A Unified Meta-Learning Theory: A Cognitive and Experimental Framework to Train Thinking and Decision Making for Human and Machine Learning

Abstract

This paper presents a groundbreaking synthesis of learning theory that redefines our understanding of the learning process through a comprehensive, integrative framework. Drawing upon extensive analysis of established learning theories-from behaviorism to connectivism and others-this work proposes a novel definition that positions learning as "the process of repetition, imitation, imagination & experimentation to use all the available tools, methods and techniques to train our brain & our thought process by observation & analysis to find best possible combinations to use for making better decisions than our current state to achieve a particular outcome." This is a revolutionary framework for understanding learning process to bridge traditional theories with future-ready practice not only encompasses both conscious and unconscious learning processes but also provides a revolutionary lens through which to understand skill acquisition, decision-making, and human potential maximization in the digital age. MetaLearning connotes learning how to learn and mastering the learning process.

Keywords: Learning, Thinking, Machine Learning, Meta Cognition, Meta Learning, Process of Learning, Decision Making