Beyond the Blackboard: AI-Driven Virtual Tutors and the Evolution of Digital Learning

Traditional learning paradigms have been profoundly altered by the incorporation of Artificial Intelligence (AI) into educational settings. The rise of AI-powered virtual tutors and their effects on the development of digital learning are examined in this paper. We look at the technical underpinnings of virtual tutors, evaluate current applications, and talk about how effective they are in comparison to conventional teaching techniques. We present findings on learner engagement, retention of knowledge, and general satisfaction from a mixed-method study that included surveys and experimental observations. Our results show that while AI-driven tutors improve learning efficiency, accessibility, and personalization, they also present ethical, equity, and data privacy issues. We wrap up by outlining potential avenues for future study to develop AI educational models that are more focused on people.

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Publication Details

Journal
International Journal of Scientific Research in Science Engineering and Technology
Published
2025-05-09
DOI
https://doi.org/10.32628/ijsrset25122204
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00
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article

Beyond the Blackboard: AI-Driven Virtual Tutors and the Evolution of Digital Learning

Neeti Panchal, Amey Dawkhar, Amita Chandekar, Sanket Ghatte
International Journal of Scientific Research in Science Engineering and Technology
Online Learning and Analytics
article

Beyond the Blackboard: AI-Driven Virtual Tutors and the Evolution of Digital Learning

Neeti Panchal, Amey Dawkhar, Amita Chandekar, Sanket Ghatte
article en

Abstract

Traditional learning paradigms have been profoundly altered by the incorporation of Artificial Intelligence (AI) into educational settings. The rise of AI-powered virtual tutors and their effects on the development of digital learning are examined in this paper. We look at the technical underpinnings of virtual tutors, evaluate current applications, and talk about how effective they are in comparison to conventional teaching techniques. We present findings on learner engagement, retention of knowledge, and general satisfaction from a mixed-method study that included surveys and experimental observations. Our results show that while AI-driven tutors improve learning efficiency, accessibility, and personalization, they also present ethical, equity, and data privacy issues. We wrap up by outlining potential avenues for future study to develop AI educational models that are more focused on people.

International Journal of Scientific Research in Science Engineering and TechnologyVol. 12(3)
MIT Art, Design and Technology University (IN)
Openalex Percentile: Top 90%
Online Learning and Analytics
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