Deep neural network based m-learning model for predicting mobile learners’ performance

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dc.contributor.authorAdnan, Muhammad
dc.contributor.authorHabib, Asad
dc.contributor.authorAshraf, Jawad
dc.contributor.authorMussadiq, Shafaq
dc.contributor.authorAli Raza, Arsalan
dc.date.accessioned2024-10-29T15:24:49Z
dc.date.available2024-10-29T15:24:49Z
dc.date.issued2020-05-08
dc.description.abstractThe use of deep learning (DL) techniques for mobile learning is an emerging field aimed at developing methods for finding mobile learners' learning behavior and exploring important learning features. The learning features (learning time, learning location, repetition rate, content types, learning performance, learning time duration, and so on) act as fuel to DL algorithms based on which DL algorithms can classify mobile learners into different learning groups. In this study, a powerful and efficient m-learning model is proposed based on DL techniques to model the learning process of m-learners. The proposed m-learning model determines the impact of independent learning features on the dependent feature i.e. learners? performance. The m-learning model dynamically and intuitively explores the weights of optimum learning features on learning performance for different learners in their learning environment. Then it split learners into different groups based on features differences, weights, and interrelationships. Because of the high accuracy of the DL technique, it was used to classify learners into five different groups whereas random forest (RF) ensemble method was used in determining each feature importance in making adaptive m-learning model. Our experimental study also revealed that the m-learning model was successful in helping m-learners in increasing their performance and taking the right decision during the learning flow.
dc.funderNo external funder
dc.identifier.citationAdnan, M. et al. (2020) Deep neural network based m-learning model for predicting mobile learners'performance. Turkish Journal of Electrical Engineering and Computer Sciences,. 28 (3), 16
dc.identifier.doihttps://doi.org/10.3906/elk-1907-8
dc.identifier.issn1303-6203
dc.identifier.urihttps://hdl.handle.net/2086/24419
dc.publisherThe Scientific and Technological Research Council of Turkey (TUBITAK-ULAKBIM) - DIGITAL COMMONS JOURNALS
dc.relation.ispartofTURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES
dc.titleDeep neural network based m-learning model for predicting mobile learners’ performance
dc.typeArticle
oaire.citation.issue3
oaire.citation.volume28

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