Paradigmatic Model of Understanding and Using Artificial Intelligence in Learning

Abstract

Introduction. Recent years have seen unprecedented global changes associated with the acceleration of the use of artificial intelligence tools as one of the main factors of the evolutionary and revolutionary engines of modern civilization, under the great influence of requirements and opportunities for all. The problems of understanding and using artificial intelligence in education are considered from various points of view, perspectives, purposes, paradigms, theories, approaches, methods, using various means of information processing. procedures, services, etc.. In our study, the modeling focuses from a higher level of generalization on the understanding and use of artificial intelligence in learning by building a general paradigmatic model in the composition of the model of learning metaphors and artificial intelligence, the paradigm model of academician V.M. Hlushkov and psychology (Behaviorism; Information processing and cognitive psychology; Individual constructivism; Social constructivism and situational learning), models "Action. Register of tasks".

Purpose. The purpose of this study is develop a formalized description with meaningful interpretations of paradigmatic model of understanding and using artificial intelligence in learning. in which "Artificial intelligence is an additional means of survival" (Glushkov's Paradigm).

Methods. System methodology, methods of reduction, abstraction, analogies, analysis, synthesis.

Results. For the first time, a general paradigmatic model of understanding and use of artificial intelligence in learning was developed as part of the model of learning metaphors and artificial intelligence, the paradigm model of academician V.M. Hlushkov and psychology (Behaviorism; Information processing and cognitive psychology; Individual constructivism; Social constructivism and situational learning), models "Action. Register of tasks".

Conclusion. In the era of digital transformation, solving the complex problem of building and practical use of a general paradigmatic model of understanding and use of artificial intelligence in learning requires the complex solution of many relevant complex scientific and practical problems, tasks such as: multidisciplinarity and multiculturalism; understanding and explanation; evaluation, forecast, evolution, variability, complexity, scaling, property protection, elimination of uncertainty, interoperability, harmonization with existing and planned official and de facto standards, at the same time, it is necessary to overcome numerous difficulties, barriers, challenges and problems of structuring and integration of various specific models. Therefore, a necessary condition and requirement for the systematic improvement of general and specific models is a comprehensive interpretation of abstractions in the context of the specified problems, as well as their practical testing using available information processing systems in order to identify and disseminate unique best practices and experience to all interested parties. The main directions of further research for the systematic integration of the results of the vertical and horizontal reduction of the general model "Action. Register of tasks": 1. Definition and use of specific mathematical theories for the information presentation of Status Quo evolution models, for individuals and legal entities, in particular, for the assessment and forecast of the growth of the Status Quo evolution assessment in various scaling units such as a natural number, matrix, graph, space; 2. Determination and use of specific mathematical theories for the visualization of metaphors of the information representation of models of the evolution of Status Quo; 3. Determination and use of specific theories from psychology for the informative presentation of evolution models of the Status Quo of a specific person, team, organization, community.