Neural Modeling of Learning: Integrating Cognitive Psychology and Artificial Intelligence Applications

Abstract

This paper aims to present an integrative framework combining three main fields: neural modeling, cognitive psychology, and artificial intelligence applications, within the context of developing learning processes and educational research. The paper addresses the problem of a clear gap between the individual progress made in each of these fields on the one hand, and the absence of an applied model that integrates them within a unified educational framework on the other. The paper seeks to: build a shared conceptual foundation, design practical activities that simulate principles of neural modeling, and explore future educational applications based on this integration. The workshop methodology adopts an interactive, hands-on approach including brainstorming, paper-based and computer-based simulations of simple neural networks, collaborative design of educational scenarios in small groups, and group discussion of ethical and practical challenges. Expected outcomes include: a shared understanding of integration concepts across the three fields, participants' ability to design preliminary educational scenarios, and the development of a list of challenges and opportunities. The paper recommends conducting experimental studies to test the effectiveness of integrative models, developing new measurement tools that combine behavioral and neural indicators, and establishing ethical codes governing the use of cognitive-based artificial intelligence in education. The paper concludes that integrative neural modeling represents a promising horizon for educational research, provided that technological tools remain in service of the human learner and their well-being, not as a substitute or reduction of them.