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About 10,000 papers for “knowledge structure”

Knowledge Structure

Schack, Thomas, Bläsing, Bettina, Eklund, Robert C. et al. · PUB – Publications at Bielefeld University (Bielefeld University) · 2014

Knowledge about tasks and the environment is organized hierarchically in the human cognitive system, involving the diverse long-term memory (LTM) systems and working memory. Knowledge structures underlying task performance are fundamental elements of action control in sports. Experts' skills are often based on the efficient access to relevant task knowledge as well as on enhanced physical abilities. In the history of research in general psychology, motor control, and sport psychology (SP), knowledge structures have been addressed in different ways, focusing on their significance for task performance from different perspectives. In the field of motor control, Richard A. Schmidt's generalized motor program (GMP) theory has been one of the most prevalent theories used to explain how we control coordinated movements and how we therefore develop structured plans and knowledge. GMP theory is based on feedback-based models, such as James A. Adams's closed-loop theory of motor learning, and adopts the concept of ...

Cited by 0

PRACTICAL RELATION TO LEGAL KNOWLEDGE: KNOWLEDGE STRUCTURE

Zhanna Pavlenko, Сусанна Робертівна Водорєзова · The Bulletin of Yaroslav Mudryi National Law University Series Philosophy philosophies of law political science sociology · 2019

Problem setting. Modern IT technologies consolidate a new attitude to legal knowledge, which from a technological point of view is a "raw material" for artificial legal systems. Technological approach to legal knowledge can not be identified with technology or method, as it is a special operational system of legal acts with legal knowledge for the purpose of its translation from society into an artificial dialogue system, in particular intellectual. Therefore, it is necessary to study the cognitive and informational aspects of the movement of legal knowledge, in particular, their means of obtaining, the mechanisms for selection, dissemination, transformation, accumulation, translation and application, as well as ways to automate these complex processes based on modern high-tech digital devices. We are talking about little-known and extremely topical issues of processing legal knowledge and transforming them into an active information resource. These problems require comprehensive, multidimensional comprehension.Recent research and publications analysis. The results of the analysis of scientific sources and publications indicate that these trends require a deep and thorough study of the particularities of the practical relationship to legal knowledge. New information technologies have contributed to the development of the idea of the diversity of human knowledge. The results of the research of these problems give an opportunity to note that, in general, systematic scientific comprehension of the complex, volumetric and multidimensional problems of practical relevance to legal knowledge need further study.Paper objectiv. The purpose of this article is to consider certain aspects of the practical relation to legal knowledge based on the results of understanding this issue by various representatives of the humanities and interdisciplinary researchers.Paper main body. The article substantiates that the practical attitude to legal knowledge with the advent of artificial intellectual systems has highlighted the problem of extracting, representing and using knowledge in the field of jurisprudence. It is revealed that new information technologies have translated the issues of the specifics of human knowledge, the peculiarities of the interrelation of its main levels into the plane of practical problems associated with the transformation of personal knowledge into formalized (computer). It is determined that the practical attitude towards legal knowledge cannot be identified with either technology or method. It is shown that the attitude towards knowledge as a resource includes the operation of "extracting" knowledge from an expert. The questions are analyzed how and in what way the subject can become aware of the implicit components of personal knowledge.Conclusions of the research. Technological attitude to legal knowledge - mandatory stage in the design of artificial intelligence systems, which includes an action on the study of the microenvironment (knowledge and information needs of users), as well as the design of the intellectual basis of the computer, so that the latter becomes a quasi-subject in communication with the user, that is, the computer understands the system's requests, stores the subject of the dialogue, knowledge of the subject area and poorly structured problems, secondary texts - the arguments of one or another computer solution. The analysis of technological attitude to legal knowledge requires new methodological schemes. Technological attitude to legal knowledge is not identical neither with formalization, nor with algorithmic methodology. The methodology of technological relation to legal knowledge is a complex problem that can be solved on the basis of a constructive dialogue between the developers of artificial intelligence systems and lawyers. The structure of knowledge is fundamentally complex, it includes various facts from the relevant field of law, the relationship between them, the rules of action, knowledge of how to include knowledge in the artificial intelligence system. All this translates into the specifics of human knowledge, the peculiarities of the relationship between its main levels in the area of actual practical problems that require the attention of scholars, therefore the prospects for further research in this direction are directly related to the study of the structure of knowledge in the field of law.

Cited by 0Open access

Knowledge as Residual Structure

G.M. Sturm · Zenodo (CERN European Organization for Nuclear Research) · 2026

This work proposes a constraint-anchored interpretation of intelligence, arguing that cognitive dynamics are shaped primarily by structural limitations rather than goal-driven optimization. The framework introduces Constraint-Observed Intelligence (COI), a model describing how perception, reasoning, and decision processes emerge from boundary conditions, information accessibility, and temporal resolution limits. The paper positions intelligence as a system-level phenomenon arising from constraint interactions across biological and artificial substrates.

Cited by 0Open access

Organizational knowledge management structure

Steven Walczak · The Learning Organization · 2005

Purpose – To propose and evaluate a novel management structure that encourages knowledge sharing across an organization.\nDesign/methodology/approach – The extant literature on the impact of organizational culture and its link to management structure is examined and used to develop a new knowledge sharing management structure. Roadblocks to implementing a new management structure and methods for overcoming these impediments are discussed. The efficacy of the proposed management structure is evaluated empirically by examining its effect on organizations that have implemented portions of the proposed structure.\nFindings – The foundational ideas behind the proposed knowledge management organizational structure and the structure itself have been implemented in parts at various organizations located both in the USA and internationally. While the full management structure model has not been evaluated, the portions implemented in various organizations have enabled these organizations to assume leading roles in their respective industries.\nResearch limitations/implications – The proposed knowledge sharing management structure has not been fully implemented under controlled circumstances. The empirical evaluation is performed on portions of the proposed model, thus the full impact of the proposed management structure may well exceed the described benefits and additional structural‐shift roadblocks may limit the realization of the proposed benefits.\nPractical implications – The proposed knowledge sharing management structure gives managers a practical way to approach cross organizational knowledge sharing, which is frequently identified as a theoretical benefit of knowledge management. Means for diminishing or circumventing recognized impediments to organizational change are described to further facilitate the implementation of the proposed cross‐organizational knowledge sharing structure.\nOriginality/value – The proposed knowledge sharing management structure is organized around knowledge‐based teams of knowledge workers, but further extends this concept to include larger knowledge groups to transform an organization into a knowledge‐based organization. If an organization's functional structure can be successfully transformed, then this enables the maximization of competitive advantage realized through knowledge management initiatives, more specifically through knowledge sharing. Upper level management, who are responsible for organizational change are the primary audience, though the principals described may be implemented through a more grass roots approach by lower level management.

Cited by 182

The Structure of Knowledge

Knowledge management · 2018

This chapter proposes two interdependent ways of perceiving systems in a company that result in two possible ways to structure knowledge. The first way is the perception of a system through the messages that it sends us and the codes that it expresses. The second way is the perception of a system as a general system, in the sense of General System Theory, popularized in France by Jean-Louis Le Moigne's famous works. The semiotic hypothesis tells us that knowledge is a representation of a system that is coded by information and this information has a meaning in a given context of interpretation. The systemic hypothesis tells us that knowledge is a representation of a system that describes its structure, function and evolution. The macroscope is constructed by breaking down each point of view of the semiotic triangle into the three points of view of the systemic triangle.

Cited by 0

Knowledge Structure in Amarakosa

Sivaja S Nair · Zenodo (CERN European Organization for Nuclear Research) · 2010

Amarakośa is the most celebrated and authoritative ancient<br> thesaurus of Sanskrit. It is one of the books which an Indian child<br> learning through the Indian traditional educational system memorizes as<br> early as his first year of formal learning. Though it appears as a linear<br> list of words, close inspection of it shows a rich organisation of words<br> expressing various relations a word bears with other words. Thus when<br> a child studies Amarakośa further, the linear list of words unfolds into<br> a knowledge web. In this paper, we describe our effort to make the<br> implicit knowledge in Amarakośa explicit. A model for storing such<br> structure is discussed and a web tool is described that answers the<br> queries by reconstructing the links among words from the structured<br> tables dynamically.

Cited by 0Open access

Knowledge as Residual Structure

G.M. Sturm · Zenodo (CERN European Organization for Nuclear Research) · 2026

This work proposes a constraint-anchored interpretation of intelligence, arguing that cognitive dynamics are shaped primarily by structural limitations rather than goal-driven optimization. The framework introduces Constraint-Observed Intelligence (COI), a model describing how perception, reasoning, and decision processes emerge from boundary conditions, information accessibility, and temporal resolution limits. The paper positions intelligence as a system-level phenomenon arising from constraint interactions across biological and artificial substrates.

Cited by 0Open access