Artificial Intelligence Techniques for Distance Education: A Systematic Literature Review

In the current era, education, like other fields, relies heavily on big data. Moreover, artificial intelligence, including affective computing, is one of the most essential and popular technologies adopted by educational institutions to process and analyze big data. In this systematic review, many p...

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Autores principales:	Aayat Aljarrah, Mustafa Ababneh, Damla Karagozlu, Fezile Ozdamli
Formato:	article
Lenguaje:	EN
Publicado:	UIKTEN 2021
Materias:	face recognition machine learning convolutional neural network image processing emotion detection distance learning artificial intelligence Education L Technology T
Acceso en línea:	https://doaj.org/article/352f1e78938e4e228e46aeb08dc1c5f0
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spelling	oai:doaj.org-article:352f1e78938e4e228e46aeb08dc1c5f02021-12-01T10:48:53ZArtificial Intelligence Techniques for Distance Education: A Systematic Literature Review10.18421/TEM104-182217-83092217-8333https://doaj.org/article/352f1e78938e4e228e46aeb08dc1c5f02021-11-01T00:00:00Zhttps://www.temjournal.com/content/104/TEMJournalNovember2021_1621_1629.pdfhttps://doaj.org/toc/2217-8309https://doaj.org/toc/2217-8333In the current era, education, like other fields, relies heavily on big data. Moreover, artificial intelligence, including affective computing, is one of the most essential and popular technologies adopted by educational institutions to process and analyze big data. In this systematic review, many previous research types related to improving educational systems using artificial intelligence techniques were studied, such as: deep learning, machine learning, and affective computing. This systematic review aims to identify the gaps in students' emotional understanding in distance education systems. The world has recently witnessed the spread of educational processes for distance learning, especially in the university and the enormous open online courses (MOOCs). Besides, the COVID-19 pandemic has been involved in changing all educational processes to a distance learning system. The results indicated that these systems recorded a high success rate. However, the teacher does not fully understand the student’s emotional state during the educational session. It also lacks monitoring or monitoring during the electronic exams, which are electronic exams. So, it is a widespread problem in distance learning.Aayat AljarrahMustafa AbabnehDamla KaragozluFezile OzdamliUIKTENarticleface recognitionmachine learningconvolutional neural networkimage processingemotion detectiondistance learningartificial intelligenceEducationLTechnologyTENTEM Journal, Vol 10, Iss 4, Pp 1621-1629 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	face recognition machine learning convolutional neural network image processing emotion detection distance learning artificial intelligence Education L Technology T
spellingShingle	face recognition machine learning convolutional neural network image processing emotion detection distance learning artificial intelligence Education L Technology T Aayat Aljarrah Mustafa Ababneh Damla Karagozlu Fezile Ozdamli Artificial Intelligence Techniques for Distance Education: A Systematic Literature Review
description	In the current era, education, like other fields, relies heavily on big data. Moreover, artificial intelligence, including affective computing, is one of the most essential and popular technologies adopted by educational institutions to process and analyze big data. In this systematic review, many previous research types related to improving educational systems using artificial intelligence techniques were studied, such as: deep learning, machine learning, and affective computing. This systematic review aims to identify the gaps in students' emotional understanding in distance education systems. The world has recently witnessed the spread of educational processes for distance learning, especially in the university and the enormous open online courses (MOOCs). Besides, the COVID-19 pandemic has been involved in changing all educational processes to a distance learning system. The results indicated that these systems recorded a high success rate. However, the teacher does not fully understand the student’s emotional state during the educational session. It also lacks monitoring or monitoring during the electronic exams, which are electronic exams. So, it is a widespread problem in distance learning.
format	article
author	Aayat Aljarrah Mustafa Ababneh Damla Karagozlu Fezile Ozdamli
author_facet	Aayat Aljarrah Mustafa Ababneh Damla Karagozlu Fezile Ozdamli
author_sort	Aayat Aljarrah
title	Artificial Intelligence Techniques for Distance Education: A Systematic Literature Review
title_short	Artificial Intelligence Techniques for Distance Education: A Systematic Literature Review
title_full	Artificial Intelligence Techniques for Distance Education: A Systematic Literature Review
title_fullStr	Artificial Intelligence Techniques for Distance Education: A Systematic Literature Review
title_full_unstemmed	Artificial Intelligence Techniques for Distance Education: A Systematic Literature Review
title_sort	artificial intelligence techniques for distance education: a systematic literature review
publisher	UIKTEN
publishDate	2021
url	https://doaj.org/article/352f1e78938e4e228e46aeb08dc1c5f0
work_keys_str_mv	AT aayataljarrah artificialintelligencetechniquesfordistanceeducationasystematicliteraturereview AT mustafaababneh artificialintelligencetechniquesfordistanceeducationasystematicliteraturereview AT damlakaragozlu artificialintelligencetechniquesfordistanceeducationasystematicliteraturereview AT fezileozdamli artificialintelligencetechniquesfordistanceeducationasystematicliteraturereview
_version_	1718405226592993280

Artificial Intelligence Techniques for Distance Education: A Systematic Literature Review

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