The Adaptive Learning Ecosystem: How AI Transforms Digital Education Through Continuous Feedback Loops
DOI:
https://doi.org/10.5281/zenodo.17972381Keywords:
Adaptive Learning Systems, Artificial Intelligence in Education, Personalized Learning Pathways, Learning Analytics, Educational EquityAbstract
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.
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