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Model detecting learning styles with artificial neural network

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10.3926/jotse.540
 
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hdl:2117/133873

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Hasibuan, Muhammad Said
Nugroho, Lukito Edi
Santosa, Paulus Insap
Document typeArticle
Defense date2019-02
PublisherOmniaScience
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
This work is protected by the corresponding intellectual and industrial property rights. Except where otherwise noted, its contents are licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
Currently the detection of learning styles from the external aspect has not produced optimal results. This research tries to solve the problem by using an internal approach. The internal approach is one that derives from the personality of the learner. One of the personality traits that each learner possesses is prior knowledge. This research starts with the prior knowledge generation process using the Latent Semantic Indexing (LSI) method. LSI is a technique using Singular Value Decomposition (SVD) to find meaning in a sentence. LSI works to generate the prior knowledge of each learner. After the prior knowledge is raised, then one can predict learning style using the artificial neural network (ANN) method. The results of this study are more accurate than the results of detection conducted with an external approach.
CitationHasibuan, M. S.; Nugroho, L. E.; Santosa, P. I. Model detecting learning styles with artificial neural network. "JOTSE: Journal of Technology and Science Education", Febrer 2019, vol. 9, núm. 1, p. 85-95. 
URIhttp://hdl.handle.net/2117/133873
DOI10.3926/jotse.540
DLB-2000-2012
ISSN2013-6374
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