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Reseach Article

Adapted Regulation Level’s Flipped Classroom using Educational Data-mining

by Mohamed Mimis, Youssef Es-saady, Mohamed El Hajji, Abdellah Ouled Guejdi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 24
Year of Publication: 2018
Authors: Mohamed Mimis, Youssef Es-saady, Mohamed El Hajji, Abdellah Ouled Guejdi
10.5120/ijca2018918033

Mohamed Mimis, Youssef Es-saady, Mohamed El Hajji, Abdellah Ouled Guejdi . Adapted Regulation Level’s Flipped Classroom using Educational Data-mining. International Journal of Computer Applications. 181, 24 ( Oct 2018), 28-32. DOI=10.5120/ijca2018918033

@article{ 10.5120/ijca2018918033,
author = { Mohamed Mimis, Youssef Es-saady, Mohamed El Hajji, Abdellah Ouled Guejdi },
title = { Adapted Regulation Level’s Flipped Classroom using Educational Data-mining },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2018 },
volume = { 181 },
number = { 24 },
month = { Oct },
year = { 2018 },
issn = { 0975-8887 },
pages = { 28-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number24/30036-2018918033/ },
doi = { 10.5120/ijca2018918033 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:06:58.673155+05:30
%A Mohamed Mimis
%A Youssef Es-saady
%A Mohamed El Hajji
%A Abdellah Ouled Guejdi
%T Adapted Regulation Level’s Flipped Classroom using Educational Data-mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 24
%P 28-32
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Adaptation and individualization of learning is a major challenge when using flipped class as a teaching method. In this paper, we propose a recommendation system for flipped classroom to individualize learning in the classroom based on Data Mining algorithms. This system allows the teacher to predict a classification of learners before administering the tasks to be accomplished and the adapted teaching resources, using attributes related to the activity logs on the e-learning platform, to the online evaluations (Quiz) and to demographic data. The results show that the use of this model as a learning strategy optimizes the time of learning and improves the learner’s performance.

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Index Terms

Computer Science
Information Sciences

Keywords

Educational data mining flipped classroom regulation of learning adaptation hybrid learning.