生成语法
生成模型
心理学
钥匙(锁)
实证研究
计算机科学
学业成绩
高等教育
系统回顾
体验式学习
学生参与度
数学教育
经验证据
人工智能
教育研究
变量(数学)
组分(热力学)
出处
期刊:Journal of Educational Technology Systems
[SAGE]
日期:2025-11-28
卷期号:54 (3): 537-560
被引量:5
标识
DOI:10.1177/00472395251400089
摘要
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.
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