Integration of Learning and Neuroscience Theories with AI-based Technologies in Intelligent Learning System in Accordance of Whiteheadian Tradition and Contemporary Process Theory

Abstract

The purpose of the article is to present the possibility of integrating basic learning theories into the Extended Intelligent Learning System for data processing, optimization, adaptation and decision making in learning, which is based on the combination of teacher and intelligent tutor with artificial intelligence implemented, which supports the target formation, learning strategy, pedagogy and control. As a framework for the creation of the integrative model of theories, process philosophy is used, which enables a better understanding and explanation of the different paradigms and their functional combination. The article explores the strengths and weaknesses of selected theories and focuses primarily on constructivism, as numerous studies on learning theories have found that a constructive approach to learning is at the heart of many models in both traditional and digital learning in the Era of Big Data. The article explores certain influential learning theories, including the AI methods, their advantages, flaws and fields of intersection with neurosciences in terms of their application in intelligent training systems. The goal of developing the integrative model is to realize the learner's potential in personalized knowledge formation in an intelligent learning environment and to enhance the efficiency of learning.