OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 20.03.2026, 12:42

Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.

Developing Adaptive Learning Technologies with AI for Students with Disabilities

2025·0 Zitationen·Science Journal of EducationOpen Access
Volltext beim Verlag öffnen

0

Zitationen

1

Autoren

2025

Jahr

Abstract

Traditional educational frameworks, characterized by standardized curricula and a uniform pace of instruction, frequently struggle to meet the varied learning requirements of students with disabilities. This systemic rigidity contributes to a persistent gap in educational outcomes and reveals the limitations of existing non-AI assistive tools, which are often static and unable to adapt to a learner's progress. The purpose of this article is to address this critical issue by examining the development of adaptive learning technologies driven by Artificial Intelligence (AI) to provide genuinely individualized educational experiences. It proposes a systematic approach for creating effective and ethical systems tailored to students with diverse needs. The methodology for this conceptual work involves a systematic review of the existing body of knowledge, which informs the introduction of a new development framework. This proposed framework outlines the essential components for robust adaptive systems, including: dynamic user profiling to create a rich, continuously updated understanding of a student’s learning patterns; generative AI models for the real-time creation and modification of educational content; immediate and constructive feedback mechanisms; and longitudinal progress monitoring to inform educators and guide long-term learning trajectories. The article concludes that while AI offers powerful tools to build more inclusive and equitable educational environments, its potential can only be realized through responsible and ethical implementation. The development process must be guided by a firm commitment to mitigating algorithmic bias, ensuring transparency and explainability in AI-driven decisions, establishing clear lines of accountability, and upholding robust data privacy standards. Ultimately, the successful integration of these advanced technologies depends on a foundation of ethical principles and human oversight to ensure fair and effective support for all students.

Ähnliche Arbeiten

Autoren

Institutionen

Themen

Intelligent Tutoring Systems and Adaptive LearningOnline Learning and AnalyticsArtificial Intelligence in Healthcare and Education
Volltext beim Verlag öffnen