What type of study is this?

This is a In Vitro Study study.

August 20, 2025F1000ResearchOpen Access

Personalised and Collaborative Learning Experience (PCLE) Framework for AI-driven Learning Management System (LMS)

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Authors

CWClaireta Tang WeilingMultimedia University LLLew Sook LingMultimedia University OYOoi Shih YinMultimedia University

Discussion

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Implication

This study demonstrates collaborative filtering improves course recommendations in AI-driven e-learning systems, suggesting better student engagement.

Key Points

Collaborative filtering improved course recommendations, enhancing student engagement in e-learning environments.
K-Nearest Neighbours outperformed other models on the Coursera dataset, achieving superior accuracy throughout the study.
Machine learning models like KNN, SVD, and NCF were used to evaluate model performance on two education-related datasets.
Findings highlight the importance of dataset characteristics on algorithm effectiveness, underscoring future research potential for diverse contexts.

Cite This Study

Weiling et al. (2025) studied this question.

synapsesocial.com/papers/68af4cd3ad7bf08b1ead5fb0 https://doi.org/10.12688/f1000research.166248.1

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August 20, 2025F1000ResearchOpen Access

Personalised and Collaborative Learning Experience (PCLE) Framework for AI-driven Learning Management System (LMS)

View Full Paper

Ask AI

Bookmark

Authors

CWClaireta Tang WeilingMultimedia University LLLew Sook LingMultimedia University OYOoi Shih YinMultimedia University

Discussion

Member takes

Implication

This study demonstrates collaborative filtering improves course recommendations in AI-driven e-learning systems, suggesting better student engagement.

Key Points

Collaborative filtering improved course recommendations, enhancing student engagement in e-learning environments.
K-Nearest Neighbours outperformed other models on the Coursera dataset, achieving superior accuracy throughout the study.
Machine learning models like KNN, SVD, and NCF were used to evaluate model performance on two education-related datasets.
Findings highlight the importance of dataset characteristics on algorithm effectiveness, underscoring future research potential for diverse contexts.

Cite This Study

Weiling et al. (2025) studied this question.

synapsesocial.com/papers/68af4cd3ad7bf08b1ead5fb0 https://doi.org/10.12688/f1000research.166248.1

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