THE ADAPTIVE LEARNING ECOSYSTEM: HOW AI TRANSFORMS DIGITAL EDUCATION THROUGH CONTINUOUS FEEDBACK LOOPS

This article examines the transformative impact of artificial intelligence on digital education platforms, tracing the evolution from basic computer-assisted instruction to sophisticated adaptive learning environments powered by deep learning architectures. The article explores five key dimensions of this technological revolution: the historical development of AI in educational contexts; deep learning models that enable personalized learning pathways through behavioral analysis, dynamic difficulty adjustment, and content sequencing; experimentation infrastructures that facilitate evidence-based EdTech development; auto-instrumentation systems that provide scalable tracking and AI-enhanced session replays; and the emerging impacts on diverse learner populations with promising evidence for narrowing achievement gaps. The article highlights how AI-driven educational technologies continuously adapt to individual learner needs through sophisticated feedback loops, creating personalized learning experiences that optimize engagement and outcomes while raising important considerations regarding implementation, ethics, and privacy.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-18
DOI
https://doi.org/10.5281/zenodo.17972380
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

THE ADAPTIVE LEARNING ECOSYSTEM: HOW AI TRANSFORMS DIGITAL EDUCATION THROUGH CONTINUOUS FEEDBACK LOOPS

Zenodo (CERN European Organization for Nuclear Research)
Intelligent Tutoring Systems and Adaptive Learning
article

THE ADAPTIVE LEARNING ECOSYSTEM: HOW AI TRANSFORMS DIGITAL EDUCATION THROUGH CONTINUOUS FEEDBACK LOOPS

article en

Abstract

This article examines the transformative impact of artificial intelligence on digital education platforms, tracing the evolution from basic computer-assisted instruction to sophisticated adaptive learning environments powered by deep learning architectures. The article explores five key dimensions of this technological revolution: the historical development of AI in educational contexts; deep learning models that enable personalized learning pathways through behavioral analysis, dynamic difficulty adjustment, and content sequencing; experimentation infrastructures that facilitate evidence-based EdTech development; auto-instrumentation systems that provide scalable tracking and AI-enhanced session replays; and the emerging impacts on diverse learner populations with promising evidence for narrowing achievement gaps. The article highlights how AI-driven educational technologies continuously adapt to individual learner needs through sophisticated feedback loops, creating personalized learning experiences that optimize engagement and outcomes while raising important considerations regarding implementation, ethics, and privacy.

Zenodo (CERN European Organization for Nuclear Research)
Arizona State University (US)
Openalex Percentile: Top 19%
Intelligent Tutoring Systems and Adaptive Learning
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