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Artificial Intelligence-Driven Personalized Learning: Psychological Implications and Educational Outcomes

Year: 2025

Type: article

Abstract: This paper explores the psychological implications and educational outcomes of artificial intelligence (AI)-driven personalized learning systems. The study delves into how AI facilitates customized learning experiences, adapting to individual student needs and learning styles. The research highlights the impact of AI on student motivation, cognitive load, and academic performance, as well as potential ethical concerns such as data privacy and algorithmic bias. Empirical findings from various case studies demonstrate how AI-driven platforms enhance engagement and retention rates. The study concludes with recommendations for optimizing AI use in education while addressing associated challenges.

Source: International journal of education, humanities and social sciences.

DOI: 10.70088/3wnrs278

Authors: Junyao Wang, Yasmin Hussain, Chencheng Mao

Institution: City University Malaysia

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: hybrid

OpenAlex ID: W4407108044

FWCI: 7.749

Cites:

Cited by: 7

Related to: 10