Models of cognition and language currently in use as frameworks for computer applications present a clear disequilibrium: they neglect productive mental activities, as for instance synthesis, and over-estimate receptive ones, as analysis. The paper focuses on the Kantian concept of object-synthesis as a basic mental mechanism and underlines its importance for an equilibrated model of cognitive processing. Integration of the Kantian approach with Ceccato’s model of mental operations could allow to implement synthetic operations in computer applications. A syntactic parser (von Glasersfeld and Pisani, 1970) which implements Ceccato’s approach to cognition, semantics and linguistics is reproposed to the attention of AI researchers: it could be used as a basis for a modern implementation of object-synthesis in knowledge representation and natural language processing.
Cáceres E. (2011) Steps toward a constructivist and coherentist theory of judicial reasoning in civil law tradition. Law and neuroscience: Current Legal Issues 13: 459–482.
This chapter presents a theoretical model of judicial reasoning that satisfactorily integrates partially provided explanations by three different theoretical research paradigms: philosophy of law, legal epistemology, and artificial intelligence and law. The model emerges from the application of knowledge elicitation and knowledge representation methods, and uses the theory of neural networks as a theoretical metaphor to generate explanations and visual representations. The epistemological status of the model is of constructivist stripe: it is in line with the contemporary research tendencies within cognitive psychology that propose that judicial reasoning may be better understood if a coherentist and a connectionist approach is taken.
Jonassen D. H. (1991) Objectivism versus constructivism: Do we need a new philosophical paradigm? Journal of Educational Research 39(3): 5–14. https://cepa.info/5215
Many scholars in the instructional systems field have addressed the paradigm shift in the field of learning psychology and its implications for instructional systems technology (IST). This article analyzes the philosophical assumptions underlying IST and its behavioral and cognitive foundations, each of which is primarily objectivistic, which means that knowing and learning are processes for representing and mirroring reality. The philosophical assumptions of objectivism are then contrasted with constructivism, which holds that knowing is a process of actively interpreting and constructing individual knowledge representations. The implications of constructivism for IST provide a context for asking the reader to consider to what extent our field should consider this philosophical paradigm shift.
Peschl M. F. (1992) Construction, representation, and the embodiment of knowledge, meaning, and symbols in neural structures: Towards an alternative understanding of knowledge representation and philosophy of science. Connection Science 4(3–4): 327–338.
In this paper an alternative concept and understanding of knowledge representation in neural networks is presented. It is based on the assumption that (natural or artificial) neural structures are responsible for the generation of an organism’s behavior which is in interaction with its environment. This requires a completely new interpretation of neural systems as knowledge representing devices. The concepts of constructivism second-order cybernetics, embodiment of knowledge and functional fitness play an important role in this context. The idea of an structural isomorphism between the environment and representing structures will be given up in favor of a more sophisticated epistemological concept and constructive relation. As an implication knowledge becomes system relative and ‘private’ – an alternative understanding of language, symbols, communication, etc., which is based on these epistemological and neuroscientific ideas will be discussed.
Peschl M. F. (1997) The representational relation between environmental structures and neural systems: Autonomy and environmental dependency in neural knowledge representation. Nonlinear Dynamics, Psychology. and Life Sciences 1(2): 99–121.
In this paper it will be shown that in neural systems with a recurrent architecture, the traditional concepts of knowledge representation cannot be applied any more; no stable representational relationship of reference can be found. That is why a redefinition of the relationship between the states of the environment and the internal representational states is proposed. Studying the dynamics of recurrent neural systems reveals that the goal of representation is no longer to map the environment as accurately as possible to the representation system (e.g., to symbols) It is suggested that it is more appropriate to look at neural systems as physical dynamical devices embodying the (transformation) knowledge for sensorimotor integration and for generating adequate behavior enabling the organism’s survival. As an implication the representation is determined not only by the environment, but highly depends on the organization, structure, and constraints of the representation system as well as the sensory/motor systems which are embedded in a particular body structure. This leads to a system relative concept of representation. By transforming recurrent neural networks into the domain of finite automata, the dynamics as well as the epistemological implications become more clear. In recurrent neural systems a type of balance between the autonomy of the representation and the environmental dependence/influence emerges. This not only affects the traditional concept of knowledge representation, but has also implications for the understanding of semantics, language, communication, and even science.
Peschl M. F. (2001) Constructivism, cognition, and science: An investigation of its links and possible shortcomings. Special Issue “The Impact of Radical Constructivism on Science” edited by Alexander Riegler. Foundations of Science 6(1–3): 125–161. https://cepa.info/3635
This paper addresses the questions concerning the relationship between scientific and cognitive processes. The fact that both, science and cognition, aim at acquiring some kind of knowledge or representation about the “world” is the key for establishing a link between these two domains. It turns out that the constructivist framework represents an adequate epistemological foundation for this undertaking, as its focus of interest is on the (constructive) relationship between the world and its representation. More specifically, it will be shown how cognitive processes and their primary concern to construct a representation of the environment and to generate functionally fitting behavior can act as the basis for embedding the activities and dynamics of the process of science in them by making use of constructivist concepts, such as functional fitness, structure determinedness, etc. Cognitive science and artificial life provide the conceptual framework of representational spaces and their interaction between each other and with the environment enabling us to establish this link between cognitive processes and the development/dynamics of scientific theories. The concepts of activation, synaptic weight, and genetic (representational) spaces are powerful tools which can be used as “explanatory vehicles” for a cognitive foundation of science, more specifically for the “context of discovery” (i.e., the development, construction, and dynamics of scientific theories and paradigms). Representational spaces do not only offer us a better understanding of embedding science in cognition, but also show, how the constructivist framework, both, can act as an adequate epistemological foundation for these processes and can be instantiated by these representational concepts from cognitive science. The final part of this paper addresses some more fundamental questions concerning the positivistic and constructivist understanding of science and human cognition. Among other things it is asked, whether a purely functionalist and quantitative view of the world aiming almost exclusively at its prediction and control is really satisfying for our intellect (having the goal of achieving a profound understanding of reality).
Peschl M. P. & Stary C. (1998) The role of cognitive modeling for user interface design representations: An epistemological analysis of knowledge engineering in the context of human-computer interaction. Minds and Machines 8(2): 203–236. https://cepa.info/4545
In this paper we review some problems with traditional approaches for acquiring and representing knowledge in the context of developing user interfaces. Methodological implications for knowledge engineering and for human-computer interaction are studied. It turns out that in order to achieve the goal of developing human-oriented (in contrast to technology-oriented) human-computer interfaces developers have to develop sound knowledge of the structure and the representational dynamics of the cognitive system which is interacting with the computer. //We show that in a first step it is necessary to study and investigate the different levels and forms of representation that are involved in the interaction processes between computers and human cognitive systems. Only if designers have achieved some understanding about these representational mechanisms, user interfaces enabling individual experiences and skill development can be designed. In this paper we review mechanisms and processes for knowledge representation on a conceptual, epistemological, and methodological level, and sketch some ways out of the identified dilemmas for cognitive modeling in the domain of human-computer interaction.
Riegler A. (2007) The radical constructivist dynamics of cognition. In: Wallace B. (ed.) The Mind, the Body and the World: Psychology After Cognitivism?. Imprint, London: 91–115. https://cepa.info/1777
The radical constructivist perspective points in the direction of a post-cognitivist psychology which (a) does not get stuck in perceptual overload, (b) does not run into epistemological problems of (propositional) knowledge representation, (c) takes the undifferentiated encoding of nervous signals into consideration, (d) does not exclude animals from being cognitive, and (e) accounts for implicit knowledge.
Scott B. (2001) Conversation theory: A constructivist, dialogical approach to educational technology. Cybernetics & Human Knowing 8(4): 25–46. https://cepa.info/1803
This paper overviews conversation theory, as developed over three decades by Pask, Scott and others, with particular emphasis on its application to the field of educational technology. Topics covered include models for learning and teaching, individual differences in approaches to learning, CASTE Course Assembly System and Tutorial Environment and associated principles for course design and tutorial strategies, knowledge and task analysis and knowledge representation for course design. The paper begins with a brief biographical note on the life and work of Gordon Pask and ends with some examples of current applications and some thoughts about the role of conversation theory in future developments in educational technology.