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.

Key words: artificial life, connectionism, knowledge representation, meaning, neural computation, semantics, symbol.

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.

Key words: cognition, computational neuroscience, connectionism, epistemology, knowledge representation, neural systems and dynamics.

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).

Key words: cognitive science, functional fitness, human person, knowledge (representation), (natural) science, representational space

Purpose: In the educational field a lack of focus on the process of arriving at a level of profound understanding of a phenomenon can be observed. While classical approaches in education focus on “downloading,” repeating, or sometimes optimizing relatively stable chunks of knowledge (both facts and procedural knowledge), this paper proposes to shift the center of attention towards a more dynamic and constructivist perspective: learning as a process of individual and collective knowledge creation and knowledge construction. The goal of this process is to profoundly understand a phenomenon in its multi-dimensionality and complexity and to reflect on the processes that have lead to this understanding. The issue we want to tackle in this paper is how this profound understanding can be brought about in a technology-enhanced learning environment. Method: Part 1 of this paper explores strategies of technology-enhanced knowledge sharing/creation in the field of higher education. Part 2 presents a successful blended learning scenario that illustrates the implementation of these learning strategies in a concrete course design. In this case study students are involved in active theory construction processes by conducting virtual experiments with a virtual organism. Part 3 elaborates on the epistemological implications of this case study. Findings: A constructivist framework for modes of knowing and modes of coming to know is developed. It is shown that – in order to reach a profound understanding of a phenomenon – it is essential to take into account the multi-facetted character of knowledge and to use the strategy of double-loop learning. Conclusion: This leads to an understanding of learning/teaching as a process of socio-epistemological engineering. Furthermore, the role of the teacher changes in such a constructivist setting of learning/teaching: Their primary task is to provide a “pedagogically (and technologically) augmented environment.” They are responsible for creating an atmosphere of collective knowledge construction and reflection. Beyond the role of a coach and moderator the teacher has to act as a facilitator or “enabler” for the (individual and collective) processes of double-loop learning.

Key words: blended learning, collaborative co-construction, collective learning, double-loop learning, e-learning, individual learning, knowledge construction, knowledge creation, organizational learning, socio-epistemological engineering, university teaching

Purpose: Ernst von Glasersfeld’s question concerning the relationship between scientific/rational knowledge and the domain of wisdom and how these forms of knowledge come about is the starting point. This article aims at developing an epistemological as well as methodological framework that is capable of explaining how profound change can be brought about in various contexts, such as in individual cultivation, in organizations, in processes of radical innovation, etc. This framework is based on the triple-loop learning strategy and the U-theory approach, which opens up a perspective on how the domains of scientific/rational knowledge, constructivism, and wisdom could grow together more closely. Method: This article develops a strategy which is referred to as “triple-loop learning,” which is not only the basis for processes of profound change, but also brings about a new dimension in the field of learning and knowledge dynamics: the existential realm and the domain of wisdom. A concrete approach that puts into practice the triple-loop learning strategy is presented. The final section shows, how these concepts can be interpreted in the context of the constructivist approach and how they might offer some extensions to this paradigm. Findings: The process of learning and change has to be extended to a domain that concerns existential issues as well as questions of wisdom. Profound change can only happen if these domains are taken into consideration. The triple-loop learning strategy offers a model that fulfills this criterion. It is an “epistemo-existential strategy” for profound change on various levels. Conclusion: The (cognitive) processes and attitudes of receptivity, suspension, redirecting, openness, deep knowing, as well as “profound change/innovation from the interior” turn out to be core concepts in this process. They are compatible with constructivist concepts. Von Glasersfeld’s concept of functional fitness is carried to an extreme in the suggested approach of profound change and finds an extension in the existential domain.

Key words: double-loop learning, individual cultivation, radical innovation, knowledge creation, knowledge society, personality development, presencing, profound change, triple-loop learning, U-theory, wisdom

Innovation has become one of the most important issues in modern knowledge society. As opposed to radical innovation this paper introduces the concept of Emergent Innovation: this approach tries to balance and integrate the demand both for radically new knowledge and at the same time for an organic development from within the organization. From a more general perspective one can boil down this problem to the question of how to cope with the new and with profound change (in knowledge). This question will be dealt with in the first part of the paper. As an implication the alternative approach of Emergent Innovation will be presented in the second part: this approach looks at innovation as a socio-epistemological process of “learning from the future” in order to create (radically) new knowledge in a sustainable and “organic” manner. Implications for knowledge society will be discussed.

Upshot: This response focuses on the following issues, which summarize the points made by the commentaries: (i) further reflection on and details of the methodological framework that was applied to studying the proposed design of our innovation course, (ii) the issue of generalizability of the findings for teaching innovation (in this context the question of generic or transferable skills will become central), and (iii) finally, more precise explanation of what we mean by “learning from the future as it emerges.”

Context: Radical constructivism (RC) is seen as a fruitful way to teach innovation, as Ernst von Glasersfeld’s concepts of knowing, learning, and teaching provide an epistemological framework fostering processes of generating an autonomous conceptual understanding. Problem: Classical educational approaches do not meet the requirements for teaching and learning innovation because they mostly aim at students’ competent performance, not at students’ understanding and developing their creative capabilities. Method: Analysis of theoretical principles from the constructivist framework and how they can be used as a foundation for designing a course in the field of innovation. The empirical results are based on qualitative journal entries that were coded and categorized according to Charmaz’s grounded theory approach. Results: It is shown that there is a close relationship between learning and innovation processes. The proposed investigated course design based on RC incorporates the following concepts: the course setting is understood as a framework to guide understanding; students work in teams and are subjective constructors of their own knowledge; instructors take on the role of coaches, guiding students through an innovation process as co-creators. Such a framework facilitates dynamic processes of assimilation and accommodation, as well as perturbation through the “other,” which potentially lead to novel, and viable, conceptual structures crucial for sustainable innovation. Constructivist Content: The paper argues in favor of RC principles in the context of teaching and learning. The proposed course setting is oriented at von Glasersfeld’s understanding of knowing, learning, and teaching (vs. training. It outlines theoretical and practical aspects of these principles in the context of a course design for innovation. Furthermore, it shows the importance of von Glasersfeld’s concept of intersubjectivity for processes of accommodation and the generation of (novel) autonomous conceptual structures. The interplay between creating coherence, perturbation, and irritation through interacting with the “other” (in the form of co-students and instructors) is assumed to be vital for such processes, as it leads to the creation of not only novel but also viable conceptual structures, therefore re-establishing a relative equilibrium critical for sustainable innovation.

Key words: Innovation, teaching, learning, course design, co-creation, Enabling Space, radical constructivism.

Context: Cognitive science, as an interdisciplinary research endeavour, poses challenges for teaching and learning insofar as the integration of various participating disciplines requires a reflective approach, considering and making explicit different epistemological attitudes and hidden assumptions and premises. Only few curricula in cognitive science face this integrative challenge. Problem: The lack of integrative activities might result from different challenges for people involved in truly interdisciplinary efforts, such as discussing issues on a conceptual level, negotiating colliding frameworks or sets of premises, asking profound questions challenging one’s own paradigm, and differences in terminologies, as well as from the “personal” challenge of realising one’s own limits of knowledge and, hence, the need to trust in another person’s expertise. This implies that the proposed curriculum structure provides an “epistemic laboratory”: a space for experiencing and negotiating, as well as constructing different viewpoints in a trustful setting. Approach: A newly-designed interdisciplinary cognitive science curriculum is presented that is based on a constructivist epistemology. We suggest that a careful construction of the learning space is a necessary requirement. The MEi:CogSci curriculum is designed and structured in such a way that enables didactical measures that allow for collaborative construction of meaning by discussing concepts, methods and terminologies and also hidden assumptions. Findings: The experience with four cohorts of students has shown that a truly interdisciplinary approach to cognitive science demands a different attitude towards knowledge as well as towards teaching and learning on both sides: the teacher and the student. The research orientation promotes an understanding of knowledge as something that is actively constructed, rendering the role of the teacher that of a co-learner rather than a transmitter of knowledge, thereby also changing the responsibility of students.

Key words: learning space, interdisciplinarity, cognitive science, curriculum design, epistemological reflection, teacher, constructivist pedagogy