Generative AI in Higher Education: A Systematic Review of Its Effects on Learning Outcomes and Academic Performance

The integration of Generative AI tools in higher education has sparked significant interest, yet their impact on student learning engagement and academic performance remains unclear. This SLR examines empirical studies to determine whether Generative AI enhances engagement and improves learning outcomes in higher education. Following the PRISMA framework, we analyzed peer-reviewed articles from 2018 to 2024, identifying key trends, methodologies, and conflicting findings. Results reveal mixed evidence: while some studies report increased engagement and performance, others highlight limitations, including over-reliance on AI and variable effectiveness across disciplines. The review also identifies gaps in longitudinal and large-scale studies, calling for more rigorous research to assess Generative AI's pedagogical impact. Findings provide insights for educators and policymakers on optimizing Generative AI integration while addressing potential challenges.

Authors

Institutions

Publication Details

Journal
Journal of Educational Technology Systems
Published
2025-11-28
DOI
https://doi.org/10.1177/00472395251400089
Citations
3
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
1.96
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Generative AI in Higher Education: A Systematic Review of Its Effects on Learning Outcomes and Academic Performance

Kellie Hon
3 citations
Journal of Educational Technology Systems
Artificial Intelligence in Healthcare and Education
1.96
article

Generative AI in Higher Education: A Systematic Review of Its Effects on Learning Outcomes and Academic Performance

Kellie Hon
article en
3 citations

Abstract

The integration of Generative AI tools in higher education has sparked significant interest, yet their impact on student learning engagement and academic performance remains unclear. This SLR examines empirical studies to determine whether Generative AI enhances engagement and improves learning outcomes in higher education. Following the PRISMA framework, we analyzed peer-reviewed articles from 2018 to 2024, identifying key trends, methodologies, and conflicting findings. Results reveal mixed evidence: while some studies report increased engagement and performance, others highlight limitations, including over-reliance on AI and variable effectiveness across disciplines. The review also identifies gaps in longitudinal and large-scale studies, calling for more rigorous research to assess Generative AI's pedagogical impact. Findings provide insights for educators and policymakers on optimizing Generative AI integration while addressing potential challenges.

Journal of Educational Technology SystemsVol. 54(3)
Nilai University (MY)
Openalex Percentile: Top 10%
Artificial Intelligence in Healthcare and Education
1.96
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.