<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This study proposes models for searching and recommending learning resources to meet the needs of learners, helping to achieve better student performance results. The study suggests a general architecture for searching and recommending learning resources. It specifically proposes (1) the model of learning resource classification based on deep learning techniques such as MLP; (2) the approach for searching learning resources based on document similarity; (3) the model to predict learning performance using deep learning techniques including learning performance prediction model on all student data using CNN, another model on ability group using MLP, and the other model on per student using LSTM; (4) the learning resource recommendation model using deep matrix factorization. Experimental results show that the proposed models are feasible for the classification, search, ranking prediction, and recommendation of learning resources in higher education institutions.</p>
</abstract>

This study proposes models for searching and recommending learning resources to meet the needs of learners, helping to achieve better student performance results. The study suggests a general architecture for searching and recommending learning resources. It specifically proposes (1) the model of learning resource classification based on deep learning techniques such as MLP; (2) the approach for searching learning resources based on document similarity; (3) the model to predict learning performance using deep learning techniques including learning performance prediction model on all student data using CNN, another model on ability group using MLP, and the other model on per student using LSTM; (4) the learning resource recommendation model using deep matrix factorization. Experimental results show that the proposed models are feasible for the classification, search, ranking prediction, and recommendation of learning resources in higher education institutions.

Novel Approaches for Searching and Recommending Learning Resources

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Novel Approaches for Searching and Recommending Learning Resources"}

This study proposes models for searching and recommending learning resources to meet the needs of learners, helping to achieve better student performance...

Novel Approaches for Searching and Recommending Learning Resources

Online veröffentlicht: 12. Juni 2023

Seitenbereich: 151 - 169

Eingereicht: 14. Nov. 2022

Akzeptiert: 12. Mai 2023

DOI: https://doi.org/10.2478/cait-2023-0019

Schlüsselwörter
Learning resources, learning performance prediction, learning resources recommendation, deep learning, machine learning

© 2023 Tran Thanh Dien et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Novel Approaches for Searching and Recommending Learning Resources

Online veröffentlicht: 12. Juni 2023

Seitenbereich: 151 - 169

Eingereicht: 14. Nov. 2022

Akzeptiert: 12. Mai 2023

DOI: https://doi.org/10.2478/cait-2023-0019

SchlüsselwörterLearning resources, learning performance prediction, learning resources recommendation, deep learning, machine learning

© 2023 Tran Thanh Dien et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Learning resources, learning performance prediction, learning resources recommendation, deep learning, machine learning