Development and Implementation of An Adaptive Learning Platform Based on Artificial Intelligence Technology
Abstract
This article presents the development and implementation process of the Adaptive Digital Didactic–Content Remediation System (ADD–CRS), built on artificial intelligence (AI) technology. The purpose of the research is to identify knowledge gaps in digital learning, adaptively remediate them, and ensure transparency in the teaching process. The ADD–CRS system was designed based on a two-stage adaptive retraining methodology, aimed at reducing cognitive load and enhancing learning efficiency. Additionally, the system enables teachers to automatically generate and analyze tests and assignments linked to specific source locations. Future research is planned to focus on automated task assessment, integration with electronic gradebooks, and full automation of formative, midterm, and final assessment processes.