Artificial Intelligence Techniques for Distance Education: A Systematic Literature Review
Artificial Intelligence Techniques for Distance Education: A Systematic Literature Review
Author(s): Aayat Aljarrah, Mustafa Ababneh, Damla Karagozlu, Fezile ÖzdamlıSubject(s): ICT Information and Communications Technologies, Distance learning / e-learning
Published by: UIKTEN - Association for Information Communication Technology Education and Science
Keywords: Face recognition; Machine learning; Convolutional Neural Network; Image processing; Emotion detection; Distance learning; artificial intelligence
Summary/Abstract: 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.
Journal: TEM Journal
- Issue Year: 10/2021
- Issue No: 4
- Page Range: 1621-1629
- Page Count: 9
- Language: English