AI-DRIVEN EDUCATIONAL INTERVENTIONS: AN EMPIRICAL STUDY ON THEIR EFFICACY IN IMPROVING ACADEMIC PERFORMANCE

This article examines the transformative impact of Artificial Intelligence (AI) on education, focusing on its role in enhancing student learning and academic performance. Through a comprehensive analysis of current literature and empirical data, we investigate key applications of AI in educational settings, including personalized learning systems, administrative automation, intelligent content creation, and data analytics. Our findings reveal that AI-driven educational interventions significantly improve student engagement, knowledge retention, and overall academic achievement. Adaptive learning platforms and AI tutors demonstrate particular efficacy in tailoring educational experiences to individual student needs. However, the article also identifies critical challenges, such as data privacy concerns and potential algorithmic biases, that require careful consideration. By synthesizing quantitative performance metrics with qualitative assessments of student and educator experiences, this article provides a nuanced understanding of AI's potential to revolutionize education. The article concludes with a discussion of future directions for AI in education and offers recommendations for policymakers and educational institutions to effectively leverage AI technologies while addressing ethical considerations.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-09
DOI
https://doi.org/10.5281/zenodo.13736122
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
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article

AI-DRIVEN EDUCATIONAL INTERVENTIONS: AN EMPIRICAL STUDY ON THEIR EFFICACY IN IMPROVING ACADEMIC PERFORMANCE

Zenodo (CERN European Organization for Nuclear Research)
Online Learning and Analytics
article

AI-DRIVEN EDUCATIONAL INTERVENTIONS: AN EMPIRICAL STUDY ON THEIR EFFICACY IN IMPROVING ACADEMIC PERFORMANCE

article en

Abstract

This article examines the transformative impact of Artificial Intelligence (AI) on education, focusing on its role in enhancing student learning and academic performance. Through a comprehensive analysis of current literature and empirical data, we investigate key applications of AI in educational settings, including personalized learning systems, administrative automation, intelligent content creation, and data analytics. Our findings reveal that AI-driven educational interventions significantly improve student engagement, knowledge retention, and overall academic achievement. Adaptive learning platforms and AI tutors demonstrate particular efficacy in tailoring educational experiences to individual student needs. However, the article also identifies critical challenges, such as data privacy concerns and potential algorithmic biases, that require careful consideration. By synthesizing quantitative performance metrics with qualitative assessments of student and educator experiences, this article provides a nuanced understanding of AI's potential to revolutionize education. The article concludes with a discussion of future directions for AI in education and offers recommendations for policymakers and educational institutions to effectively leverage AI technologies while addressing ethical considerations.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 64%
Online Learning and Analytics
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AI-DRIVEN EDUCATIONAL INTERVENTIONS: AN EMPIRICAL STUDY ON THEIR EFFICACY IN IMPROVING ACADEMIC PERFORMANCE · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS