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

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.

Authors

Institutions

Publication Details

Journal
International journal of education, humanities and social sciences.
Published
2025-02-03
DOI
https://doi.org/10.70088/3wnrs278
Citations
3
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
5.08
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

J Wang, Yasmin Hussain, Chencheng Mao
3 citations
International journal of education, humanities and social sciences.
Online Learning and Analytics
5.08
article

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

J Wang, Yasmin Hussain, Chencheng Mao
article en
3 citations

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.

International journal of education, humanities and social sciences.Vol. 2(1)
City University Malaysia (MY)
Openalex Percentile: Top 5%
Online Learning and Analytics
5.08
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Artificial Intelligence-Driven Personalized Learning: Psychological Implications and Educational Outcomes — J Wang, Yasmin Hussain, et al. · International journal of education, humanities and social sciences. (2025) | TGRS Research Map | TGRS