What question did this study set out to answer?

The aim is to explore how artificial intelligence can transform education through personalized and predictive learning models.

May 10, 2026Open Access

Artificial Intelligence for Personalized and Predictive Education: A Review

Key Points

The aim is to explore how artificial intelligence can transform education through personalized and predictive learning models.
Reviewed the integration of AI in educational frameworks through learner and teaching models.
Proposed a hybrid teaching framework utilizing artificial neural networks for classification and performance prediction.
Analyzed data-driven approaches to improve educational engagement and administrative efficiency.
Achieved a prediction accuracy of up to 97.8% using extended data inputs in performance prediction.
Identified increased engagement and accessibility through AI-driven methodologies.
Highlighted ethical concerns regarding data privacy and reliance on technology in educational settings.

Abstract

Artificial Intelligence (AI) is increasingly redefining educational paradigms through adaptive learning, intelligent assessment, and data-driven decision-making. This study conceptualizes AI as an extension of human intelligence and examines its integration via learner, teaching, and knowledge models to enable personalized and efficient learning environments. A hybrid teaching framework employing Artificial Neural Networks (ANN) is proposed for student classification and performance prediction, demonstrating accuracy up to 97.8% with extended data inputs. The findings highlight AI’s role in enhancing engagement, accessibility, and administrative efficiency. However, ethical concerns, particularly data privacy and over-reliance on automation, remain critical. The study emphasizes a balanced human–AI synergy to ensure effective, inclusive, and ethically grounded education systems.

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