Artificial Intelligence-driven personalization and Learning Analytics in Ayurveda education: A framework for next-generation learning management systems

ABSTRACT: The integration of Artificial Intelligence (AI) and learning analytics offers innovative potential for Ayurveda education by enabling adaptive, data-informed, and learner-centric experiences. This paper presents a conceptual framework for an AI-driven Learning management system specifically designed for Ayurveda education, aligning Traditional knowledge paradigms with modern digital learning methodologies. The proposed framework aims to enable personalized content delivery, learner engagement tracking, and predictive insights for educators through a modular architecture comprising analytics, personalization, and visualization layers. The evaluation approach is proposed through a pilot design focusing on usability, learning effectiveness, and system adaptability as key metrics. As a conceptual and implementation-oriented framework, the study does not report empirical outcomes but instead outlines an enabling digital infrastructure for future evaluation and deployment in Ayurveda education.

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Publication Details

Journal
International Journal of Ayurveda Research
Published
2025-10-01
DOI
https://doi.org/10.4103/ijar.ijar_312_25
Primary Topic
Traditional Chinese Medicine Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence-driven personalization and Learning Analytics in Ayurveda education: A framework for next-generation learning management systems

Miren Karamta, Vinay V. Thakur
International Journal of Ayurveda Research
Traditional Chinese Medicine Studies
article

Artificial Intelligence-driven personalization and Learning Analytics in Ayurveda education: A framework for next-generation learning management systems

Miren Karamta, Vinay V. Thakur
article en

Abstract

ABSTRACT: The integration of Artificial Intelligence (AI) and learning analytics offers innovative potential for Ayurveda education by enabling adaptive, data-informed, and learner-centric experiences. This paper presents a conceptual framework for an AI-driven Learning management system specifically designed for Ayurveda education, aligning Traditional knowledge paradigms with modern digital learning methodologies. The proposed framework aims to enable personalized content delivery, learner engagement tracking, and predictive insights for educators through a modular architecture comprising analytics, personalization, and visualization layers. The evaluation approach is proposed through a pilot design focusing on usability, learning effectiveness, and system adaptability as key metrics. As a conceptual and implementation-oriented framework, the study does not report empirical outcomes but instead outlines an enabling digital infrastructure for future evaluation and deployment in Ayurveda education.

International Journal of Ayurveda ResearchVol. 6(4)
Government of Gujarat (IN)
Openalex Percentile: Top 44%
Traditional Chinese Medicine Studies
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