaction: ascribed vs. intrinsic intentionality” in Proceedings of the workshop on cognition: A bridge between robotics and interaction , 9–10.

Zlatev, J. (2001). The epigenesis of meaning in human beings, and possibly robots. Minds Mach. 11, 155–195. doi: 10.1023/A:1011218919464

Keywords: development, methods, infants, cognitive science, change process

Citation: Airenti G (2019) The Place of Development in the History of Psychology and Cognitive Science. Front. Psychol . 10:895. doi: 10.3389/fpsyg.2019.00895

Received: 03 September 2018; Accepted: 03 April 2019; Published: 24 April 2019.

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*Correspondence: Gabriella Airenti, [email protected]

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