Leveraging LLMs and wearables to provide personalized recommendations for enhancing student well-being and academic performance through a proof of concept

Leveraging LLMs and wearables to provide personalized recommendations for enhancing student well-being and academic performance through a proof of concept

Abstract Traditional one-size-fits-all recommendations for student well-being and academic success may not be optimal. Personalized recommendations based on individual data hold promise. This study explores the potential of Large Language Models (LLMs) to generate personalized recommendations for 12...

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Bibliographic Details
Main Authors: Arfan Ahmed, Sarah Aziz, Alaa Abd-alrazaq, Rawan AlSaad, Javaid Sheikh
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
Subjects:
Large Language models (LLMs)
Personalized recommendations
Student well-being
Academic performance
Wearable technology
Surveys
Online Access:https://doi.org/10.1038/s41598-025-89386-2
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https://doi.org/10.1038/s41598-025-89386-2

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