Titlebook: Computational Learning Theories; Models for Artificia David C. Gibson,Dirk Ifenthaler Book 2024 The Editor(s) (if applicable) and The Autho

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A Complex Hierarchical Framework of Learning,al design, cognitive science, complexity, and sociocultural theory. As a tri-level network of entities and relationships (i.e. nodes and edges of a network), the model includes a causal mechanism of learning with strong domain generality that is extended to perspectives on learning processes in micr

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Complexity Theory and Learning,of Keller and Piaget, to discuss the causal learning cycle as an imperative of the evolution of intelligence. The chapter incorporates the principles of dissipative structure theory and autocatalysis to explain how learning processes evolve and self-organize, suggesting a paradigm shift in understan

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Informal Social Learning,t, and the incorporation of real-life experiences in learning. The Piaget-Keller-Kauffman mechanisms described at the micro level are extended into team and organizational learning and referenced with key theories as a bridge to a formal network structure of social cognition presented in the followi

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AI Assisting Individuals as Team Members,team’s or organization’s agency while keeping the imperative causal role of learning in focus for each member. The chapter asserts that AI applications at the meso level must balance individual needs for contributing to the team with the team’s mission. Conflicts must be resolved to the benefit of t

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A Network Theory of Culture, via a network theory of culture. Cultural historical activity theory is proposed as the network representation of the macro level, which encompasses the HPL theory of community (Chaps. ., ., and .), and in turn the HPL model encompasses the PKK theory of learning (Chaps. ., ., and .). Units of anal

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Open Questions,the impacts one might have on others in a team or organizational setting. However, the framework did not directly address the issue of ‘theory of mind’ (ToM) arising in a generative-AI social learning agent that is simultaneously self-learning while acting as a participant observer on a team.

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David C. Gibson,Dirk IfenthalerIntegrates learning and complexity theories.Outlines AI roles for individual, team and organizational learning.Provides advanced perspectives in learning theories related to advances in artificial int